Porcel José M, Trujillano Javier, Porcel Laura, Esquerda Aureli, Bielsa Silvia
Pleural Medicine and Clinical Ultrasound Unit, Department of Internal Medicine, Arnau de Vilanova University Hospital, IRBLleida, Lleida, Spain.
Department of Intensive Care Unit, Arnau de Vilanova University Hospital, Lleida, Spain.
ERJ Open Res. 2025 Jun 30;11(3). doi: 10.1183/23120541.01030-2024. eCollection 2025 May.
Heart failure (HF) is a common cause of pleural effusion (PE); however, its diagnosis can be challenging owing to overlapping clinical features with other causes. Measuring N-terminal pro-brain natriuretic peptide (NT-proBNP) levels is diagnostically useful, but the optimal cut-off point must be determined. This study aimed to optimise NT-proBNP cut-offs for diagnosing HF-related PEs and develop a scoring model to improve diagnostic precision.
A retrospective analysis was conducted on 2005 patients with PEs, who were divided into derivation and validation cohorts. Receiver operating characteristic curve analysis identified the optimal cut-off point for NT-proBNP in pleural fluid and serum. A scoring system was developed based on logistic regression (TRIPOD statement) that included both clinical and laboratory variables. Its diagnostic accuracy was compared with that of existing methods using the area under the curve (AUC).
NT-proBNP ≥2500 pg·mL was found to be the optimal cut-off for identifying HF-related effusions. Pleural fluid NT-proBNP levels tended to have superior diagnostic accuracy compared with serum NT-proBNP levels. A scoring system, denominated as BANCA (bilateral effusions on chest radiographs, age, NT-proBNP levels in pleural fluid, cholesterol in pleural fluid, and albumin gradient), demonstrated an AUC of 0.957, outperforming existing diagnostic criteria for identifying cardiac effusions. In cases misclassified as exudates by Light's criteria, the BANCA score accurately identified 80% of the HF-related PEs.
The BANCA score is a reliable tool for diagnosing HF-related PEs, offering superior accuracy compared with conventional methods. It is particularly useful for identifying cardiac effusions that are misclassified using traditional criteria.
心力衰竭（HF）是胸腔积液（PE）的常见病因；然而，由于其临床特征与其他病因重叠，其诊断可能具有挑战性。测量N末端脑钠肽前体（NT-proBNP）水平有助于诊断，但必须确定最佳截断点。本研究旨在优化用于诊断HF相关PE的NT-proBNP截断值，并开发一种评分模型以提高诊断准确性。
对2005例PE患者进行回顾性分析，将其分为推导队列和验证队列。通过受试者工作特征曲线分析确定胸腔积液和血清中NT-proBNP的最佳截断点。基于逻辑回归（TRIPOD声明）开发了一个评分系统，该系统包括临床和实验室变量。使用曲线下面积（AUC）将其诊断准确性与现有方法进行比较。
发现NT-proBNP≥2500 pg·mL是识别HF相关积液的最佳截断值。与血清NT-proBNP水平相比，胸腔积液NT-proBNP水平的诊断准确性往往更高。一个名为BANCA（胸部X线片双侧积液、年龄、胸腔积液NT-proBNP水平、胸腔积液胆固醇和白蛋白梯度）的评分系统显示AUC为0.957，优于现有诊断心脏积液的标准。在根据Light标准被误分类为渗出液的病例中，BANCA评分准确识别了80%的HF相关PE。
BANCA评分是诊断HF相关PE的可靠工具，与传统方法相比具有更高的准确性。它对于识别使用传统标准误分类的心脏积液特别有用。
