Risk factors and predictive model of diarrhoea among patients with severe stroke.

Risk factors and predictive model of diarrhoea among patients with severe stroke.:

Risk factors and predictive model of diarrhoea among patients with severe stroke.

World Neurosurg. 2019 Dec 31;:

Authors: Xiang Y, Li F, Peng J, Qin D, Yuan M, Liu G

Abstract

AIMS: To investigate the risk factors and predictive model of diarrhoea among patients with severe stroke.

METHODS: The study analysed the retrospective clinical data of patients with new-onset stroke who had been admitted to the intensive care unit (ICU) at the Department of Neurology of X Hospital, between September 2017 and April 2018. All data were analysed with a binary logistic regression, and a logistic regression equation was used to build a predictive model of diarrhoea among patients with severe stroke.

RESULTS: A total of 153 patients with severe stroke were included in this study, including 45 patients (29.41%) with diarrhoea. The binary logistic multivariate analysis showed that the National Institutes of Health Stroke Scale score at admission (odds ratio [OR] = 1.123, 95% CIs [1.016, 1.242]), the Glasgow Coma Scale score at admission (OR = 1.563, 95% CIs [1.048, 2.330]), antibiotic use (OR = 2.168, 95% CIs [1.041, 4.514]), gavage feeding time (OR = 1.260, 95% CIs [1.098, 1.445]), and hospital stay before the occurrence of diarrhoea (OR = 0.652, 95% CIs [0.552, 0.770]). The receiver operating characteristic (ROC) curve was 0.862 (95% CIs: 0.799-0.925), the specificity was 0.778, the sensitivity was 0.843.

CONCLUSIONS: The National Institutes of Health Stroke Scale score at admission, the Glasgow Coma Scale score at admission, antibiotic use, gavage feeding time, and hospital stay before the occurrence of diarrhoea independently predict diarrhoea among patients with severe stroke. This model can be used to predict the risk of diarrhoea among patients with severe stroke.

PMID: 31901495 [PubMed - as supplied by publisher]