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Development and validation of a postoperative delirium prediction model for patients admitted to an intensive care unit in China: a prospective study

Cite this dataset

Xing, Huanmin et al. (2019). Development and validation of a postoperative delirium prediction model for patients admitted to an intensive care unit in China: a prospective study [Dataset]. Dryad. https://doi.org/10.5061/dryad.gb5mkkwk3

Abstract

Objectives: We aimed to develop and validate a postoperative delirium (POD) prediction model for patients admitted to the intensive care unit (ICU).

Design: A prospective study was conducted.

Setting: The study was conducted in the surgical, cardiovascular surgical, and trauma surgical ICUs of an affiliated hospital of a medical university in Heilongjiang Province, China.

Participants: This study included 400 patients (≥18 years old) admitted to the ICU after surgery.

Primary and secondary outcome measures: The primary outcome measure was postoperative delirium assessment during ICU stay.

Results: The model was developed using 300 consecutive ICU patients and was validated using 100 patients from the same ICUs. The model was based on five risk factors: Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity; acid-base disturbance; and history of coma, diabetes, or hypertension. The model had an area under the receiver operating characteristics curve of 0.852 (95% confidence interval: 0.802–0.902), Youden index of 0.5789, sensitivity of 70.73%, and specificity of 87.16%. The Hosmer-Lemeshow goodness of fit was 5.203 (P = 0.736). At a cut-off of 24.5%, the sensitivity and specificity were 71% and 69%, respectively.

Conclusions: The model, which used readily available data, exhibited high predictive value regarding risk of intensive care unit postoperative delirium (ICU-POD) at admission. Use of this model may facilitate better implementation of preventive treatments and nursing measures.