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Volume 10
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Healthcare, Volume 10, Issue 1 (January 2022) – 177 articles

Cover Story (view full-size image): In 1997, a prospective population-based study started in northeastern Germany—the Study of Health in Pomerania (SHIP). Whereas most epidemiological studies focus on selected diseases, SHIP examines health and illness in their whole complexity. Since 2008, the extensive program has included whole-body MR imaging at 1.5 Tesla. The huge amount of data allowed generating reference values, determining the prevalence and incidence of diseases or incidental findings, and analyzing associations between morphological MR phenotypes and the genome, risk factors, subclinical disorders or manifest affliction. In a retrospective 12 years after initiation, the more than 100 publications that originated from these SHIP-MR data were analyzed regarding which MR sequences were most frequently used for scientific output, or which manuscripts have gained most citations and ranked highest. View this paper.
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10 pages, 957 KiB  
Concept Paper
Implementation of Compassionate Communities: The Taipei Experience
by Chia-Jen Liu, Sheng-Jean Huang and Samuel Shih-Chih Wang
Healthcare 2022, 10(1), 177; https://doi.org/10.3390/healthcare10010177 - 17 Jan 2022
Cited by 7 | Viewed by 3779
Abstract
A worldwide movement to empower communities to support their members to care for each other at the end of life (EoL) has emerged since Kellehear published the Compassionate City Charter. This current report discusses the implementation experiences and preliminary outcomes of Compassionate Communities [...] Read more.
A worldwide movement to empower communities to support their members to care for each other at the end of life (EoL) has emerged since Kellehear published the Compassionate City Charter. This current report discusses the implementation experiences and preliminary outcomes of Compassionate Communities (CC) in Taipei City. Using the guidance of the Charter and international experiences, we have developed and multiplied a culturally sensitive, sustainable, and holistic CC program that composes municipal hospital, social, and other services, partnering with community leaders, non-governmental organizations, university students, and volunteers. Innovative campaigns, such as workshops, conferences, and the Life Issue Café, have been delivered to facilitate engagement, public education, and leadership with reverence to folk beliefs and the use of existing social networks. We have identified a model with strong collaborative leadership, high participation rates, and ongoing commitment. The gaps between asking/accepting and providing help were bridged when social connectedness was strengthened. We also integrated home-based medical care, home-based palliative care, and advance care planning to help the vulnerable who live alone, with poor status, or with limited resource access, and continue to support the community throughout the COVID-19 pandemic. Full article
(This article belongs to the Special Issue Public Health Palliative Care and Public Palliative Care Education)
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<p>Core values and strategies of compassionate communities in Taipei.</p> Full article ">Figure 2
<p>Method of Life Issue Café.</p> Full article ">
12 pages, 268 KiB  
Article
The Impact of Migration Status on Adolescents’ Mental Health during COVID-19
by Christoph Pieh, Rachel Dale, Andrea Jesser, Thomas Probst, Paul L. Plener and Elke Humer
Healthcare 2022, 10(1), 176; https://doi.org/10.3390/healthcare10010176 - 17 Jan 2022
Cited by 21 | Viewed by 4783
Abstract
The purpose of this study was to compare mental health in adolescents with and without migration background after a semester of remote schooling and almost a year of social distancing in Austria. An online survey, supported by the Austrian Federal Ministry of Education, [...] Read more.
The purpose of this study was to compare mental health in adolescents with and without migration background after a semester of remote schooling and almost a year of social distancing in Austria. An online survey, supported by the Austrian Federal Ministry of Education, Science and Research, was conducted from 3rd February to 28th February 2021 measuring well-being (WHO-5), depression (PHQ-9), anxiety (GAD-7), sleep quality (ISI), stress (PSS-10), and disordered eating (EAT-8). A matched-pairs analysis with and without migration background was conducted and was checked with whole sample analysis. From a total of 3052 participants, N = 508 had a migration background (first or second generation) and N = 479 could be matched according to age, gender, region, and education with adolescents without migration background. Matched-pairs analyses showed that migration background is associated with poorer mental health concerning well-being, depression, anxiety, and insomnia scores (all p-values < 0.05). Prevalence of depressive symptoms (64.5% vs. 56.5%), anxiety symptoms (53.5% vs. 46.0%), as well as insomnia (31.9% vs. 21.0%) is higher in adolescents with migration background (all p-values ≤ 0.02). Comparison of the whole sample (N = 3052) confirmed these results. Results suggest that migration status is a risk factor for mental health problems among adolescents during the COVID-19 pandemic and highlight the need to implement easily accessible culture- and language-specific health promotion and prevention strategies. Full article
(This article belongs to the Special Issue Mental Health in Times of Pandemic: Protective and Risk Factors)
16 pages, 3370 KiB  
Article
Diagnostic Performance of a Deep Learning Model Deployed at a National COVID-19 Screening Facility for Detection of Pneumonia on Frontal Chest Radiographs
by Jordan Z. T. Sim, Yong-Han Ting, Yuan Tang, Yangqin Feng, Xiaofeng Lei, Xiaohong Wang, Wen-Xiang Chen, Su Huang, Sum-Thai Wong, Zhongkang Lu, Yingnan Cui, Soo-Kng Teo, Xin-Xing Xu, Wei-Min Huang and Cher-Heng Tan
Healthcare 2022, 10(1), 175; https://doi.org/10.3390/healthcare10010175 - 17 Jan 2022
Cited by 8 | Viewed by 2425
Abstract
(1) Background: Chest radiographs are the mainstay of initial radiological investigation in this COVID-19 pandemic. A reliable and readily deployable artificial intelligence (AI) algorithm that detects pneumonia in COVID-19 suspects can be useful for screening or triage in a hospital setting. This study [...] Read more.
(1) Background: Chest radiographs are the mainstay of initial radiological investigation in this COVID-19 pandemic. A reliable and readily deployable artificial intelligence (AI) algorithm that detects pneumonia in COVID-19 suspects can be useful for screening or triage in a hospital setting. This study has a few objectives: first, to develop a model that accurately detects pneumonia in COVID-19 suspects; second, to assess its performance in a real-world clinical setting; and third, by integrating the model with the daily clinical workflow, to measure its impact on report turn-around time. (2) Methods: The model was developed from the NIH Chest-14 open-source dataset and fine-tuned using an internal dataset comprising more than 4000 CXRs acquired in our institution. Input from two senior radiologists provided the reference standard. The model was integrated into daily clinical workflow, prioritising abnormal CXRs for expedited reporting. Area under the receiver operating characteristic curve (AUC), F1 score, sensitivity, and specificity were calculated to characterise diagnostic performance. The average time taken by radiologists in reporting the CXRs was compared against the mean baseline time taken prior to implementation of the AI model. (3) Results: 9431 unique CXRs were included in the datasets, of which 1232 were ground truth-labelled positive for pneumonia. On the “live” dataset, the model achieved an AUC of 0.95 (95% confidence interval (CI): 0.92, 0.96) corresponding to a specificity of 97% (95% CI: 0.97, 0.98) and sensitivity of 79% (95% CI: 0.72, 0.84). No statistically significant degradation of diagnostic performance was encountered during clinical deployment, and report turn-around time was reduced by 22%. (4) Conclusion: In real-world clinical deployment, our model expedites reporting of pneumonia in COVID-19 suspects while preserving diagnostic performance without significant model drift. Full article
(This article belongs to the Section Artificial Intelligence in Medicine)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Workflow of pre-training, initializing, and fine-tuning processes. C1 is a multi-label classifier with 14 elements, and C2 is a classifier containing two neurons.</p> Full article ">Figure 2
<p>NCID Screening Centre Workflow.</p> Full article ">Figure 3
<p>AI Model Deployment Infrastructure.</p> Full article ">Figure 4
<p>ROC curves for the 7 models and the ensemble model on the POC offsite test. The AUCs of individual models are 0.9185, 0.9355, 0.9265, 0.9163, 0.9285, 0.8976, and 0.9120. The ensemble AUC = 0.9369 (marked by red *, indicated by the arrow in the image). The highest individual model DenseNet121 has an AUC = 0.9355 (shown in blue + line).</p> Full article ">Figure 5
<p>POC test result: ROC curves for the proposed ensemble model (in red, AUC = 0.9369, 95% CI (0.8755, 0.9687)) and other models from the following: Oh et al. (patch-based) [<a href="#B35-healthcare-10-00175" class="html-bibr">35</a>] in green, AUC = 0.9144; Chen et al. (mmdetection) [<a href="#B36-healthcare-10-00175" class="html-bibr">36</a>] in blue, AUC = 0.8655; Ozturk et al. (Darknet) [<a href="#B37-healthcare-10-00175" class="html-bibr">37</a>] in black, AUC = 0.9051; and Minaee et al. (SqueezeNet) [<a href="#B38-healthcare-10-00175" class="html-bibr">38</a>] in cyan, AUC = 0.9002.</p> Full article ">Figure 6
<p>Deployment test result: ROC curves for the proposed ensemble model: AUC = 0.9456, maximum of F1 = 0.9118.</p> Full article ">Figure A1
<p>Distribution of SARS-CoV-2 RT-PCR Test Results of training set, Proof-of-Concept and Deployment datasets.</p> Full article ">Figure A2
<p>Selected true-positive example. The algorithm correctly diagnosed pneumonia in this case, where bilateral, multifocal airspace opacities are seen.</p> Full article ">Figure A3
<p>Selected false-positive example. This example demonstrates a potential pitfall in CXRs with prominent breast shadows.</p> Full article ">Figure A4
<p>Selected false-negative example. The airspace changes in this case are relatively mild, posing a greater challenge to the algorithm.</p> Full article ">
10 pages, 239 KiB  
Article
Correlations between Diabetes Mellitus Self-Care Activities and Glycaemic Control in the Adult Population: A Cross-Sectional Study
by Mihaela Simona Popoviciu, Violeta Nicoleta Marin, Cosmin Mihai Vesa, Simona Diana Stefan, Roxana Adriana Stoica, Cristian Serafinceanu, Emanuele Maria Merlo, Ali A Rizvi, Manfredi Rizzo, Stefan Busnatu and Anca Pantea Stoian
Healthcare 2022, 10(1), 174; https://doi.org/10.3390/healthcare10010174 - 17 Jan 2022
Cited by 28 | Viewed by 3708
Abstract
Although it is well known that lifestyle changes can affect plasma glucose levels, there is little formal evidence for the sustained effectiveness of exercise and diet in diabetes mellitus (DM) management. Self-care in DM refers to the real-life application of the knowledge that [...] Read more.
