Suppr超能文献

开发并验证一种评分系统,以识别心源性胸腔渗出液。

Development and validation of a scoring system for the identification of pleural exudates of cardiac origin.

机构信息

Pleural Medicine Unit, Arnau de Vilanova University Hospital, IRBLleida, Lleida, Spain.

Department of Pulmonology, University Clinical Hospital of Santiago de Compostela, Santiago de Compostela, Spain.

出版信息

Eur J Intern Med. 2018 Apr;50:60-64. doi: 10.1016/j.ejim.2017.11.008. Epub 2017 Nov 20.

Abstract

BACKGROUND

Light's criteria misclassify about 30% of cardiac effusions as exudates, possibly leading to unnecessary testing. Our purpose was to derive and validate a scoring model to effectively identify these falsely categorized cardiac effusions, in the setting of natriuretic peptide lacking data.

METHODS

We retrospectively analyzed data from 3182 patients with exudative pleural effusions based on Light's criteria, of whom 276 had heart failure (derivation set). A scoring model was generated with those variables identified as independent predictors of cardiac effusions in a logistic regression analysis, and further evaluated in an independent population of 1165 patients.

RESULTS

The score consisted of age ≥75years (3 points), albumin gradient >1.2g/dL (3 points), pleural fluid lactate dehydrogenase <250U/L (2 points), bilateral effusions on chest radiograph (2 points), and protein gradient >2.5g/dL (1 point). At the best cutoff of ≥7 points, the score yielded 92% diagnostic accuracy, a likelihood ratio positive of 12.7 and a likelihood ratio negative of 0.39 for labeling cardiac effusions in the derivation sample. The respective figures in the validation sample were 87%, 6.5 and 0.33. Notably, the score had higher discriminatory properties than protein and albumin gradients in both the derivation (respective area under the curve - AUC - of 0.925, 0.825, and 0.801) and validation (respective AUC of 0.908 0.862 and 0.802; all p≤0.01) cohorts.

CONCLUSIONS

A simple scoring system can assist clinicians in accurately identifying false cardiac exudates when natriuretic peptides are not available.

摘要

背景

Light 的标准将约 30%的心包积液误诊为渗出液,这可能导致不必要的检查。我们的目的是在缺乏利钠肽数据的情况下,建立并验证一种评分模型,以有效地识别这些错误分类的心包积液。

方法

我们回顾性分析了根据 Light 标准诊断为渗出性胸腔积液的 3182 例患者的数据,其中 276 例患者患有心力衰竭(推导集)。使用逻辑回归分析确定的变量生成评分模型,并在 1165 例独立患者中进一步评估。

结果

评分由年龄≥75 岁(3 分)、白蛋白梯度>1.2g/dL(3 分)、胸腔积液乳酸脱氢酶<250U/L(2 分)、胸部 X 线双侧积液(2 分)和蛋白梯度>2.5g/dL(1 分)组成。最佳截断值≥7 分时,该评分在推导样本中对诊断为心源性积液的准确性为 92%,阳性似然比为 12.7,阴性似然比为 0.39。在验证样本中,相应的数值分别为 87%、6.5 和 0.33。值得注意的是,在推导(分别为 0.925、0.825 和 0.801)和验证(分别为 0.908、0.862 和 0.802)队列中,评分的判别能力均高于蛋白和白蛋白梯度。

结论

当利钠肽不可用时,一种简单的评分系统可以帮助临床医生准确识别假性心脏渗出液。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验