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Objectives: To identify risk factors for developing a fracture-related infection in operatively treated ballistic tibia fractures and to report the microbiologic results of intraoperative cultures., Design: Retrospective review., Setting: Level 1 trauma center., Patients/participants: One hundred thirty-three adults with operatively treated low-velocity ballistic tibia fractures, from 2011 to 2021., Intervention: One dose of prophylactic cefazolin or equivalent as well as perioperative prophylaxis., Main Outcome Measurements: Deep infection rate., Results: The deep infection rate was 12% (16/134) with no significant difference in injury characteristics, index surgical characteristics, or time to antibiotics between the groups ( P > 0.05). Patients who were slightly older (35.5 vs. 27 median years, P = 0.005) and with higher median body mass indexes (BMIs) (30.09 vs. 24.51, P = 0.021) developed a deep infection. 56.3% of patients presented with signs of infection within the first 100 days after injury. Nine patients had polymicrobial infections. There were 29 isolated organisms, 69% were uncovered by first-generation cephalosporin prophylaxis (anaerobes, gram-negative rods, Enterococcus, methicillin resistant Staphylococcus Aureus [MRSA] ), and 50% of patients developed recalcitrant infection and required a second reoperation where 6 organisms were isolated, half of which were not covered by first-generation prophylaxis ( Enterococcus, Staphylococcus Aureus MRSA )., Conclusions: We found a deep infection rate of 12% among ballistic tibia fractures receiving standard-of-care antibiotic prophylaxis. Increased age and body mass index were associated with deep infections. Half became recalcitrant requiring a second reoperation. 66.7% of isolated organisms were not covered by first-generation cephalosporin prophylaxis. Consideration should be given to treatment options such as broader prophylaxis or local antibiotic treatment., Level of Evidence: IV., Competing Interests: Dr. Brianna R. Fram reports paid consulting for Synthes. Dr. Joseph R. Hsu reports consultancy and speaker fees for Stryker, consultancy for Globus Medical, speaker fees from Smith & Nephew speakers' bureau, speaker fees from Integra Lifesciences, and speaker fees from Depuy/Synthes. The remaining authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Orthopaedic Trauma Association.)

In-flight medical incidents are becoming increasingly critical as passengers with diverse health profiles increase in the skies. In this paper, we reviewed how airlines, aviation authorities, and healthcare professionals respond to such emergencies. The analysis was focused on the strategies developed by the top ten airlines in the world by examining training in basic first aid, collaboration with ground-based medical support, and use of onboard medical equipment. Appropriate training of crew members, availability of adequate medical resources on board airplanes, and improved capabilities of dialogue between a flying plane and medical doctors on the ground will contribute to a positive outcome of the majority of medical issues on board airlines. In this respect, the adoption of advanced telemedicine solutions and the improvement of real-time teleconsultations between aircraft and ground-based professionals can represent the future of aviation medicine, offering more safety and peace of mind to passengers in case of medical problems during a flight.

There is no doubt that brain tumors are one of the leading causes of death in the world. A biopsy is considered the most important procedure in cancer diagnosis, but it comes with drawbacks, including low sensitivity, risks during biopsy treatment, and a lengthy wait for results. Early identification provides patients with a better prognosis and reduces treatment costs. The conventional methods of identifying brain tumors are based on medical professional skills, so there is a possibility of human error. The labor-intensive nature of traditional approaches makes healthcare resources expensive. A variety of imaging methods are available to detect brain tumors, including magnetic resonance imaging (MRI) and computed tomography (CT). Medical imaging research is being advanced by computer-aided diagnostic processes that enable visualization. Using clustering, automatic tumor segmentation leads to accurate tumor detection that reduces risk and helps with effective treatment. This study proposed a better Fuzzy C-Means segmentation algorithm for MRI images. To reduce complexity, the most relevant shape, texture, and color features are selected. The improved Extreme Learning machine classifies the tumors with 98.56% accuracy, 99.14% precision, and 99.25% recall. The proposed classifier consistently demonstrates higher accuracy across all tumor classes compared to existing models. Specifically, the proposed model exhibits accuracy improvements ranging from 1.21% to 6.23% when compared to other models. This consistent enhancement in accuracy emphasizes the robust performance of the proposed classifier, suggesting its potential for more accurate and reliable brain tumor classification. The improved algorithm achieved accuracy, precision, and recall rates of 98.47%, 98.59%, and 98.74% on the Fig share dataset and 99.42%, 99.75%, and 99.28% on the Kaggle dataset, respectively, which surpasses competing algorithms, particularly in detecting glioma grades. The proposed algorithm shows an improvement in accuracy, of approximately 5.39%, in the Fig share dataset and of 6.22% in the Kaggle dataset when compared to existing models. Despite challenges, including artifacts and computational complexity, the study's commitment to refining the technique and addressing limitations positions the improved FCM model as a noteworthy advancement in the realm of precise and efficient brain tumor identification.

Objectives: To evaluate the work relative value units (RVUs) attributed per minute of operative time (wRVU/min) in fixation of acetabular fractures, evaluate surgical factors that influence wRVU/min, and compare wRVU/min with other procedures., Design: Retrospective., Setting: Level 1 academic center., Patient Selection Criteria: Two hundred fifty-one operative acetabular fractures (62 A, B, C) from 2015 to 2021., Outcome Measures and Comparisons: Work relative value unit per minute of operative time for each acetabular current procedural terminology (CPT) code. Surgical approach, patient positioning, total room time, and surgeon experience were collected. Comparison wRVU/min were collected from the literature., Results: The mean wRVU per surgical minute for each CPT code was (1) CPT 27226 (isolated wall fracture): 0.091 wRVU/min, (2) CPT 27227 (isolated column or transverse fracture): 0.120 wRVU/min, and (3) CPT 27228 (associated fracture types): 0.120 wRVU/min. Of fractures with single approaches, anterior approaches generated the least wRVU/min (0.091 wRVU/min, P = 0.0001). Average nonsurgical room time was 82.1 minutes. Surgeon experience ranged from 3 to 26 years with operative time decreasing as surgeon experience increased ( P = 0.03). As a comparison, the wRVU/min for primary and revision hip arthroplasty have been reported as 0.26 and 0.249 wRVU/min, respectively., Conclusions: The wRVUs allocated per minute of operative time for acetabular fractures is less than half of other reported hip procedures and lowest for isolated wall fractures. There was a significant amount of nonsurgical room time that should be accounted for in compensation models. This information should be used to ensure that orthopaedic trauma surgeons are being appropriately supported for managing these fractures., Level of Evidence: Economic Level IV. See Instructions for Authors for a complete description of levels of evidence., Competing Interests: The authors report no conflict of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Hypertensive retinopathy (HR) results from the microvascular retinal changes triggered by hypertension, which is the most common leading cause of preventable blindness worldwide. Therefore, it is necessary to develop an automated system for HR detection and evaluation using retinal images. We aimed to propose an automated approach to identify and categorize the various degrees of HR severity. A new network called the spatial convolution module (SCM) combines cross-channel and spatial information, and the convolution operations extract helpful features. The present model is evaluated using publicly accessible datasets ODIR, INSPIREVR, and VICAVR. We applied the augmentation to artificially increase the dataset of 1200 fundus images. The different HR severity levels of normal, mild, moderate, severe, and malignant are finally classified with the reduced time when compared to the existing models because in the proposed model, convolutional layers run only once on the input fundus images, which leads to a speedup and reduces the processing time in detecting the abnormalities in the vascular structure. According to the findings, the improved SVM had the highest detection and classification accuracy rate in the vessel classification with an accuracy of 98.99% and completed the task in 160.4 s. The ten-fold classification achieved the highest accuracy of 98.99%, i.e., 0.27 higher than the five-fold classification accuracy and the improved KNN classifier achieved an accuracy of 98.72%. When computation efficiency is a priority, the proposed model's ability to quickly recognize different HR severity levels is significant.