Although it is well known that lifestyle changes can affect plasma glucose levels, there is little formal evidence for the sustained effectiveness of exercise and diet in diabetes mellitus (DM) management. Self-care in DM refers to the real-life application of the knowledge that the patient gained during the education programmes. The goals are to bring about changes in the patient’s behaviour, thus improving glycaemic control. We evaluated the influence of DM self-care activities (SCA) on glycaemic control in a total of 159 patients with DM. Plasma glycated haemoglobin (HbA1c) levels were used to monitor glycaemic control, while SCA were assessed using the standardised Diabetes Self-Management Questionnaire (DSMQ). In our study, 53% of the patients had a HbA1c ≥ 7%. In univariate linear regression models, a statistically significant inverse association was observed between the HbA1c (the dependent variable) and both the DSMQ Dietary Control Score (R2 = 0.037, p = 0.0145) and the DSMQ Sum Score (R2 = 0.06, p = 0.0014). The mean absolute change in the HbA1c% associated with one standard deviation (SD) change in the DSMQ Sum Score, independent of the other significant variables retained in the compacted multivariate regression model, was −0.419% (confidence interval: 95%: from −0.18 to −0.65). Although the impact of the DSMQ Score was modest when compared to the other independent variables in the multivariate model, the findings emphasise the importance of maintaining optimal lifestyle changes to avoid hyperglycaemia and its complications. In conclusion, enhanced self-management of DM is associated with improved glucose control. In patients with chronic diseases such as DM, the role of streamlining SCA encompassing physical activity and proper dietary choices is imperative because of a significantly reduced access to healthcare globally as a result of the COVID-19 pandemic. Full article
(This article belongs to the Special Issue Diabetes and Comorbidities)
13 pages, 263 KiB  
Article
Association of Built Environmental Features with Rates of Infectious Diseases in Remote Indigenous Communities in the Northern Territory, Australia
by Amal Chakraborty, Victor Maduabuchi Oguoma, Neil T. Coffee, Peter Markey, Alwin Chong, Margaret Cargo and Mark Daniel
Healthcare 2022, 10(1), 173; https://doi.org/10.3390/healthcare10010173 - 17 Jan 2022
Cited by 2 | Viewed by 1914
Abstract
The health of Indigenous Australians is far poorer than non-Indigenous Australians, including an excess burden of infectious diseases. The health effect of built environmental (BE) features on Indigenous communities receives little attention. This study’s objective was to determine associations between BE features and [...] Read more.
The health of Indigenous Australians is far poorer than non-Indigenous Australians, including an excess burden of infectious diseases. The health effect of built environmental (BE) features on Indigenous communities receives little attention. This study’s objective was to determine associations between BE features and infectious disease incidence rates in remote Indigenous communities in the Northern Territory (NT), Australia. Remote Indigenous communities (n = 110) were spatially joined to 93 Indigenous Locations (ILOC). Outcomes data were extracted (NT Notifiable Diseases System) and expressed as ILOC-specific incidence rates. Counts of buildings were extracted from community asset maps and grouped by function. Age-adjusted infectious disease rates were dichotomised, and bivariate binomial regression used to determine the relationships between BE variables and infectious disease. Infrastructure Shelter BE features were universally associated with significantly elevated disease outcomes (relative risk 1.67 to 2.03). Significant associations were observed for Services, Arena, Community, Childcare, Oval, and Sports and recreation BE features. BE groupings associated with disease outcomes were those with communal and/or social design intent or use. Comparable BE groupings without this intent or use did not associate with disease outcomes. While discouraging use of communal BE features during infectious disease outbreaks is a conceptually valid countermeasure, communal activities have additional health benefits themselves, and infectious disease transmission could instead be reduced through repairs to infrastructure, and more infrastructure. This is the first study to examine these associations simultaneously in more than a handful of remote Indigenous communities to illustrate community-level rather than aggregated population-level associations. Full article
27 pages, 4641 KiB  
Review
Pathway of Trends and Technologies in Fall Detection: A Systematic Review
by Rohit Tanwar, Neha Nandal, Mazdak Zamani and Azizah Abdul Manaf
Healthcare 2022, 10(1), 172; https://doi.org/10.3390/healthcare10010172 - 17 Jan 2022
Cited by 45 | Viewed by 7714
Abstract
Falling is one of the most serious health risk problems throughout the world for elderly people. Considerable expenses are allocated for the treatment of after-fall injuries and emergency services after a fall. Fall risks and their effects would be substantially reduced if a [...] Read more.
Falling is one of the most serious health risk problems throughout the world for elderly people. Considerable expenses are allocated for the treatment of after-fall injuries and emergency services after a fall. Fall risks and their effects would be substantially reduced if a fall is predicted or detected accurately on time and prevented by providing timely help. Various methods have been proposed to prevent or predict falls in elderly people. This paper systematically reviews all the publications, projects, and patents around the world in the field of fall prediction, fall detection, and fall prevention. The related works are categorized based on the methodology which they used, their types, and their achievements. Full article
(This article belongs to the Special Issue Cybersecurity and the Digital Health: An Investigation on the State of the Art and the Position of the Actors)
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Figure 1
<p>Fall risk factors [<a href="#B11-healthcare-10-00172" class="html-bibr">11</a>].</p> Full article ">Figure 2
<p>Types of falls [<a href="#B8-healthcare-10-00172" class="html-bibr">8</a>,<a href="#B9-healthcare-10-00172" class="html-bibr">9</a>,<a href="#B10-healthcare-10-00172" class="html-bibr">10</a>].</p> Full article ">Figure 3
<p>Fall detection approaches [<a href="#B2-healthcare-10-00172" class="html-bibr">2</a>].</p> Full article ">Figure 4
<p>Review methodology.</p> Full article ">Figure 5
<p>Types of sensors used in fall detection.</p> Full article ">Figure 6
<p>Variation of the number of publications (per publisher).</p> Full article ">Figure 7
<p>Variation of the number of publications (publisher-wise).</p> Full article ">Figure 8
<p>Qualitative analysis of various fall prediction and prevention techniques.</p> Full article ">Figure 9
<p>Patents granted on fall prediction or detection.</p> Full article ">
10 pages, 821 KiB  
Article
Twelve-Week Lower Trapezius-Centred Muscular Training Regimen in University Archers
by Chien-Nan Liao, Chun-Hao Fan, Wei-Hsiu Hsu, Chia-Fang Chang, Pei-An Yu, Liang-Tseng Kuo, Bo-Ling Lu and Robert Wen-Wei Hsu
Healthcare 2022, 10(1), 171; https://doi.org/10.3390/healthcare10010171 - 17 Jan 2022
Cited by 5 | Viewed by 3502 | Correction
Abstract
Archery is a fine-motor-skill sport, in which success results from multiple factors including a fine neuromuscular tuning. The present study hypothesised that lower trapezius specific training can improve archers’ performance with concomitant changes in muscle activity and shoulder kinematics. We conducted a prospective [...] Read more.
Archery is a fine-motor-skill sport, in which success results from multiple factors including a fine neuromuscular tuning. The present study hypothesised that lower trapezius specific training can improve archers’ performance with concomitant changes in muscle activity and shoulder kinematics. We conducted a prospective study in a university archery team. Athletes were classified into exercise and control groups. A supervised lower trapezius muscle training program was performed for 12 weeks in the exercise group. The exercise program focused on a lower trapezius-centred muscular training. Performance in a simulated game was recorded as the primary outcome, and shoulder muscle strength, kinematics, and surface electromyography were measured and analysed. In the exercise group, the average score of the simulation game increased from 628 to 639 after the training regimens (maximum score was 720), while there were no such increases in the control group. The lower trapezius muscle strength increased from 8 to 9 kgf after training regimens and shoulder horizontal abductor also increased from 81 to 93 body weight% for the exercise group. The upper/lower trapezius ratio decreased from 2.2 to 1.1 after training. The lower trapezius exercise training regimen could effectively improve the performance of an archer with a simultaneous increase in shoulder horizontal abductor and lower trapezius muscle strength. Full article
(This article belongs to the Special Issue Improving Athletes’ Performance and Avoiding Health Issues)
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<p>Scores of simulation game. * <span class="html-italic">p</span> ≤ 0.05 between pre- and post-exercise.</p> Full article ">Figure 2
<p>(<b>A</b>). Lower trapezius muscle strength of bow side; (<b>B</b>). Horizontal abductor of bow side. * <span class="html-italic">p</span> ≤ 0.05 between pre- and post-exercise.</p> Full article ">Figure 3
<p>Upper trapezius/lower trapezius ratio as indicated through electromyography. * <span class="html-italic">p</span> ≤ 0.05 between pre- and post-exercise.</p> Full article ">
11 pages, 1871 KiB  
Article
An Abrupt Transition to Digital Teaching—Norwegian Medical Students and Their Experiences of Learning Output during the Initial Phase of the COVID-19 Lockdown
by Henriette K. Helland, Thorkild Tylleskär, Monika Kvernenes and Håkon Reikvam
Healthcare 2022, 10(1), 170; https://doi.org/10.3390/healthcare10010170 - 17 Jan 2022
Cited by 5 | Viewed by 2141
Abstract
Norwegian universities closed almost all on-campus activities on the 12 March 2020 following a lockdown decision of the Norwegian government in response to the COVID-19 pandemic. Online and digital teaching became the primary method of teaching. The goal of this study was to [...] Read more.
Norwegian universities closed almost all on-campus activities on the 12 March 2020 following a lockdown decision of the Norwegian government in response to the COVID-19 pandemic. Online and digital teaching became the primary method of teaching. The goal of this study was to investigate how the transition to digital education impacted on medical students enrolled at the University of Bergen (UiB). Key points were motivation, experience of learning outcomes, and fear of missing out on important learning. Using an online questionnaire, students were asked to evaluate the quality of both lectures and taught clinical skills and to elaborate on their experience of learning output, examination, and digital teaching. Answers from 230 students were included in the study. Opinions on the quality and quantity of lectures offered and their experience of learning output varied based on gender, seniority and the amount of time spent on part time jobs. Students at UiB were generally unhappy with the quality of teaching, especially lessons on clinical skills, although both positive and negative experiences were reported. Securing a satisfying offer of clinical teaching will be important to ensure and increase the student experience of learning output in the time ahead. Full article
(This article belongs to the Collection E-learning and Digital Training in Healthcare Education: Current Trends and New Challenges)
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<p>Student experience expressed on a Likert scale regarding technical, academic, and pedagogical quality on pre-recorded PowerPoint with sound, pre-recorded video lectures and live video lectures.</p> Full article ">Figure 2
<p>Distribution of agreement, disagreement, or neutral view on statements regarding clinical and practical education.</p> Full article ">Figure 3
<p>Likert scale mean value on student opinion regarding clinical and practical education depending on semester of study. Learning output: My learning output from digital clinical and practical teaching has been the same as with physical teaching.</p> Full article ">Figure 4
<p>Student attitude to questions regarding their own learning experience this semester. Information: Necessary information about changes in education offer has been given; Learning output: My learning output during digital teaching has been equal to that of physical teaching; Knowledge acquired: I have acquired the necessary amount of knowledge during digital teaching; Motivation: I have been motivated for learning during digital teaching; Potential loss of knowledge: I am anxious that digital teaching has caused me to miss out on important knowledge; Positivity towards digital teaching: I have a positive attitude towards the possibility of digital teaching the next semester.</p> Full article ">
12 pages, 1258 KiB  
Article
A Noninvasive Risk Stratification Tool Build Using an Artificial Intelligence Approach for Colorectal Polyps Based on Annual Checkup Data
by Chieh Lee, Tsung-Hsing Lin, Chen-Ju Lin, Chang-Fu Kuo, Betty Chien-Jung Pai, Hao-Tsai Cheng, Cheng-Chou Lai and Tsung-Hsing Chen
Healthcare 2022, 10(1), 169; https://doi.org/10.3390/healthcare10010169 - 17 Jan 2022
Cited by 4 | Viewed by 2567
Abstract
Colorectal cancer is the leading cause of cancer-related deaths worldwide, and early detection has proven to be an effective method for reducing mortality. The machine learning method can be implemented to build a noninvasive stratifying tool that helps identify patients with potential colorectal [...] Read more.
