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Derivation and validation of a prediction rule for sedative-associated delirium during acute respiratory failure
Niall T Prendergast1, Chukwudi A Onyemekwu2, Kelly M Toth2
1Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine in the Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Objective:
To derive and validate a simple, transparent model that quantifies risk for sedative-associated delirium in mechanically ventilated ICU patients, which could be used to guide decisions about personalized sedation.
Design:
We performed backward stepwise logistic regression to derive a model predictive of sedative-associated delirium. We validated this model internally using hundredfold bootstrapping. We then validated this model externally in a separate prospective cohort of mechanically ventilated ICU patients.
Setting:
Five US hospitals, including one academic, one private, and three veterans hospitals.
Patients:
The parent cohort consisted of 1040 patients with either septic or cardiogenic shock, acute respiratory failure, or both. From the parent cohort 836 patients who received mechanical ventilation were selected to comprise the derivation cohort.
Interventions:
None.
Measurements And Main Results:
Backwards stepwise regression produced a model with age, BMI, sepsis, SOFA, malignancy, COPD, sex, and doses of opioids, propofol, and benzodiazepines as predictors of sedative-associated delirium. The model had very good discriminative power, with an area under the receiver-operator curve (AUROC) of 0.83. Internal validation via bootstrapping showed preserved discriminatory function with an AUROC of 0.81 and graphical evidence of good calibration. External validation in a separate set of 340 patients showed good discrimination, with AUROC of 0.70.
Conclusions:
Risk for sedative-associated delirium during acute respiratory failure requiring mechanical ventilation can be quantified using a simple, transparent model, which can now be validated in a prospective study.
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