S Yuvarajan, Radhakrishnan Praveen, Krishnamurthy Durga, Cherukkumalli Navya, Ravikumar Sagana
Department of Respiratory Medicine, Sri Manakula Vinayagar Medical College and Hospital, Puducherry, IND.
Department of Obstetrics and Gynaecology, Sri Lakshminarayana Institute of Medical Sciences, Puducherry, IND.
Cureus. 2025 Jul 30;17(7):e89046. doi: 10.7759/cureus.89046. eCollection 2025 Jul.
Sarcoidosis is a complex, multisystem granulomatous disease of unknown etiology, often presenting a diagnostic challenge due to its highly variable clinical manifestations and its overlap with infectious and neoplastic diseases. This is especially problematic in regions with a high burden of tuberculosis (TB), such as India, where the clinical and radiological features of sarcoidosis and TB can be remarkably similar. Early, accurate diagnosis is imperative to guide treatment and avoid inappropriate therapy, yet no universally accepted diagnostic scoring system exists.
The objective of this study was to develop and internally validate a novel, composite clinical scoring tool named the Yuvarajan Sarcoidosis Diagnostic Score (YSDS) to aid in the diagnosis of sarcoidosis using routinely available clinical, radiologic, laboratory, and histopathologic parameters.
A retrospective observational study was conducted at a tertiary care hospital in South India. Medical records of 94 patients evaluated for suspected sarcoidosis between January 2022 and January 2025 were reviewed. Patients were categorized into sarcoidosis (n = 63) and non-sarcoidosis groups (n = 31) based on histopathological confirmation, radiological features, and exclusion of differential diagnoses. Multivariate logistic regression was used to identify significant independent predictors of sarcoidosis. These predictors were used to create a weighted diagnostic score, and their diagnostic accuracy was assessed using receiver operating characteristic (ROC) curve analysis.
Five independent predictors were identified: bilateral hilar lymphadenopathy (BHL) on chest imaging, elevated serum angiotensin-converting enzyme (ACE) levels, histologic presence of non-caseating granulomas, negative Mantoux test, and characteristic extrapulmonary manifestations such as uveitis, parotid gland enlargement, or lupus pernio. Each parameter was assigned a score based on the regression coefficient. The YSDS score ranged from 0 to 13, with a cutoff ≥8 yielding a sensitivity of 87.3% (55/63), specificity of 83.9% (26/31), positive predictive value (PPV) of 89.6% (55/61), negative predictive value (NPV) of 80.6% (26/33), and an overall accuracy of 85.9% (81/94). The area under the ROC curve was 0.90, indicating excellent discriminatory power.
The YSDS is a statistically robust, easy-to-implement clinical tool that enhances diagnostic confidence in sarcoidosis, particularly in settings where TB and other granulomatous diseases are prevalent. It offers a promising strategy for standardized diagnostic assessment and warrants external validation in larger, prospective cohorts.
结节病是一种病因不明的复杂多系统肉芽肿性疾病,由于其临床表现高度可变且与感染性和肿瘤性疾病存在重叠,常常带来诊断挑战。在结核病负担较高的地区,如印度,这一问题尤为突出,因为结节病和结核病的临床及影像学特征可能极为相似。早期准确诊断对于指导治疗及避免不恰当治疗至关重要,但目前尚无普遍接受的诊断评分系统。
本研究的目的是开发并内部验证一种名为尤瓦拉詹结节病诊断评分(YSDS)的新型综合临床评分工具,以利用常规可得的临床、放射学、实验室及组织病理学参数辅助结节病的诊断。
在印度南部的一家三级医疗中心进行了一项回顾性观察研究。回顾了2022年1月至2025年1月期间对94例疑似结节病患者进行评估的病历。根据组织病理学确诊、放射学特征及排除鉴别诊断,将患者分为结节病组(n = 63)和非结节病组(n = 31)。采用多因素逻辑回归确定结节病的显著独立预测因素。这些预测因素用于创建加权诊断评分,并使用受试者工作特征(ROC)曲线分析评估其诊断准确性。
确定了五个独立预测因素:胸部影像学显示双侧肺门淋巴结肿大(BHL)、血清血管紧张素转换酶(ACE)水平升高、非干酪样肉芽肿的组织学表现、结核菌素试验阴性以及葡萄膜炎、腮腺肿大或冻疮样狼疮等特征性肺外表现。根据回归系数为每个参数分配一个分数。YSDS评分范围为0至13,截断值≥8时,敏感性为87.3%(55/63),特异性为83.9%(26/31),阳性预测值(PPV)为89.6%(55/61),阴性预测值(NPV)为80.6%(26/33),总体准确率为85.9%(81/94)。ROC曲线下面积为0.90,表明具有出色的鉴别能力。
YSDS是一种统计学上可靠、易于实施的临床工具,可增强对结节病的诊断信心,尤其是在结核病和其他肉芽肿性疾病流行的环境中。它为标准化诊断评估提供了一种有前景的策略,值得在更大规模的前瞻性队列中进行外部验证。