Colorectal cancer is the leading cause of cancer-related deaths worldwide, and early detection has proven to be an effective method for reducing mortality. The machine learning method can be implemented to build a noninvasive stratifying tool that helps identify patients with potential colorectal precancerous lesions (polyps). This study aimed to develop a noninvasive risk-stratified tool for colorectal polyps in asymptomatic, healthy participants. A total of 20,129 consecutive asymptomatic patients who underwent a health checkup between January 2005 and August 2007 were recruited. Positive relationships between noninvasive risk factors, such as age, Helicobacter pylori infection, hypertension, gallbladder polyps/stone, and BMI and colorectal polyps were observed (p < 0.0001), regardless of sex, whereas significant findings were noted in men with tooth disease (p = 0.0053). A risk stratification tool was developed, for colorectal polyps, that considers annual checkup results from noninvasive examinations. For the noninvasive stratified tool, the area under the receiver operating characteristic curve (AUC) of obese females (males) aged <50 years was 91% (83%). In elderly patients (>50 years old), the AUCs of the stratifying tools were >85%. Our results indicate that the risk stratification tool can be built by using random forest and serve as an efficient noninvasive tool to identify patients requiring colonoscopy. Full article
(This article belongs to the Special Issue Artificial Intelligence (AI) and Machine Learning (ML) in Human Health and Healthcare)
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<p>Diagram for proposed <span class="html-italic">Heuristic</span>.</p> Full article ">Figure 2
<p>Forest chart of colorectal polyps’ risk factors in female patients. Underweight = 0, normal = 1, overweight = 2, and obesity = 3.</p> Full article ">Figure 3
<p>Forest chart of colorectal polyps’ risk factors in male patients. Underweight = 0, normal = 1, overweight = 2, and obesity = 3.</p> Full article ">
11 pages, 918 KiB  
Review
The Potential Benefit of Hydroxychloroquine in Chronic Placental Inflammation of Unknown Etiology Associated with Adverse Pregnancy Outcomes
by Alexandra Bouariu, Nicolae Gică, Anca Marina Ciobanu, Ana Maria Scutelnicu, Mihaela Roxana Popescu and Anca Maria Panaitescu
Healthcare 2022, 10(1), 168; https://doi.org/10.3390/healthcare10010168 - 17 Jan 2022
Cited by 6 | Viewed by 3107
Abstract
The placenta is the site of connection between maternal and fetal circulation, and the liaison is established early in pregnancy. A large variety of pregnancy complications such as preterm birth, fetal growth restriction, or pregnancy loss have placental expression and can be accompanied [...] Read more.
The placenta is the site of connection between maternal and fetal circulation, and the liaison is established early in pregnancy. A large variety of pregnancy complications such as preterm birth, fetal growth restriction, or pregnancy loss have placental expression and can be accompanied in some cases of acute or chronic identifiable placental inflamatory lesions. Chronic placental inflammatory (CPI) lesions include chronic villitis of unknow etiology (CVUE), chronic intervillositis of unknown etiology, CIUE (also described as chronic histiocytic intervillositis, CHI), and chronic deciduits. Hydroxychloroquine (HCQ) has been prescribed with good results during pregnancy to prevent adverse perinatal outcomes in maternal autoimmune conditions. Its success has paved the way to its use in CPI as CIUE/CHI; however, to date, there are no prospective, informatively designed, controlled studies on its value in these setting. This review aims to explore the potential role of HCQ in CPI of unknown etiology. Ideally, properly designed, probably multicentric studies should be undertaken to fully understand HCQ’s role for prevention of adverse pregnancy outcomes after a chronic placental inflammation. Full article
(This article belongs to the Special Issue Maternal Nutrition on Neonatal Health)
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<p>Steps in the clinical management of adverse pregnancy outcomes associated with placental inflammation; the focus is on prevention in subsequent pregnancies.</p> Full article ">Figure 2
<p>Chronic placenta inflammation is found in some cases of preterm birth (PTB), fetal growth restriction (FGR) and preeclampsia (PE), miscarriage, and stillbirth. These “great obstetrical syndromes” may share a common pathophysiology.</p> Full article ">
11 pages, 1481 KiB  
Article
Sociodemographic and Clinical Characteristics Associated with Improvements in Quality of Life for Participants with Opioid Use Disorder
by Assaf Gottlieb, Christine Bakos-Block, James R. Langabeer and Tiffany Champagne-Langabeer
Healthcare 2022, 10(1), 167; https://doi.org/10.3390/healthcare10010167 - 16 Jan 2022
Cited by 5 | Viewed by 2306
Abstract
Background: The Houston Emergency Opioid Engagement System was established to create an access pathway into long-term recovery for individuals with opioid use disorder. The program determines effectiveness across multiple dimensions, one of which is by measuring the participant’s reported quality of life (QoL) [...] Read more.
Background: The Houston Emergency Opioid Engagement System was established to create an access pathway into long-term recovery for individuals with opioid use disorder. The program determines effectiveness across multiple dimensions, one of which is by measuring the participant’s reported quality of life (QoL) at the beginning of the program and at successive intervals. Methods: A visual analog scale was used to measure the change in QoL among participants after joining the program. We then identified sociodemographic and clinical characteristics associated with changes in QoL. Results: 71% of the participants (n = 494) experienced an increase in their QoL scores, with an average improvement of 15.8 ± 29 points out of a hundred. We identified 10 factors associated with a significant change in QoL. Participants who relapsed during treatment experienced minor increases in QoL, and participants who attended professional counseling experienced the largest increases in QoL compared with those who did not. Conclusions: Insight into significant factors associated with increases in QoL may inform programs on areas of focus. The inclusion of counseling and other services that address factors such as psychological distress were found to increase participants’ QoL and success in recovery. Full article
(This article belongs to the Special Issue Qualitative Health Research Applied to Clinical and Educational Settings)
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<p>Histogram of the number of QoL assessments conducted per individual after the baseline assessment. #, Number.</p> Full article ">Figure 2
<p>Histogram of the first (<b>Top</b>) and last (<b>Bottom</b>) time for QoL assessment in days from baseline.</p> Full article ">Figure 3
<p>Histogram of baseline QoL scores.</p> Full article ">Figure 4
<p>Histogram of the average (<b>Top</b>) and last (<b>Bottom</b>) change in QoL scores from baseline.</p> Full article ">Figure 5
<p>Scatter plot of the change in QoL scores relative to baseline scores.</p> Full article ">
26 pages, 75205 KiB  
Article
Deep Ensemble Learning-Based Models for Diagnosis of COVID-19 from Chest CT Images
by Mohamed Mouhafid, Mokhtar Salah, Chi Yue and Kewen Xia
Healthcare 2022, 10(1), 166; https://doi.org/10.3390/healthcare10010166 - 15 Jan 2022
Cited by 16 | Viewed by 3068
Abstract
Novel coronavirus (COVID-19) has been endangering human health and life since 2019. The timely quarantine, diagnosis, and treatment of infected people are the most necessary and important work. The most widely used method of detecting COVID-19 is real-time polymerase chain reaction (RT-PCR). Along [...] Read more.
Novel coronavirus (COVID-19) has been endangering human health and life since 2019. The timely quarantine, diagnosis, and treatment of infected people are the most necessary and important work. The most widely used method of detecting COVID-19 is real-time polymerase chain reaction (RT-PCR). Along with RT-PCR, computed tomography (CT) has become a vital technique in diagnosing and managing COVID-19 patients. COVID-19 reveals a number of radiological signatures that can be easily recognized through chest CT. These signatures must be analyzed by radiologists. It is, however, an error-prone and time-consuming process. Deep Learning-based methods can be used to perform automatic chest CT analysis, which may shorten the analysis time. The aim of this study is to design a robust and rapid medical recognition system to identify positive cases in chest CT images using three Ensemble Learning-based models. There are several techniques in Deep Learning for developing a detection system. In this paper, we employed Transfer Learning. With this technique, we can apply the knowledge obtained from a pre-trained Convolutional Neural Network (CNN) to a different but related task. In order to ensure the robustness of the proposed system for identifying positive cases in chest CT images, we used two Ensemble Learning methods namely Stacking and Weighted Average Ensemble (WAE) to combine the performances of three fine-tuned Base-Learners (VGG19, ResNet50, and DenseNet201). For Stacking, we explored 2-Levels and 3-Levels Stacking. The three generated Ensemble Learning-based models were trained on two chest CT datasets. A variety of common evaluation measures (accuracy, recall, precision, and F1-score) are used to perform a comparative analysis of each method. The experimental results show that the WAE method provides the most reliable performance, achieving a high recall value which is a desirable outcome in medical applications as it poses a greater risk if a true infected patient is not identified. Full article
(This article belongs to the Topic Artificial Intelligence in Healthcare)
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<p>Flowchart of the Ensemble Learning framework.</p> Full article ">Figure 2
<p>The detailed number of patients considered to compose SARS-CoV-2 CT-scan dataset [<a href="#B42-healthcare-10-00166" class="html-bibr">42</a>].</p> Full article ">Figure 3
<p>(<b>A</b>) Shows a CT of the lungs of COVID-19 (+) patient, in which a ground-glass opacity is visible in the lower lobes (red arrows). (<b>B</b>) Represents a CT of the lungs of COVID-19 (−) patient, in which there are no abnormalities. (<b>C</b>) Depicts infected patch samples. (<b>D</b>) Reflects non-infected patch samples. SARS-CoV-2 CT-scan dataset [<a href="#B42-healthcare-10-00166" class="html-bibr">42</a>] is the source for these images.</p> Full article ">Figure 4
<p>Age distribution of COVID-19 (+) patients.</p> Full article ">Figure 5
<p>The gender ratio of COVID-19 (+) patients.</p> Full article ">Figure 6
<p>(<b>A</b>) Shows a CT of the lungs of COVID-19 (+) patient, in which there are multiple patchy ground-glass opacities in bilateral subpleural areas indicated by red arrows. (<b>B</b>) Represents a CT of the lungs of a COVID-19 (−) patient with normal controls. (<b>C</b>) Depicts infected patch samples. (<b>D</b>) Reflects non-infected patch samples. COVID-CT dataset [<a href="#B22-healthcare-10-00166" class="html-bibr">22</a>] is the source for these images.</p> Full article ">Figure 7
<p>Transfer Learning approach.</p> Full article ">Figure 8
<p>Representation of the convolution operation.</p> Full article ">Figure 9
<p>Representation of the flattening operation.</p> Full article ">Figure 10
<p>An example of a drop-out layer with a 50% drop-out probability.</p> Full article ">Figure 11
<p>Architecture of modified VGG19. Conv: Convolutional Layer.</p> Full article ">Figure 12
<p>Architecture of modified ResNet50.</p> Full article ">Figure 13
<p>Architecture of modified DenseNet201.</p> Full article ">Figure 14
<p>Representation of the 2-Levels Stacking approach.</p> Full article ">Figure 15
<p>Representation of the 3-Levels Stacking approach.</p> Full article ">Figure 16
<p>Representation of the Logistic Function (The values of this function have been plotted as <math display="inline"><semantics> <mi>z</mi> </semantics></math> varies from −∞ to +∞).</p> Full article ">Figure 17
<p>Representation of the Weighted Average Ensemble approach.</p> Full article ">Figure 18
<p>The optimal weights received for the Base-Learners based on the performance of the recall score function on the SARS-CoV-2 CT-scan dataset [<a href="#B42-healthcare-10-00166" class="html-bibr">42</a>] (note that the weights range between 0 and 1).</p> Full article ">Figure 19
<p>Grad-CAM visualizations. (<b>A</b>) Sample CT images from the SARS-CoV-2 CT-scan dataset [<a href="#B42-healthcare-10-00166" class="html-bibr">42</a>]. (<b>B</b>) Sample CT images from the COVID-CT dataset [<a href="#B22-healthcare-10-00166" class="html-bibr">22</a>].</p> Full article ">Figure 20
<p>The performance evaluation metrics on both chest CT datasets for all studied models.</p> Full article ">
11 pages, 474 KiB  
Article
Impact of a Digital Intervention for Literacy in Depression among Portuguese University Students: A Randomized Controlled Trial
by Lersi D. Durán, Ana Margarida Almeida, Ana Cristina Lopes and Margarida Figueiredo-Braga
Healthcare 2022, 10(1), 165; https://doi.org/10.3390/healthcare10010165 - 15 Jan 2022
Cited by 2 | Viewed by 2224
Abstract
Digital interventions are important tools to promote mental health literacy among university students. “Depression in Portuguese University Students” (Depressão em Estudantes Universitários Portugueses, DEEP) is an audiovisual intervention describing how symptoms can be identified and what possible treatments can be applied. The aim [...] Read more.
