2019
DOI: 10.1016/j.surg.2018.06.053
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Predicting ICU readmission among surgical ICU patients: Development and validation of a clinical nomogram

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Cited by 17 publications
(31 citation statements)
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“…There is a problem associated with patients being readmitted to the intensive care unit (ICU) following transfer from the ICU to the medical floor. Hospitals rely on quality metrics to address many aspects of patient care; one of those metrics is the unplanned ICU readmission within 72 hours of transfer [1]. ICU readmission or bounce backs are associated with worse outcomes for the patient and increased resource utilization [2].…”
Section: Introductionmentioning
confidence: 99%
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“…There is a problem associated with patients being readmitted to the intensive care unit (ICU) following transfer from the ICU to the medical floor. Hospitals rely on quality metrics to address many aspects of patient care; one of those metrics is the unplanned ICU readmission within 72 hours of transfer [1]. ICU readmission or bounce backs are associated with worse outcomes for the patient and increased resource utilization [2].…”
Section: Introductionmentioning
confidence: 99%
“…Among the most common reasons for readmissions were pneumonia and respiratory failure [18,19]. Although primary reasons for readmission to the ICU have been established within the medical critical care population, the reasons have not clearly been delineated for the surgical population [1]. This problem has been identified at the national level [1,5] and at the local level as well.…”
Section: Introductionmentioning
confidence: 99%
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“…Many variables have been identified as potential risk factors predisposing to ICU bounceback. These include Glasgow Coma Score <9, 4 increasing age, 8,9,13,14,17,19,21,22,24,25,[30][31][32] male gender, 4,12,[18][19][20] and existence of concurrent comorbidities. 4,7,21 Initial ICU length of stay is also a risk factor for ICU bounceback.…”
mentioning
confidence: 99%
“…14 A nomogram is a line chart that depicts scales for variable (risk of readmission) involved in a particular formula in such a way that corresponding values for each variable (respiratory rate, blood urea nitrogen, age, serum glucose, sodium chloride, history of atrial fibrillation, history of renal insufficiency) lie in a straight line intersecting all of the scales. 14,46 Risk factors of bounceback were identified with points assigned to each predictor variable to graphically assess overall risk. Although general details of various strategies introduced to combat ICU readmissions have been described, no conclusive evidence has yet materialized regarding best practices to lower bounceback rates.…”
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confidence: 99%