Search

Background/purposeDuring pandemics like SARS-CoV-2, healthcare providers' well-being and morale are in particular at stake. Burnout may substantially hinder the well-being and morale of healthcare providers, challenging our efforts at disease containment. This study investigated the relationship between perceived COVID-19 stigma and burnout symptoms among physicians and nurses. We further aimed to identify potential factors that may moderate this relationship, including profession, clinical contact with COVID-19 patients, and prior experience with 2003 SARS-CoV-1.MethodsWe used a web-based, structured survey from March 12th to 29th, 2020 to collect cross-sectional, self-reported data. Participants were provided with a link to the survey which took them on average 5-8 minutes. Survey consisted of demographic characteristics, clinical experiences, perceived COVID-19 related stigma, and burnout symptoms. Linear regression with bootstrapping techniques was adopted to test the relations between stigma and burnout, as well as other potential moderators, while adjusting for demographic and clinical factors.ResultsOf the 1421 consented respondents, 357 identified as physicians while 1064 identified as nurses. Participants reported some levels of stigma, and noticeable burnout symptoms. Burnout symptoms were positively correlated with COVID-19 stigma, profession, and currently care for confirmed/suspected COVID-19 patients. The interaction between stigma and profession (Stigma × Nurses) but no other interaction terms reached the significance level, suggesting that the slope for nurses was flatter than the slope for physicians.ConclusionThe study results suggest that COVID-19 stigma may contribute to burnout among physicians and nurses, and this relation may not vary across clinical roles and experiences but profession.

Accurate segmentation of the left ventricle (LV) using echocardiogram (Echo) images is essential for cardiovascular analysis. Conventional techniques are labor-intensive and exhibit inter-observer variability. Deep learning has emerged as a powerful tool for automated medical image segmentation, offering advantages in speed and potentially superior accuracy. This study explores the efficacy of employing a YOLO (You Only Look Once) segmentation model for automated LV segmentation in Echo images. YOLO, a cutting-edge object detection model, achieves exceptional speed–accuracy balance through its well-designed architecture. It utilizes efficient dilated convolutional layers and bottleneck blocks for feature extraction while incorporating innovations like path aggregation and spatial attention mechanisms. These attributes make YOLO a compelling candidate for adaptation to LV segmentation in Echo images. We posit that by fine-tuning a pre-trained YOLO-based model on a well-annotated Echo image dataset, we can leverage the model's strengths in real-time processing and precise object localization to achieve robust LV segmentation. The proposed approach entails fine-tuning a pre-trained YOLO model on a rigorously labeled Echo image dataset. Model performance has been evaluated using established metrics such as mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 50% (mAP50) with 98.31% and across a range of IoU thresholds from 50% to 95% (mAP50:95) with 75.27%. Successful implementation of YOLO for LV segmentation has the potential to significantly expedite and standardize Echo image analysis. This advancement could translate to improved clinical decision-making and enhanced patient care. [ABSTRACT FROM AUTHOR]

Background Whether rapid transportation can benefit patients with trauma remains controversial. We determined the association between prehospital time and outcome to explore the concept of the 'golden hour' for injured patients. Methods and findings We conducted a retrospective cohort study of trauma patients transported from the scene to hospitals by emergency medical service (EMS) from January 1, 2016, to November 30, 2018, using data from the Pan-Asia Trauma Outcomes Study (PATOS) database. Prehospital time intervals were categorized into response time (RT), scene to hospital time (SH), and total prehospital time (TPT). The outcomes were 30-day mortality and functional status at hospital discharge. Multivariable logistic regression was used to investigate the association of prehospital time and outcomes to adjust for factors including age, sex, mechanism and type of injury, Injury Severity Score (ISS), Revised Trauma Score (RTS), and prehospital interventions. Overall, 24,365 patients from 4 countries (645 patients from Japan, 16,476 patients from Korea, 5,358 patients from Malaysia, and 1,886 patients from Taiwan) were included in the analysis. Among included patients, the median age was 45 years (lower quartile [Q1]-upper quartile [Q3]: 25-62), and 15,498 (63.6%) patients were male. Median (Q1-Q3) RT, SH, and TPT were 20 (Q1-Q3: 12-39), 21 (Q1-Q3: 16-29), and 47 (Q1-Q3: 32-60) minutes, respectively. In all, 280 patients (1.1%) died within 30 days after injury. Prehospital time intervals were not associated with 30-day mortality. The adjusted odds ratios (aORs) per 10 minutes of RT, SH, and TPT were 0.99 (95% CI 0.92-1.06, p = 0.740), 1.08 (95% CI 1.00-1.17, p = 0.065), and 1.03 (95% CI 0.98-1.09, p = 0.236), respectively. However, long prehospital time was detrimental to functional survival. The aORs of RT, SH, and TPT per 10-minute delay were 1.06 (95% CI 1.04-1.08, p < 0.001), 1.05 (95% CI 1.01-1.08, p = 0.007), and 1.06 (95% CI 1.04-1.08, p < 0.001), respectively. The key limitation of our study is the missing data inherent to the retrospective design. Another major limitation is the aggregate nature of the data from different countries and unaccounted confounders such as in-hospital management. Conclusions Longer prehospital time was not associated with an increased risk of 30-day mortality, but it may be associated with increased risk of poor functional outcomes in injured patients. This finding supports the concept of the 'golden hour' for trauma patients during prehospital care in the countries studied., Author(s): Chi-Hsin Chen 1, Sang Do Shin 2, Jen-Tang Sun 3, Sabariah Faizah Jamaluddin 4, Hideharu Tanaka 5, Kyoung Jun Song 2, Kentaro Kajino 6, Akio Kimura 7, Edward Pei-Chuan [...]

Injury is a major cause of morbidity and mortality in children. However, the epidemiology and prehospital care for pediatric unintentional injuries in Asia are still unclear. A total of 9,737 pediatric patients aged <18 years with unintentional injuries cared for at participating centers of the Pan-Asian Trauma Outcome Study (PATOS) from October 2015 to December 2020 were reviewed retrospectively. Patients were divided into two groups: those <8 and those ≥8 years of age. Variables such as patient demographics, injury epidemiology, Injury Severity Score (ISS), and prehospital care were collected. Injury severity and administered prehospital care stratified by gross national income were also analyzed. Pediatric unintentional injuries accounted for 9.4% of EMS-transported trauma cases in the participating Asian centers, and the mortality rate was 0.88%. The leading cause of injury was traffic injuries in older children aged ≥8 years (56.5%), while falls at home were common among young children aged <8 years (43.9%). Compared with younger children, older children with similar ISS tended to receive more prehospital interventions. Uneven disease severity was found in that older children in lower-middle and upper-middle-income countries had higher ISS compared with those in high-income countries. The performance of prehospital interventions also differed among countries with different gross national incomes. Immobilizations were the most performed prehospital intervention followed by oxygen administration, airway management, and pain control; only one patient received prehospital thoracentesis. Procedures were performed more frequently in high-income countries than in upper-middle-income and lower-middle-income countries. The major cause of injury was road traffic injuries in older children, while falls at home were common among young children. Prehospital care in pediatric unintentional injuries in Asian countries was not standardized and might be insufficient, and the economic status of countries may affect the implementation of prehospital care. [ABSTRACT FROM AUTHOR]