A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis
A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis
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DOI：
10.1371/journal.pone.0162797
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发表时间：
2016-09-16
期刊：
影响因子：
3.7
通讯作者：
Saraiva, Margarida
中科院分区：
文献类型：
--
作者：
Bastos, Helder Novais;Osorio, Nuno S.;Saraiva, Margarida
结核病给人类和经济造成了高昂的代价，包括在欧洲。这项研究是为了开发一种严重程度评估工具来分层肺结核(PTB)患者的死亡风险。对681例肺结核患者进行了回顾性分析，建立了以6个月死亡率为预后指标的多因素Logistic回归分析模型。开发了一个临床评分系统，并针对103名患者的验证队列进行了测试。预测模型选择了5个危险因素：低氧性呼吸衰竭(OR 4.7，95%CI 2.8~7.9)，年龄=50岁(OR 2.9，95%CI 1.7~4.8)，双肺受累(OR 2.5，95%CI 1.44.4)，=1个显著的并发症-HIV感染、糖尿病、肝功能衰竭或肝硬变、充血性心力衰竭和慢性呼吸系统疾病(OR 2.3，95%CI 1.3~3.8)，以及Hb。12g/dL(OR 1.8，95%CI 1.1-3.1)。开发了一种结核病风险评估工具(TREAT)，对死亡风险较低(得分=6)的患者进行分层。各组的死亡率分别为2.9%、22.9%和53.9%。该模型在验证队列中的表现同样很好。我们提供了一种新的、易于使用的临床评分系统，在医疗保健便利的环境中识别具有高死亡率风险的肺结核患者，帮助临床医生决定哪些患者在治疗期间需要更密切的医疗护理。
Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age >= 50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.44.4), >= 1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin < 12 g/dL (OR 1.8, 95% CI 1.1-3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score = 6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.