Adding initial NIHSS or modified Rankin scale scores at discharge did not significantly improve the predictive ability of LACE or TSL models for 30-day readmission or mortality after ischemic stroke.
Cohort (n=4,843)
Yes
Does adding initial NIHSS or mRS score at discharge improve predictive models for 30-day nonelective readmission or mortality in patients with ischemic stroke?
Adding initial NIHSS or discharge mRS scores to administrative or comprehensive predictive models does not significantly improve the prediction of 30-day readmission or mortality after ischemic stroke.
Absolute Event Rate: 0.69% vs 0.69%
Background: Patients with stroke have high rates of all-cause readmission and case fatality. Limited information is available on how to predict these outcomes. Objective: We aimed to assess whether adding the initial National Institutes of Health Stroke Scale (NIHSS) score or modified Rankin scale (mRS) score at discharge improved predictive models of 30-day nonelective readmission or 30-day mortality poststroke. Methods: Using a cohort of patients with ischemic stroke in a large multiethnic integrated health care system from June 15, 2018, to April 29, 2020, we tested 2 predictive models for a composite outcome (30-day nonelective readmission or death). The models were based on administrative data (Length of Stay, Acuity, Charlson Comorbidities, Emergency Department Use score; LACE) as well as a comprehensive model (Transition Support Level; TSL). The models, initial NIHSS score, and mRS scores at discharge, were tested independently and in combination with age and sex. We assessed model performance using the area under the receiver operator characteristic (c-statistic), Nagelkerke pseudo-R2, and Brier score. Results: The study cohort included 4843 patients with 5014 stroke hospitalizations. Average age was 71.9 (SD 14) years, 50.6% (2537/5014) were female, and 52.1% (2614/5014) were White. Median initial NIHSS score was 4 (IQR 2-8). There were 538 (10.7%) nonelective readmissions and 150 (3.9%) deaths within 30 days. The logistic models revealed that the best performing models were TSL (c-statistic=0.69) and TSL plus mRS score at discharge (c-statistic=0.69). Conclusions: We found that neither the initial NIHSS score nor the mRS score at discharge significantly enhanced the predictive ability of the LACE or TSL models. Future efforts at prediction of short-term stroke outcomes will need to incorporate new data elements.
Nguyen‐Huynh et al. (Tue,) conducted a cohort in Ischemic stroke (n=4,843). Addition of NIHSS or mRS scores to predictive models vs. Base predictive models (LACE or TSL) was evaluated on 30-day nonelective readmission or death. Adding initial NIHSS or modified Rankin scale scores at discharge did not significantly improve the predictive ability of LACE or TSL models for 30-day readmission or mortality after ischemic stroke.