Digital interventions are important tools to promote mental health literacy among university students. “Depression in Portuguese University Students” (Depressão em Estudantes Universitários Portugueses, DEEP) is an audiovisual intervention describing how symptoms can be identified and what possible treatments can be applied. The aim of this study was to evaluate the impact of this intervention. A random sample of 98 students, aged 20–38 years old, participated in a 12-week study. Participants were recruited through social media by the academic services and institutional emails of two Portuguese universities. Participants were contacted and distributed into four study groups (G1, G2, G3 and G4): G1 received the DEEP intervention in audiovisual format; G2 was given the DEEP in text format; G3 received four news articles on depression; G4 was the control group. A questionnaire was shared to collect socio-demographic and depression knowledge data as a pre-intervention method; content was then distributed to each group following a set schedule; the depression knowledge questionnaire was then administered to compare pre-intervention, post-intervention and follow-up literacy levels. Using the Scheffé and Least Significant Difference (LSD) multiple comparisons test, it was found that G1, which received the DEEP audiovisual intervention, differed significantly from the other groups, with higher depression knowledge scores in post-intervention stages. The DEEP audiovisual intervention, compared to the other formats used (narrative text format; news format), proved to be an effective tool for increasing depression knowledge in university students. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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<p>Timeline of the assessment design.</p> Full article ">
24 pages, 2114 KiB  
Article
Using Simulation Optimization to Solve Patient Appointment Scheduling and Examination Room Assignment Problems for Patients Undergoing Ultrasound Examination
by Ping-Shun Chen, Gary Yu-Hsin Chen, Li-Wen Liu, Ching-Ping Zheng and Wen-Tso Huang
Healthcare 2022, 10(1), 164; https://doi.org/10.3390/healthcare10010164 - 15 Jan 2022
Cited by 9 | Viewed by 4059
Abstract
This study investigates patient appointment scheduling and examination room assignment problems involving patients who undergo ultrasound examination with considerations of multiple examination rooms, multiple types of patients, multiple body parts to be examined, and special restrictions. Following are the recommended time intervals based [...] Read more.
This study investigates patient appointment scheduling and examination room assignment problems involving patients who undergo ultrasound examination with considerations of multiple examination rooms, multiple types of patients, multiple body parts to be examined, and special restrictions. Following are the recommended time intervals based on the findings of three scenarios in this study: In Scenario 1, the time interval recommended for patients’ arrival at the radiology department on the day of the examination is 18 min. In Scenario 2, it is best to assign patients to examination rooms based on weighted cumulative examination points. In Scenario 3, we recommend that three outpatients come to the radiology department every 18 min to undergo ultrasound examinations; the number of inpatients and emergency patients arriving for ultrasound examination is consistent with the original time interval distribution. Simulation optimization may provide solutions to the problems of appointment scheduling and examination room assignment problems to balance the workload of radiological technologists, maintain high equipment utilization rates, and reduce waiting times for patients undergoing ultrasound examination. Full article
(This article belongs to the Special Issue Management and Automation of Health Organizations)
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<p>The flowchart of patient’s appointment procedure at the radiology department.</p> Full article ">Figure 2
<p>The flowchart of patient-examination room assignment at the radiology department.</p> Full article ">Figure 3
<p>The warm-up period of the simulation model in this study.</p> Full article ">Figure 4
<p>(<b>a</b>) Simulation of the logic for assigning patients to the ultrasound examination rooms. (<b>b</b>) Simulation of the ultrasound examination processes.</p> Full article ">Figure 4 Cont.
<p>(<b>a</b>) Simulation of the logic for assigning patients to the ultrasound examination rooms. (<b>b</b>) Simulation of the ultrasound examination processes.</p> Full article ">Figure 5
<p>The results of optimization performed by the simulation model at different time intervals.</p> Full article ">Figure 6
<p>The best four feasible solutions after optimization.</p> Full article ">
13 pages, 2141 KiB  
Article
Solving Patient Allocation Problem during an Epidemic Dengue Fever Outbreak by Mathematical Modelling
by Jung-Fa Tsai, Tai-Lin Chu, Edgar Hernan Cuevas Brun and Ming-Hua Lin
Healthcare 2022, 10(1), 163; https://doi.org/10.3390/healthcare10010163 - 15 Jan 2022
Cited by 6 | Viewed by 2762
Abstract
Dengue fever is a mosquito-borne disease that has rapidly spread throughout the last few decades. Most preventive mechanisms to deal with the disease focus on the eradication of the vector mosquito and vaccination campaigns. However, appropriate mechanisms of response are indispensable to face [...] Read more.
Dengue fever is a mosquito-borne disease that has rapidly spread throughout the last few decades. Most preventive mechanisms to deal with the disease focus on the eradication of the vector mosquito and vaccination campaigns. However, appropriate mechanisms of response are indispensable to face the consequent events when an outbreak takes place. This study applied single and multiple objective linear programming models to optimize the allocation of patients and additional resources during an epidemic dengue fever outbreak, minimizing the summation of the distance travelled by all patients. An empirical study was set in Ciudad del Este, Paraguay. Data provided by a privately run health insurance cooperative was used to verify the applicability of the models in this study. The results can be used by analysts and decision makers to solve patient allocation problems for providing essential medical care during an epidemic dengue fever outbreak. Full article
(This article belongs to the Special Issue Computing and Artificial Intelligence Techniques for Healthcare Applications: Second Edition)
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<p>Population areas and hospitals in the map of Ciudad del Este.</p> Full article ">Figure 2
<p>Objective function values (in kilometers) and number of patients during the six-week period.</p> Full article ">
9 pages, 1238 KiB  
Article
Clinical Study on the Efficacy and Safety of Arginine Administered Orally in Association with Other Active Ingredients for the Prevention and Treatment of Sarcopenia in Patients with COVID-19-Related Pneumonia, Hospitalized in a Sub-Intensive Care Unit
by Carolina Bologna and Eduardo Pone
Healthcare 2022, 10(1), 162; https://doi.org/10.3390/healthcare10010162 - 14 Jan 2022
Cited by 10 | Viewed by 4057
Abstract
In order to evaluate the efficacy of oral supplementation with 3 g of arginine per day associated with creatine, L-carnitine, aspartic acid, magnesium, selenium and vitamins C and E (Argivit© Aesculapius Farmaceutici) in the prevention and treatment of sarcopenia in patients with COVID-19-related [...] Read more.
In order to evaluate the efficacy of oral supplementation with 3 g of arginine per day associated with creatine, L-carnitine, aspartic acid, magnesium, selenium and vitamins C and E (Argivit© Aesculapius Farmaceutici) in the prevention and treatment of sarcopenia in patients with COVID-19-related pneumonia, we conducted a parallel randomized study comparing it with standard therapy alone. Forty patients on standard therapy plus supplementation were compared with a control group of 40 patients, all hospitalized at the sub-intensive care unit of the Del Mare Hospital in Naples, with a clinical diagnosis of SARS-CoV-2 infection and COVID-19 pneumonia. Muscle strength was assessed with the handgrip test and muscle ultrasound. Arginine-supplemented patients had an average grip strength of 23.5 at the end of hospitalization compared with 22.5 in the untreated group with less reduction, showing statistical significance (p < 0.001). In the same way, the thickness of the vastus lateralis quadriceps femoris muscle measured at the end of hospitalization showed less reduction on ultrasound, with a higher average value in the group receiving treatment than in the group of patients without supplementation (p < 0.001). Upon discharge there was a 58.40% reduction in ventilation days in patients with arginine supplementation compared with the control group. Full article
(This article belongs to the Special Issue COVID-19 after One Year of Clinical Experience: Unexpected Clinical Presentations or Complications and Post-COVID-19 Clinical Features)
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<p>Handgrip test at T0 and T1. There is a better control of the grip strength (handgrip) for the treated subjects compared to the control group (<span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 2
<p>Strength assessment: right vastus lateralis muscle thickness. A maintenance of the right vastus lateralis muscle thickness was observed for the treated subjects compared to the control group (<span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 3
<p>BMI T0 and T1. There is a conservation of the body mass index (BMI) for the treated subjects compared to the control group (<span class="html-italic">p</span> &lt; 0.015).</p> Full article ">Figure 4
<p>Days of ventilation at discharge. There was a 58.40% reduction in ventilation days in treated subjects compared to the control group (<span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 5
<p>Number of total days of hospitalization. At discharge there was a 9.63% reduction in the number of total hospitalization days for the treated subjects compared to the control group (<span class="html-italic">p</span> &lt; 0.020).</p> Full article ">Figure 6
<p>Need for orotracheal intubation and transfer to intensive care unit. Number of ICU transfers for treated subjects and control group (<span class="html-italic">p</span> = 0.481).</p> Full article ">
9 pages, 422 KiB  
Project Report
Postcode Lottery in Healthcare? Findings from the Scottish National Comprehensive Geriatric Assessment in Secondary Care Audit 2019
by Catriona Young, Alison I. C. Donaldson, Christine H. McAlpine, Marc Locherty, Adrian D. Wood and Phyo Kyaw Myint
Healthcare 2022, 10(1), 161; https://doi.org/10.3390/healthcare10010161 - 14 Jan 2022
Viewed by 2328
Abstract
Comprehensive Geriatric Assessment (CGA) is provided differently across Scotland. The Scottish Care of Older People (SCoOP) CGA Audit was a national audit conducted in 2019 to assess this variation in acute hospitals. Two versions of audit questionnaires about the provision of CGA were [...] Read more.
