Sidorenko Irina, Brodkorb Silke, Felderhoff-Müser Ursula, Rieger-Fackeldey Esther, Krüger Marcus, Feddahi Nadia, Kovtanyuk Andrey, Lück Eva, Lampe Renée
Department of Clinical Medicine, Center for Digital Health and Technology, Orthopedic Department, Research Unit for Pediatric Neuroorthopedics and Cerebral Palsy of the Buhl-Strohmaier Foundation, Klinikum rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Clinic for Neonatology, Munich Clinic Harlaching & Schwabing, Munich, Germany.
Front Neurol. 2024 Oct 18;15:1465440. doi: 10.3389/fneur.2024.1465440. eCollection 2024.
Intraventricular hemorrhage (IVH)4 is one of the most threatening neurological complications associated with preterm birth which can lead to long-term sequela such as cerebral palsy. Early recognition of IVH risk may prevent its occurrence and/or reduce its severity. Using multivariate logistic regression analysis, risk factors significantly associated with IVH were identified and integrated into risk scales. A special aspect of this study was the inclusion of mathematically calculated cerebral blood flow (CBF) as an independent predictive variable in the risk score. Statistical analysis was based on clinical data from 254 preterm infants with gestational age between 23 and 30 weeks of pregnancy. Several risk scores were developed for different clinical situations. Their efficacy was tested using ROC analysis, and validation of the best scores was performed on an independent cohort of 63 preterm infants with equivalent gestational age. The inclusion of routinely measured clinical parameters significantly improved IVH prediction compared to models that included only obstetric parameters and medical diagnoses. In addition, risk assessment with numerically calculated CBF demonstrated higher predictive power than risk assessments based on standard clinical parameters alone. The best performance in the validation cohort (with AUC = 0.85 and TPR = 0.94 for severe IVH, AUC = 0.79 and TPR = 0.75 for all IVH grades and FPR = 0.48 for cases without IVH) was demonstrated by the risk score based on the MAP, pH, CRP, CBF and leukocytes count.
脑室内出血(IVH)是与早产相关的最具威胁性的神经并发症之一,可导致脑瘫等长期后遗症。早期识别IVH风险可预防其发生和/或降低其严重程度。通过多因素逻辑回归分析,确定了与IVH显著相关的风险因素并将其纳入风险量表。本研究的一个特殊方面是将数学计算的脑血流量(CBF)作为风险评分中的一个独立预测变量纳入。统计分析基于254例孕周在23至30周之间的早产婴儿的临床数据。针对不同临床情况制定了多个风险评分。使用ROC分析测试了它们的效能,并在一个孕周相当的63例早产婴儿的独立队列中对最佳评分进行了验证。与仅包括产科参数和医学诊断的模型相比,纳入常规测量的临床参数显著改善了IVH预测。此外,与仅基于标准临床参数的风险评估相比,用数字计算的CBF进行风险评估显示出更高的预测能力。基于平均动脉压(MAP)、pH值、C反应蛋白(CRP)、CBF和白细胞计数的风险评分在验证队列中表现最佳(重度IVH的曲线下面积[AUC] = 0.85,真阳性率[TPR] = 0.94;所有IVH分级的AUC = 0.79,TPR = 0.75;无IVH病例的假阳性率[FPR] = 0.48)。