Iezzoni L I, Shwartz M, Ash A S, Mackiernan Y D
Department of Medicine, Harvard Medical School, Beth Israel Hospital, Charles A. Dana Research Institute, Boston, MA, USA.
Med Decis Making. 1996 Oct-Dec;16(4):348-56. doi: 10.1177/0272989X9601600405.
To see whether severity-adjusted predictions of likelihoods of in-hospital death for stroke patients differed among severity measures.
The study sample 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 Seventy Score of Patient Management Categories (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 predicted by a second measure.
MedisGroups and the physiology scores predicted similar odds of death for 82.2% of the patients. MedisGroups and PMCs disagreed the most, with very different odds predicted for 61.6% of patients. Patients viewed as more severely III 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.
Some pairs of severity measures ranked over 60% of patients very differently by predicted probability of death. Studies of severity-adjusted stroke outcomes may produce different results depending on which severity measure is used for risk adjustment.
探讨针对卒中患者院内死亡可能性的严重程度调整预测在不同严重程度衡量标准之间是否存在差异。
研究样本包括来自94家医院的9407例卒中患者,其中916例(9.7%)在院内死亡。使用逻辑回归,将年龄、性别以及五种严重程度衡量标准中的每一种作为自变量,为每位患者计算死亡概率,这五种衡量标准分别为:入院时MedisGroups死亡概率评分;基于入院时17项生理变量的评分;疾病分期死亡概率模型;患者管理类别(PMC)七十评分;以及全患者精细化诊断组(APR-DRG)。比较每种严重程度衡量标准预测的每位患者的死亡几率。针对不同严重程度衡量标准预测的死亡几率差异极大的患者,检查了卒中预后不良的七个临床指标的频率。当一种严重程度衡量标准预测的死亡几率小于另一种衡量标准预测值的0.5倍或大于2.0倍时,认为优势比差异极大。
对于82.2%的患者,MedisGroups和生理评分预测的死亡几率相似。MedisGroups和PMC的分歧最大,61.6%的患者预测的死亡几率差异极大。被MedisGroups和生理评分视为病情更严重的III级患者比被其他严重程度衡量标准视为病情更重的患者更有可能出现临床卒中表现。这表明MedisGroups和生理评分在临床上更具可信度。
某些严重程度衡量标准对超过60%的患者按预测死亡概率排序时差异极大。根据用于风险调整的严重程度衡量标准不同,严重程度调整后的卒中结局研究可能会产生不同结果。