Objectives: High blood pressure is a common health concern among seafarers. However, due to the remote nature of their work, it can be difficult for them to access regular monitoring of their blood pressure. Therefore, the development of a risk prediction model for hypertension in seafarers is important for early detection and prevention. This study developed a risk prediction model of self-reported hypertension for telemedicine., Design: A cross-sectional epidemiological study was employed., Setting: This study was conducted among seafarers aboard ships. Data on sociodemographic, occupational and health-related characteristics were collected using anonymous, standardised questionnaires., Participants: This study involved 8125 seafarers aged 18-70 aboard 400 vessels between November 2020 and December 2020. 4318 study subjects were included in the analysis. Seafarers over 18 years of age, active (on duty) during the study and willing to give informed consent were the inclusion criteria., Outcome Measures: We calculated the adjusted OR (AOR) with 95% CIs using multiple logistic regression models to estimate the associations between sociodemographic, occupational and health-related characteristics and self-reported hypertension. We also developed a risk prediction model for self-reported hypertension for telemedicine based on seafarers' characteristics., Results: Among the 4318 participants, 55.3% and 44.7% were non-officers and officers, respectively. 20.8% (900) of the participants reported having hypertension. Multivariable analysis showed that age (AOR: 1.08, 95% CI 1.07 to 1.10), working long hours per week (AOR: 1.02, 95% CI 1.01 to 1.03), work experience at sea (10+ years) (AOR: 1.79, 95% CI 1.33 to 2.42), being a non-officer (AOR: 1.75, 95% CI 1.44 to 2.13), snoring (AOR: 3.58, 95% CI 2.96 to 4.34) and other health-related variables were independent predictors of self-reported hypertension, which were included in the final risk prediction model. The sensitivity, specificity and accuracy of the predictive model were 56.4%, 94.4% and 86.5%, respectively., Conclusion: A risk prediction model developed in the present study is accurate in predicting self-reported hypertension in seafarers' onboard ships., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Diabetic retinopathy (DR) is an eye disease associated with diabetes that can lead to blindness. Early diagnosis is critical to ensure that patients with diabetes are not affected by blindness. Deep learning plays an important role in diagnosing diabetes, reducing the human effort to diagnose and classify diabetic and non-diabetic patients. The main objective of this study was to provide an improved convolution neural network (CNN) model for automatic DR diagnosis from fundus images. The pooling function increases the receptive field of convolution kernels over layers. It reduces computational complexity and memory requirements because it reduces the resolution of feature maps while preserving the essential characteristics required for subsequent layer processing. In this study, an improved pooling function combined with an activation function in the ResNet-50 model was applied to the retina images in autonomous lesion detection with reduced loss and processing time. The improved ResNet-50 model was trained and tested over the two datasets (i.e., APTOS and Kaggle). The proposed model achieved an accuracy of 98.32% for APTOS and 98.71% for Kaggle datasets. It is proven that the proposed model has produced greater accuracy when compared to their state-of-the-art work in diagnosing DR with retinal fundus images.

Objective : From medicine via radio to telemedicine, personalized medical care at sea has improved significantly over the years. Currently, very little research has been conducted on telemedicine services and tools at sea. This study aims to review real-time case studies of seafarers' personalized treatment via telemedical devices published in medical journals. Methods : A literature search was conducted using three libraries such as PubMed (Medline), Cumulative Index to Nursing and Allied Health Literature (CINAHL), BioMed Central, and Google Scholar. The Medical Subject Headings (MeSH) were used for information retrieval and document selection was conducted based on the guidelines of preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 flowchart. Selected articles were subjected to quality checks using the Newcastle-Ottawa scale (NOS). Results : The literature search produced 785 papers and documents. The selection was conducted in three stages such as selection, screening, and inclusion. After applying predefined inclusion and exclusion criteria, only three articles on real-time medical assistance with telemedical tools were identified. It is reported that medical attention is delivered to seafarers in real time thanks to advancements in telemedicine, satellite technology, and video conferencing. Conclusions : By improving the quality of medical care and reducing response times for medical emergencies at sea, lives have been saved. There are still several gaps despite these advancements. Medical assistance at sea should therefore be improved to address many of the still unsolved issues.

Optimal treatment of orthopaedic extremity trauma includes meticulous care of both bony and soft tissue injuries. Historically, clinical scenarios involving soft tissue defects necessitated the assistance of a plastic surgeon. While their expertise in coverage options and microvascular repair is invaluable, barriers preventing collaboration are common. Acellular dermal matrices represent a promising and versatile tool for orthopaedic trauma surgeons to keep in their toolbox. These biological scaffolds are each unique in how they are used and promote healing. This review explores some commercial products and offers guidance for selection in different clinical scenarios involving traumatic wounds., Competing Interests: Dr. J. R. Hsu reports consultancy and speaker fees for Stryker, consultancy and speaker fees from Smith & Nephew speakers' bureau, speaker fees from Integra Lifesciences, and speaker fees from Depuy/Synthes. All other authors have no competing interests to disclose., (Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Orthopaedic Trauma Association.)

