Department of Neurology Nursing, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, Sichuan 610072, China.
Comput Math Methods Med. 2022 Jun 20;2022:8392854. doi: 10.1155/2022/8392854. eCollection 2022.
With the continuous improvement of medical technology and the aging of the population, the death rate of stroke is gradually decreasing, but the recurrence rate is still high, and the number of recurrences is increasing, resulting in disability and other symptoms, which brings great burden and distress to patients and their families. As the number of strokes increases, neurological impairment becomes more and more severe, affecting patients' ability to live, socialize, and work, and seriously reducing their quality of life. Clustered care is a combination of evidence-based linked interventions and a multidisciplinary team providing the best possible care through evidence-based research and highly operational practice, and it can improve outcomes for ischemic stroke patients more than implementation alone. This paper presents a Cox proportional risk regression-based model, using it to build the most used semi-parametric model for multifactorial survival analysis, due to its advantages of both parametric and nonparametric models, and to analyze the factors influencing survival time in study subjects with incomplete data. The proposed strategy has been found to be useful in predicting ischemic stroke recurrence and cluster care interventions for patients.
随着医疗技术的不断提高和人口老龄化，中风的死亡率逐渐下降，但复发率仍然很高，且复发人数不断增加，导致残疾等症状，给患者及其家庭带来了巨大的负担和痛苦。随着中风患者数量的增加，神经功能损伤越来越严重，影响了患者的生活、社交和工作能力，严重降低了他们的生活质量。集群护理是将循证链接干预措施与多学科团队相结合，通过循证研究和高度操作性实践为患者提供最佳护理，可改善缺血性中风患者的预后，其效果优于单独实施。本文提出了一种基于 Cox 比例风险回归的模型，使用它构建多因素生存分析中最常用的半参数模型，由于其兼具参数和非参数模型的优势，用于分析存在不完全数据的研究对象的生存时间的影响因素。该策略已被证明对预测缺血性中风复发和集群护理干预患者有用。
