Kanneganti Vidyasagar, Thakar Sumit, Aryan Saritha, Kini Prayaag, Mohan Dilip, Hegde Alangar S
Department of Neurological Sciences, Sri Sathya Sai Institute of Higher Medical Sciences, Bengaluru, Karnataka, India.
Department of Cardiology, Sri Sathya Sai Institute of Higher Medical Sciences, Bengaluru, Karnataka, India.
J Neurosci Rural Pract. 2021 Apr;12(2):302-307. doi: 10.1055/s-0041-1722819. Epub 2021 Mar 15.
Cardiogenic brain abscess (CBA) is the commonest noncardiac cause of morbidity and mortality in cyanotic heart disease (CHD). The clinical diagnosis of a CBA is often delayed due to its nonspecific presentations and the scarce availability of computed tomography (CT) imaging in resource-restricted settings. We attempted to identify parameters that reliably point to the diagnosis of a CBA in patients with Tetralogy of Fallot (TOF). From among 150 children with TOF treated at a tertiary care institute over a 15-year period from 2001 to 2016, 30 consecutive patients with CBAs and 85 age- and sex-matched controls without CBAs were included in this retrospective case-control study. Demographic and clinical features, laboratory investigations, and baseline echocardiographic findings were analyzed for possible correlations with the presence of a CBA. Variables demonstrating significant bivariate correlations with the presence of a CBA were further analyzed using multivariate logistic regression (LR) analysis. Various LR models were tested for their predictive value, and the best model was then validated on a hold-out dataset of 25 patients. Among the 26 variables tested for bivariate associations with the presence of a CBA, some of the clinical, echocardiographic, and laboratory variables demonstrated significant correlations ( < 0.05). LR analysis revealed elevated neutrophil-lymphocyte ratio and erythrocyte sedimentation rate values and a lower age-adjusted resting heart rate percentile to be the strongest independent biomarkers of a CBA. The LR model was statistically significant, (χ = 23.72, <0.001), and it fitted the data well. It explained 53% (Nagelkerke ) of the variance in occurrence of a CBA, and correctly classified 83.93% of cases. The model demonstrated a good predictive value (area under the curve: 0.80) on validation analysis. This study has identified simple clinical and laboratory parameters that can serve as reliable pointers of a CBA in patients with TOF. A scoring model-the 'BA-TOF' score-that predicts the occurrence of a CBA has been proposed. Patients with higher scores on the proposed model should be referred urgently for a CT confirmation of the diagnosis. Usage of such a diagnostic aid in resource-limited settings can optimize the pickup rates of a CBA and potentially improve outcomes.
心源性脑脓肿(CBA)是青紫型心脏病(CHD)中最常见的非心脏性发病和死亡原因。由于其临床表现不具特异性,且在资源有限的环境中难以获得计算机断层扫描(CT)成像,CBA的临床诊断常常延迟。我们试图确定能可靠指向法洛四联症(TOF)患者CBA诊断的参数。
在2001年至2016年的15年期间,一家三级医疗机构收治了150例TOF患儿,本回顾性病例对照研究纳入了30例连续的CBA患者以及85例年龄和性别匹配的无CBA对照。分析人口统计学和临床特征、实验室检查以及基线超声心动图结果,以寻找与CBA存在可能的相关性。
对与CBA存在显著双变量相关性的变量,进一步采用多因素逻辑回归(LR)分析。测试各种LR模型的预测价值,然后在25例患者的保留数据集上验证最佳模型。
在测试的26个与CBA存在双变量关联的变量中,一些临床、超声心动图和实验室变量显示出显著相关性(<0.05)。LR分析显示,中性粒细胞与淋巴细胞比值升高、红细胞沉降率升高以及年龄校正后的静息心率百分位数降低是CBA最强的独立生物标志物。LR模型具有统计学意义(χ² = 23.72,<0.001),且对数据拟合良好。它解释了CBA发生变异的53%(Nagelkerke R²),并正确分类了83.93%的病例。该模型在验证分析中显示出良好的预测价值(曲线下面积:0.80)。
本研究确定了简单的临床和实验室参数,可作为TOF患者CBA的可靠指标。我们提出了一个预测CBA发生的评分模型——“BA-TOF”评分。该模型得分较高的患者应紧急转诊进行CT诊断确认。在资源有限的环境中使用这种诊断辅助工具可以优化CBA的检出率,并可能改善治疗结果。