Literature DB >> 23711267

Surgical intensive care unit admission variables predict subsequent readmission.

Matthew E Lissauer1, Jose J Diaz, Mayur Narayan, Paulesh K Shah, Nader N Hanna.   

Abstract

Intensive care unit (ICU) readmissions are associated with increased resource use. Defining predictors may improve resource use. Surgical ICU patients requiring readmission will have different characteristics than those who do not. We conducted a retrospective cohort study of a prospectively maintained database. The Acute Physiology and Chronic Health Evaluation (APACHE) IV quality database identified patients admitted January 1 through December 31, 2011. Patients were divided into groups: NREA = patients admitted to the ICU, discharged, and not readmitted versus REA = patients admitted to the ICU, discharged, and readmitted. Comparisons were made at index admission, not readmission. Categorical variables were compared by Fisher's exact testing and continuous variables by t test. Multivariate logistic regression identified independent predictors of readmission. There were 765 admissions. Seventy-seven patients required readmission 94 times (12.8% rate). Sixty-two patients died on initial ICU admission. Admission severity of illness was significantly higher (APACHE III score: 69.54 ± 21.11 vs 54.88 ± 23.48) in the REA group. Discharge acute physiology scores were equal between groups (47.0 ± 39.2 vs 44.2 ± 34.0, P = nonsignificant). In multivariate analysis, REA patients were more likely admitted to emergency surgery (odds ratio, 1.9; 95% confidence interval, 1.01 ± 3.5) more likely to have a history of immunosuppression (2.7, 1.4 ± 5.3) or higher Acute Physiology Score (1.02; 1.0 ± 1.03) than NREA. Patients who require ICU readmission have a different admission profile than those who do not "bounce back." Understanding these differences may allow for quality improvement projects such as instituting different discharge criteria for different patient populations.

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Year:  2013        PMID: 23711267

Source DB:  PubMed          Journal:  Am Surg        ISSN: 0003-1348            Impact factor:   0.688


  5 in total

1.  The effects of data sources, cohort selection, and outcome definition on a predictive model of risk of thirty-day hospital readmissions.

Authors:  Colin Walsh; George Hripcsak
Journal:  J Biomed Inform       Date:  2014-08-23       Impact factor: 6.317

Review 2.  Association of severity of illness and intensive care unit readmission: A systematic review.

Authors:  Evan G Wong; Ann M Parker; Doris G Leung; Emily P Brigham; Alicia I Arbaje
Journal:  Heart Lung       Date:  2016 Jan-Feb       Impact factor: 2.210

3.  Utilizing a transfer of care bundle to reduce unplanned readmissions to the cardiac intensive care unit.

Authors:  Jean Storey; Jonathan W Byrnes; Jeffrey Anderson; James Brown; Katherine Clarke-Myers; Melissa Kimball; Candice Meyer; Laurie Mustin; Gina Schoenling; Nicolas Madsen
Journal:  BMJ Qual Saf       Date:  2017-07-08       Impact factor: 7.035

4.  The Modified Early Warning Score as a Predictive Tool During Unplanned Surgical Intensive Care Unit Admission.

Authors:  Annandita Kumar; Hussam Ghabra; Fiona Winterbottom; Michael Townsend; Philip Boysen; Bobby D Nossaman
Journal:  Ochsner J       Date:  2020

5.  Association between the Predicted Value of APACHE IV Scores and Intensive Care Unit Mortality: A Secondary Analysis Based on EICU Dataset.

Authors:  Yuan Xu; Sheng Chao; Yulin Niu
Journal:  Comput Math Methods Med       Date:  2022-04-06       Impact factor: 2.238

  5 in total

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