Comprehensive Geriatric Assessment (CGA) is provided differently across Scotland. The Scottish Care of Older People (SCoOP) CGA Audit was a national audit conducted in 2019 to assess this variation in acute hospitals. Two versions of audit questionnaires about the provision of CGA were developed (one each for larger hospitals and remote/rural areas) and piloted. The questionnaires were sent to representatives from all hospitals in Scotland using the REDCap (Research Electronic Data Capture) system. The survey asked each service to provide information on CGA service delivery at the ‘front door’. The questionnaire was open for completion between February and July 2019. Of the 28 Scottish hospitals which receive acute admissions, we received information from 26 (92.9% response rate). Reporting sites included seven hospitals from remote and rural locations in the Scottish Highlands and Islands. Significant variations were observed across participating sites for all key aspects studied: dedicated frailty units, routes of admission, staffing, liaison with other services and rehabilitation provision. The 2019 SCoOP CGA audit highlights areas of CGA services that could be improved and variation in specialist CGA service access, structure and staffing at the front door across Scotland. Whether this variation has an impact on the outcomes of older people requires further evaluation. Full article
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<p>Operational hours of the frailty units.</p> Full article ">
11 pages, 907 KiB  
Article
Cost-Effectiveness of Upper Extremity Dry Needling in Chronic Stroke
by Daniel Fernández-Sanchis, Natalia Brandín-de la Cruz, Carolina Jiménez-Sánchez, Marina Gil-Calvo, Pablo Herrero and Sandra Calvo
Healthcare 2022, 10(1), 160; https://doi.org/10.3390/healthcare10010160 - 14 Jan 2022
Cited by 10 | Viewed by 2769
Abstract
Introduction: Dry needling is a non-pharmacological approach that has proven to be effective in different neurological conditions. Objective: The aim of this study was to evaluate the cost-effectiveness of a single dry needling session in patients with chronic stroke. Methods: A cost-effectiveness analysis [...] Read more.
Introduction: Dry needling is a non-pharmacological approach that has proven to be effective in different neurological conditions. Objective: The aim of this study was to evaluate the cost-effectiveness of a single dry needling session in patients with chronic stroke. Methods: A cost-effectiveness analysis was performed based on a randomized controlled clinical trial. The results obtained from the values of the EuroQol-5D questionnaire and the Modified Modified Ashworth Scale were processed in order to obtain the percentage of treatment responders and the quality-adjusted life years (QALYs) for each alternative. The cost analysis was that of the hospital, clinic, or health center, including the equipment and physiotherapist. The cost per respondent and the incremental cost-effectiveness ratio of each alternative were assessed. Results: Twenty-three patients with stroke were selected. The cost of DN treatment was EUR 14.96, and the data analysis showed a favorable cost-effectiveness ratio of both EUR/QALY and EUR/responder for IG, although the sensitivity analysis using limit values did not confirm the dominance (higher effectiveness with less cost) of the dry needling over the sham dry needling. Conclusions: Dry needling is an affordable alternative with good results in the cost-effectiveness analysis—both immediately, and after two weeks of treatment—compared to sham dry needling in persons with chronic stroke. Full article
(This article belongs to the Special Issue Neurorehabilitation: Looking Back and Moving Forward)
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<p>Variation of QOL during the study timeline. Abbreviations—IG: intervention group; SG: sham group. * <span class="html-italic">p</span> &lt; 0.05 within IG; ** <span class="html-italic">p</span> &lt; 0.05 between IG and SG.</p> Full article ">Figure 2
<p>Cost-effectiveness plane. The average, minimum, and maximum values of the IG and SG are shown on the right-hand side of the cost-effectiveness threshold of EUR 20,000/QALY. Abbreviations—IG: intervention group; SG: sham group.</p> Full article ">
17 pages, 1623 KiB  
Perspective
Information Security in Medical Robotics: A Survey on the Level of Training, Awareness and Use of the Physiotherapist
by Lisa Monoscalco, Rossella Simeoni, Giovanni Maccioni and Daniele Giansanti
Healthcare 2022, 10(1), 159; https://doi.org/10.3390/healthcare10010159 - 14 Jan 2022
Cited by 8 | Viewed by 2961
Abstract
Cybersecurity is becoming an increasingly important aspect to investigate for the adoption and use of care robots, in term of both patients’ safety, and the availability, integrity and privacy of their data. This study focuses on opinions about cybersecurity relevance and related skills [...] Read more.
Cybersecurity is becoming an increasingly important aspect to investigate for the adoption and use of care robots, in term of both patients’ safety, and the availability, integrity and privacy of their data. This study focuses on opinions about cybersecurity relevance and related skills for physiotherapists involved in rehabilitation and assistance thanks to the aid of robotics. The goal was to investigate the awareness among insiders about some facets of cybersecurity concerning human–robot interactions. We designed an electronic questionnaire and submitted it to a relevant sample of physiotherapists. The questionnaire allowed us to collect data related to: (i) use of robots and its relationship with cybersecurity in the context of physiotherapy; (ii) training in cybersecurity and robotics for the insiders; (iii) insiders’ self-assessment on cybersecurity and robotics in some usage scenarios, and (iv) their experiences of cyber-attacks in this area and proposals for improvement. Besides contributing some specific statistics, the study highlights the importance of both acculturation processes in this field and monitoring initiatives based on surveys. The study exposes direct suggestions for continuation of these types of investigations in the context of scientific societies operating in the rehabilitation and assistance robotics. The study also shows the need to stimulate similar initiatives in other sectors of medical robotics (robotic surgery, care and socially assistive robots, rehabilitation systems, training for health and care workers) involving insiders. Full article
(This article belongs to the Special Issue Rehabilitation and Robotics: Are They Working Well Together?)
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<p>Model of the impact of the cyber-attacks in the investigated field.</p> Full article ">Figure 2
<p>Diagram describing the inclusion process.</p> Full article ">Figure 3
<p>Use of rehabilitation robotics in the <span class="html-italic">workplace (* 102 is different from the sum of the three choices, because it is a multiple-choice question)</span>.</p> Full article ">Figure 4
<p>Role of the use of rehabilitation robotics by physiotherapists.</p> Full article ">Figure 5
<p>Physiotherapists’ interaction with social robots.</p> Full article ">Figure 6
<p>Level of training on the regulatory framework (also referred to robotics).</p> Full article ">Figure 7
<p>Level of awareness on the role of the physiotherapist on Cyb.</p> Full article ">Figure 8
<p>Experiences with cyber-attacks which occurred more than one time after categorization.</p> Full article ">
11 pages, 11409 KiB  
Case Report
Giant Sternal Chondrosarcoma in a 50-Year-Old Patient
by Cezar Pavelescu, Alexandru Bebliuc, Rareș Asmarandei, Maria Sabina Safta, Ondin Zaharia, Victor Sebastian Costache, Adrian Molnar, Daniela Gheorghiță, Cristian Voica and Horațiu Moldovan
Healthcare 2022, 10(1), 158; https://doi.org/10.3390/healthcare10010158 - 14 Jan 2022
Cited by 2 | Viewed by 2109
Abstract
Chondrosarcomas represent approximately 20% of primary malignant bone cancers, being known as the most frequent neoplasia of the anterior thoracic wall. In our case, we present a case of a primary sternal chondrosarcoma in a 50-year-old female patient that has been polychemiotherapy and [...] Read more.
Chondrosarcomas represent approximately 20% of primary malignant bone cancers, being known as the most frequent neoplasia of the anterior thoracic wall. In our case, we present a case of a primary sternal chondrosarcoma in a 50-year-old female patient that has been polychemiotherapy and radiotherapy treated for breast cancer. Despite the initial treated malignancy of breast cancer in the personal pathologic history of the patient, it was discovered that the sternal tumor was not a metastatic disease from the breast neoplasm. After multiple investigations, the patient was successfully treated for the sternal chondrosarcoma after a radical sternal resection with a chest wall reconstruction completed with two titanium plates that were anchored on the ribs and with the placement of methyl methacrylate mesh. Full article
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<p>Histopathology images from the biopsy, H&amp;E stain: (<b>A</b>)—20× and (<b>B</b>)—40× resolution.</p> Full article ">Figure 2
<p>Initial CT aspect.</p> Full article ">Figure 3
<p>PET-CT scan.</p> Full article ">Figure 4
<p>Immunohistochemistry images showing marker CD 34 positive for sternal chondrosarcoma.</p> Full article ">Figure 5
<p>Immunohistochemistry images showing marker p63 positive for sternal chondrosarcoma: (<b>A</b>)—20× and (<b>B</b>)—40× resolution.</p> Full article ">Figure 6
<p>Immunohistochemistry images showing marker S100 positive for sternal chondrosarcoma: (<b>A</b>)—20× and (<b>B</b>)—40× resolution.</p> Full article ">Figure 7
<p>Preoperative CT scan (transversal view).</p> Full article ">Figure 8
<p>Preoperative CT scan (sagittal view).</p> Full article ">Figure 9
<p>Preoperative aspect of the tumor.</p> Full article ">Figure 10
<p>Intraoperative aspect, after tumor resection.</p> Full article ">Figure 11
<p>The isolated left brachiocephalic trunk, during surgery.</p> Full article ">Figure 12
<p>Thoracic wall reconstruction aspect.</p> Full article ">Figure 13
<p>Final postoperative aspect.</p> Full article ">
10 pages, 273 KiB  
Article
The Prevalence, Management and Impact of Dysmenorrhea on Medical Students’ Lives—A Multicenter Study
by Romina-Marina Sima, Mihaela Sulea, Julia Caroline Radosa, Sebastian Findeklee, Bashar Haj Hamoud, Mihai Popescu, Gabriel Petre Gorecki, Anca Bobircă, Florin Bobirca, Catalin Cirstoveanu and Liana Ples
Healthcare 2022, 10(1), 157; https://doi.org/10.3390/healthcare10010157 - 14 Jan 2022
Cited by 11 | Viewed by 7079
Abstract
Introduction: Dysmenorrhea is defined as the presence of painful menstruation, and it affects daily activities in different ways. The aims of this study were to assess the prevalence and management of dysmenorrhea and to determine the impact of dysmenorrhea on the quality of [...] Read more.
