Application of the WeChat Platform to Implement Continuous Nursing for Patients After Percutaneous Coronary Intervention.
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| Abstract |
BACKGROUND Percutaneous coronary intervention (PCI) is an effective treatment for coronary heart disease. However, a lack of cardiac rehabilitation and continuous nursing management leads to repeated patient hospitalizations. Long-term systematic rehabilitation and nursing management after discharge are key to ensuring quality of treatment and patient quality of life. This study aimed to explore the application of the WeChat platform in continuous nursing after PCI. MATERIAL AND METHODS This was a retrospective case-control study. The clinical data of 63 patients in our cardiac center who underwent PCI between June 2017 and January 2018 were recorded. Patients were divided into 2 groups: the continuous nursing through the WeChat platform (intervention) group and the conventional nursing (control) group. The Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), and Seattle Angina Questionnaire (SAQ) were used as the evaluation tools. RESULTS The SAQ scores in all 5 SAQ dimensions in the continuous nursing group were significantly higher than those of the control group at the 1-year follow-up. Scores on the SAS and SDS scales at 1-year follow-up were significantly better in the intervention group than in the control group. The SAS and SDS scores in both groups were better at the 1-year follow-up, but the difference was statistically significant in the continuous nursing group and not in the control group. CONCLUSIONS Using the WeChat platform can make continuous nursing more convenient and effective for patients after PCI. It may reduce the occurrence of complications, relieve patient depression and anxiety, and improve patient quality of life.
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| Authors | Sheng-Huo Zhou, Shu-Ting Huang, Ning Xu, Liang-Wang Chen, Qiang Chen |
| Journal | Medical science monitor : international medical journal of experimental and clinical research (Med Sci Monit) Vol. 26 Pg. e925444 (Dec 29 2020) ISSN: 1643-3750 [Electronic] United States |
| PMID | 33372172 (Publication Type: Journal Article) |
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