Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models

BackgroundAcute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS).MethodsThe DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration.ResultsA total of 12,026 patients were included and the median age was 67 (interquartile range: 57–75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001).ConclusionThe DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.Electronic supplementary materialThe online version of this article (doi:10.1186/s12883-014-0214-z) contains supplementary material, which is available to authorized users

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models

BACKGROUND: Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS). METHODS: The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration. RESULTS: A total of 12,026 patients were included and the median age was 67 (interquartile range: 57–75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001). CONCLUSION: The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12883-014-0214-z) contains supplementary material, which is available to authorized users

Cost-effectiveness of thrombolysis within 4.5 hours of acute ischemic stroke in China.

BACKGROUND: Previous economic studies conducted in developed countries showed intravenous tissue-type plasminogen activator (tPA) is cost-effective for acute ischemic stroke. The present study aimed to determine the cost-effectiveness of tPA treatment in China, the largest developing country. METHODS: A combination of decision tree and Markov model was developed to determine the cost-effectiveness of tPA treatment versus non-tPA treatment within 4.5 hours after stroke onset. Outcomes and costs data were derived from the database of Thrombolysis Implementation and Monitor of acute ischemic Stroke in China (TIMS-China) study. Efficacy data were derived from a pooled analysis of ECASS, ATLANTIS, NINDS, and EPITHET trials. Costs and quality-adjusted life-years (QALYs) were compared in both short term (2 years) and long term (30 years). One-way and probabilistic sensitivity analyses were performed to test the robustness of the results. RESULTS: Comparing to non-tPA treatment, tPA treatment within 4.5 hours led to a short-term gain of 0.101 QALYs at an additional cost of CNY 9,520 (US$1,460), yielding an incremental cost-effectiveness ratio (ICER) of CNY 94,300 (US$ 14,500) per QALY gained in 2 years; and to a long-term gain of 0.422 QALYs at an additional cost of CNY 6,530 (US$1,000), yielding an ICER of CNY 15,500 (US$ 2,380) per QALY gained in 30 years. Probabilistic sensitivity analysis showed that tPA treatment is cost-effective in 98.7% of the simulations at a willingness-to-pay threshold of CNY 105,000 (US$ 16,200) per QALY. CONCLUSIONS: Intravenous tPA treatment within 4.5 hours is highly cost-effective for acute ischemic strokes in China

Risk score to predict hospital-acquired pneumonia after spontaneous intracerebral hemorrhage

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, 0.72-0.77) and validation (AUROC, 0.76; 95% confidence interval, 0.71-0.79) cohorts. The ICH-APS-A was more sensitive for patients with length of stay >48 hours (AUROC, 0.78; 95% confidence interval, 0.75-0.81) than those with length of stay 48 hours. © 2014 American Heart Association, Inc.Link_to_subscribed_fulltex

Baseline characteristics of patients according to statin use.

<p>DM: diabetes mellitus; CHD: coronary arterial disease; AF: atrial fibrillation; Smoking: current or previous smoking; Alcohol: moderate or heavy alcohol consumption; NIHSS: the National Institutes of Health Stroke Scale evaluated within 24 hours after admission; IQR : indicates interquartile range; Minor stroke: NIHSS scale <5; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; TC: total cholesterol; TG: triglycerides; RMB: Ren Min Bi.</p

Significant Predictors of Clinical Outcome at 3 months.

<p>AF: atrial fibrillation, Smoking: current or previous smoking, NIHSS: the National Institutes of Health Stroke Scale evaluated within 24 hours after admission; RMB:Ren Min Bi.</p

Flow diagram defining the potentially eligible patients with acute stroke for statins treatment.

<p>Flow diagram defining the potentially eligible patients with acute stroke for statins treatment.</p

Percentage of mRS scores and death at 3 months for ischemic stroke patients stratified by statin use within hospitalization.

<p>Percentage of mRS scores and death at 3 months for ischemic stroke patients stratified by statin use within hospitalization.</p

Multivariate analyses of functional outcomes at 3 months for all patients and patients stratified by severity of stroke.

<p>Multivariate analyses of functional outcomes at 3 months for all patients and patients stratified by severity of stroke.</p

Patient Functional Outcomes According to Statin Use at 3 Months.

<p>Patient Functional Outcomes According to Statin Use at 3 Months.</p