Purpose: This cohort study evaluated the effectiveness of noninvasive heart rate variability (HRV) analysis to assess the risk of cardiovascular disease over a period of 8 years. Methods: Personal and working characteristics were collected before biochemistry examinations and 5 min HRV tests from the Taiwan Bus Driver Cohort Study (TBDCS) in 2005. This study eventually identified 161 drivers with cardiovascular disease (CVD) and 627 without between 2005 and 2012. Estimation of the hazard ratio was analyzed by using the Cox proportional-hazards model. Results: Subjects with CVD had an overall lower standard deviation of NN intervals (SDNN) than their counterparts did. The SDNN index had a strong association with CVD, even after adjusting for risk factors. Using a median split for SDNN, the hazard ratio of CVD was 1.83 (95% CI = 1.10–3.04) in Model 1 and 1.87 (95% CI = 1.11–3.13) in Model 2. Furthermore, the low-frequency (LF) index was associated with a risk of CVD in the continuous approach. For hypertensive disease, the SDNN index was associated with increased risks in both the continuous and dichotomized approaches. When the root-mean-square of the successive differences (RMSSDs), high frequency (HF), and LF were continuous variables, significant associations with hypertensive disease were observed. Conclusions: This cohort study suggests that SDNN and LF levels are useful for predicting 8 year CVD risk, especially for hypertensive disease. Further research is required to determine preventive measures for modifying HRV dysfunction, as well as to investigate whether these interventions could decrease CVD risk among professional drivers.

During the coronavirus disease (COVID-19) pandemic, we admitted suspected or confirmed COVID-19 patients to our isolation wards between 2 March 2020 and 4 May 2020, following a well-designed and efficient assessment protocol. We included 217 patients suspected of COVID-19, of which 27 had confirmed COVID-19. The clinical characteristics of these patients were used to train artificial intelligence (AI) models such as support vector machine (SVM), decision tree, random forest, and artificial neural network for diagnosing COVID-19. When analyzing the performance of the models, SVM showed the highest sensitivity (SVM vs. decision tree vs. random forest vs. artificial neural network: 100% vs. 42.86% vs. 28.57% vs. 71.43%), while decision tree and random forest had the highest specificity (SVM vs. decision tree vs. random forest vs. artificial neural network: 88.37% vs. 100% vs. 100% vs. 94.74%) in the diagnosis of COVID-19. With the aid of AI models, physicians may identify COVID-19 patients earlier, even with few baseline data available, and segregate infected patients earlier to avoid hospital cluster infections and to ensure the safety of medical professionals and ordinary patients in the hospital.

Topic: To evaluate the efficacy and safety of femtosecond laser-assisted cataract surgery (FLACS) vs conventional phacoemulsification in eyes with shallow anterior chambers or primary angle-closure disease, with endothelial cell loss (ECL) as the primary outcome (PROSPERO: CRD420251274747). Clinical Relevance: Shallow anterior chambers pose unique surgical challenges during phacoemulsification, placing the corneal endothelium at increased risk of damage. This population, disproportionately prevalent in Asia, is expected to grow substantially with aging demographics, underscoring the need for optimized surgical strategies. Methods: MEDLINE, Embase, and Cochrane CENTRAL were searched through January 2026. Randomized controlled trials and observational studies comparing FLACS with conventional phacoemulsification were included. Risk of bias was assessed using Cochrane Risk of Bias 2 tool and Newcastle-Ottawa Scale. Pooled estimates were calculated using random-effects models; certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation framework. Results: 6 studies (505 eyes) were analyzed. FLACS was associated with lower ECL (mean difference [MD] −4.97%; 95% CI −8.27 to −1.67; P = .003; I ² = 98%) and cumulative dissipated energy (MD −2.47; 95% CI −3.64 to −1.30; P < .001; I ² = 14% in sensitivity analysis). FLACS was associated with 60% lower odds of early postoperative complications (odds ratio 0.40; 95% CI 0.23-0.68; P < .001; I ² = 0%). Visual outcomes were comparable. Conclusions: FLACS was associated with fewer early postoperative complications, supported by moderate-certainty evidence, and with lower ECL and ultrasound energy, although the magnitude of these benefits remains uncertain on low-certainty evidence.