Clinical characterization and mortality predictors in a terminal hospital

Introduction: the stroke represents one of the main causes of morbidity and mortality globally, with a significant impact on public health. The identification of mortality predictors is essential for clinical decision making.Aim: characterize patients diagnosed with stroke and determine mortality predictors.Methods: an observational, analytical and retrospective study was carried out at the Dr. Miguel Enriquez Surgical Clinical Hospital from January to December 2024. The qualitative variables were summarized in absolute frequencies and percentages. The quantitative variables in average and standard deviation. To evaluate the association between qualitative variables the JI square test was applied. To determine the factors associated with mortality, a multivariate binary regression model was adjusted.Results: 883 patients were studied. The ischemic stroke was the most frecuent and within in the cerebral infarction of therotrombotic etiology prevailed (79.9%). With respect to the age variable, for each additional year the probability of death increases by 5%, OR 1.05 (IC 95%: 1.02-1.08, p< 0. 001). As for the Glasgow scale for each additional point, the probability of death decreases by 15%, OR 0.85 (IC 95%: 0.80- 0.90). On the other hand, patients with cerebral edema have 3.5 times higher risk of death OR 3.50 (IC 95%: 2.40- 5.10).Conclusions: the influence of clinical and demographic factors on ICTUS mortality provides tools to stratify the risk, contributing to optimize decisions in medical practice.

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Journal
South Health and Policy
Published
2025-05-08
DOI
https://doi.org/10.56294/shp2025237
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
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article

Clinical characterization and mortality predictors in a terminal hospital

Deborah Cabrera Rodríguez, Maytee Olivera Vega, Lisbel Garzón Cutiño, Carlos Alberto Marin Rojo
South Health and Policy
Sepsis Diagnosis and Treatment
article

Clinical characterization and mortality predictors in a terminal hospital

Deborah Cabrera Rodríguez, Maytee Olivera Vega, Lisbel Garzón Cutiño, Carlos Alberto Marin Rojo
article en

Abstract

Introduction: the stroke represents one of the main causes of morbidity and mortality globally, with a significant impact on public health. The identification of mortality predictors is essential for clinical decision making.Aim: characterize patients diagnosed with stroke and determine mortality predictors.Methods: an observational, analytical and retrospective study was carried out at the Dr. Miguel Enriquez Surgical Clinical Hospital from January to December 2024. The qualitative variables were summarized in absolute frequencies and percentages. The quantitative variables in average and standard deviation. To evaluate the association between qualitative variables the JI square test was applied. To determine the factors associated with mortality, a multivariate binary regression model was adjusted.Results: 883 patients were studied. The ischemic stroke was the most frecuent and within in the cerebral infarction of therotrombotic etiology prevailed (79.9%). With respect to the age variable, for each additional year the probability of death increases by 5%, OR 1.05 (IC 95%: 1.02-1.08, p< 0. 001). As for the Glasgow scale for each additional point, the probability of death decreases by 15%, OR 0.85 (IC 95%: 0.80- 0.90). On the other hand, patients with cerebral edema have 3.5 times higher risk of death OR 3.50 (IC 95%: 2.40- 5.10).Conclusions: the influence of clinical and demographic factors on ICTUS mortality provides tools to stratify the risk, contributing to optimize decisions in medical practice.

South Health and PolicyVol. 4
Hospital Oncológico Docente "Conrado Benítez García" (CU), Universidad de Ciencias Médicas de la Habana (CU)
Openalex Percentile: Top 83%
Sepsis Diagnosis and Treatment
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Clinical characterization and mortality predictors in a terminal hospital — Deborah Cabrera Rodríguez, Maytee Olivera Vega, et al. · South Health and Policy (2025) | TGRS Research Map | TGRS