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Prohormones for prediction of adverse medical outcome in community-acquired pneumonia and lower respiratory tract infections

机译：预测社区获得性肺炎和下呼吸道感染不良医学结果的前体

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IntroductionMeasurement of prohormones representing different pathophysiological pathways could enhance risk stratification in patients with community-acquired pneumonia (CAP) and other lower respiratory tract infections (LRTI).MethodsWe assessed clinical parameters and five biomarkers, the precursor levels of adrenomedullin (ADM), endothelin-1 (ET1), atrial-natriuretic peptide (ANP), anti-diuretic hormone (copeptin), and procalcitonin in patients with LRTI and CAP enrolled in the multicenter ProHOSP study. We compared the prognostic accuracy of these biomarkers with the pneumonia severity index (PSI) and CURB65 (Confusion, Urea, Respiratory rate, Blood pressure, Age 65) score to predict serious complications defined as death, ICU admission and disease-specific complications using receiver operating curves (ROC) and reclassification methods.ResultsDuring the 30 days of follow-up, 134 serious complications occurred in 925 (14.5%) patients with CAP. Both PSI and CURB65 overestimated the observed mortality (X2 goodness of fit test: P = 0.003 and 0.01). ProADM or proET1 alone had stronger discriminatory powers than the PSI or CURB65 score or any of either score components to predict serious complications. Adding proADM alone (or all five biomarkers jointly) to the PSI and CURB65 scores, significantly increased the area under the curve (AUC) for PSI from 0.69 to 0.75, and for CURB65 from 0.66 to 0.73 (P < 0.001, for both scores). Reclassification methods also established highly significant improvement (P < 0.001) for models with biomarkers if clinical covariates were more flexibly adjusted for. The developed prediction models with biomarkers extrapolated well if evaluated in 434 patients with non-CAP LRTIs.ConclusionsFive biomarkers from distinct biologic pathways were strong and specific predictors for short-term adverse outcome and improved clinical risk scores in CAP and non-pneumonic LRTI. Intervention studies are warranted to show whether an improved risk prognostication with biomarkers translates into a better clinical management and superior allocation of health care resources.Trial RegistrationNCT00350987.
机译：前言测量代表不同病理生理途径的激素可增强社区获得性肺炎（CAP）和其他下呼吸道感染（LRTI）患者的危险分层。方法我们评估了临床参数和5种生物标志物，肾上腺髓质素（ADM）的前体水平，内皮素-一项多中心ProHOSP研究纳入了LRTI和CAP患者的心房利钠肽（ANP），抗利尿激素（copeptin）和降钙素1（ET1）。我们将这些生物标志物的预后准确性与肺炎严重程度指数（PSI）和CURB65（意识错乱，尿素，呼吸频率，血压，65岁）评分进行了比较，以预测严重并发症，包括死亡，ICU入院和使用疾病的特定并发症结果在随访的30天中，有925名（14.5％）CAP患者发生134例严重并发症。 PSI和CURB65都高估了观察到的死亡率（X2拟合优度：P = 0.003和0.01）。单独的ProADM或proET1具有比PSI或CURB65评分或任何一个评分成分均强的辨别力，可以预测严重的并发症。在PSI和CURB65评分中单独添加proADM（或同时添加所有五个生物标志物），可使PSI的曲线下面积（AUC）从0.69显着增加到0.75，而CURB65的曲线下面积从0.66增至0.73（两个评分均P <0.001） 。如果更灵活地调整临床协变量，则重分类方法还可以为具有生物标志物的模型建立非常显着的改善（P <0.001）。如果在434例非CAP LRTIs患者中进行评估，则开发出的带有生物标志物的预测模型可以很好地外推。结论来自不同生物学途径的5种生物标志物是短期不良结局，CAP和非肺源性LRTI的临床风险评分提高的强而特异性的预测因子。有必要进行干预研究，以表明使用生物标志物改善风险预后是否可以转化为更好的临床管理和更好的医疗保健资源分配。试验注册NCT00350987。

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