Machine learning to develop a predictive model of pressure injury in persons with spinal cord injury
Luther S, Thomason S, Sabharwal S, Finch D, McCart J, Toyinbo P, Bouayad L, Lapcevic W, Hahm B, Hauser R, Matheny M, Powell-Cope G. Machine learning to develop a predictive model of pressure injury in persons with spinal cord injury. Spinal Cord 2023, 61: 513-520. PMID: 37598263, DOI: 10.1038/s41393-023-00924-z.Peer-Reviewed Original ResearchMeSH KeywordsCohort StudiesHumansMachine LearningPressure UlcerRetrospective StudiesSpinal Cord DiseasesSpinal Cord InjuriesConceptsPressure injuriesAmerican Spinal Cord Injury Association Impairment ScaleSCI/D CentersSpinal cord injury/diseaseReceiver-operating curve analysisNew pressure injuryModifiable risk factorsElectronic health record dataSCI/DSpinal cord injuryHealth record dataInjury/diseaseTwo-step logistic regressionLogistic regression modelsCohort studyRegression modelsStudy designACord injurySevere gradesRisk factorsImpairment ScaleHigh riskClinical implicationsTotal daysAnnual exam