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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