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Men Experience Higher Risk of Pneumonia and Death After Intracerebral Hemorrhage.

ABSTRACT: BACKGROUND:Infectious complications worsen outcome after intracerebral hemorrhage (ICH). We investigated the impact of sex on post-ICH infections and mortality. METHODS:Consecutive ICH patients (admitted to a single hospital between 1994 and 2015) were retrospectively assessed via chart review to ascertain the following in-hospital infections: urinary tract infection (UTI), pneumonia, and sepsis. Adjusted logistic regression was performed to identify associations between sex, infection, and mortality at 90 days. RESULTS:Two thousand and four patients were investigated, 1071 (53.7%) males. Men were more likely to develop pneumonia (21.9 vs 15.5% p < 0.001) and sepsis (3.4 vs 1.6%, p = 0.009), whereas women had higher risk of UTI (19.9 vs 11.7% p < 0.001). Multivariate analyses confirmed association between male sex and pneumonia (Odds Ratio (OR) 1.37, 95% confidence interval (CI) 1.08-1.74, p = 0.011). Male sex (OR 1.40; CI 1.07-1.85; p = 0.015) and infection (OR 1.56; CI 1.11-1.85; p = 0.011) were independently associated with higher 90-day mortality. CONCLUSIONS:Types and rates of infection following ICH differ by sex. Male sex independently increases pneumonia risk, which subsequently increases 90-day mortality. Sex-specific preventive strategies to reduce the risk of these complications may be one strategy to improve ICH outcomes.

SUBMITTER: Marini S

PROVIDER: S-EPMC5775939 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Men Experience Higher Risk of Pneumonia and Death After Intracerebral Hemorrhage.

Marini Sandro S Morotti Andrea A Lena Umme K UK Goldstein Joshua N JN Greenberg Steven M SM Rosand Jonathan J Anderson Christopher D CD

Neurocritical care 20180201 1

<h4>Background</h4>Infectious complications worsen outcome after intracerebral hemorrhage (ICH). We investigated the impact of sex on post-ICH infections and mortality.<h4>Methods</h4>Consecutive ICH patients (admitted to a single hospital between 1994 and 2015) were retrospectively assessed via chart review to ascertain the following in-hospital infections: urinary tract infection (UTI), pneumonia, and sepsis. Adjusted logistic regression was performed to identify associations between sex, infe ...[more]

PMID: 28730561

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Project description:PurposeWe develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH).MethodWe applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between 2015 and 2018 from the Chinese Stroke Center Alliance (CSCA). During the training of ICH-LR2S2, patients were randomly divided into two groups - 80% for the training set and 20% for model validation. A prospective test set was developed using 12,523 patients recruited in 2019. To further verify its effectiveness, we tested ICH-LR2S2 on an external dataset of 24,860 patients from the China National Stroke Registration Management System II (CNSR II). The performance of ICH-LR2S2 was measured by the area under the receiver operating characteristic curve (AUROC).ResultsThe incidence of SAP in the dataset was 25.52%. A 24-point ICH-LR2S2 was developed from independent predictors, including age, modified Rankin Scale, fasting blood glucose, National Institutes of Health Stroke Scale admission score, Glasgow Coma Scale score, C-reactive protein, dysphagia, Chronic Obstructive Pulmonary Disease, and current smoking. The results showed that ICH-LR2S2 achieved an AUC = 0.749 [95% CI 0.739-0.759], which outperforms the best baseline ICH-APS (AUC = 0.704) [95% CI 0.694-0.714]. Compared with the previous ICH risk scores, ICH-LR2S2 incorporates fasting blood glucose and C-reactive protein, improving its discriminative ability. Machine learning methods such as XGboost (AUC = 0.772) [95% CI 0.762-0.782] can further improve our prediction performance. It also performed well when further validated by the external independent cohort of patients (n = 24,860), ICH-LR2S2 AUC = 0.784 [95% CI 0.774-0.794].ConclusionICH-LR2S2 accurately distinguishes SAP patients based on easily available clinical features. It can help identify high-risk patients in the early stages of diseases.

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Men Experience Higher Risk of Pneumonia and Death After Intracerebral Hemorrhage.

Publications

Men Experience Higher Risk of Pneumonia and Death After Intracerebral Hemorrhage.

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