Kaewwinud Jeerawat, Pienchitlertkajorn Sireethorn, Koomtanapat Kamolphop, Lumkul Lalita, Wongyikul Pakpoom, Phinyo Phichayut
Department of Medicine, Surin Hospital, Surin, Thailand.
Center for Clinical Epidemiology and Clinical Statistics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Heliyon. 2023 Dec 12;10(1):e23440. doi: 10.1016/j.heliyon.2023.e23440. eCollection 2024 Jan 15.
Diagnosing tuberculous pleural effusion (TPE) in patients presenting with Lymphocyte-Predominant Exudative pleural effusion (LPE) is challenging, due to the poor clinical utility of TB culture. Adenosine deaminase (ADA) has been recommended for diagnosis, but its high cost and limited availability hinder its clinical utility. We aim to develop diagnostic prediction tools for Thai patients with LPE in scenarios where pleural fluid ADA is available but yields negative results and in situations where pleural fluid ADA is not available.
Two diagnostic prediction tools were developed using retrospective data from patients with LPE at Surin Hospital. Model 1 is for ADA-negative results, and Model 2 is for situations where pleural fluid ADA testing is unavailable. The models were derived using multivariable logistic regression and presented as two clinical scoring systems: round-up and count scoring. The score cut-point that achieves a positive predictive value (PPV) comparable to the post-test probability of a pleural fluid ADA at a cut-point of 40 U/L was used as a threshold for initiating anti-TB treatment.
A total of 359 patients were eligible for analysis, with 166 diagnosed with TPE and 193 diagnosed with non-TPE. Age <40 years, fever, pleural fluid protein ≥5 g/dL, male gender, pleural fluid color, and pleural fluid ADA ≥20 U/L were identified as final predictors. Both models demonstrated excellent discriminative ability (AuROC: 0.85 to 0.89). The round-up scoring demonstrated PPV above 90% at cut-off points of 4 and 4.5, while the count scoring achieved cut-off points of 3 and 4 for Model 1 (Lex-2P2A) and Model 2 (Lex-2P-MAC), respectively.
These diagnostic tools offer valuable assistance in differentiating between TPE and non-TPE in LPE patients with negative pleural fluid ADA (Lex-2P2A) and in settings where pleural fluid ADA testing is not available (Lex-2P-MAC). Implementing these diagnostic scores may have the potential to improve TPE diagnosis and facilitate prompt initiation of treatment.
对于以淋巴细胞为主的渗出性胸腔积液（LPE）患者，诊断结核性胸腔积液（TPE）具有挑战性，因为结核培养的临床实用性较差。腺苷脱氨酶（ADA）已被推荐用于诊断，但其高成本和有限的可及性阻碍了其临床应用。我们旨在为泰国LPE患者开发诊断预测工具，适用于胸腔积液ADA检测结果为阴性的情况以及无法进行胸腔积液ADA检测的情况。
利用素林医院LPE患者的回顾性数据开发了两种诊断预测工具。模型1用于ADA检测结果为阴性的情况，模型2用于无法进行胸腔积液ADA检测的情况。这些模型通过多变量逻辑回归得出，并以两种临床评分系统呈现：四舍五入评分和计数评分。将达到与胸腔积液ADA在40 U/L切点时的检测后概率相当的阳性预测值（PPV）的评分切点用作启动抗结核治疗的阈值。
共有359例患者符合分析条件，其中166例诊断为TPE，193例诊断为非TPE。年龄<40岁、发热、胸腔积液蛋白≥5 g/dL、男性、胸腔积液颜色以及胸腔积液ADA≥20 U/L被确定为最终预测因素。两个模型均显示出出色的鉴别能力（曲线下面积：0.85至0.89）。四舍五入评分在4和4.5的切点处显示PPV高于90%，而计数评分在模型1（Lex-2P2A）和模型2（Lex-2P-MAC）中分别达到3和4的切点。
这些诊断工具为鉴别胸腔积液ADA检测结果为阴性的LPE患者（Lex-2P2A）以及无法进行胸腔积液ADA检测的情况下（Lex-2P-MAC）的TPE和非TPE提供了有价值的帮助。实施这些诊断评分可能有改善TPE诊断并促进及时开始治疗的潜力。
