Development of an Instrument for Preoperative Prediction of Adverse Discharge in Patients Scheduled for Cardiac Surgery
| Autor: | Maximilian Hammer, Sankalp Sehgal, Stephanie D. Grabitz, Andre F. Gosling, Feroze Mahmood, Matthias Eikermann, Kadhiresan R. Murugappan, Anastasia D. Katsiampoura, Luca J Wachtendorf, Kamal R. Khabbaz |
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| Rok vydání: | 2021 |
| Předmět: |
Adult
medicine.medical_specialty Medizin Psychological intervention 030204 cardiovascular system & hematology Logistic regression 03 medical and health sciences 0302 clinical medicine 030202 anesthesiology medicine Humans Cardiac Surgical Procedures Retrospective Studies Skilled Nursing Facilities business.industry Incidence (epidemiology) Reproducibility of Results Retrospective cohort study Length of Stay Patient Discharge Confidence interval Cardiac surgery Anesthesiology and Pain Medicine Brier score Emergency medicine Cohort Female Cardiology and Cardiovascular Medicine business |
| Zdroj: | Journal of Cardiothoracic and Vascular Anesthesia. 35:482-489 |
| ISSN: | 1053-0770 |
| Popis: | Objective 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. Design 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. Setting University hospital network. Participants Adult patients living at home prior to surgery, who underwent coronary artery bypass grafting and/or valve procedures at the authors’ institution. Interventions None. Measurements and Main Results 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. Conclusions 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. |
| Databáze: | OpenAIRE |
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