Supplementary Material for: Computed Tomography Findings for Intracerebral Hemorrhage Have Little Incremental Impact on Post-Stroke Mortality Prediction Model Performance

Background: Stroke outcome studies often combine cases of intracerebral hemorrhage (ICH) and ischemic stroke (IS). These studies of mixed stroke typically ignore computed tomography (CT) findings for ICH cases, though the impact of omitting these traditional predictors of ICH mortality is unknown. We investigated the incremental impact of ICH CT findings on mortality prediction model performance. Methods: Cases of ICH and IS (2000–2003) were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) project. Base models predicting 30-day mortality included demographics, stroke type, and clinical findings (National Institutes of Health Stroke Scale (NIHSS) +/– Glasgow Coma Scale (GCS)). The impact of adding CT data (volume, intraventricular hemorrhage, infratentorial location) was assessed with the area under the curve (AUC), unweighted sum of squared residuals (Ŝ), and integrated discrimination improvement (IDI). The model assessment was performed first for the mixed case of IS and ICH, and then repeated for ICH cases alone to determine whether any lack of improvement in model performance with CT data for mixed stroke type was due to IS cases naturally forming a larger proportion of the total sample than ICH. Results: A total of 1,256 cases were included (86% IS, 14% ICH). Thirty-day mortality was 16% overall (11% for IS; 43% for ICH). When both clinical scales (NIHSS and GCS) were included, none of the model performance measures showed improvement with the addition of CT findings whether considering IS and ICH together (ΔAUC: 0.002, 95% CI –0.01, 0.02; ΔŜ: –3.0, 95% CI –9.1, 2.6; IDI: 0.017, 95% CI –0.004, 0.05) or considering ICH cases alone (ΔAUC: 0.02, 95% CI –0.02, 0.08; ΔŜ: –2.0, 95% CI –9.7, 3.4; IDI 0.065, 95% CI –0.03, 0.21). If NIHSS was the only clinical scale included, there was still no improvement in AUC or Ŝ when CT findings were added for the sample with IS/ICH combined (ΔAUC: 0.005, 95% CI –0.01, 0.02; ΔŜ: –5.0, 95% CI –11.6, 1.0) or for ICH cases alone (ΔAUC: 0.05, 95% CI –0.002, 0.11; ΔŜ: –4.2, 95% CI –11.5, 2.3). However, IDI was improved when NIHSS was the only clinical scale for IS/ICH combined (IDI: 0.029, 95% CI 0.002, 0.065) and ICH alone (IDI: 0.12, 95% CI 0.005, 0.26). Conclusions: Excluding ICH CT findings had only minimal impact on mortality prediction model performance whether examining ICH and IS together or ICH alone. These findings have important implications for the design of clinical studies involving ICH patients.背景：卒中预后研究常将脑出血（intracerebral hemorrhage, ICH）与缺血性卒中（ischemic stroke, IS）病例合并分析。此类混合卒中研究通常会忽略脑出血病例的计算机断层扫描（computed tomography, CT）结果，但忽略这类ICH死亡率传统预测因素所带来的影响尚不明确。本研究旨在探讨ICH的CT影像结果对死亡率预测模型性能的增量影响。 方法：本研究从科珀斯克里斯蒂脑卒中监测（Brain Attack Surveillance in Corpus Christi, BASIC）项目中提取了2000年至2003年的ICH与IS病例。预测30天死亡率的基础模型纳入了人口学资料、卒中类型及临床评估指标（美国国立卫生研究院卒中量表（National Institutes of Health Stroke Scale, NIHSS）±格拉斯哥昏迷量表（Glasgow Coma Scale, GCS））。通过曲线下面积（area under the curve, AUC）、未加权残差平方和（unweighted sum of squared residuals, Ŝ）以及综合判别改善指数（integrated discrimination improvement, IDI），评估添加CT相关数据（血肿体积、脑室内出血、幕下病灶位置）对模型的影响。模型评估首先针对IS与ICH的混合病例组开展，随后仅针对ICH病例组重复进行，以明确混合卒中分析中CT数据未带来模型性能提升的原因，是否源于IS病例在总样本中占比天然高于ICH病例。 结果：本研究共纳入1256例病例，其中IS占86%，ICH占14%。总体30天死亡率为16%（IS组为11%，ICH组为43%）。当同时纳入两种临床量表（NIHSS与GCS）时，无论针对IS与ICH的合并样本（ΔAUC：0.002，95%置信区间（confidence interval, CI）：-0.01~0.02；ΔŜ：-3.0，95%CI：-9.1~2.6；IDI：0.017，95%CI：-0.004~0.05），还是仅针对ICH病例组（ΔAUC：0.02，95%CI：-0.02~0.08；ΔŜ：-2.0，95%CI：-9.7~3.4；IDI：0.065，95%CI：-0.03~0.21），添加CT结果均未使模型性能指标出现显著改善。若仅纳入NIHSS作为临床评估量表，无论针对IS与ICH的合并样本（ΔAUC：0.005，95%CI：-0.01~0.02；ΔŜ：-5.0，95%CI：-11.6~1.0），还是仅针对ICH病例组（ΔAUC：0.05，95%CI：-0.002~0.11；ΔŜ：-4.2，95%CI：-11.5~2.3），添加CT结果后AUC与Ŝ均未出现改善。但当仅以NIHSS作为临床评估量表时，合并样本与ICH单独样本的IDI均出现显著提升：合并样本IDI为0.029，95%CI：0.002~0.065；ICH单独样本IDI为0.12，95%CI：0.005~0.26。 结论：无论针对ICH与IS的合并样本还是仅针对ICH病例组，忽略ICH的CT影像结果对死亡率预测模型性能的影响均极小。本研究结果对涉及ICH患者的临床研究设计具有重要指导意义。