Background: The progressive aging of populations, primarily in the industrialized western world, is accompanied by the increased incidence of several non-transmittable diseases, including neurodegenerative diseases and adult-onset dementia disorders. To stimulate adequate interventions, including treatment and preventive measures, an early, accurate diagnosis is necessary. Conventional magnetic resonance imaging (MRI) represents a technique quite common for the diagnosis of neurological disorders. Increasing evidence indicates that the association of artificial intelligence (AI) approaches with MRI is particularly useful for improving the diagnostic accuracy of different dementia types. Objectives: In this work, we have systematically reviewed the characteristics of AI algorithms in the early detection of adult-onset dementia disorders, and also discussed its performance metrics. Methods: A document search was conducted with three databases, namely PubMed (Medline), Web of Science, and Scopus. The search was limited to the articles published after 2006 and in English only. The screening of the articles was performed using quality criteria based on the Newcastle-Ottawa Scale (NOS) rating. Only papers with an NOS score ≥ 7 were considered for further review. Results: The document search produced a count of 1876 articles and, because of duplication, 1195 papers were not considered. Multiple screenings were performed to assess quality criteria, which yielded 29 studies. All the selected articles were further grouped based on different attributes, including study type, type of AI model used in the identification of dementia, performance metrics, and data type. Conclusions: The most common adult-onset dementia disorders occurring were Alzheimer's disease and vascular dementia. AI techniques associated with MRI resulted in increased diagnostic accuracy ranging from 73.3% to 99%. These findings suggest that AI should be associated with conventional MRI techniques to obtain a precise and early diagnosis of dementia disorders occurring in old age.

Purpose: The purpose of this study was to determine and establish the MCID for the NAHS at 2 years in patients undergoing hip arthroscopy for femoroacetabular impingement syndrome (FAIS)., Methods: Patients that underwent primary hip arthroscopy for FAIS between 2010 and 2016 were analyzed for eligibility. Data were collected from a single surgeon's hip arthroscopy database. MCID was calculated for the NAHS utilizing a distribution-based method., Results: The study included 298 patients (184 females) with an average age of 40.4 ± 13.0 years and average body mass index (BMI) of 25.7 ± 4.2 kg/m 2 . At baseline, the cohort's average NAHS score was 48.7 ± 13.6 and demonstrated an improvement of 36.5 ± 17.0 for NAHS at follow-up. This resulted in MCID values of + 8.5 for NAHS., Conclusion: This is the first study to report the MCID (+ 8.5) for NAHS following primary hip arthroscopy, and as such, is a valuable contribution to future hip arthroscopy research., Level of Evidence: IV., (© 2021. The Author(s), under exclusive licence to The Author(s) under exclusive licence to European Society of Sports Traumatology, Knee Surgery, Arthroscopy (ESSKA).)

Background: Intertrochanteric hip fractures are among the most common and most expensive diagnoses in the Medicare population. Liposomal bupivacaine is a novel preparation of a commonly used analgesic agent that, when used intraoperatively, decreases narcotic requirements and hospital length of stay and increases the likelihood of discharge to home. The purpose of this investigation was to determine whether there was an economic benefit to utilizing intraoperative liposomal bupivacaine in patients with fragility intertrochanteric hip fractures in comparison to a group of patients who did not receive liposomal bupivacaine., Methods: This is a retrospective observational study performed at two academic medical centers. Fifty-six patients with intertrochanteric hip fractures treated with cephalomedullary nail implant who received standard hip fracture pain management protocol were compared to a cohort of 46 patients with intertrochanteric hip fractures who received additional intraoperative injections of liposomal bupivacaine. All other standards of care were identical. A cost analysis was completed including the cost of liposomal bupivacaine, operating room costs, and discharge destination. Statistical significance was set at p < 0.05., Results: Although the length of hospital stay was similar between the two groups (3.2 days vs. 3.8 days, p = 0.08), patients receiving intraoperative liposomal bupivacaine had a lower likelihood of discharge to a skilled nursing facility (84.8% vs. 96.4%, p = 0.002) and a longer operative time (73.4 minutes vs 67.2 minutes, p = 0.004). The cost-benefit analysis indicated that for an investment of $334.18 in the administration of 266 mg of liposomal bupivacaine, there was a relative saving of $1,323.21 compared to the control group. The benefit-cost ratio was 3.95, indicating a $3.95 benefit for each $1 spent in liposomal bupivacaine., Conclusions: Despite the increased initial cost, intraoperative use of liposomal bupivacaine was found to be a cost-effective intervention due to the higher likelihood of discharge to home during the postoperative management of patients with intertrochanteric hip fractures., Competing Interests: CONFLICT OF INTEREST: No potential conflict of interest relevant to this article was reported., (Copyright © 2022 by The Korean Orthopaedic Association.)

Background: The availability of better healthcare services is critical for onboard seafarers. The development of expert systems can help ships with limited medical facilities, which allow the shipside doctors to properly refer symptoms to remote doctors. This allows clinicians to make a correct diagnosis from there, which leads to proper treatment. A software named Marine Doctor (M Doc) has been developed by incorporating computing technologies to address this objective. Methods: With the help of Information and Communication Technology (ICT) this application can support the provision of appropriate medical assistance to seafarers. The system was developed with Python Tkinter (frontend) and PHP (backend) languages. MySQL was used as a server database. Results: Seafarers can use M Doc to benefit from medical advice that can reduce complications due to misdiagnosis and help doctors to make better-informed decisions. By automatically collecting appropriate sequences of symptoms, doctors will be able to generate proper information for referral of patient symptoms and subsequent advice based on the data. Conclusions: Technology that supports experts on board ships in better interacting with Telemedical Maritime Assistance Services (TMAS) could define the future of medical assistance at sea.

Introduction: In biobanks, participants' biological samples are stored for future research. The application of artificial intelligence (AI) involves the analysis of data and the prediction of any pathological outcomes. In AI, models are used to diagnose diseases as well as classify and predict disease risks. Our research analyzed AI's role in the development of biobanks in the healthcare industry, systematically. Methods: The literature search was conducted using three digital reference databases, namely PubMed, CINAHL, and WoS. Guidelines for preferred reporting elements for systematic reviews and meta-analyses (PRISMA)-2020 in conducting the systematic review were followed. The search terms included "biobanks", "AI", "machine learning", and "deep learning", as well as combinations such as "biobanks with AI", "deep learning in the biobanking field", and "recent advances in biobanking". Only English-language papers were included in the study, and to assess the quality of selected works, the Newcastle-Ottawa scale (NOS) was used. The good quality range (NOS ≥ 7) is only considered for further review. Results: A literature analysis of the above entries resulted in 239 studies. Based on their relevance to the study's goal, research characteristics, and NOS criteria, we included 18 articles for reviewing. In the last decade, biobanks and artificial intelligence have had a relatively large impact on the medical system. Interestingly, UK biobanks account for the highest percentage of high-quality works, followed by Qatar, South Korea, Singapore, Japan, and Denmark. Conclusions: Translational bioinformatics probably represent a future leader in precision medicine. AI and machine learning applications to biobanking research may contribute to the development of biobanks for the utility of health services and citizens.

