Background: In 3%-19% of patients, reintubation is needed 48-72 hours following extubation, which increases intensive care unit (ICU) morbidity, mortality, and expenses. Extubation failure is frequently caused by diaphragm dysfunction. Ultrasonography can be used to determine the mobility and thickness of the diaphragm. This study looked at the role of diaphragm excursion (DE) and thickening fraction in predicting successful extubation from mechanical ventilation. Methods: Thirty-one patients were extubated with the advice of an ICU consultant using the ICU weaning regimen and diaphragm ultrasonography was performed. Ultrasound DE and thickening fraction were measured three times: at the commencement of the T-piece experiment, at 10 minutes, and immediately before extubation. All patients' parameters were monitored for 48 hours after extubation. Rapid shallow breathing index (RSBI) was also measured at the same time. Results: Successful extubation was significantly correlated with DE (P<0.001). Receiver curve analysis for DE to predict successful extubation revealed good properties (area under the curve [AUC], 0.83; P<0.001); sensitivity, 77.8%; specificity, 84.6%; positive predictive value (PPV), 84.6%; negative predictive value (NPV), 73.3% while cut-off value, 11.43 mm. Diaphragm thickening fraction (DTF) also revealed moderate curve properties (AUC, 0.69; P=0.06); sensitivity, 61.1%; specificity, 84.6%; PPV, 87.5%; NPV, 61.1% with cut-off value 22.33% although former one was slightly better. RSBI could not reach good receiver operating characteristic value at cut-off points 100 breaths/min/L (AUC, 0.58; P=0.47); sensitivity, 66.7%; specificity, 53.8%; PPV, 66.7%; NPV, 53.8%). Conclusions: To decrease the rate of reintubation, DE and DTF are better indicators of successful extubation. DE outperforms DTF.

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BackgroundDuring the COVID-19 pandemic, online education and entertainment have increased significantly due to strict isolation and frequent lockdowns. This study intended to explore the prevalence and potential factors associated with computer vision syndrome (CVS) among the postsecondary students of Bangladesh pursuing online education.MethodsIn total, there were 917 postsecondary students participated in this study. Information on sociodemographic variables, and CVS symptom-related variables were collected using a prevalidated self-administered questionnaire. The CVS questionnaire was used to assess an individual’s CVS status. The bivariate association between CVS and other categorical variables was obtained using a χ2 test. A multivariable logistic regression model was used to explore variables associated with the CVS.ResultsThe overall prevalence of CVS was 68.16%. Most common symptoms were headache (42.4%), feeling of worsening eyesight (23.2%), and eye pain (23.2%). CVS was associated with educational status (p=0.03), family history of eye-related problems (p<0.001), personal history of eye-related problems (p<0.001), usage of eye accessories (p<0.001), type of device used for online education (p<0.01), average daily use (p<0.01), and usage pattern (p=0.02). After adjusting for confounders, CVS was significantly related to the use of mobile or tablet (adjusted OR, AOR 8.954, 95% CI 1.57 to 51.063), continuing online education for more than 12 hours/day without any break or insufficient break (AOR 7.654, 95% CI 1.625 to 36.053), and previous family (AOR 3.189, 95% CI 1.751 to 5.811) or personal history of eye problems or headaches, or insomnia (AOR 6.214, 95% CI 2.783 to 13.878).ConclusionA high prevalence of CVS was observed among the post-secondary students in Bangladesh. Since an extensive use of digital screens is somewhat unavoidable during unprecedented times, such as COVID-19, educators should include CVS awareness and prevention in their curricula.

BackgroundPeople are becoming more dependent on technology than ever before. Today’s children and adults are heavily plugged into electronics, which raises concerns for their physical and cognitive development. This cross-sectional study was conducted to assess the relationship between media usage and cognitive function among school-going children.MethodsThis cross-sectional study was conducted in 11 schools in 3 of Bangladesh’s most populous metropolitan areas: Dhaka, Chattogram and Cumilla. A semistructured questionnaire with three sections was used to obtain data from the respondents: (1) background information, (2) PedsQL Cognitive Functioning Scale and (3) Problematic Media Use Measure Short Form. Stata (V.16) was used for statistical analysis. Mean and SD were used to summarise quantitative variables. Qualitative variables were summarised using frequency and percentage. The χ2test was used to explore bivariate association between categorical variables, and a binary logistic regression model was fit to investigate the factors associated with the cognitive function of the study participants after adjusting for confounders.ResultsThe mean age of total of 769 participants was 12.0±1.8 years, and the majority (67.31%) were females. The prevalence of high gadget addiction and poor cognitive function was 46.9% and 46.5%, respectively, among the participants. After adjusting the factors, this study found a statistically significant relationship (adjusted OR 0.4, 95% CI 0.3 to 0.7) between gadget addiction and cognitive function. In addition, the duration of breast feeding was a predictor of cognitive function as well.ConclusionThis study found digital media addiction as a predictor of decreased cognitive performance in children who use digital gadgets regularly. Although the cross-sectional design of the study precludes causal relationships from being determined, the study finding deserves further examination via longitudinal research.

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Health professionals and medical students are at increased risk of the imposter phenomenon (IP) in other words, the imposter syndrome, due to the challenging nature of their professions. It is particularly concerning since it is linked to a higher incidence of burnout and suicidal ideation. We must first thoroughly grasp its prevalence and associated factors to address this issue. However, no published review of the data includes a meta-analysis to help understand the character and associated factors of IP among medical workers and medical students. This study aims to investigate IP prevalence and risk factors among healthcare personnel. Five online databases will be searched for papers published in English between January 2000 and December 2022, and 2 independent reviewers will filter, select studies, extract data, and evaluate the risk of bias in each piece. The retrieved articles will be included based on strict inclusion and exclusion criteria. A third reviewer will decide on any disagreements between the 2 reviewers. Where appropriate, a meta-analysis will be conducted using the random-effects model. The heterogeneity of the studies will be examined, and a sensitivity analysis will be done depending on the study quality. The purpose of this review is to determine the prevalence and risk factors for IP among healthcare personnel. The review’s findings will emphasize the severity and contributing factors of the problem, therefore guiding policy for future actions.

Background When caring for COVID-19 patients, using personal protective equipment (PPE) may significantly lower the risk of infection of health care workers (HCWs). However, adverse responses due to PPE use have been observed during the 2003 SARS pandemic. This study will highlight the different adverse reactions caused by face mask use, one of the essential components of PPE in the HCWs, and identify the factors associated with these problems. Methods This cross-sectional survey was conducted between September and October 2021. 404 HCWs were selected by snowball sampling from four randomly selected healthcare facilities of Bangladesh. Trained volunteers collected data by face-to-face interview using a pretested structured questionnaire. Data were analyzed using STATA (v.16) and summarized using frequency and relative frequency. Later, the chi-square test was used to explore bivariate relationships, and the binary logistic regression model was fit to identify the predictors. Results The majority of the respondents were 26–36 years (70.30%), male (69.80%), and doctors (74.50%). 48.76% of the respondents had unfavorable skin responses beneath the face masks; female gender, physicians, professionals working more than 32 hours a week, wearing N95, and more than one mask were predictors of skin problem. 28.47% and 60.15% of all participants suffered from some form of oral and neurological problems, respectively. Conclusion Face mask use sequelae, especially skin, oral and neurological problems, are prevalent among health care workers. Therefore, necessary precautionary measures should be taken to safeguard our frontlines.