Preventing postoperative moderate- and high-risk pressure injuries with artificial intelligence-powered smart decompression mattress on in middle-aged and elderly patients: a retrospective cohort analysis

• Published in: British journal of hospital medicine (London, England : 2005) Vol. 85; no. 8; p. 1
• Main Authors: Yang, Feiying, Chen, Huiying, Shan, Yajuan, Che, Liping, Tang, Qi, Hu, Fanglin
• Format: Journal Article
• Language: English
• Published: England 30.08.2024
• Subjects: Aged; Artificial Intelligence; Beds; Decompression - methods; Female; Humans; Male; Middle Aged; Postoperative Complications - epidemiology; Postoperative Complications - prevention & control; Pressure Ulcer - epidemiology; Pressure Ulcer - etiology; Pressure Ulcer - prevention & control; Retrospective Studies; Smart decompression mattress; Artificial intelligence cloud platform; Risk of occurrence; Pressure injury
• ISSN: 1750-8460
• DOI: 10.12968/hmed.2024.0112

Artificial intelligence technology has attained rapid development in recent years. The integration of artificial intelligence applications into pressure reduction mattresses, giving rise to artificial intelligence-powered pressure reduction mattresses, is expected to provide personalised intelligent pressure reduction solutions, through automatic user's data-based adjustment of the patient's local pressure condition to prevent pressure injury. The purpose of this study was to investigate the effectiveness of artificial intelligence-powered smart decompression in the prevention of postoperative medium- and high-risk pressure injury in middle-aged and elderly patients. A total of 400 middle-aged and elderly patients admitted to our hospital from June 2021 to December 2023 were selected as study subjects. Patients were categorised into observation and control groups according to the medical record system. General demographic data of the patients were collected. The propensity score matching method was used to balance the baseline data of the two groups of patients. The incidence, severity, complications and sleep quality in the matched study subjects were also compared. After matching, there were 96 patients in the two groups, and the differences in baseline data between the two groups were not statistically significant. Pressure injury and the total incidence of complications in the observation group were significantly lower than those in the control group ( < 0.05). Before treatment, there was no difference in the scores of all aspects of the Richards Campbell Sleep Questionnaire between the two groups ( > 0.05). After treatment, the scores of all aspects of Richards Campbell Sleep Questionnaire in the observation group were significantly lower than those in the control group ( < 0.05). The artificial intelligence-powered smart decompression mattress can significantly prevent moderate- and high-risk pressure injury, effectively reducing the incidence of pressure injury and complications in postoperative long-term bedridden patients, alleviating the severity of pressure injury, relieving the pressure on various parts, and improving the sleep quality of patients.