Evidence map›Paper›PMID 42032510›Full record

SynthesisBMC cardiovascular disorders2026

Risk prediction models for postoperative delirium in adult patients undergoing cardiac surgery: a systematic review and meta-analysis.

Boyuan Wang, Wanqiu Du, Haozhou Shen, Jie Sun, Hailong Cao, Zhengli Huang, Xiaoyan Wang

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC cardiovascular disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Boyuan Wang *Interventional Radiology and Vascular Surgery Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Wanqiu Du *Anesthesiology, Surgery and Pain Management Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Haozhou ShenAnesthesiology, Surgery and Pain Management Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Jie SunAnesthesiology, Surgery and Pain Management Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Hailong CaoCardiovascular Surgery Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Zhengli HuangInterventional Radiology and Vascular Surgery Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Xiaoyan WangInterventional Radiology and Vascular Surgery Department, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China. xywang2023@seu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPostoperative delirium (POD), a frequent complication following cardiac surgery, is associated with adverse clinical outcomes. Despite the development of numerous prediction models for estimating the risk of POD, the overall performance and methodological quality of these models are not well understood.

objectiveTo systematically review and meta-analyze the performance of prediction models for postoperative delirium in adult patients undergoing cardiac surgery, with a particular emphasis on model discrimination and the identification of key predictors.

methodsThis study included studies that developed or validated multivariable prediction models for POD in adults undergoing cardiac surgery. Ten databases were searched from inception to July 10, 2025. Data extraction followed a standardized form based on the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist. Risk of bias and applicability were assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was performed using R software.

resultsA total of 22 studies comprising 27 prediction models were included. All studies were rated as having a high risk of bias. The pooled area under the curve for modeling cohorts was 0.821 (95% CI: 0.778–0.858; 95%PI: 0.562–0.943), indicating a robust discrimination despite substantial heterogeneity (I²=96.7%, τ2 = 0.3692). Seven significant predictors were identified, including age, history of cerebrovascular disease, cardiopulmonary bypass time, mechanical ventilation time, American Society of Anesthesiologists classification, operative time, and Acute Physiology and Chronic Health Evaluation II (APACHE II) score.

conclusionAlthough, existing prediction models for POD in patients undergoing cardiac surgery demonstrate promising performance, the evidence is limited by high risk of bias and heterogeneity across studies. There remains a need to improve methodological rigor, such as multicenter prospective studies and external validation. RELEVANCE TO CLINICAL PRACTICE: This systematically review provides a reference for the development and validation of subsequent models for adults undergoing cardiac surgery. Although with modest discrimination, future models should focus on the construction of the preoperative models, which provide more opportunities for early prevention. CLINICAL TRIAL NUMBER: PROSPERO: CRD420251081560.

Indexed as

Cardiac Surgical ProceduresDecision Support TechniquesDeliriumAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPredictive Value of TestsRisk AssessmentRisk FactorsTreatment OutcomeAdultCardiac surgeryDeliriumMeta-analysis

Identifiers

PMID42032510
PMCPMC13255340

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.