Prediction of pulmonary intensive care unit readmissions with Stability and Workload Index for Transfer score

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dc.contributor.authorErtan, Ozlem
dc.contributor.authorCelik, Deniz
dc.contributor.authorYildiz, Murat
dc.contributor.authorKurt, Hasret Gizem
dc.date.accessioned2026-01-24T12:29:12Z
dc.date.available2026-01-24T12:29:12Z
dc.date.issued2023
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractBACKGROUND AND AIM: Readmission of patients discharged from the intensive care unit (ICU) to the ICU is common and increases mortality. The Stability and Workload Index for Trans-fer (SWIFT) score is a scoring system developed and validated to predict the risk of readmission to the ICU. We evaluated the usability of this scoring system in patients with respiratory failure in a pulmonary intensive care unit (PICU). METHODS: This study was a retrospective cross-sectional study that included patients hospi-talized in the PICU between January 1, 2020, and December 31, 2020. Patients who were dis-charged to the clinic or home and readmitted in the first 7-30 days were included in the study. Patients referred to an upper-level ICU or another hospital and those who died in the hospital were excluded from the study. RESULTS: A total of 442 patients received inpatient treatment during the study period, and 421 patients were included. Eight (1.9%) patients were readmitted within the first 7 days, and 25 (5.9%) patients were readmitted within 7-30 days. There was no significant difference between the SWIFT score, Acute Physiology and Chronic Health Evaluation II (APACHE II), and modified Charlson Comorbidity Index (mCCI) scores of the readmitted patients and those who were not. We calculated the area under the curve value for the SWIFT score as 0.548 (95% CI: 0.440-0.656). CONCLUSIONS: For patients discharged from the PICU, neither the SWIFT score nor APACHE II and mCCI were not sufficient to predict readmission. This study showed that existing scoring systems is insufficient to predict the readmission of patients with respiratory failure, and there is still a need for scoring systems to predict the readmission of these patients.
dc.identifier.doi10.14744/ejp.2022.4001
dc.identifier.endpage106
dc.identifier.issn2148-3620
dc.identifier.issn2148-5402
dc.identifier.issue2
dc.identifier.scopus2-s2.0-105009919563
dc.identifier.scopusqualityN/A
dc.identifier.startpage98
dc.identifier.trdizinid1276075
dc.identifier.urihttps://doi.org/10.14744/ejp.2022.4001
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1276075
dc.identifier.urihttps://hdl.handle.net/20.500.12868/5206
dc.identifier.volume25
dc.identifier.wosWOS:001050294700004
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherKare Publ
dc.relation.ispartofEurasian Journal of Pulmonology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260121
dc.subjectAPACHE II score
dc.subjectintensive care
dc.subjectreadmission
dc.subjectSWIFT score
dc.titlePrediction of pulmonary intensive care unit readmissions with Stability and Workload Index for Transfer score
dc.typeArticle

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