Background: Although three established models for predicting the return of spontaneous circulation (ROSC) in out-of-hospital cardiac arrest (OHCA) exist, combinational external validation of these models remains limited. This study aimed to externally validate and compare the performance of three predictive models—RACA, P-ROSC, and UB-ROSC–and provide evidence to guide the selection and application of predictive models for prehospital ROSC in diverse settings. Methods: A retrospective validation was conducted using the National Taiwan University Hospital Hsinchu and Yunlin Branch Out-of-Hospital Cardiac Arrest Research Databases. Patients with EMS-treated OHCAs admitted to the hospital between January 2016 and July 2023 were recruited. The primary outcome was prehospital ROSC. Model performance was evaluated using discrimination, calibration, sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic odds ratio. Calibration and density distribution plots were generated. Results: All three models demonstrated moderate-to-high discrimination with AUROCs of 0.758 (RACA), 0.755 (P-ROSC), and 0.747 (UB-ROSC). The RACA score exhibited better calibration across the risk deciles, whereas the P-ROSC and UB-ROSC scores tended to overestimate the probabilities at higher predicted risk levels. The P-ROSC score required fewer variables and showed the best separation between prehospital and non-prehospital ROSC cases. Optimal cut-off values for the RACA, P-ROSC, and UB-ROSC scores were 0.45, 41, and − 13, respectively, with corresponding sensitivities of 62 %, 56 %, and 71 % and specificities of 78 %, 82 %, and 69 %. All models achieved high NPVs (>96 %), but PPVs remained low (16–21 %). Conclusions: The P-ROSC, which requires fewer variables, has emerged as the most practical model for Taiwanese populations. However, the choice of the model should be guided by the availability of variables, regional EMS characteristics, and trends in prehospital ROSC rates.

Leptospirosis is a zoonotic infection with public health implications and diverse clinical presentations, ranging from mild symptoms to severe, life-threatening disease. In critical cases, it can cause multiorgan failure and death. Diagnosis is typically based on clinical suspicion and confirmed by laboratory testing. However, in acute, life-threatening cases, obtaining a history of exposure and recognizing early symptoms may be challenging. Traditional diagnostic methods for identifying causative pathogens are time-consuming and limited. Next-generation sequencing (NGS) has emerged as a novel diagnostic tool that identifies pathogens using DNA or RNA from bodily fluids, offering more timely, unbiased results, especially for fastidious or non-culturable organisms.

In line with global population aging, the number of lesbian, gay, bisexual, and transgender (LGBT+) older adults is expected to continue to increase. Compared to their heterosexual peers, LGBT+ older adults have poorer physical and psychological health status, experience less social support, and face more barriers when accessing healthcare services, which may lead to higher health disparities and a lower quality of life within LGBT+ older populations. Healthcare providers have been shown to be inadequately prepared to address the unique healthcare needs and challenges of LGBT+ older adults, often leaving these individuals forced to receive care that does not meet their health needs and expectations. Based on the Declaration on Universal Health Coverage proposed by the United Nations and the World Health Organization, medical care and long-term care facilities must provide to healthcare providers training courses in culturally competent care and foster LGBT-friendly care environments to achieve health equity and universal health coverage for LGBT+ populations.

Pei-Lin Lee serves as Clinical Associate Professor, School of Medicine, National Taiwan University; Consultant, Center of Sleep Disorder, National Taiwan University Hospital. Her current academic positions at international sleep societies include American Academy of Sleep Medicine Fellow and Co-Chair International Assembly; Asian Society of Sleep Medicine, Sleep Medicine Education Task Force committee member. Her current research focuses on the era of new technology and big data in sleep medicine; and intervention on sleep and metabolism in sleep disordered breathing.