精细化护理在缺血性脑卒中患者介入治疗围手术期中的应用效果
Application Effect of Refined Nursing in the Perioperative Period of Cerebral Ischemic Stroke Interventional Therapy
王湛 1赵文利 1李海云1
作者信息
- 1. 河南省人民医院介入导管室,河南省护理医学重点实验室,郑州大学人民医院,郑州 450000
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摘要
目的:探讨精细化护理在缺血性脑卒中患者介入治疗围手术期中的应用效果.方法:选择 2021 年 6 月至2022 年 4 月在本院进行介入治疗的 103 例缺血性脑卒中患者作为研究对象.依据围手术期采取的不同干预模式,将其分为观察组(n =52,采取精细化护理措施)与对照组(n =51,采取常规护理措施).比较两组的护理满意度及并发症发生率.结果:观察组的护理满意度为 96.15%(50/52),明显高于对照组的 76.47%(39/51),差异有统计学意义(P＜0.05);观察组的并发症发生率为 17.30%(9/52),明显低于对照组的 49.01%(25/51),差异有统计学意义(P＜0.05).结论:对缺血性脑卒中患者介入治疗围手术期实施精细化护理,有利于降低其围手术期并发症发生率,提高手术安全性,应用效果更佳,值得临床应用和推广.
Abstract
Objective:To analyze the application effect of refined nursing in the perioperative period of interventional treatment of cerebral ischemic stroke patients.Methods:A total of 103 patients with cerebral ischemic stroke who underwent interventional therapy admitted in our hospital from June 2021 to April 2022 were selected as the research objects,and divide into an observation group(n =52,received refined nursing)and a control group(n =51,received routine nursing)based on the implementation of different intervention modes during the perioperative period.The nursing satisfaction and the incidence of complications were compared between the two groups.Results:The nursing satisfaction of the observation group was 96.15%(50/52),and the nursing satisfaction of the control group was 76.47%(39/51),which was significantly higher than that of the control group(P＜0.05);the incidence of complications in the observation group was 17.30%(9/52),which was significantly lower than that 49.01%(25/51)in the control group(P＜0.05).Conclusion:Refined nursing is more conducive to reducing the incidence of perioperative complications in the treatment of cerebral ischemic stroke patients,improving safety,and achieving better application results.It is worth of clinical application and promotion.
关键词
缺血性脑卒中/介入治疗/围手术期/精细化护理/应用效果Key words
Cerebral ischemic stroke/Interventional therapy/Perioperative period/Refined nursing/Application effect引用本文复制引用
出版年
2024
NETL
NSTL
万方数据