Yu Xian-Feng, Yin Wen-Wen, Huang Chao-Juan, Yuan Xin, Xia Yu, Zhang Wei, Zhou Xia, Sun Zhong-Wu
Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, China.
World J Clin Cases. 2021 Nov 6;9(31):9440-9451. doi: 10.12998/wjcc.v9.i31.9440.
The identification of risk factors for recurrence in patients with minor ischemic stroke (MIS) is a critical medical need.
To develop a nomogram for individualized prediction of in-hospital recurrence in MIS patients.
Based on retrospective collection, a single-center study was conducted at the First Affiliated Hospital of Anhui Medical University from January 2014 to December 2019. Univariate and multivariate logistic regression analyses were used to determine the risk factors associated with MIS recurrence. The least absolute shrinkage and selection operator regression was performed for preliminary identification of potential risk factors. Uric acid, systolic blood pressure, serum total bilirubin (STBL), and ferritin were integrated for nomogram construction. The predictive accuracy and calibration of the nomogram model were assessed by the area under the receiver operating characteristic curve (AUC-ROC) and Hosmer-Lemeshow test, respectively.
A total of 2216 MIS patients were screened. Among them, 155 were excluded for intravascular therapy, 146 for unknown National Institutes of Health Stroke Scale score, 195 for intracranial hemorrhage, and 247 for progressive stroke. Finally, 1244 patients were subjected to further analysis and divided into a training set ( = 796) and a validation set ( = 448). Multivariate logistic regression analysis revealed that uric acid [odds ratio (OR): 0.997, 95% confidence interval (CI): 0.993-0.999], ferritin (OR: 1.004, 95%CI: 1.002-1.006), and STBL (OR: 0.973, 95%CI: 0.956-0.990) were independently associated with in-hospital recurrence in MIS patients. Our model showed good discrimination; the AUC-ROC value was 0.725 (95%CI: 0.646-0.804) in the training set and 0.717 (95%CI: 0.580-0.785) in the validation set. Moreover, the calibration between nomogram prediction and the actual observation showed good consistency. Hosmer-Lemeshow test results confirmed that the nomogram was well-calibrated ( = 0.850).
Our present findings suggest that the nomogram may provide individualized prediction of recurrence in MIS patients.
识别轻度缺血性卒中(MIS)患者复发的危险因素是一项迫切的医学需求。
建立一种列线图,用于个体化预测MIS患者的院内复发情况。
基于回顾性收集,2014年1月至2019年12月在安徽医科大学第一附属医院进行了一项单中心研究。采用单因素和多因素逻辑回归分析来确定与MIS复发相关的危险因素。进行最小绝对收缩和选择算子回归以初步识别潜在危险因素。将尿酸、收缩压、血清总胆红素(STBL)和铁蛋白整合用于构建列线图。分别通过受试者操作特征曲线下面积(AUC-ROC)和Hosmer-Lemeshow检验评估列线图模型的预测准确性和校准情况。
共筛选出2216例MIS患者。其中,155例因血管内治疗被排除,146例因美国国立卫生研究院卒中量表评分未知被排除,195例因颅内出血被排除,247例因进展性卒中被排除。最终,1244例患者接受进一步分析,并分为训练集(n = 796)和验证集(n = 448)。多因素逻辑回归分析显示,尿酸[比值比(OR):0.997,95%置信区间(CI):0.993 - 0.999]、铁蛋白(OR:1.004, 95%CI:1.002 - 1.006)和STBL(OR:0.973, 95%CI:0.956 - 0.990)与MIS患者的院内复发独立相关。我们的模型显示出良好的区分度;训练集中AUC-ROC值为0.725(95%CI:0.646 - 0.804),验证集中为0.717(95%CI:0.580 - 0.785)。此外,列线图预测与实际观察之间的校准显示出良好的一致性。Hosmer-Lemeshow检验结果证实列线图校准良好(P = 0.850)。
我们目前的研究结果表明,该列线图可能为MIS患者的复发提供个体化预测。