Generally, seafarers face a higher risk of illnesses and accidents than land workers. In most cases, there are no medical professionals on board seagoing vessels, which makes disease diagnosis even more difficult. When this occurs, onshore doctors may be able to provide medical advice through telemedicine by receiving better symptomatic and clinical details in the health abstracts of seafarers. The adoption of text mining techniques can assist in extracting diagnostic information from clinical texts. We applied lexicon sentimental analysis to explore the automatic labeling of positive and negative healthcare terms to seafarers' text healthcare documents. This was due to the lack of experimental evaluations using computational techniques. In order to classify diseases and their associated symptoms, the LASSO regression algorithm is applied to analyze these text documents. A visualization of symptomatic data frequency for each disease can be achieved by analyzing TF-IDF values. The proposed approach allows for the classification of text documents with 93.8% accuracy by using a machine learning model called LASSO regression. It is possible to classify text documents effectively with tidy text mining libraries. In addition to delivering health assistance, this method can be used to classify diseases and establish health observatories. Knowledge developed in the present work will be applied to establish an Epidemiological Observatory of Seafarers' Pathologies and Injuries. This Observatory will be a collaborative initiative of the Italian Ministry of Health, University of Camerino, and International Radio Medical Centre (C.I.R.M.), the Italian TMAS.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor impairment, as well as tremors, stiffness, and rigidity. Besides the typical motor symptomatology, some Parkinsonians experience non-motor symptoms such as hyposmia, constipation, urinary dysfunction, orthostatic hypotension, memory loss, depression, pain, and sleep disturbances. The correct diagnosis of PD cannot be easy since there is no standard objective approach to it. After the incorporation of machine learning (ML) algorithms in medical diagnoses, the accuracy of disease predictions has improved. In this work, we have used three deep-learning-type cascaded neural network models based on the audial voice features of PD patients, called Recurrent Neural Networks (RNN), Multilayer Perception (MLP), and Long Short-Term Memory (LSTM), to estimate the accuracy of PD diagnosis. A performance comparison between the three models was performed on a sample of the subjects' voice biomarkers. Experimental outcomes suggested that the LSTM model outperforms others with 99% accuracy. This study has also presented loss function curves on the relevance of good-fitting models to the detection of neurodegenerative diseases such as PD.

Adult-onset dementia disorders represent a challenge for modern medicine. Alzheimer's disease (AD) represents the most diffused form of adult-onset dementias. For half a century, the diagnosis of AD was based on clinical and exclusion criteria, with an accuracy of 85%, which did not allow for a definitive diagnosis, which could only be confirmed by post-mortem evaluation. Machine learning research applied to Magnetic Resonance Imaging (MRI) techniques can contribute to a faster diagnosis of AD and may contribute to predicting the evolution of the disease. It was also possible to predict individual dementia of older adults with AD screening data and ML classifiers. To predict the AD subject status, the MRI demographic information and pre-existing conditions of the patient can help to enhance the classifier performance. In this work, we proposed a framework based on supervised learning classifiers in the dementia subject categorization as either AD or non-AD based on longitudinal brain MRI features. Six different supervised classifiers are incorporated for the classification of AD subjects and results mentioned that the gradient boosting algorithm outperforms other models with 97.58% of accuracy.

Objective: This prospective in vivo study aimed to compare the clinical behavior of a flowable composite resin (Genial Universal Flo, GC) and a nanohybrid universal composite resin (Tetric Evo Ceram, Ivoclar Vivadent) used in Class I and II direct esthetic restorations in posterior teeth., Methods: A total of 108 Class I and II direct restorations were performed in patients aged between 20 and 60 years. The originality of this study lies in the fact that both materials were placed in pairs, in the same clinical environment (i.e., the same patient and the same type of tooth). The evaluations were performed now of restoration and after 2-weeks, 6-, 12-, and 24-months intervals using clinical examination, clinical photographs, and radiological examination, according to modified USPHS criteria. Statistical analysis was performed using the Fisher exact test and chi-square analysis., Results: At baseline, the universal composite resin showed better esthetic properties such as surface luster, surface staining marginal staining. Both materials regressed significantly over time with no significant difference between groups., Conclusions: Both flowable and nanohybrid composite resins exhibit acceptable clinical performance. The present 24 months of evaluation of different composites showed that the G-ænial Universal Flo could be an effective esthetic material for posterior restoration. No significant difference between both materials over time concerning surface luster, surface staining, and marginal staining.

The second wave of a novel coronavirus in Italy has caused 247,369 new cases and 1782 deaths only in October 2020. This significantly alarming infectious disease controlling board to impose again mitigation measures for controlling the epidemic growth. In this paper, we estimate the latest COVID-19 reproduction number (R&#95;0) and project the epidemic size for the future 45 days. The R&#95;0 value has calculated as 2.83 (95% CI: 1.5-4.2) and the cumulative incidences 100,015 (95% CI; 73,201-100,352), and daily incidences might be reached up to 15,012 (95% CI: 8234-16,197) respectively., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)

Introduction: Adverse effects on personalized care and outcomes of cardiovascular diseases (CVD) could occur if health systems do not work in an efficient manner. The pandemic caused by COVID-19 has opened new perspectives for the execution and advancement of cardiovascular tests through telemedicine platforms., Objective: This study aimed to analyze the usefulness of telemedical systems for providing personal care in the prevention of CVD., Methods: A systematic review analysis was conducted on the literature available from libraries such as PubMed (Medline), Scopus (Embase), and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Data available in the last 10 years (2011-2020) were also examined by PRISMA guidelines. The selected studies were divided into two categories: (1) benefits of telemedicine in CVD prevention, and (2) recent progress in telemedical services for personalized care of CVD., Results: The literature search produced 587 documents, and 19 articles were considered in this review. Results highlighted that the timely delivery of preventive care for CVD which can be implemented virtually can benefit and modify morbidity and mortality. This could also reduce the pressure on hospitals by decreasing acute CVD occurrence among the general population. The use of these technologies can also help to reduce access to hospitals and other medical devices when not necessary., Conclusions: Telemedicine platforms can be used for regular checkups for CVD and contribute to preventing the occurrence of acute events and more in general the progression of CVD.

