Methods: We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of ...

Among adults who underwent upper gastrointestinal (GI) endoscopic procedures with rocuronium-induced neuromuscular block, reversal using sugammadex was associated with a lower risk for the failure of ...

Correspondence to Dr Yoshihiko Taniguchi, Kinki Chuo Chest Medical Center, Sakai 591-8555, Japan; taniguchi.yoshihiko.ny{at}mail.hosp.go.jp Objectives Opioids are often administered for cancer-related ...

Background Propensity score (PS) methods are frequently used in cardiovascular clinical research. Previous evaluations revealed poor reporting of PS methods, however a comprehensive and current ...

Background The Pipeline Flex embolization device with Shield technology (PED Shield, Medtronic, Irvine, CA, USA) is a flow diverter designed to reduce thrombogenicity through phosphorylcholine surface ...

psweight() is a Mata class that computes inverse-probability weighting (IPW) weights for average treatment effect, average treatment effect on the treated, and average treatment effect on the ...

Correspondence to Dr Nguyen Thi Thu Thuong, Faculty of Economics, TNU-University of Economics and Business Administration, Thai Nguyen, Vietnam; nttthuong{at}tueba.edu.vn Objectives The study aims to ...

Background Cigarette smoking imposes substantial health and economic burdens on China, yet its full impact remains significantly underestimated and based on outdated data. This study aims to ...

Abstract: This study investigates the bidirectional relationship between emotional changes and physical activity, specifically focusing on the number of steps taken. Using Propensity Score Matching ...

ABSTRACT: This study was aimed at the impact of AI technology on milk production and livelihoods of the farmers in Saesie-tsaedaemba District Eastern Zone, Tigray, Ethiopia. In the study area, AI is a ...

Abstract: Existing machine learning methods for retail product sales forecasting often rely on their own time series data and tend to ignore the correlation between the target retail product and other ...