Introduction: Dysmenorrhea is defined as the presence of painful menstruation, and it affects daily activities in different ways. The aims of this study were to assess the prevalence and management of dysmenorrhea and to determine the impact of dysmenorrhea on the quality of life of medical students. Material and methods: The study conducted was prospective, analytical and observational and was performed between 7 November 2019 and 30 January 2020 in five university centers from Romania. The data was collected using an original questionnaire regarding menstrual cycles and dysmenorrhea. The information about relationships with family or friends, couples’ relationships and university activity helped to assess the effects of dysmenorrhea on quality of life. The level of significance was set at p < 0.05. Results: The study comprised 1720 students in total. The prevalence of dysmenorrhea was 78.4%. During their menstrual period, most female students felt more agitated or nervous (72.7%), more tired (66.9%), as if they had less energy for daily activities (75.9%) and highly stressed (57.9%), with a normal diet being difficult to achieve (30.0%). University courses (49.4%), social life (34.5%), couples’ relationships (29.6%), as well as relationships with family (21.4%) and friends (15.4%) were also affected, depending on the duration and intensity of the pain. Conclusion: Dysmenorrhea has a high prevalence among medical students and could affect the quality of life of students in several ways. During their menstrual period, most female students feel as if they have less energy for daily activities and exhibit a higher level of stress. The intensity of the symptoms varies considerably and, with it, the degree of discomfort it creates. Most student use both pharmacological and non-pharmacological methods to reduce pain (75.7%). University courses, social life, couples’ relationships, as well as relationships with family and friends are affected, depending on the duration and intensity of the pain. Full article
10 pages, 777 KiB  
Article
Super-Spreaders or Victims of Circumstance? Childhood in Canadian Media Reporting of the COVID-19 Pandemic: A Critical Content Analysis
by Sarah Ciotti, Shannon A. Moore, Maureen Connolly and Trent Newmeyer
Healthcare 2022, 10(1), 156; https://doi.org/10.3390/healthcare10010156 - 14 Jan 2022
Cited by 7 | Viewed by 2467
Abstract
This qualitative research study, a critical content analysis, explores Canadian media reporting of childhood in Canada during the COVID-19 global pandemic. Popular media plays an important role in representing and perpetuating the dominant social discourse in highly literate societies. In Canadian media, the [...] Read more.
This qualitative research study, a critical content analysis, explores Canadian media reporting of childhood in Canada during the COVID-19 global pandemic. Popular media plays an important role in representing and perpetuating the dominant social discourse in highly literate societies. In Canadian media, the effects of the pandemic on children and adolescents’ health and wellbeing are overshadowed by discussions of the potential risk they pose to adults. The results of this empirical research highlight how young people in Canada have been uniquely impacted by the COVID-19 global pandemic. Two dominant narratives emerged from the data: children were presented “as a risk” to vulnerable persons and older adults and “at risk” of adverse health outcomes from contracting COVID-19 and from pandemic lockdown restrictions. This reflects how childhood was constructed in Canadian society during the pandemic, particularly how children’s experiences are described in relation to adults. Throughout the pandemic, media reports emphasized the role of young people’s compliance with public health measures to prevent the spread of COVID-19 and save the lives of older persons. Full article
(This article belongs to the Special Issue Direct and Indirect Effects of the Ongoing COVID-19 Pandemic on Physical and Mental Health)
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<p>Sources of Data.</p> Full article ">
33 pages, 13277 KiB  
Article
Artificial Intelligence Analysis of Gene Expression Predicted the Overall Survival of Mantle Cell Lymphoma and a Large Pan-Cancer Series
by Joaquim Carreras, Naoya Nakamura and Rifat Hamoudi
Healthcare 2022, 10(1), 155; https://doi.org/10.3390/healthcare10010155 - 14 Jan 2022
Cited by 23 | Viewed by 4727
Abstract
Mantle cell lymphoma (MCL) is a subtype of mature B-cell non-Hodgkin lymphoma characterized by a poor prognosis. First, we analyzed a series of 123 cases (GSE93291). An algorithm using multilayer perceptron artificial neural network, radial basis function, gene set enrichment analysis (GSEA), and [...] Read more.
Mantle cell lymphoma (MCL) is a subtype of mature B-cell non-Hodgkin lymphoma characterized by a poor prognosis. First, we analyzed a series of 123 cases (GSE93291). An algorithm using multilayer perceptron artificial neural network, radial basis function, gene set enrichment analysis (GSEA), and conventional statistics, correlated 20,862 genes with 28 MCL prognostic genes for dimensionality reduction, to predict the patients’ overall survival and highlight new markers. As a result, 58 genes predicted survival with high accuracy (area under the curve = 0.9). Further reduction identified 10 genes: KIF18A, YBX3, PEMT, GCNA, and POGLUT3 that associated with a poor survival; and SELENOP, AMOTL2, IGFBP7, KCTD12, and ADGRG2 with a favorable survival. Correlation with the proliferation index (Ki67) was also made. Interestingly, these genes, which were related to cell cycle, apoptosis, and metabolism, also predicted the survival of diffuse large B-cell lymphoma (GSE10846, n = 414), and a pan-cancer series of The Cancer Genome Atlas (TCGA, n = 7289), which included the most relevant cancers (lung, breast, colorectal, prostate, stomach, liver, etcetera). Secondly, survival was predicted using 10 oncology panels (transcriptome, cancer progression and pathways, metabolic pathways, immuno-oncology, and host response), and TYMS was highlighted. Finally, using machine learning, C5 tree and Bayesian network had the highest accuracy for prediction and correlation with the LLMPP MCL35 proliferation assay and RGS1 was made. In conclusion, artificial intelligence analysis predicted the overall survival of MCL with high accuracy, and highlighted genes that predicted the survival of a large pan-cancer series. Full article
(This article belongs to the Special Issue Artificial Intelligence (AI) and Machine Learning (ML) in Human Health and Healthcare)
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<p>General architecture for multilayer perceptron (MLP) networks. A neural network is a set of non-linear data modeling tools consisting of input layers plus one or two hidden layers. The multilayer perceptron procedure is a feedforward architecture. In comparison to RBF, the MLP con find more complex relationships but it is slower to compute. The MLP network is a function of one or more predictors (also called inputs or independent variables) that minimizes the prediction error of one or more target variables (also called outputs) [<a href="#B32-healthcare-10-00155" class="html-bibr">32</a>,<a href="#B33-healthcare-10-00155" class="html-bibr">33</a>,<a href="#B60-healthcare-10-00155" class="html-bibr">60</a>].</p> Full article ">Figure 2
<p>General architecture for radial basis function (RBF) networks. A radial basis function (RBF) network is a feed-forward, supervised learning network with only one hidden layer, called the radial basis function layer [<a href="#B32-healthcare-10-00155" class="html-bibr">32</a>,<a href="#B33-healthcare-10-00155" class="html-bibr">33</a>,<a href="#B60-healthcare-10-00155" class="html-bibr">60</a>].</p> Full article ">Figure 3
<p>Sensitivity analysis. Independent variable importance analysis. Performs a sensitivity analysis, which computes the importance of each predictor in determining the neural network [<a href="#B32-healthcare-10-00155" class="html-bibr">32</a>,<a href="#B33-healthcare-10-00155" class="html-bibr">33</a>,<a href="#B60-healthcare-10-00155" class="html-bibr">60</a>].</p> Full article ">Figure 4
<p>Summary of the analysis methodology. The analysis was comprised of two methods, one based on the analysis of 20,862 genes and a second based on 10 immuno-oncology panels. This research used artificial neural networks and several machine learning techniques to identify genes associated with the overall survival of the patients. Correlation with known MCL pathogenic genes and the LLMPP MCL35 proliferation assay was also made.</p> Full article ">Figure 5
<p>Artificial neural network analysis for the prediction of the overall survival of mantle cell lymphoma (Method 1). From a start point of 20,862 genes, using several neural networks, a correlation between the overall survival outcome and several mantle cell lymphoma pathogenic genes managed to reduce to a final set of 10 genes. These 10 genes correlated with the survival of the patients, but also with the proliferation index as expressed by <span class="html-italic">MKI67</span> gene: MLP, multilayer perceptron; RBF, radial basis function; OS, overall survival; DA, dead/alive; GSEA, gene set enrichment analysis; AUC, area under the curve.</p> Full article ">Figure 6
<p>Multilayer perceptron analysis using the selected 58 genes (Method 1 continuation). As shown in <a href="#healthcare-10-00155-f004" class="html-fig">Figure 4</a>, the neural networks reduced the initial input of 20,862 genes to 58 predictive genes. Next, the overall survival outcome (dead/alive) was predicted using 58 genes and a neural network. Several parameters display the network performance: model summary; classification results; receiver operating characteristic ROC curve; cumulative gains chart; lift chart; predicted by observed chart; and the independent variable importance analysis. ROC analysis displays a curve for each categorical dependent variable and category and the area under each curve [<a href="#B34-healthcare-10-00155" class="html-bibr">34</a>,<a href="#B35-healthcare-10-00155" class="html-bibr">35</a>,<a href="#B36-healthcare-10-00155" class="html-bibr">36</a>,<a href="#B44-healthcare-10-00155" class="html-bibr">44</a>,<a href="#B45-healthcare-10-00155" class="html-bibr">45</a>,<a href="#B55-healthcare-10-00155" class="html-bibr">55</a>,<a href="#B56-healthcare-10-00155" class="html-bibr">56</a>]. The genes were ranked according to their normalized importance for predicting the overall survival outcome as a dichotomic variables (dead vs. alive). A GSEA analysis confirmed the association toward a dead outcome. The characteristics of the network were as follows. Case processing: training <span class="html-italic">n</span> = 93 (76%); testing <span class="html-italic">n</span> = 30 (24%). Units <span class="html-italic">n</span> = 58. Rescaling = standardized. Hidden layer: number = 1; units = 2; activation function = hyperbolic tangent. Output layer: dependent variables = 1 (overall survival outcome dead/alive); units = 2, activation function = softmax, error function = cross-entropy. Model summary: training, cross-entropy error = 30.8, 14% of incorrect predictions; testing, cross-entropy error = 14.5, 23% of incorrect predictions. Classification: training, 86% overall correct (93.8% alive, 82% dead); testing, 77% overall correct (82% alive, 74% dead). Area under the curve = 0.9. Top 10 most relevant genes were <span class="html-italic">RAB13</span>, <span class="html-italic">ZFYVE19</span>, <span class="html-italic">FANCG</span>, <span class="html-italic">KIF18A</span>, <span class="html-italic">RPGRIP1L</span>, <span class="html-italic">YBX3</span>, <span class="html-italic">ZCCHC4</span>, <span class="html-italic">NCLN</span>, <span class="html-italic">OLFM1</span>, and <span class="html-italic">PDZRN3</span>. A complete description of the multilayer perceptron is present in our recent publication (Carreras J. et al. Artificial Neural Networks Predicted the Overall Survival and Molecular Subtypes of Diffuse Large B-Cell Lymphoma Using a Pan-cancer Immune-Oncology Panel. <span class="html-italic">Cancers</span> <b>2021</b>, <span class="html-italic">13</span>, 6384; <a href="https://doi.org/10.3390/cancers13246384" target="_blank">https://doi.org/10.3390/cancers13246384</a>) [<a href="#B58-healthcare-10-00155" class="html-bibr">58</a>].</p> Full article ">Figure 7