Objective: The largest pandemic in history, the COVID-19 pandemic, has been declared a doomsday globally. The second wave spreading worldwide has devastating consequences in every sector of life. Several measures to contain and curb its infection have forged significant challenges for the education community. With an estimated 1.6 billion learners, the closure of schools and other educational institutions has impacted more than 90% of students worldwide from the elementary to tertiary level. Methods: In a view to studying impacts on student's fraternity, this article aims at addressing alternative ways of educating-more specifically, online education-through the analysis of Google trends for the past year. The study analyzed the platforms of online teaching and learning systems that have been enabling remote learning, thereby limiting the impact on the education system. Thorough text analysis is performed on an existing dataset from Kaggle to retrieve insight on the clustering of words that are more often looked at during this pandemic to find the general patterns of their occurrence. Findings: The results show that the coronavirus patients are the most trending patterns in word search clustering, with the education system being at the control and preventive measures to bring equilibrium in the system of education. There has been significant growth in online platforms in the last year. Existing assets of educational establishments have effectively converted conventional education into new-age online education with the help of virtual classes and other key online tools in this continually fluctuating scholastic setting. The effective usage of teaching tools such as Microsoft Teams, Zoom, Google Meet, and WebEx are the most used online platforms for the conduction of classes, and whiteboard software tools and learning apps such as Vedantu, Udemy, Byju's, and Whitehat Junior have been big market players in the education system over the pandemic year, especially in India. Conclusions: The article helps to draw a holistic approach of ongoing online teaching-learning methods during the lockdown and also highlights changes that took place in the conventional education system amid the COVID pandemic to overcome the persisting disruption in academic activities and to ensure correct perception towards the online procedure as a normal course of action in the new educational system. To fill in the void of classroom learning and to minimize the virus spread over the last year, digital learning in various schools and colleges has been emphasized, leading to a significant increase in the usage of whiteboard software platforms.

Overweight and obesity are key risk factors of cardiovascular disease (CVD). Obesity is currently presented as a pro-inflammatory state with an expansion in the outflow of inflammatory cytokines, such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), alongside the expanded emission of leptin. The present review aimed to evaluate the relationship between obesity and inflammation and their impacts on the development of cardiovascular disease. A literature search was conducted by employing three academic databases, namely PubMed (Medline), Scopus (EMBASE), and the Cumulative Index to Nursing and Allied Health Literature (CINAHL). The search presented 786 items, and by inclusion and exclusion filterers, 59 works were considered for final review. The Newcastle-Ottawa Scale (NOS) method was adopted to conduct quality assessment; 19 papers were further selected based on the quality score. Obesity-related inflammation leads to a low-grade inflammatory state in organisms by upregulating pro-inflammatory markers and downregulating anti-inflammatory cytokines, thereby contributing to cardiovascular disease pathogenesis. Because of inflammatory and infectious symptoms, adipocytes appear to instigate articulation and discharge a few intense stage reactants and carriers of inflammation. Obesity and inflammatory markers are strongly associated, and are important factors in the development of CVD. Hence, weight management can help prevent cardiovascular risks and poor outcomes by inhibiting inflammatory mechanisms., Competing Interests: No authors have any conflicts of interest during the publication of the manuscript.

The novel coronavirus disease (COVID-19) is an ongoing pandemic with large global attention. However, spreading false news on social media sites like Twitter is creating unnecessary anxiety towards this disease. The motto behind this study is to analyses tweets by Indian netizens during the COVID-19 lockdown. The data included tweets collected on the dates between 23 March 2020 and 15 July 2020 and the text has been labelled as fear, sad, anger, and joy. Data analysis was conducted by Bidirectional Encoder Representations from Transformers (BERT) model, which is a new deep-learning model for text analysis and performance and was compared with three other models such as logistic regression (LR), support vector machines (SVM), and long-short term memory (LSTM). Accuracy for every sentiment was separately calculated. The BERT model produced 89% accuracy and the other three models produced 75%, 74.75%, and 65%, respectively. Each sentiment classification has accuracy ranging from 75.88-87.33% with a median accuracy of 79.34%, which is a relatively considerable value in text mining algorithms. Our findings present the high prevalence of keywords and associated terms among Indian tweets during COVID-19. Further, this work clarifies public opinion on pandemics and lead public health authorities for a better society.

The purpose of this study was to provide a United States perspective on alloplastic total joint replacement. We sought to estimate the inpatient burden and report the most common adverse events using two administrative datasets. The National Inpatient Sample was queried from October 2015 to December 2016 for total joint replacement admissions using International Classification of Diseases 10 th revision codes, and the Manufacturer and User Facility Device Experience registry was queried from January 2009 to September 2019 using manufacturer brands. The combined final sample included 114 inpatient admissions and 392 adverse events. Mean age was 43.1 years, and most patients were white (82.7%) and female (86.0%). The mean hospital charge was $108,709.43 and the mean length of stay was 2.6 days. The most common adverse events were infection (26.3%), heterotopic bone (20.9%), and poor intraoperative fit (14.0%). Fifty-four percent of cases had bilateral total joint replacements, 24.6% had simultaneous subcutaneous abdominal fat grafting, and 11.4% had simultaneous maxillary repositioning. Fat grafting and maxillary repositioning were not associated with any significant difference in the length of stay or cost. Compared to unilateral cases, bilateral total joint replacements carried significantly greater charges (P<0.01), but no increased length of stay (P=0.70), suggesting that bilateral and unilateral cases may experience a similar postoperative course., (Copyright © 2020 International Association of Oral and Maxillofacial Surgeons. All rights reserved.)

