Research on the construction and effect of a precision nursing model for cardiopulmonary rehabilitation in chronic disease patients based on internet of things technology
基于物联网技术的慢性病患者心肺康复精准护理模式构建与效果研究

摘要

目的 探究分析基于物联网技术的慢性病患者心肺康复精准护理模式构建与效果。方法 选取2024年1月至2024年12月期间，院内慢性病患者共102例，作为此次研究对象。通过随机数表法，将102例患者随机分为对照组与观察组。对照组采用常规护理措施，观察组则接受基于物联网技术的心肺康复精准护理方案，对比两组肺功能状态，心功能指标以及生活质量。结果 干预前两组第1秒用力呼气容积（对照组60.22±2.21，观察组60.13±2.17）、用力肺活量（对照组2.16±0.16，观察组2.24±0.17）、呼气流量峰值（对照组63.75±3.20，观察组76.10±4.03），左室射血分数（对照组19.78±2.19，观察组19.83±2.32）、左室短轴缩短率（对照组46.85±5.07，观察组46.92±5.11），左室收缩末期内径（对照组41.25±4.30，观察组42.81±4.77）以及SF-36评分（对照组生理机能、社会功能、生理职能、情感职能、躯体疼痛、精神健康、一般健康状态、精力评分分别为：54.41±5.40、50.90±6.61、57.50±5.10、52.47±5.99、56.26±5.45、50.31±6.33、51.70±6.49、53.29±5.38。观察组生理机能、社会功能、生理职能、情感职能、躯体疼痛、精神健康、一般健康状态、精力评分分别为：54.46±5.48、51.02±6.77、57.80±5.08、52.53±5.94、57.18±6.00、50.23±6.45、51.87±5.20、53.02±5.90）对比，P＞0.05。干预后观察组呼气流量峰值（对照组1.93±0.19，观察组2.96±0.27）、用力肺活量（对照组2.50±0.21，观察组3.33±0.32）以及第1秒用力呼气容积（对照组63.75±3.20，观察组76.10±4.03）均高于对照组，左室射血分数（对照组22.99±2.61，观察组26.80±3.01）、左室短轴缩短率（对照组53.13±3.77，观察组58.69±4.20）高于对照组，左室收缩末期内径（对照组34.69±3.25，观察组30.70±3.01）低于对照组，SF-36评分（对照组生理机能、社会功能、生理职能、情感职能、躯体疼痛、精神健康、一般健康状态、精力评分分别为：65.88±6.10、61.75±7.08、70.03±6.56、69.02±6.36、67.69±5.94、56.45±7.14、66.77±7.91、67.60±6.05。观察组生理机能、社会功能、生理职能、情感职能、躯体疼痛、精神健康、一般健康状态、精力评分分别为：78.20±6.53、76.12±7.49、80.23±6.82、79.20±6.68、72.44±6.30、78.69±7.49、79.83±8.60、78.80±6.53）高于对照组，P＜0.05。结论 基于物联网技术的心肺康复精准护理可显著改善患者肺功能状态，心功能指标以及生活质量，差值分析进一步证实干预效果更显著值得推广与应用。

Abstract

Objective To explore and analyze the construction and effect of a precise cardiopulmonary rehabilitation nursing model for chronic disease patients based on Internet of Things (IoT) technology.
Methods A total of 102 inpatients with chronic diseases from January 2024 to December 2024 were selected as the research subjects. Using a random number table method, these 102 patients were randomly divided into a control group and an observation group. The control group received conventional nursing measures, while the observation group received a precise cardiopulmonary rehabilitation nursing program based on IoT technology. The pulmonary function status, cardiac function indicators, and quality of life of the two groups were compared.
Results Before the intervention, there were no significant differences between the two groups in forced expiratory volume in 1 second (control group: 60.22±2.21, observation group: 60.13±2.17), forced vital capacity (control group: 2.16±0.16, observation group: 2.24±0.17), peak expiratory flow (control group: 63.75±3.20, observation group: 76.10±4.03), left ventricular ejection fraction (control group: 19.78±2.19, observation group: 19.83±2.32), left ventricular fractional shortening (control group: 46.85±5.07, observation group: 46.92±5.11), left ventricular end-systolic diameter (control group: 41.25±4.30, observation group: 42.81±4.77), and SF-36 scores (for the control group, the scores of physical functioning, social functioning, role-physical, role-emotional, bodily pain, mental health, general health, and vitality were 54.41±5.40, 50.90±6.61, 57.50±5.10, 52.47±5.99, 56.26±5.45, 50.31±6.33, 51.70±6.49, and 53.29±5.38 respectively; for the observation group, the scores of physical functioning, social functioning, role-physical, role-emotional, bodily pain, mental health, general health, and vitality were 54.46±5.48, 51.02±6.77, 57.80±5.08, 52.53±5.94, 57.18±6.00, 50.23±6.45, 51.87±5.20, and 53.02±5.90 respectively) (P > 0.05). After the intervention, the peak expiratory flow (control group: 1.93±0.19, observation group: 2.96±0.27), forced vital capacity (control group: 2.50±0.21, observation group: 3.33±0.32), and forced expiratory volume in 1 second (control group: 63.75±3.20, observation group: 76.10±4.03) in the observation group were all higher than those in the control group. The left ventricular ejection fraction (control group: 22.99±2.61, observation group: 26.80±3.01) and left ventricular fractional shortening (control group: 53.13±3.77, observation group: 58.69±4.20) in the observation group were higher than those in the control group, while the left ventricular end-systolic diameter (control group: 34.69±3.25, observation group: 30.70±3.01) was lower than that in the control group. The SF-36 scores in the observation group (physical functioning: 78.20±6.53, social functioning: 76.12±7.49, role-physical: 80.23±6.82, role-emotional: 79.20±6.68, bodily pain: 72.44±6.30, mental health: 78.69±7.49, general health: 79.83±8.60, vitality: 78.80±6.53) were higher than those in the control group (physical functioning: 65.88±6.10, social functioning: 61.75±7.08, role-physical: 70.03±6.56, role-emotional: 69.02±6.36, bodily pain: 67.69±5.94, mental health: 56.45±7.14, general health: 66.77±7.91, vitality: 67.60±6.05) (P < 0.05).
Conclusion   The precise cardiopulmonary rehabilitation nursing based on IoT technology can significantly improve patients' pulmonary function, cardiac function indicators, and quality of life. The difference analysis further confirms that the intervention effect is more significant and worthy of promotion and application.