Development of an Instrument for Preoperative Prediction of Adverse Discharge in Patients Scheduled for Cardiac Surgery.


Journal

Journal of cardiothoracic and vascular anesthesia
ISSN: 1532-8422
Titre abrégé: J Cardiothorac Vasc Anesth
Pays: United States
ID NLM: 9110208

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 03 07 2020
revised: 10 08 2020
accepted: 11 08 2020
pubmed: 8 9 2020
medline: 20 5 2021
entrez: 7 9 2020
Statut: ppublish

Résumé

Inability of home discharge occurs in nearly a third of patients undergoing cardiac surgery and is associated with increased mortality. The authors aimed to evaluate the incidence and risk factors for adverse discharge disposition (ADD) after cardiac surgery and develop a prediction tool for preoperative risk assessment. This retrospective cohort study included adult patients undergoing cardiac surgery between 2010 and 2018. The primary outcome was ADD, defined as in-hospital mortality, discharge to a skilled nursing facility, or transfer to a long-term care hospital. The authors created a prediction tool using stepwise backward logistic regression and used 5-fold and leave-one-out cross-validation. University hospital network. Adult patients living at home prior to surgery, who underwent coronary artery bypass grafting and/or valve procedures at the authors' institution. None. A total of 3,760 patients were included in the final study cohort. The observed rate of ADD was 33.3%. The prediction model showed good discrimination and accuracy, with C-statistic of 0.78 (95% confidence interval [CI] 0.76-0.79) and unmodified Brier score of 0.177 (reliability 0.001). The final model comprised 14 predictors. Patients who experienced ADD were more likely to be older, of female sex, to have had higher length of hospital stay prior to surgery, and to have undergone emergency surgery. The authors present an instrument for prediction of loss of the ability to live independently in patients undergoing cardiac surgery. The authors' score may be useful in identifying high-risk patients such that earlier coordination of care can be initiated in this vulnerable patient population.

Identifiants

pubmed: 32893054
pii: S1053-0770(20)30822-3
doi: 10.1053/j.jvca.2020.08.028
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

482-489

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Andre F Gosling (AF)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Maximilian Hammer (M)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Stephanie Grabitz (S)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Luca J Wachtendorf (LJ)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Anastasia Katsiampoura (A)

Department of Anesthesiology, Critical Care and Pain Medicine, St. Elizabeth's Medical Center, Tufts Medical School, Brighton, MA.

Kadhiresan R Murugappan (KR)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Sankalp Sehgal (S)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Kamal R Khabbaz (KR)

Department of Surgery, Division of Cardiothoracic Surgery, Beth Israel Deaconess Medical Center, Boston, MA.

Feroze Mahmood (F)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Matthias Eikermann (M)

Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Universitaet Duisburg Essen, Medizinische Fakultaet, Essen, Germany. Electronic address: meikerma@bidmc.harvard.edu.

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