<p>Overall survival analysis (Method 1 continuation). Because of the neural network analysis and dimensional reduction (<a href="#healthcare-10-00155-f004" class="html-fig">Figure 4</a> and <a href="#healthcare-10-00155-f005" class="html-fig">Figure 5</a>), a final set of 10 genes with overall survival relationship was highlighted. These genes not only correlated with the clinical outcome but also with the proliferation index, as expressed by <span class="html-italic">MKI67</span>. Of note, ki67 is a marker routinely used for prediction in mantle cell lymphoma, and the most relevant marker of the LLMPP MCL35 proliferation assay.</p> Full article ">Figure 8
<p>Artificial neural network analysis for predicting of the overall survival of mantle cell lymphoma using several immune oncology panels (Method 2). Overall survival was predicted using 10 immuno-oncology panels. After several multilayer perceptron analyses, a set of 125 genes predicted the overall survival outcome (dead/alive) with high accuracy. Among the most relevant genes, <span class="html-italic">TYMS</span> was highlighted. GSEA analysis had a sinusoidal-like, with some genes enriched toward dead or alive survival outcomes.</p> Full article ">Figure 9
<p>Overall survival in a pan-cancer series. The multilayer perceptron using the 20,862 genes identified a final set of 19 genes with prognostic value in mantle cell lymphoma. As a start point of the gene expression of the set of 19 genes and using a risk-score formula [<a href="#B36-healthcare-10-00155" class="html-bibr">36</a>,<a href="#B46-healthcare-10-00155" class="html-bibr">46</a>], we confirmed that these genes also contributed to the overall survival of diffuse large B-cell lymphoma (DLBCL). Additionally, these genes could also predict the overall survival of a pan-cancer series of 7289 cases from The Cancer Genome Atlas (TCGA) program that included the most frequent human cancers. Of note, the weight and direction of the overall survival association was different in each subtype of neoplasia. Risk scores were calculated by multiplying the beta values of the multivariate Cox regression analysis for overall survival of each gene with the values of the corresponding gene expressions, as previously described [<a href="#B58-healthcare-10-00155" class="html-bibr">58</a>].</p> Full article ">Figure 10
<p>Overall survival in a pan cancer series.</p> Full article ">Figure 11
<p>Bayesian network. A Bayesian network successfully modeled the overall survival outcome (dead/alive) using the 19 genes, previously identified in the neural network analysis (<a href="#healthcare-10-00155-f005" class="html-fig">Figure 5</a>, Method 1). The Bayesian network enables you to build a probability model by combining observed and recorded evidence with “common-sense” real-world knowledge to establish the likelihood of occurrences by using seemingly unlinked attributes. The node focuses on Tree Augmented Naïve Bayes (TAN) and Markov Blanket networks that are primarily used for classification. This graphical model shows the variables (nodes) and the probabilistic, or conditional, independencies between them. The links of the network (arcs) may represent causal relationships, but the links do not necessary represent direct cause and effect. This Bayesian network is used to calculate the probability of a patient of being alive or dead, given the gene expression of 19 genes, if the probabilistic independencies between the gene expression and the overall survival outcome as displayed on the graph hold true. Bayesian networks are very robust in case of missing data.</p> Full article ">Figure 12
<p>C5.0 decision tree model. A decision tree successfully modeled the overall survival outcome (dead/alive) using the 19 genes, previously identified in the neural network analysis (<a href="#healthcare-10-00155-f005" class="html-fig">Figure 5</a>, Method 1). This model uses the C5.0 algorithm to build either a decision tree or a rule set. A C5.0 model works by splitting the sample based on the field that provides the maximum information gain. Each subsample defined by the first split is then split again, usually based on a different field, and the process repeats until the subsamples cannot be split any further. Finally, the lowest-level splits are reexamined, and those that do not contribute significantly to the value are removed. In this model, the target field (variable) must be categorical (i.e., nominal or ordinal, such as de overall survival outcome as dead vs. alive). The input fields (predictors) can be of any type (in our analysis, the 19 genes were entered as quantitative gene expression). The C5.0 models are quite robust in the presence of problems such as missing data and large numbers of input fields. The C5.0 tree shows how using only the gene expression of 9 genes, the overall survival outcome as dead or alive can be predicted with high accuracy.</p> Full article ">Figure 13
<p>Addition of the MCL35 proliferation signature in a Bayesian network. A Bayesian network modeling was performed using the highlighted genes of both Methods 1 (19 genes) and Methods 2 (15) with the previously identified prognostic genes of MCL of the LLMPP, the MCL35 signature. Some of the most relevant genes are highlighted, in red for the bad, green for the good prognostic genes, and their interrelationships (arrows).</p> Full article ">Figure 14
<p>Overall survival according to the immunohistochemical expression of RGS1.</p> Full article ">Figure A1
<p>Differential gene expression of the set of 19 genes per cancer subtype. Based on a risk-score formula and the gene expression of 19 genes, the overall survival for each risk-group could be calculated. The contribution in the prognosis for each gene is shown on the right. This Figure is complementary to <a href="#healthcare-10-00155-f009" class="html-fig">Figure 9</a>.</p> Full article ">
11 pages, 1058 KiB  
Review
Artificial Intelligence Advances in the World of Cardiovascular Imaging
by Bhakti Patel and Amgad N. Makaryus
Healthcare 2022, 10(1), 154; https://doi.org/10.3390/healthcare10010154 - 14 Jan 2022
Cited by 14 | Viewed by 4533
Abstract
The tremendous advances in digital information and communication technology have entered everything from our daily lives to the most intricate aspects of medical and surgical care. These advances are seen in electronic and mobile health and allow many new applications to further improve [...] Read more.
The tremendous advances in digital information and communication technology have entered everything from our daily lives to the most intricate aspects of medical and surgical care. These advances are seen in electronic and mobile health and allow many new applications to further improve and make the diagnoses of patient diseases and conditions more precise. In the area of digital radiology with respect to diagnostics, the use of advanced imaging tools and techniques is now at the center of evaluation and treatment. Digital acquisition and analysis are central to diagnostic capabilities, especially in the field of cardiovascular imaging. Furthermore, the introduction of artificial intelligence (AI) into the world of digital cardiovascular imaging greatly broadens the capabilities of the field both with respect to advancement as well as with respect to complete and accurate diagnosis of cardiovascular conditions. The application of AI in recognition, diagnostics, protocol automation, and quality control for the analysis of cardiovascular imaging modalities such as echocardiography, nuclear cardiac imaging, cardiovascular computed tomography, cardiovascular magnetic resonance imaging, and other imaging, is a major advance that is improving rapidly and continuously. We document the innovations in the field of cardiovascular imaging that have been brought about by the acceptance and implementation of AI in relation to healthcare professionals and patients in the cardiovascular field. Full article
(This article belongs to the Special Issue The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?)
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<p>Artificial intelligence subsets into which the principles of AI can be divided.</p> Full article ">Figure 2
<p>Cardiac imaging modalities that allow for the gathering of data that informs the formation of artificial intelligence that then is used for optimization of the evaluation of patients undergoing cardiac imaging.</p> Full article ">
15 pages, 3225 KiB  
Article
The Artificial Intelligence in Digital Radiology: Part 2: Towards an Investigation of acceptance and consensus on the Insiders
by Francesco Di Basilio, Gianluca Esposisto, Lisa Monoscalco and Daniele Giansanti
Healthcare 2022, 10(1), 153; https://doi.org/10.3390/healthcare10010153 - 14 Jan 2022
Cited by 11 | Viewed by 2622
Abstract
Background. The study deals with the introduction of the artificial intelligence in digital radiology. There is a growing interest in this area of scientific research in acceptance and consensus studies involving both insiders and the public, based on surveys focused mainly on single [...] Read more.
Background. The study deals with the introduction of the artificial intelligence in digital radiology. There is a growing interest in this area of scientific research in acceptance and consensus studies involving both insiders and the public, based on surveys focused mainly on single professionals. Purpose. The goal of the study is to perform a contemporary investigation on the acceptance and the consensus of the three key professional figures approaching in this field of application: (1) Medical specialists in image diagnostics: the medical specialists (MS)s; (2) experts in physical imaging processes: the medical physicists (MP)s; (3) AI designers: specialists of applied sciences (SAS)s. Methods. Participants (MSs = 92: 48 males/44 females, averaged age 37.9; MPs = 91: 43 males/48 females, averaged age 36.1; SAS = 90: 47 males/43 females, averaged age 37.3) were properly recruited based on specific training. An electronic survey was designed and submitted to the participants with a wide range questions starting from the training and background up to the different applications of the AI and the environment of application. Results. The results show that generally, the three professionals show (a) a high degree of encouraging agreement on the introduction of AI both in imaging and in non-imaging applications using both standalone applications and/or mHealth/eHealth, and (b) a different consent on AI use depending on the training background. Conclusions. The study highlights the usefulness of focusing on both the three key professionals and the usefulness of the investigation schemes facing a wide range of issues. The study also suggests the importance of different methods of administration to improve the adhesion and the need to continue these investigations both with federated and specific initiatives. Full article
(This article belongs to the Special Issue The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?)
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<p>Output of the search on PubMed on acceptance and consensus on AI in radiology.</p> Full article ">Figure 2
<p>Interconnection among experts and AI.</p> Full article ">Figure 3
<p>Features investigated by means of the electronic survey.</p> Full article ">Figure 4
<p>Contributions to the survey by the two different methods.</p> Full article ">Figure 5
<p>The percentage of adhesion to the survey by the two different methods.</p> Full article ">Figure 6
<p>Suggestions for improvement with the obtained frequency of occurrence.</p> Full article ">Figure A1
<p>An example of the survey (first print screen).</p> Full article ">Figure A2
<p>An example of the survey (second print screen).</p> Full article ">
15 pages, 469 KiB  
Article
Aspects of Prevention of Urinary Tract Infections Associated with Urinary Bladder Catheterisation and Their Implementation in Nursing Practice
by Jitka Krocová and Radka Prokešová
Healthcare 2022, 10(1), 152; https://doi.org/10.3390/healthcare10010152 - 13 Jan 2022
Cited by 4 | Viewed by 6755
Abstract
In the case of the prevention of catheter-associated urinary tract infections (CAUTI) related to healthcare provision, high-quality and comprehensively provided nursing care is essential. Implementation of preventive strategies is based on recommended procedures, and the introduction of whole sets of measures has been [...] Read more.