Background : The ongoing pandemic due to the novel coronavirus (COVID-19) is becoming a serious global threat. Experts suggest that the infection can be controlled by immediate prevention measures. Sailing is one of the occupational categories more vulnerable to this virus outbreak due to the proximity of the working conditions. Objective: Awareness and knowledge assessments of seafarers towards the current epidemic is mandatory to understand the effectiveness and success of the infection control measures adopted by shipping companies. Methods: In this study, we presented an online questionnaire survey to determine the knowledge levels of COVID-19 among seafarers. The data were collected by self-reported survey, and analysis was done by the analysis of variance (ANOVA). The t -test was used to understand the knowledge attitude differences to COVID-19 among different occupational groups of seafarers, and the p -value ≤ of 0.05 was considered statistically significant. Results: Among 1,458 responses received, 92.82% had a college or university degree. The results reported that the mean COVID-19 knowledge score was 5.82 (standard deviation = 0.51, range 0-6), and the overall correct percentage was 97%. There was a statistically significant difference between age groups (F (4, 1453) = 5.44, p < 0.001) and educational groups (F (4, 1453) = 1.52, p < 0.001). The knowledge score was not significantly different across the educational status of the participants (F (2, 1455) = 1.52, p = 0.220). Conclusions : The present study highlighted good knowledge and behaviours among sailors about COVID-19. However, shipping companies need to come up with new campaigns to hold optimistic practices and suitable guidelines on ships, including cruise boats, to keep sea workers always alert and collaborative in mitigating the spread of COVID-19.

Purpose: To identify clinical and radiographic factors associated with failure of revision hip arthroscopy (RHA)., Methods: A database was used to identify patients who underwent primary hip arthroscopy and revision hip arthroscopy (RHA) from January 2007 to December 2017 for the indication of femoroacetabular impingement and failure of the index procedure, respectively. The primary outcome was defined as the change, or difference, in the preoperative to postoperative alpha angle between patients with successful RHA and those with failed RHA. Failure was defined as reoperation on the operative hip for any indication or a modified Harris Hip Score (mHHS) of less than 70 at the 1-year postoperative time point. All patients had a minimum of 2 years' follow-up from the date of revision hip surgery. Patients with a history of revision were divided into those with failed revisions and those with successful revisions. The inclusion criteria for failed revision included a history of subsequent revision surgery (or arthroplasty) or an mHHS of less than 70 at final follow-up., Results: The study included 26 patients, comprising 8 (31%) with failed RHA and 18 (69%) with successful revision. The failure group showed a significantly smaller decrease in the alpha angle with surgery, measured on the Dunn view, compared with the success group. When the preoperative alpha angle was held constant, each 1° increase in the difference between the preoperative and postoperative alpha angles achieved during surgery was associated with a 17% decrease in the odds of failure. Patients included in the success group had both a higher preoperative mHHS (44.2 ± 8.6 vs 34.7 ± 9.6) and a higher postoperative mHHS (83.2 ± 8.3 vs 62.3 ± 14.2) than patients with failed RHA. There was a statistically significant difference in the frequency of patients who achieved the patient acceptable symptomatic state of +74.0 between the failure (25%) and success (83%) groups; 88% of patients in the failure group met the minimal clinically important difference, whereas 100% of patients in the success group (n = 18) met it., Conclusions: Complete resection of cam lesions as determined by changes in the alpha angle, anterior offset, and head-neck ratio when measured on the Dunn 45° view correlates with positive clinical outcomes after RHA., Level of Evidence: III, Retrospective Comparative Study., (© 2020 by the Arthroscopy Association of North America. Published by Elsevier Inc.)

Background: Health observatory (HO) models are helpful in gathering, analyzing, interpreting, and circulating reliable and quality information on population health and health service delivery. In this study, we proposed an HO conceptual model to enhance seafarer's health, which subjects to disease trends., Methods: Three methods were followed during the study: a systematic collection of seafarer's health data from the Centro Internazionale Radio Medico (C.I.R.M.) repository, an integrative review of existing seafarer's policy, and both open and closed questionnaires were distributed to stakeholders to develop clinical knowledge. C.I.R.M. is the Italian Telemedical Maritime Assistance Service (TMAS). Results and Discussion. A three-layer HO framework was developed, and each layer had its components and functionalities. The proposed HO model integrated with the outcomes of the mentioned methods was working as the origin of the framework. In this way, we can design a standard infrastructure in ships and risk assessment conduction., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2020 Gopi Battineni et al.)

Background: Previous research has demonstrated a statistically significant relationship between hip arthroscopy outcomes and age., Purpose: To investigate the link, if any, between hip arthroscopy outcomes and intraoperative pathology as well as with patient age and sex., Study Design: Cohort study; Level of evidence, 3., Methods: Of 272 female patients aged ≥14 years undergoing primary hip arthroscopy for femoroacetabular impingement between August 2010 and September 2017, and with 2-year patient-reported outcome scores, a total of 194 (71.3%) were included for final analysis. These patients were separated into 3 age-based cohorts: <30 years (n = 44), 30 to 45 years (n = 74), and >45 years (n = 76). Their data were then analyzed and compared with respect to patient characteristic information, intraoperative pathology, and functional outcome scores for statistical significance, which was set at P < .05., Results: When an analysis of variance was conducted for the 3 age groups at 2-year follow-up, there was a statistically significant difference for modified Hip Harris Score ( P = .0003; <30 years, 88.26 ± 13.1 [mean ± SD]; 30-45 years, 82.68 ± 18.0; >45 years, 75.03 ± 19.5). The results of an analysis of variance comparing 2-year Non-arthritic Hip Score were also statistically significant ( P = .0002; <30 years, 89.9 ± 13.7; 30-45 years, 85.8 ± 15.8; >45 years, 78.1 ± 17.2). Results of logistic regression demonstrated that the odds of a cam-type lesion decreased by 0.971 for every additional year in age among female patients. The odds of achieving the patient-acceptable symptomatic state decreased by a factor of 0.96 for each additional year in age ( P < .0004)., Conclusion: Surgical treatment of femoroacetabular impingement in females led to improved functional outcomes at 2 years of follow-up, although older female patients did worse after hip arthroscopy as compared with their younger counterparts. There may be an age-dependent decrease in incidence of cam-type lesions in female patients.

Background: Internet represents a relevant source of information, but reliability of data that can be obtained by the web is still an unsolved issue. Non-reliable online information may have a relevance, especially in taking decisions related to health problems. Uncertainties on the quality of online health data may have a negative impact on health-related choices of citizens., Objective: This work consisted in a cross-sectional literature review of published papers on online health information. The two main research objectives consisted in the analysis of trends in the use of health web sites and in the quality assessment and reliability levels of web medical sites., Methods: Literature research was made using four digital reference databases, namely PubMed, British Medical Journal, Biomed, and CINAHL. Entries used were "trustworthy of medical information online," "survey to evaluate medical information online," "medical information online," and "habits of web-based health information users". Analysis included only papers published in English. The Newcastle Ottawa Scale was used to conduct quality checks of selected works., Results: Literature analysis using the above entries resulted in 212 studies. Twenty-four articles in line with study objectives, and user characteristics were selected. People more prone to use the internet for obtaining health information were females, younger people, scholars, and employees. Reliability of different online health sites is an issue taken into account by the majority of people using the internet for obtaining health information and physician assistance could help people to surf more safe health web sites., Conclusions: Limited health information and/or web literacy can cause misunderstandings in evaluating medical data found in the web. An appropriate education plan and evaluation tools could enhance user skills and bring to a more cautious analysis of health information found in the web., (© The Author(s) 2020.)

