Prediction models for postoperative delirium after cardiac surgery: Systematic review and critical appraisal

Shining Cai; Jingjing Li; Jian Gao; Wenyan Pan; Yuxia Zhang

doi:10.1016/j.ijnurstu.2022.104340

Prediction models for postoperative delirium after cardiac surgery: Systematic review and critical appraisal

Int J Nurs Stud. 2022 Dec:136:104340. doi: 10.1016/j.ijnurstu.2022.104340. Epub 2022 Aug 6.

Authors

Shining Cai¹, Jingjing Li¹, Jian Gao², Wenyan Pan³, Yuxia Zhang⁴

Affiliations

¹ Department of Nursing, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China; The Centre for Critical Care Zhongshan Hospital: A Joanna Briggs Institute Center of Excellence, China.
² Center of Clinical Epidemiology and Evidence-based Medicine, Fudan University, Shanghai 200032, China; Department of Nutrition, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
³ Department of Nursing, Zhongshan Hospital, Fudan University, Shanghai 200032, China; The Centre for Critical Care Zhongshan Hospital: A Joanna Briggs Institute Center of Excellence, China. Electronic address: pan.wenyan@zs-hospital.sh.cn.
⁴ Department of Nursing, Zhongshan Hospital, Fudan University, Shanghai 200032, China; The Centre for Critical Care Zhongshan Hospital: A Joanna Briggs Institute Center of Excellence, China. Electronic address: zhang.yuxia@zs-hospital.sh.cn.

PMID: 36208541
DOI: 10.1016/j.ijnurstu.2022.104340

Abstract

Background: Many studies have developed or validated prediction models to estimate the risk of delirium after cardiac surgery, but the quality of the model development and model applicability remain unknown.

Objectives: To systematically review and critically evaluate currently available prediction models for delirium after cardiac surgery.

Data sources: PubMed, EMBASE, and MEDLINE were systematically searched. This systematic review was registered in PROSPERO (Registration ID: CRD42021251226).

Study selection: Prospective or retrospective cohort studies were considered eligible if they developed or validated prediction models or scoring systems for delirium in the ICU. We included studies involving adults (age ≥18 years) undergoing cardiac surgery and excluded studies that did not validate a prediction model.

Data extraction: Data extraction was independently performed by two authors using a standardized data extraction form based on the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies checklist. Quality of the models was assessed with the Prediction Model Risk of Bias Assessment Tool (PROBAST).

Data synthesis: Of 5469 screened studies, 13 studies described 10 prediction models. The postoperative delirium incidence varied from 11.3 % to 51.6 %. The most frequently used predictors were age and cognitive impairment. The reported areas under the curve or C-statistics were between of 0.74 and 0.91 in the derivation set. The reported AUCs in the external validation set were between 0.54 and 0.90. All the studies had a high risk of bias, mainly owing to poor reporting of the outcome domain and analysis domain; 10 studies were of high concern regarding applicability.

Conclusions: The current models for predicting postoperative delirium in the ICU after cardiac surgery had a high risk of bias according to the PROBAST. Future studies should focus on improving current prediction models or developing new models with rigorous methodology.

Keywords: Cardiac surgery; Intensive care unit; Postoperative delirium; Prediction model.

Publication types

Review
Systematic Review

MeSH terms

Adolescent
Adult
Cardiac Surgical Procedures* / adverse effects
Delirium* / etiology
Humans
Prospective Studies
Retrospective Studies