Risk prediction models for delirium in the intensive care unit after cardiac surgery: a systematic review and independent external validation
| Autor: | Gavin M. Joynt, Chun Hung Chiu, Anna Lee, Jing Lan Mu, Veronica Ka Wai Lai, Malcolm J. Underwood, Tony Gin |
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| Rok vydání: | 2016 |
| Předmět: |
medicine.medical_specialty
Calibration (statistics) Risk prediction models law.invention Decision Support Techniques 03 medical and health sciences 0302 clinical medicine law Risk Factors Linear regression medicine Humans 030212 general & internal medicine Cardiac Surgical Procedures Prospective cohort study Intensive care medicine APACHE business.industry External validation Delirium Reproducibility of Results 030208 emergency & critical care medicine Length of Stay Intensive care unit Cardiac surgery Intensive Care Units Anesthesiology and Pain Medicine Hong Kong medicine.symptom business |
| Zdroj: | British journal of anaesthesia. 118(3) |
| ISSN: | 1471-6771 |
| Popis: | Numerous risk prediction models are available for predicting delirium after cardiac surgery, but few have been directly compared with one another or been validated in an independent data set. We conducted a systematic review to identify validated risk prediction models of delirium (using the Confusion Assessment Method-Intensive Care Unit tool) after cardiac surgery and assessed the transportability of the risk prediction models on a prospective cohort of 600 consecutive patients undergoing cardiac surgery at a university hospital in Hong Kong from July 2013 to July 2015. The discrimination (c-statistic), calibration (GiViTI calibration belt), and clinical usefulness (decision curve analysis) of the risk prediction models were examined in a stepwise manner. Three published high-quality intensive care unit delirium risk prediction models (n=5939) were identified: Katznelson, the original PRE-DELIRIC, and the international recalibrated PRE-DELIRIC model. Delirium occurred in 83 patients (13.8%, 95% CI: 11.2-16.9%). After updating the intercept and regression coefficients in the Katznelson model, there was fair discrimination (0.62, 95% CI: 0.58-0.66) and good calibration. As the original PRE-DELIRIC model was already validated externally and recalibrated in six countries, we performed a logistic calibration on the recalibrated model and found acceptable discrimination (0.75, 95% CI: 0.72-0.79) and good calibration. Decision curve analysis demonstrated that the recalibrated PRE-DELIRIC risk model was marginally more clinically useful than the Katznelson model. Current models predict delirium risk in the intensive care unit after cardiac surgery with only fair to moderate accuracy and are insufficient for routine clinical use. |
| Databáze: | OpenAIRE |
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