A Tool to Predict Readmission to the Intensive Care Unit in Surgical Critical Care Patients-The RISC Score.

anemia fluid balance functional mobility hyperglycemia readmission to the intensive care unit score development surgical intensive care unit

Journal

Journal of intensive care medicine
ISSN: 1525-1489
Titre abrégé: J Intensive Care Med
Pays: United States
ID NLM: 8610344

Informations de publication

Date de publication:
Nov 2021
Historique:
pubmed: 26 8 2020
medline: 8 10 2021
entrez: 26 8 2020
Statut: ppublish

Résumé

Readmission to the Intensive Care Unit (ICU) is associated with a high risk of in-hospital mortality and higher health care costs. Previously published tools to predict ICU readmission in surgical ICU patients have important limitations that restrict their clinical implementation. We sought to develop a clinically intuitive score that can be implemented to predict readmission to the ICU after surgery or trauma. We designed the score to emphasize modifiable predictors. In this retrospective cohort study, we included surgical patients requiring critical care between June 2015 and January 2019 at Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA. We used logistic regression to fit a prognostic model for ICU readmission from a priori defined, widely available candidate predictors. The score performance was compared with existing prediction instruments. Of 7,126 patients, 168 (2.4%) were readmitted to the ICU during the same hospitalization. The final score included 8 variables addressing demographical factors, surgical factors, physiological parameters, ICU treatment and the acuity of illness. The maximum score achievable was 13 points. Potentially modifiable predictors included the inability to ambulate at ICU discharge, substantial positive fluid balance (>5 liters), severe anemia (hemoglobin <7 mg/dl), hyperglycemia (>180 mg/dl), and long ICU length of stay (>5 days). The score yielded an area under the receiver operating characteristic curve of 0.78 (95% CI 0.74-0.82) and significantly outperformed previously published scores. The performance of the underlying model was confirmed by leave-one-out cross-validation. The RISC-score is a clinically intuitive prediction instrument that helps identify surgical ICU patients at high risk for ICU readmission. The simplicity of the score facilitates its clinical implementation across surgical divisions.

Sections du résumé

BACKGROUND BACKGROUND
Readmission to the Intensive Care Unit (ICU) is associated with a high risk of in-hospital mortality and higher health care costs. Previously published tools to predict ICU readmission in surgical ICU patients have important limitations that restrict their clinical implementation. We sought to develop a clinically intuitive score that can be implemented to predict readmission to the ICU after surgery or trauma. We designed the score to emphasize modifiable predictors.
METHODS METHODS
In this retrospective cohort study, we included surgical patients requiring critical care between June 2015 and January 2019 at Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA. We used logistic regression to fit a prognostic model for ICU readmission from a priori defined, widely available candidate predictors. The score performance was compared with existing prediction instruments.
RESULTS RESULTS
Of 7,126 patients, 168 (2.4%) were readmitted to the ICU during the same hospitalization. The final score included 8 variables addressing demographical factors, surgical factors, physiological parameters, ICU treatment and the acuity of illness. The maximum score achievable was 13 points. Potentially modifiable predictors included the inability to ambulate at ICU discharge, substantial positive fluid balance (>5 liters), severe anemia (hemoglobin <7 mg/dl), hyperglycemia (>180 mg/dl), and long ICU length of stay (>5 days). The score yielded an area under the receiver operating characteristic curve of 0.78 (95% CI 0.74-0.82) and significantly outperformed previously published scores. The performance of the underlying model was confirmed by leave-one-out cross-validation.
CONCLUSION CONCLUSIONS
The RISC-score is a clinically intuitive prediction instrument that helps identify surgical ICU patients at high risk for ICU readmission. The simplicity of the score facilitates its clinical implementation across surgical divisions.

Identifiants

pubmed: 32840427
doi: 10.1177/0885066620949164
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1296-1304

Auteurs

Maximilian Hammer (M)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Stephanie D Grabitz (SD)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Bijan Teja (B)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Karuna Wongtangman (K)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Marjorie Serrano (M)

Cardiovascular Intensive Care Unit, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Sara Neves (S)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Shahla Siddiqui (S)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Xinling Xu (X)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

Matthias Eikermann (M)

Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 1811Harvard Medical School, Boston, MA, USA.

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Classifications MeSH