Evidence map›Paper›PMID 40691668›Full record

ArticleEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2025

Validation of the Oklahoma predictor model for discharge destination in patients with major traumatic injury: a cross-sectional study.

Aaron Alvarado, Vivian Nguyen, Bradley Cox, Ali Esparham, Michael Charles, Nasir Mushtaq, Geoffrey Chow, Zhamak Khorgami

Abstract readValidation Study
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In one paragraph

Article in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Aaron AlvaradoDepartment of Surgery, University of Oklahoma School of Community Medicine - Tulsa, 4444 41st St, Suite #1700, Tulsa, OK, 74135, USA.
Vivian NguyenDepartment of Surgery, University of Oklahoma School of Community Medicine - Tulsa, 4444 41st St, Suite #1700, Tulsa, OK, 74135, USA.
Bradley CoxDepartment of Surgery, University of Oklahoma School of Community Medicine - Tulsa, 4444 41st St, Suite #1700, Tulsa, OK, 74135, USA.
Ali EsparhamSchool of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Michael CharlesTrauma Services, Ascension St. John Medical Center, Tulsa, OK, USA.
Nasir MushtaqDepartment of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma, Tulsa, OK, USA.
Geoffrey ChowDepartment of Surgery, University of Oklahoma School of Community Medicine - Tulsa, 4444 41st St, Suite #1700, Tulsa, OK, 74135, USA.
Zhamak KhorgamiDepartment of Surgery, University of Oklahoma School of Community Medicine - Tulsa, 4444 41st St, Suite #1700, Tulsa, OK, 74135, USA. zhamak-khorgami@ouhsc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeProtracted in-patient stays affect trauma patient costs and hospital resource utilizations. Proper discharge placement stratification may help with early discharge planning in this group of patients. No standardized discharge destination prediction model exists. A scoring model has been developed after examining Oklahoma Trauma Database discharge destination predictors. This study's goal was patient data-driven model validation.

methodsLevel II trauma center patient data over three months, including comorbidities, injuries, and demographics were analyzed. We compared the scoring model discharge destination prediction with actual destinations.

resultsThe study included 459 patients, with 108 facility discharges. The scoring model demonstrated significant facility placement prediction (Scores ≤ 7: 11.94% or Negative Predictive Value of 88.1%; Score 8-14: 47.22% as Positive Predictive Value: and Score ≥ 15: 60.00%). Scoring 8-14 showed a 6.60-fold (95%CI: 4.11, 10.61) increase compared to ≤ 7. Scoring ≥ 15 was 11.07 times (95%CI: 1.79, 68.42) more likely than ≤ 7.

conclusionThe Oklahoma Trauma Discharge Predictive Scoring Model demonstrated significant facility discharge prediction and may assist with decreasing delay of anticipated patient discharge destination.

Indexed as

Patient DischargeWounds and InjuriesAdultAgedCross-Sectional StudiesFemaleHumansInjury Severity ScoreLength of StayMaleMiddle AgedOklahomaTrauma CentersDischarge dispositionPredictorsTraumaValidation

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.