In the case of the prevention of catheter-associated urinary tract infections (CAUTI) related to healthcare provision, high-quality and comprehensively provided nursing care is essential. Implementation of preventive strategies is based on recommended procedures, and the introduction of whole sets of measures has been shown to be effective. The objective of this research is to find out whether the providers of acute bed care have implemented the steps of CAUTI prevention, and specifically which measures leading to improved quality of care in the area of urinary infections are already in place. To determine this, we carried out quantitative research. Data were collected using a questionnaire-based investigation; we used two non-standardised and one standardised questionnaire, and the respondents were general nurses in management positions (n = 186). The results revealed that result-related CAUTI indicators are monitored by only one-third of the respondents, and records of catheterisation indication are not kept by 17.3% of general nurses. The results of the research showed deficiencies in the monitoring of CAUTI outcome and process indicators, and a weakness of the implemented preventive measures is the maintenance of catheterisation documentation. Periodic CAUTI prevention training is not implemented as recommended. It is positive that there are well-working teams of HAI prevention experts in hospitals. Full article
(This article belongs to the Special Issue Qualitative Health Research Applied to Clinical and Educational Settings)
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<p>Overview of the responses to the statement “Indication for the catheterisation is a facilitation of nursing care”.</p> Full article ">
12 pages, 219 KiB  
Article
Assessment of Pregnant Women’s Satisfaction with Model of Care Initiative: Antenatal Care Service at Primary Health Care in Cluster One in Riyadh, Saudi Arabia
by Saad M. Alhaqbani and Amen A. Bawazir
Healthcare 2022, 10(1), 151; https://doi.org/10.3390/healthcare10010151 - 13 Jan 2022
Cited by 4 | Viewed by 3401
Abstract
The current study assessed pregnant women’s satisfaction with antenatal care (ANC) services at primary health care centers (PHCs) in Riyadh Cluster One. The study was conducted at 11 PHCs where the ANC initiative has been implemented. A total of 646 pregnant women were [...] Read more.
The current study assessed pregnant women’s satisfaction with antenatal care (ANC) services at primary health care centers (PHCs) in Riyadh Cluster One. The study was conducted at 11 PHCs where the ANC initiative has been implemented. A total of 646 pregnant women were enrolled. A questionnaire was completed by participants to measure the level of satisfaction with the provided services, care, and consultation. Subsequently, the data were analyzed to determine the significant differences and conduct regression analysis. The overall satisfaction with initial triage assessment, provided services, consultation, and examination was 93.7%, 87.8%, 71.8%, and 53.9%, respectively. Regarding ANC services, education was the only statistically significant variable that influenced patient satisfaction (p < 0.05). In contrast, satisfaction with the provided care was significantly related to all the variables studied. For consultation, education (p < 0.001) and monthly income (p < 0.05) were the statistically significant role players. In the regression analysis, secondary education was statistically significantly related to the provided services, consultation, and examination. Despite the satisfactory level of ANC at the selected PHCs, higher patient satisfaction could be achieved in the future by improving the consultation and examination practices. Overall satisfaction with the health care workers at PHCs is high. Incorporating implied ameliorations would enhance the quality of services and patient satisfaction. Full article
(This article belongs to the Special Issue Maternal, Fetal and Neonatal Health)
6 pages, 1900 KiB  
Case Report
A COVID-19 Patient with Simultaneous Renal Infarct, Splenic Infarct and Aortic Thrombosis during the Severe Disease
by Georgios Mavraganis, Sofia Ioannou, Anastasios Kallianos, Gianna Rentziou and Georgia Trakada
Healthcare 2022, 10(1), 150; https://doi.org/10.3390/healthcare10010150 - 13 Jan 2022
Cited by 11 | Viewed by 2104
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been associated with a high incidence of arterial and venous thrombotic complications. However, thromboembolic events in unusual sites such as limb and visceral arterial ischemia are reported rarely in the literature. Herein, we describe [...] Read more.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been associated with a high incidence of arterial and venous thrombotic complications. However, thromboembolic events in unusual sites such as limb and visceral arterial ischemia are reported rarely in the literature. Herein, we describe a rare case of a patient with severe coronavirus disease 2019 (COVID-19) infection who experienced severe abdominal pain during the hospitalization and presented simultaneously renal artery, splenic artery and vein as well as aortic thrombi despite prophylactic antithrombotic treatment. Information about his follow-up post discharge is also provided. This case report raises significant clinical implications regarding the correct dose of antithrombotic treatment during the acute phase of the severe COVID-19 infection and highlights the need for incessant vigilance in order to detect thrombosis at unusual sites as a possible diagnosis when severe abdominal pain is present in severe COVID-19 patients. Full article
(This article belongs to the Topic Burden of COVID-19 in Different Countries)
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<p>CT pulmonary scan of the patient at day 6. The blue arrows demonstrate bilateral ground glass opacities and regions with pulmonary consolidation. The red arrow indicates the thrombi detected in the thoracic aorta.</p> Full article ">Figure 2
<p>Abdominal CT scan of the patient at day 6. The red arrow demonstrates the area of hypoattenuation in the splenic parenchyma consistent with the splenic infarct. The green arrow indicates wedge-shaped parenchyma hypodensities in the lower lobe of the left kidney, typically seen in renal infarcts.</p> Full article ">
28 pages, 8415 KiB  
Article
An Explainable Machine Learning Approach for COVID-19’s Impact on Mood States of Children and Adolescents during the First Lockdown in Greece
by Charis Ntakolia, Dimitrios Priftis, Mariana Charakopoulou-Travlou, Ioanna Rannou, Konstantina Magklara, Ioanna Giannopoulou, Konstantinos Kotsis, Aspasia Serdari, Emmanouil Tsalamanios, Aliki Grigoriadou, Konstantina Ladopoulou, Iouliani Koullourou, Neda Sadeghi, Georgia O’Callaghan and Eleni Lazaratou
Healthcare 2022, 10(1), 149; https://doi.org/10.3390/healthcare10010149 - 13 Jan 2022
Cited by 12 | Viewed by 3775 | Correction
Abstract
The global spread of COVID-19 led the World Health Organization to declare a pandemic on 11 March 2020. To decelerate this spread, countries have taken strict measures that have affected the lifestyles and economies. Various studies have focused on the identification of COVID-19’s [...] Read more.
The global spread of COVID-19 led the World Health Organization to declare a pandemic on 11 March 2020. To decelerate this spread, countries have taken strict measures that have affected the lifestyles and economies. Various studies have focused on the identification of COVID-19’s impact on the mental health of children and adolescents via traditional statistical approaches. However, a machine learning methodology must be developed to explain the main factors that contribute to the changes in the mood state of children and adolescents during the first lockdown. Therefore, in this study an explainable machine learning pipeline is presented focusing on children and adolescents in Greece, where a strict lockdown was imposed. The target group consists of children and adolescents, recruited from children and adolescent mental health services, who present mental health problems diagnosed before the pandemic. The proposed methodology imposes: (i) data collection via questionnaires; (ii) a clustering process to identify the groups of subjects with amelioration, deterioration and stability to their mood state; (iii) a feature selection process to identify the most informative features that contribute to mood state prediction; (iv) a decision-making process based on an experimental evaluation among classifiers; (v) calibration of the best-performing model; and (vi) a post hoc interpretation of the features’ impact on the best-performing model. The results showed that a blend of heterogeneous features from almost all feature categories is necessary to increase our understanding regarding the effect of the COVID-19 pandemic on the mood state of children and adolescents. Full article
(This article belongs to the Topic Burden of COVID-19 in Different Countries)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Machine learning pipeline adopted in this study.</p> Full article ">Figure 2
<p>Clustering process.</p> Full article ">Figure 3
<p>Evaluation methodology.</p> Full article ">Figure 4
<p>Evaluation process of clustering methods.</p> Full article ">Figure 5
<p>Spider plot of the number of features that belong to each feature category for the first 40 features where the best performance was achieved.</p> Full article ">Figure 6
<p>Classification results.</p> Full article ">Figure 7
<p>Change of predicted probabilities on test samples after calibration with: (<b>a</b>) Isotonic Regression method; (<b>b</b>) Platt’s (sigmoid) method.</p> Full article ">Figure 8
<p>Learned calibration map with: (<b>a</b>) Isotonic Regression method; (<b>b</b>) Platt’s (sigmoid) method.</p> Full article ">Figure 9
<p>Calibration plot of XG Boost classifier for class 0.</p> Full article ">Figure 10
<p>Calibration plot of XG Boost classifier for class 1.</p> Full article ">Figure 11
<p>Calibration plot of XG Boost classifier for class 2.</p> Full article ">Figure 12
<p>Mean SHAP values.</p> Full article ">Figure 13
<p>SHAP values of patients from class 0.</p> Full article ">Figure 14
<p>SHAP values of patients from class 1.</p> Full article ">Figure 15
<p>SHAP values of patients from class 2.</p> Full article ">Figure 16
<p>Mean SHAP values of patients from class 0 and class 1.</p> Full article ">Figure 17
<p>Mean SHAP values of patients from class 0 and class 2.</p> Full article ">Figure 18
<p>SHAP values patients from class 1 and class 2.</p> Full article ">
12 pages, 2327 KiB  
Project Report
An App about Healthy Habits as an Educational Resource during the Pandemic
by María de los Ángeles Merino-Godoy, Emilia Moreno-Sánchez, Francisco-Javier Gago-Valiente, Emília Isabel Costa and Jesús Sáez-Padilla
Healthcare 2022, 10(1), 148; https://doi.org/10.3390/healthcare10010148 - 13 Jan 2022
Cited by 7 | Viewed by 2451
Abstract
Educational institutions and their agents play a fundamental role in improving people’s health literacy and quality of life. We intend here to describe and justify an educational resource embodied in an application for mobile devices developed through a subsidized project by the Ministry [...] Read more.
Educational institutions and their agents play a fundamental role in improving people’s health literacy and quality of life. We intend here to describe and justify an educational resource embodied in an application for mobile devices developed through a subsidized project by the Ministry of Health (Government of Andalusia); the purpose of this app is to educate young people in healthy habits. The application was designed to be easily used in both smartphones and tablets with the aim of achieving good physical, psychological and social health. The project comprises several phases and the results we have so far show that, from an early age, health institutions and educational settings must work in partnership, increasing health literacy levels. This cooperative work combined with the use of this innovative approach presents an important potential for change in the lifestyles of younger generations. This type of intervention took on a special role in the pandemic context, allowing for the maintenance of the educational stimulus in a safe context. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Presentation of Healthy Jeart.</p> Full article ">Figure 2
<p>Mobile application available for Android and iOS. An app for learning by playing and sharing healthy lifestyle habits.</p> Full article ">Figure 3
<p>A game to work on healthy habits playfully.</p> Full article ">Figure 4
<p>Healthy tips and didactic resources. “Before, during and after physical exercise, an excellent hydration helps you a lot”.</p> Full article ">Figure A1
<p>Distinction of “Healthy App”.</p> Full article ">Figure A2
<p>Advanced Level Accreditation for Web Pages.</p> Full article ">
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