Enhancing Surgical Wound Monitoring: A Paired Cohort Study Evaluating a New AI-Based Application for Automatic Detection of Potential Infections

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dc.contributor.author Andrea Craus-Miguel
dc.contributor.author Marc Munar
dc.contributor.author Gabriel Moyà-Alcover
dc.contributor.author Ana María Contreras-Nogales
dc.contributor.author Manuel González-Hidalgo
dc.contributor.author Juan José Segura-Sampedro
dc.date.accessioned 2025-01-29T11:32:06Z
dc.date.available 2025-01-29T11:32:06Z
dc.identifier.citation Craus-Miguel, A., Munar, M., Moyà-Alcover, G., Contreras-Nogales, A. M., González-Hidalgo, M., i Segura-Sampedro, J. J. (2024). Enhancing Surgical Wound Monitoring: A Paired Cohort Study Evaluating a New AI-Based Application for Automatic Detection of Potential Infections. Journal of clinical medicine, 13(24), 7863.https://doi.org/https://doi.org/10.3390/jcm13247863
dc.identifier.uri http://hdl.handle.net/11201/168137
dc.description.abstract [eng]This study assessed the feasibility and security of remote surgical wound monitoring using the RedScar© smartphone app, which employs automated diagnosis for early visual detection of infections without direct healthcare personnel involvement. Additionally, patient satisfaction with telematic care was evaluated as a secondary aim. Surgical site infection (SSI) is the second leading cause of healthcare-associated infections (HAIs), leading to prolonged hospital stays, heightened patient distress, and increased healthcare costs. Methods: The study employed a prospective paired-cohort and single-blinded design, with a sample size of 47 adult patients undergoing abdominal surgery. RedScar© was used for remote telematic monitoring, evaluating the feasibility and security of this approach. A satisfaction questionnaire assessed patient experience. The study protocol was registered at ClinicalTrials.gov under the identifier NCT05485233. <strong>Results:</strong> Out of 47 patients, 41 successfully completed both remote and in-person follow-ups. RedScar© demonstrated a sensitivity of 100% in detecting SSIs, with a specificity of 83.13%. The kappa coefficient of 0.8171 indicated substantial agreement between the application’s results and human observers. Patient satisfaction with telemonitoring was high: 97.6% believed telemonitoring reduces costs, 90.47% perceived it prevents work/school absenteeism, and 80.9% found telemonitoring comfortable. Conclusions: This is the first study to evaluate an automatic smartphone application on real patients for diagnosing postoperative wound infections. It establishes the safety and feasibility of telematic follow-up using the RedScar© application for surgical wound assessment. The high sensitivity suggests its utility in identifying true cases of infection, highlighting its potential role in clinical practice. Future studies are needed to address limitations and validate the efficacy of RedScar© in diverse patient populations.
dc.format application/pdf
dc.relation.ispartof 2024
dc.rights , 2024
dc.subject.classification 61 - Medicina
dc.subject.other 61 - Medical sciences
dc.title Enhancing Surgical Wound Monitoring: A Paired Cohort Study Evaluating a New AI-Based Application for Automatic Detection of Potential Infections
dc.type info:eu-repo/semantics/article
dc.type info:eu-repo/semantics/
dc.date.updated 2025-01-29T11:32:06Z
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.identifier.doi https://doi.org/https://doi.org/10.3390/jcm13247863


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