Lee Ching-Chi, Ho Ching-Yu, Hong Ming-Yuan, Hung Yuan-Pin, Ko Wen-Chien
Clinical Medical Research Center, Division of Infectious Diseases, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No. 138, Sheng Li Road, Tainan, 70403, Taiwan.
Department of Medicine, Medical College, National Cheng Kung University, Tainan, Taiwan.
Infection. 2025 Feb;53(1):209-220. doi: 10.1007/s15010-024-02344-4. Epub 2024 Sep 19.
Misdiagnosis or delayed diagnosis of paravertebral and/or iliopsoas abscess (PVIPA) has been frequently reported to be associated with unfavorable prognosis. We aimed to develop a scoring algorithm that can easily and accurately identify patients at greater risk for PVIPA among individuals with community-onset bloodstream infections.
In a multicenter, retrospective cohort study, the score was developed with the first four study years and validated with the remaining two years. Applying logistic regression, the score values of prediction determinants were derived from the adjusted odds ratios (AOR). The performance of the scoring algorithm was assessed with the receiver operating characteristic (ROC) curve.
In the derivation (3869 patients) and validation (1608) cohorts, patients with PVIPA accounted for 1.7% and 1.4%, respectively. In the derivation cohort, five independent predictors of PVIPA were recognized using multivariable analyses: time-to-defervescence > 5 days (AOR, 7.00; 2 points), Panton-Valentine Leukocidin (PVL)-producing Staphylococcus aureus (AOR, 5.98; 2 points), intravenous drug users (AOR, 2.60; 1 points), and comorbid hemato-oncology (AOR, 0.41; -1 point) or liver cirrhosis (AOR, 2.56; 1 points). In the derivation and validation cohorts, areas under ROC curves (95% confidence intervals) of the prediction algorithm are 0.83 (0.77-0.88) and 0.85 (0.80-0.90), and a cutoff score of + 2 represents sensitivity of 83.3% and 95.7%, specificity of 68.6% and 67.7%, positive predictive values of 4.4% and 4.1%, and negative predictive values of 99.6% and 99.9%, respectively.
Of a scoring algorithm with substantial sensitivity and specificity in predicting PVIPA, PVL-producing S. aureus and Time-to-defervescence > 5 days were crucial determinants.
据报道，椎旁和/或髂腰肌脓肿（PVIPA）的误诊或延迟诊断常与不良预后相关。我们旨在开发一种评分算法，能够在社区获得性血流感染患者中轻松、准确地识别出发生PVIPA风险较高的患者。
在一项多中心回顾性队列研究中，该评分算法在前四年的研究中开发，并在接下来的两年中进行验证。应用逻辑回归，预测决定因素的评分值来自调整后的优势比（AOR）。通过受试者工作特征（ROC）曲线评估评分算法的性能。
在推导队列（3869例患者）和验证队列（1608例患者）中，PVIPA患者分别占1.7%和1.4%。在推导队列中，通过多变量分析确定了PVIPA的五个独立预测因素：退热时间>5天（AOR，7.00；2分）、产杀白细胞素（PVL）的金黄色葡萄球菌（AOR，5.98；2分）、静脉吸毒者（AOR，2.60；1分）、合并血液肿瘤学疾病（AOR，0.41；-1分）或肝硬化（AOR，2.56；1分）。在推导队列和验证队列中，预测算法的ROC曲线下面积（95%置信区间）分别为0.83（0.77-0.88）和0.85（0.80-0.90），临界评分为+2时，敏感性分别为83.3%和95.7%，特异性分别为68.6%和67.7%，阳性预测值分别为4.4%和4.1%，阴性预测值分别为99.6%和99.9%。
在预测PVIPA方面具有较高敏感性和特异性的评分算法中，产PVL的金黄色葡萄球菌和退热时间>5天是关键决定因素。
