Predicting In-hospital Mortality for Stroke Patients

Author:

Iezzoni Lisa I.,Shwartz Michael,Ash Arlene S.,Mackiernan Yevgenia D.

Abstract

Objective: To see whether severity-adjusted predictions of likelihoods of in-hospital death for stroke patients differed among severity measures. Methods: The study sam ple was 9,407 stroke patients from 94 hospitals, with 916 (9.7%) in-hospital deaths. Probability of death was calculated for each patient using logistic regression with age-sex and each of five severity measures as the independent variables: admission MedisGroups probability-of-death scores; scores based on 17 physiologic variables on admission; Disease Staging's probability-of-mortality model; the Severity Score of Pa tient Management Categones (PMCs); and the All Patient-Refined Diagnosis Groups (APR-DRGs). For each patient, the odds of death predicted by the severity measures were compared. The frequencies of seven clinical indicators of poor prognosis in stroke were examined for patients with very different odds of death predicted by different severity measures. Odds ratios were considered very different when the odds of death predicted by one severity measure was less than 0.5 or greater than 2.0 of that pre dicted by a second measure. Results: MedisGroups and the physiology scores pre dicted similar odds of death for 82.2% of the patients. MedisGroups and PMCs disa greed the most, with very different odds predicted for 61.6% of patients. Patients viewed as more severely ill by MedisGroups and the physiology score were more likely to have the clinical stroke findings than were patients seen as sicker by the other severity measures. This suggests that MedisGroups and the physiology score are more clinically credible. Conclusions: Some pairs of severity measures ranked over 60% of patients very differently by predicted probability of death. Studies of seventy-adjusted stroke outcomes may produce different results depending on which seventy measure is used for risk adjustment. Key words: seventy; risk adjustment; stroke; in-hospital deaths; mortality rates. (Med Decis Making 1996;16:348-356)

Publisher

SAGE Publications

Subject

Health Policy

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3