Development of an early prediction model for postoperative delirium in neurosurgical patients admitted to the ICU after elective craniotomy (E-PREPOD-NS): A secondary analysis of a prospective cohort study. (August 2021)

• Record Type: Journal Article
• Authors: Huang, Hua-Wei; Zhang, Guo-Bin; Li, Hao-Yi; Wang, Chun-Mei; Wang, Yu-Mei; Sun, Xiu-Mei; Chen, Jing-Ran; Chen, Guang-Qiang; Xu, Ming; Zhou, Jian-Xin
• Is Part Of: Journal of clinical neuroscience. Volume 90(2021)
• Page Start: 217
• Page End: 224
• Publication Date: 2021-08
• Subjects: Postoperative delirium -- Neurosurgical patients -- Intracranial surgery -- Risk prediction model -- Intensive care unit; Brain -- Surgery -- Periodicals; Neurosciences -- Periodicals; Nervous system -- Surgery -- Periodicals; Brain -- surgery -- Periodicals; Neurosurgical Procedures -- Periodicals; Neurosciences -- Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.jocn.2021.06.004
• Languages: English
• ISSNs: 0967-5868

Abstract

Highlights: The risk model for POD is specific to neurosurgical patients. The model enrolled predictors available at intensive care unit admission. The POD model enrolled 9 factors for neurosurgical patients admitted to the ICU. Abstract: Postoperative delirium (POD) is a significant clinical problem in neurosurgical patients after intracranial surgery. Identification of high-risk patients may optimize perioperative management, but an adequate risk model for use at early phase after operation has not been developed. In the secondary analysis of a prospective cohort study, 800 adult patients admitted to the ICU after elective intracranial surgeries were included. The POD was diagnosed as Confusion Assessment Method for the ICU positive on postoperative day 1 to 3. Multivariate logistic regression analysis was used to develop early prediction model (E-PREPOD-NS) and the final model was validated with 200 bootstrap samples. The incidence of POD in this cohort was19.6%. We identified nine variables independently associated with POD in the final model: advanced age (OR 3.336, CI 1.765–6.305, 1 point), low education level (OR 2.528, 1.446–4.419, 1), smoking history (OR 2.582, 1.611–4.140, 1), diabetes (OR 2.541, 1.201–5.377, 1), supra-tentorial lesions (OR 3.424, 2.021–5.802, 1), anesthesia duration > 360 min (OR 1.686, 1.062–2.674, 0.5), GCS < 9 at ICU admission (OR 6.059, 3.789–9.690, 1.5), metabolic acidosis (OR 13.903, 6.248–30.938, 2.5), and neurosurgical drainage tube (OR 1.924, 1.132–3.269, 0.5). The area under the receiver operator curve (AUROC) of the risk score for prediction of POD was 0.865 (95% CI 0.835–0.895). The AUROC was 0.851 after internal validation (95% CI 0.791–0.912). The model showed good calibration. The E-PREPOD-NS model can predict POD in patients admitted to the ICU after elective intracranial surgery with good accuracy. External validation is needed in the future.