Zhang Xiao-Dan, Zhang Zong-Yong, Zhao Ming-Pei, Zhang Xiang-Tao, Wang Neng, Gao Hong-Zhi, Lin Yuan-Xiang, Zheng Zong-Qing
Neurosurgery Department, The 2nd Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Clinic Center of Molecular Diagnosis and Therapy of the 2nd Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
BMC Med Inform Decis Mak. 2025 Apr 15;25(1):166. doi: 10.1186/s12911-025-02991-z.
Ischemic stroke (IS) is associated with high disability and mortality. This study aimed to identify the prognostic predictors and develop a nomogram for a prediction model for ischemic stroke patients after thrombolysis.
We retrospectively analyzed data from 359 IS patients who underwent thrombolysis. Clinical characteristics, laboratory parameters, and prognosis data were collected. One-third of the subjects were randomly selected as a validation set (n = 108) for internal validation. Logistic regression analysis was used to derive independent risk indicators. A nomogram was constructed using these indicators, and the performance of the nomogram was assessed by the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC). The agreement of the model predictions with actual observations was assessed via calibration curves, and the clinical utility of the nomogram was assessed via decision curve analysis.
Multivariate logistic regression analysis showed that age, leukocytes, Lactate Dehydrogenase to Albumin Ratio (LAR) and NIHSS were independent predictors of three-month post-thrombolysis prognosis in IS patients. We created a nomogram based on the weighting coefficients of these factors. The AUC curves showed that our model including age, leukocytes, LAR and NIHSS was more accurate in predicting prognosis than a single factor. The calibration curves showed a good fit between actual and predicted probabilities in both the training and validation groups.
LAR has a good predictive power for the prognosis of IS patients 3 months after thrombolytic therapy and can be used as a new clinical indicator to establish a practical nomogram.
缺血性中风（IS）与高致残率和死亡率相关。本研究旨在确定预后预测因素，并为溶栓后的缺血性中风患者开发一种预测模型的列线图。
我们回顾性分析了359例接受溶栓治疗的IS患者的数据。收集了临床特征、实验室参数和预后数据。三分之一的受试者被随机选为内部验证的验证集（n = 108）。采用逻辑回归分析得出独立的风险指标。使用这些指标构建列线图，并通过受试者操作特征曲线（ROC）的曲线下面积（AUC）评估列线图的性能。通过校准曲线评估模型预测与实际观察结果的一致性，并通过决策曲线分析评估列线图的临床实用性。
多因素逻辑回归分析表明，年龄、白细胞、乳酸脱氢酶与白蛋白比值（LAR）和美国国立卫生研究院卒中量表（NIHSS）是IS患者溶栓后三个月预后的独立预测因素。我们根据这些因素的加权系数创建了一个列线图。AUC曲线表明，我们包含年龄、白细胞、LAR和NIHSS的模型在预测预后方面比单一因素更准确。校准曲线表明，训练组和验证组的实际概率与预测概率之间拟合良好。
LAR对IS患者溶栓治疗后3个月的预后具有良好的预测能力，可作为建立实用列线图的新临床指标。