Increasing evidence suggests the utility of magnetic resonance imaging (MRI) as an important technique for the diagnosis of Alzheimer's disease (AD) and for predicting the onset of this neurodegenerative disorder. In this study, we present a sophisticated machine learning (ML) model of great accuracy to diagnose the early stages of AD. A total of 373 MRI tests belonging to 150 subjects (age ≥ 60) were examined and analyzed in parallel with fourteen distinct features related to standard AD diagnosis. Four ML models, such as naive Bayes (NB), artificial neural networks (ANN), K-nearest neighbor (KNN), and support-vector machines (SVM), and the receiver operating characteristic (ROC) curve metric were used to validate the model performance. Each model evaluation was done in three independent experiments. In the first experiment, a manual feature selection was used for model training, and ANN generated the highest accuracy in terms of ROC (0.812). In the second experiment, automatic feature selection was conducted by wrapping methods, and the NB achieved the highest ROC of 0.942. The last experiment consisted of an ensemble or hybrid modeling developed to combine the four models. This approach resulted in an improved accuracy ROC of 0.991. We conclude that the involvement of ensemble modeling, coupled with selective features, can predict with better accuracy the development of AD at an early stage.

Background: COVID-19 disease is becoming a global pandemic and more than 200 countries were affected because of this disease. Italy is one of the countries is largely suffered with this virus outbreak, and about 180,000 cases (as of 20 April 2020) were registered which explains the large transmissibility and reproduction case numbers., Objective: In this study, we considered the Marche region of Italy to compute different daily transmission rates (R t ) including five provinces in it. We also present forecasting of daily and cumulative incidences associated after the next thirty days. The Marche region is the 8th in terms of number of people infected in Italy and the first in terms of diffusion of the infection among the 4 regions of the center of Italy., Methods: Epidemic statistics were extracted from the national Italian Health Ministry website. We considered outbreak information where the first case registered in Marche with onset symptoms (26 February 2020) to the present date (20 April 2020). Adoption of incidence and projections with R statistics was done., Results: The median values of R t for the five provinces of Pesaro and Urbano, Ancona, Fermo, Ascoli Piceno, and Macerata, was 2.492 (1.1-4.5), 2.162 (1.0-4.0), 1.512 (0.75-2.75), 1.141 (1.0-1.6), and 1.792 (1.0-3.5) with 95% of CI achieved. The projections at end of 30th day of the cumulative incidences 323 (95% CI), and daily incidences 45 (95% CI) could be possible., Conclusions: This study highlights the knowledge of essential insights into the Marche region in particular to virus transmission dynamics, geographical characteristics of positive incidences, and the necessity of implementing mitigation procedures to fight against the COVID-19 outbreak., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Since the discovery of the Coronavirus (nCOV-19), it has become a global pandemic. At the same time, it has been a great challenge to hospitals or healthcare staff to manage the flow of the high number of cases. Especially in remote areas, it is becoming more difficult to consult a medical specialist when the immediate hit of the epidemic has occurred. Thus, it becomes obvious that if effectively designed and deployed chatbot can help patients living in remote areas by promoting preventive measures, virus updates, and reducing psychological damage caused by isolation and fear. This study presents the design of a sophisticated artificial intelligence (AI) chatbot for the purpose of diagnostic evaluation and recommending immediate measures when patients are exposed to nCOV-19. In addition, presenting a virtual assistant can also measure the infection severity and connects with registered doctors when symptoms become serious., Competing Interests: The authors declare no conflicts of interest.

Background: Till 31 March 2020, 105,792 COVID-19 cases were confirmed in Italy including 15,726 deaths which explains how worst the epidemic has affected the country. After the announcement of lockdown in Italy on 9 March 2020, situation was becoming stable since last days of March. In view of this, it is important to forecast the COVID-19 evaluation of Italy condition and the possible effects, if this lock down could continue for another 60 days., Methods: COVID-19 infected patient data has extracted from the Italian Health Ministry website includes registered and recovered cases from mid February to end March. Adoption of seasonal ARIMA forecasting package with R statistical model was done., Results: Predictions were done with 93.75% of accuracy for registered case models and 84.4% of accuracy for recovered case models. The forecasting of infected patients could be reach the value of 182,757, and recovered cases could be registered value of 81,635 at end of May., Conclusions: This study highlights the importance of country lockdown and self isolation in control the disease transmissibility among Italian population through data driven model analysis. Our findings suggest that nearly 35% decrement of registered cases and 66% growth of recovered cases will be possible., Competing Interests: Declaration of Competing Interest No author does not have any conflicts of interest., (Copyright © 2020. Published by Elsevier B.V.)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the aetiological factor of COVID-19 infection, poses problems in providing medical assistance at sea. Ships are in an isolated environment, and most of the merchant ships do not carry medical personnel or medical supplies. Telemedicine offers a real possibility to provide reasonable quality medical assistance to seagoing vessels. The fact that ships may touch ports in affected areas, the difficulties for seafarers to be assisted ashore due to quarantine measures and the crews' lack of turnover make medical assistance at sea difficult. This study has compared maritime telemedical assistance data before and during the COVID-19 pandemic to propose prevention measures., Materials and Methods: The study was based on the data from medical records of Centro Internazionale Radio Medico (C.I.R.M.) database of seafarers assisted from January 1 to June 30, in the years 2017-2020. The data were collected separately for each year. Age, sex, rank, and pathologies affecting the assisted seafarers were considered. Common signs of COVID-19 infection such as fever, cough, sore throat, shortness of breath, and other respiratory symptoms were analysed., Results: From January 1, 2017, to December 31, 2019, C.I.R.M. assisted 15,888 patients on board ships. During the first 6 months of the years under evaluation, C.I.R.M. assisted 2,419 patients in 2017, 2,444 patients in 2018, 2,694 patients in 2019, and 3,924 in 2020. The number of assisted cases almost doubled in the first 6 months (from January to June) of 2020 compared to the same period of the previous years. Gastrointestinal disorders, injuries/traumas, and dermatological pathologies were the first, second, and third most often reported causes of illness on board over the 4-year study period. A higher number of seafarers with fever, cough, sore throat, and shortness of breath were assisted during the COVID-19 pandemic than before the coronavirus outbreak. Medical requests for fever increased significantly during the COVID-19 pandemic compared to the same period from 2017 to 2019., Conclusions: The requests for medical advice for fever, sore throat, and shortness of breath were significantly more common during the coronavirus epidemic. Close follow-up, regular health education on preventing coronavirus transmission, personal protective equipment, adequate environmental hygiene, and applying other standard precautions could help minimise the risk factors for the spread of COVID-19.

