S pontaneous intracerebral hemorrhage (ICH) accounts for 10% to 15% of all strokes and is one of the leading causes of stroke-related mortality and morbidity worldwide. Patients with ICH are generally at risk of developing stroke-associated pneumonia (SAP) during acute hospitalization. Evidence has shown that SAP not only increases the length of hospital stay (LOS) and medical cost 1,2 but also is an important risk factor of mortality and morbidity after acute stroke. 3,4 Several risk factors for SAP have been identified, such as older age, 4-12 male sex, 5,6,10,11,13 current smoking, 12 diabetes mellitus, 6 hypertension, 14 atrial fibrillation, 7,10,12 congestive heart failure, 7,12,13,15 chronic obstructive pulmonary disease, 8,[12][13][14] preexisting dependency, 8,12,13,16 stroke severity, 5,6,8,12,17,18 dysphagia, [8][9][10][11][12]14,[18][19][20] and blood glucose. 12 Meanwhile, based on these risk factors, a few risk models have been developed for SAP after acute ischemic stroke. [8][9][10][11][12] Currently, no valid scoring system is available for predicting SAP after ICH in routine clinical practice or clinical trial. We hypothesized that there might be some common grounds for the development of pneumonia after acute ischemic stroke and ICH, and those predictors for SAP after acute ischemic stroke might also be useful for predicting SAP after ICH. For clinical practice, an effective risk-stratification and prognostic model for SAP after ICH would be helpful to identify vulnerable patients, allocate relevant medical resources, and implement tailored preventive strategies. In addition, for clinical trial, it could be used in nonrandomized studies to control for case-mix variation and in controlled studies as a selection criterion.Background and Purpose-We aimed to develop a risk score (intracerebral hemorrhage-associated pneumonia score, ICH-APS) for predicting hospital-acquired stroke-associated pneumonia (SAP) after ICH. Methods-The ICH-APS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Variables routinely collected at presentation were used for predicting SAP after ICH. For testing the added value of hematoma volume measure, we separately developed 2 models with (ICH-APS-B) and without (ICH-APS-A) hematoma volume included. Multivariable logistic regression was performed to identify independent predictors. The area under the receiver operating characteristic curve (AUROC), Hosmer-Lemeshow goodness-of-fit test, and integrated discrimination index were used to assess model discrimination, calibration, and reclassification, respectively. Results-The SAP was 16.4% and 17.7% in the overall derivation (n=2998) and validation (n=2000) cohorts, respectively.A 23-point ICH-APS-A was developed based on a set of predictors and showed good discrimination in the overall derivation (AUROC, 0.75; 95% confidence interval, 0. Ji et al Risk Score to Predict SAP After ICH 2621In the study, we aimed to ...
The results of this meta-analysis indicate an association of elevated GDF-15 levels with increased risk of mortality in patients with heart failure. However, the results should be interpreted with caution due to substantial heterogeneity and publication bias among the studies included in the meta-analysis.
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