Literature DB >> 31008324

Validation and comparison of two stroke prognostic models for in hospital, 30-day and 90-day mortality.

Dipankar Dutta1, Abigail Cannon1, Emily Bowen1.   

Abstract

INTRODUCTION: We aimed to validate and compare two clinical prognostic models for mortality which include the National Institutes of Health Stroke Scale (NIHSS); the Age and NIHSS Score (ANS) and case mix model (CMM) of the Sentinel Stroke National Audit Program (SSNAP). The NIHSS on admission was also tested as a prognostic score. PATIENTS AND METHODS: Prospectively collected data from the SSNAP register for a cohort of patients (ischaemic and haemorrhagic stroke) admitted over 1 year to Gloucestershire Royal Hospital, England were accessed. The ANS and CMM were calculated and tested for in hospital, 30-day and 90-day mortality using calibration plots with Hosmer-Lemeshow tests, receiver operating characteristics curves and other measures of prognostic accuracy.
RESULTS: Of 848 patients, 110 (12.9%) died in hospital, 112 (13.2%) at 30 days and 164 (19.2%) at 90 days. Calibration for all three scores was good, although Hosmer-Lemeshow test p values were <0.05 with the NIHSS alone for in hospital and 30-day deaths, suggesting deviation from good fit. The c-statistics for in hospital, 30-day and 90-day mortality were ANS (0.783, 0.782, 0.779) and CMM (0.783, 0.774, 0.758), respectively. The NIHSS alone showed fair discrimination but performed less well. A NIHSS score ≥6 was associated with significant mortality (p < 0.0001) in comparison to a score <6.
CONCLUSION: A simple prognostic model containing age and admission NIHSS only, performed as well as a more complex score at predicting in hospital, 30-day and 90-day mortality. Admission NIHSS recording should be encouraged for stroke registries.

Entities:  

Keywords:  Stroke; mortality; prognosis; prognostic score

Year:  2017        PMID: 31008324      PMCID: PMC6453188          DOI: 10.1177/2396987317703581

Source DB:  PubMed          Journal:  Eur Stroke J        ISSN: 2396-9873


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