A New Natural Language Processing-Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study.

Background: Proper analysis and interpretation of health care data can significantly improve patient outcomes by enhancing services and revealing the impacts of new technologies and treatments. Understanding the substantial impact of temporal shifts in these data is crucial. For example, COVID-19 vaccination initially lowered the mean age of at-risk patients and later changed the characteristics of those who died.

Comprehensive statistical analysis reveals significant benefits of COVID-19 vaccination in hospitalized patients: propensity score, covariate adjustment, and feature importance by permutation.

Background: COVID-19 vaccines effectively prevent infection and hospitalization. However, few population-based studies have compared the clinical characteristics and outcomes of patients hospitalized for COVID-19 using advanced statistical methods. Our objective is to address this evidence gap by comparing vaccinated and unvaccinated patients hospitalized for COVID-19.

Length of Hospitalization and Mortality among Stroke Patients before and after the Implementation of a Specialized Unit: A Retrospective Cohort Study Using Real-World Data from One Reference Hospital in Southern Brazil.

Stroke constitutes a significant global cause of mortality and disability. The implementation of stroke units influences hospital quality indicators, guiding care management. We aimed to compare hospital length of stay (LOS), in-hospital mortality, and post-discharge mortality between stroke patients admitted in the pre- and post-implementation periods of a stroke unit in a public hospital in southern Brazil.

Patients hospitalized with active tuberculosis and Covid-19 coinfection: A matched case-control from the Brazilian Covid-19 Registry.

Although control of Covid-19 has improved, the virus continues to cause infections, such as tuberculosis, that is still endemic in many countries, representing a scenario of coinfection. To compare Covid-19 clinical manifestations and outcomes between patients with active tuberculosis infection and matched controls. This is a matched case-control study based on data from the Brazilian Covid-19 Registry, in hospitalized patients aged 18 or over with laboratory confirmed Covid-19 from March 1, 2020, to March 31, 2022.

ABCO risk score for in-hospital mortality of COVID-19 patients admitted to intensive care units.

Purpose: To develop a mortality risk score for COVID-19 patients admitted to intensive care units (ICU), and to compare it with other existing scores.

Materials And Methods: This retrospective observational study included consecutive adult patients with laboratory-confirmed COVID-19 admitted to ICUs of 18 hospitals from nine Brazilian cities, from September 2021 to July 2022. Potential predictors were selected based on the literature review.