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TENOR风险评分可预测重度或难治性哮喘成人患者的医疗情况。

TENOR risk score predicts healthcare in adults with severe or difficult-to-treat asthma.

作者信息

Miller M K, Lee J H, Blanc P D, Pasta D J, Gujrathi S, Barron H, Wenzel S E, Weiss S T

机构信息

Genentech, Inc, 1 DNA Way, MS 214B, South San Francisco, CA 94044, USA.

出版信息

Eur Respir J. 2006 Dec;28(6):1145-55. doi: 10.1183/09031936.06.00145105. Epub 2006 Jul 26.

DOI:10.1183/09031936.06.00145105
PMID:16870656
Abstract

The aim of the present study was to predict which patients with severe or difficult-to-treat asthma are at highest risk for healthcare utilisation can be predicted so as to optimise clinical management. Data were derived from 2,821 adults with asthma enrolled in The Epidemiology and Natural History of Asthma: Outcomes and Treatment Regimens (TENOR) study. Multiple potential predictors were assessed at baseline using a systematic algorithm employing stepwise logistic regression. Outcomes were asthma-related hospitalisations or emergency department (ED) visits within 6 months following baseline. Overall, 239 subjects (8.5%) reported hospitalisation or ED visits at follow-up. Predictors retained after multivariate analysis were as follows: younger age; female sex; non-white race; body mass index > or =35 kg x m(-2); post-bronchodilator per cent predicted forced vital capacity <70%; history of pneumonia; diabetes; cataracts; intubation for asthma; and three or more steroid bursts in the prior 3 months. A final risk score derived from the logistic regression model ranged from 0-18 and was highly predictive (c-index: 0.78) of hospitalisation or ED visits. This tool was re-tested in a prospective validation using outcomes at 12- to 18-months follow-up among the same cohort (c-index: 0.77). The risk score derived is a clinically useful tool for assessing the likelihood of asthma-related hospitalisation or emergency department visits in adults with severe and difficult-to-treat asthma.

摘要

本研究的目的是预测哪些重度或难治性哮喘患者医疗资源利用风险最高,以便优化临床管理。数据来源于参与哮喘流行病学与自然史:结局与治疗方案(TENOR)研究的2821例成年哮喘患者。在基线时使用逐步逻辑回归的系统算法评估多个潜在预测因素。结局为基线后6个月内与哮喘相关的住院或急诊就诊情况。总体而言,239名受试者(8.5%)在随访时报告了住院或急诊就诊情况。多变量分析后保留的预测因素如下:年龄较小;女性;非白人种族;体重指数≥35 kg·m⁻²;支气管扩张剂后预测用力肺活量百分比<70%;肺炎病史;糖尿病;白内障;哮喘插管;以及前3个月内有三次或更多次类固醇冲击治疗。从逻辑回归模型得出的最终风险评分范围为0至18,对住院或急诊就诊具有高度预测性(c指数:0.78)。该工具在同一队列12至18个月随访结局的前瞻性验证中进行了重新测试(c指数:0.77)。得出的风险评分是评估重度和难治性成年哮喘患者与哮喘相关住院或急诊就诊可能性的临床有用工具。

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