A Systematic Review on Prediction Models for Postoperative Delirium in Non-cardiac Surgery Patients
Asha Khatib Iddi
School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China and Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Chernor Sulaiman Bah
School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China and Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Bongani Mbambara
School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China and Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Yanna Si
Department of Anesthesiology, Perioperative and Pain Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Kaizong Huang *
Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Jianjun Zou *
School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China and Department of Pharmacy, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
*Author to whom correspondence should be addressed.
Abstract
Introduction: Numerous risk prediction models (RPMs) for postoperative delirium (POD) following non-cardiac surgery have been developed and validated recently. However, the robustness and applicability of these models require further investigation.
Methods: Using PRISMA-2020 guidelines and PROBAST checklist, studies on POD RPMs in non-cardiac surgery patients were searched from PubMed and Google Scholar from January 2021 to December 2023. Inclusion criteria were: (a) adults (aged ≥18 years), (b) non-cardiac surgery patients, (c) development and/or validation of delirium RPMs, and (d) full papers in English. Exclusion criteria were studies not meeting these inclusion parameters.
Results: Twelve studies included non-cardiac surgery patients with varying rates of POD (3.22% to 38.30%). The Confusion Assessment Method (CAM) was commonly used for assessing POD risk, with logistic regression being the most employed prediction model. Predictors often found were age, intraoperative blood loss, albumin levels, anesthesia duration, and ICU stays. Internal validation was done in 75% of all the models included. The area under the curve (AUC) ranged from 0.68 to 0.94 for internal validation and from 0.630 to 0.880 for external validation sets. Additionally, most of the models showed a minimal risk of bias (83.3%) and were considered to have a low concern regarding their applicability (75%).
Conclusion: Based on this review, current RPMs for POD among non-cardiac surgery patients exhibit high accuracy, low risk of bias, and minimal concerns regarding their applicability. We recommend that future research prioritize the external validation of existing models to improve their clinical utility.
Keywords: Non-cardiac surgery, postoperative delirium, risk predictive models, systemic review