Purpose: Maxillomandibular advancement (MMA) is an effective treatment for obstructive sleep apnea (OSA); however, the esthetic outcome is a frequent source of concern. The purpose of the present study was to determine whether MMA altered the lay perception of patients' personality traits and emotional expressions., Materials and Methods: We conducted a survey of the lay public recruited through Qualtrics Research Services (available at: www.qualtrics.com). Clinical photographs were obtained from patients at our institution who had undergone MMA with advancement genioplasty for OSA. Survey respondents were randomized to either pre- or postoperative photograph sets and were asked to rate the clinical photographs on 6 personality and 6 emotional traits using 7-point Likert scales. The independent predictor was the preoperative or postoperative status. The dependent outcomes were the emotional and personality trait ratings. Multivariate analyses of variance were conducted to determine whether MMA had a significant effect on 2 or more emotional or personality traits. Significant results underwent post hoc testing with Bonferroni correction to determine which individual traits were affected., Results: A total of 670 individuals accessed the published survey, of whom 210 (31.3%) completed the task and had their responses included in the final sample. No significant differences were found in age (P = .54), gender (P = .31), or ethnicity (P = .26) between the included and excluded respondents. Within the final sample, 110 participants were assigned to the preoperative image set and 100 to the postoperative set. After MMA, patients were observed to have significantly different emotional expressions (P < .01) but not personality traits (P = .12). Post hoc testing found patients to be significantly less sad (P < .01) and less disgusted (P < .01)., Conclusions: MMA was accompanied by favorable changes in the lay perceptions of emotional, but not personality, traits. Patients considering surgery should recognize that their outward appearance will not be negatively affected by a large functional advancement., (Copyright © 2019 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: In recent years, the prevention of non-communicable diseases represents one of the mainproblems of preventive medicine. Significant risk factor for these diseases is sedentary lifestyle; in otherwords, lack of physical activity. It is happened, especially in seafarers, since they do not have much facilitatesto do physical exercise on board. The present study is designed to develop a simple user-guide mobileapplication to conduct activities with available equipment on board a ship., Materials and Methods: We held two pilot tests for app evolution. In the first phase, we selected members(n = 13) and produced a questionnaire related to usability, feasibility, and accessibility of the app. Basedon the responses from users, we developed the second version of the app and provided to (n = 15) randomseafarers for testing and operating., Results: On average, 93.3% of seafarers mentioned that app was easy to use, while in the first phase it wasequal to 84.6%. At the same time, 89.9% of users were satisfied with feasibility, and we had accomplished95% satisfaction rate in the second phase. Ultimately, we had achieved better responses in the secondevolution phase when compared with the first phase., Conclusions: This app is made for planning a quality physical activity program for seamen that allows a seafarerto choose the adequate activity in line with his physical characteristic, fitness level, and motivations.

Background: Few studies in low- and middle-income countries have examined the roles of couples in infant and young child feeding decision making and practices, and there is no corresponding data in the context of human immunodeficiency virus (HIV). Research aim: This study aimed to explore mothers' and fathers' perceptions of their roles in feeding decision making and practices., Methods: The authors conducted in-depth interviews with 15 mothers and their male partners, recruited from the catchment areas of two urban and two rural government clinics in Lilongwe District, Malawi. The mothers were ≥ 18 years of age, were HIV positive, and had a child < 24 months of age. Twelve of the 15 fathers were also HIV positive. The interviews were analyzed using content analysis., Results: Mothers were responsible for child care, including breastfeeding and complementary feeding. Fathers provided monetary support for purchasing food and offered verbal support to encourage mothers to implement recommended feeding practices. Many fathers found it difficult to support adequate complementary feeding because of household food insecurity. Mothers were advised on child feeding during prevention of mother-to-child transmission clinic visits. No fathers in this study accompanied women to clinic appointments, so they were less well-informed about feeding than mothers. Fathers usually deferred to mothers in feeding decision making. One-third of mothers wanted fathers to be more involved in child feeding., Conclusion: Malawian mothers' and fathers' roles in feeding decision making in the context of HIV align with local gender norms. Strategies are needed to improve fathers' knowledge of and involvement in child feeding, as desired by mothers.

Background: The reported incidence (0.16-1.5 %) of bile duct injury (BDI) during laparoscopic cholecystectomy (LC) is higher than during open cholecystectomy and has not decreased over time despite increasing experience with the procedure. The "critical view of safety" (CVS) technique may help to prevent BDI when certain criteria are met prior to division of any structures. This study aimed to evaluate the adherence of practicing surgeons to the CVS criteria during LC and the impact of a training intervention on CVS identification., Methods: LC procedures of general surgeons were video-recorded. De-identified recordings were reviewed by a blinded observer and rated on a 6-point scale using the previously published CVS criteria. A coaching program was conducted, and participating surgeons were re-assessed in the same manner., Results: The observer assessed ten LC videos, each involving a different surgeon. The CVS was adequately achieved by two surgeons (20 %). The remaining eight surgeons (80 %) did not obtain adequate CVS prior to division of any structures, despite two surgeons dictating that they did; the mean score of this group was 1.75. After training, five participating surgeons (50 %) scored > 4, and the mean increased from 1.75 (baseline) to 3.75 (p < 0.05)., Conclusions: The CVS criteria were not routinely used by the majority of participating surgeons. Further, one-fourth of those who claimed to obtain the CVS did so inadequately. All surgeons who participated in training showed improvement during their post-assessment. Our findings suggest that education of practicing surgeons in the application of the CVS during LC can result in increased implementation and quality of the CVS. Pending studies with larger samples, our findings may partly explain the sustained BDI incidence despite increased experience with LC. Our study also supports the value of direct observation of surgical practices and subsequent training for quality improvement.