Evidence map›Paper›PMID 40063281›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2025

Predictors of postoperative delirium in patients undergoing radical prostatectomy: a prospective study.

Hao Wang, Jie Chen, Jing Chen, Yanhua Chen, Yinying Qin, Tianxiao Liu, Sining Pan, Yubo Xie

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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Impact of CGA and Surgical Risk Calculator before elective cancer surgery on postoperative delirium in elderly patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Observational
  4. Article
  5. Letter to: Predictors of postoperative delirium in patients undergoing radical prostatectomy: a prospective study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Hao Wang *Department of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Jie Chen *Department of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Jing ChenDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Yanhua ChenDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Yinying QinDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Tianxiao LiuDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Sining PanDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China. 447070480@qq.com.
Yubo XieDepartment of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China. xybdoctor@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnalyze the risk factors for postoperative delirium (POD) in elderly patients undergoing radical prostatectomy, and built a predictive nomogram model for early identification of high-risk individuals.

methodsA total of 156 patients was recruited and categorized based on whether the development of POD within 7 days post-surgery. After identifying independent risk factors through univariate and multivariate logistic regression analyses, predictive models were established. The discrimination and calibration were determined by C-index and calibration curve, with five-fold cross-validation executed. A nomogram model representing the optimal model was constructed based on the results.

resultsPOD occurred in 24 (15.38%) patients. Significant differences were observed in age, anxiety, physical status, sleep disorders, blood glucose, age-adjusted Charlson comorbidity index (ACCI), anticholinergic, blood loss, postoperative infection, and postoperative pain assessed by the numerical rating scale (NRS). Logistic regression analyses showed that sleep disorders (OR:12.931, 95% CI:1.191-140.351, P = 0.035), ACCI (OR:2.608, 95% CI:1.143-5.950, P = 0.023), postoperative infection (OR:19.298, 95% CI:2.53-147.202, P = 0.04), and NRS (OR:4.033, 95% CI:1.062-15.324, P = 0.041) were independent risk factors for POD. Model 1 (postoperative infection, ACCI, preoperative sleep disorder, NRS) showed better diagnostic performance than the others, of which the area under the curve (AUC) was 0.973. The best diagnostic performance was found in model 1 through five-fold cross-validation, with a C-index of 0.963.

conclusionsThis prospective cohort study highlighted that ACCI, preoperative sleep disorder, postoperative pain, and postoperative infection were identified as independent risk factors for POD. Furthermore, the nomogram derived from model 1 proved to be effective in predicting POD in elderly patients undergoing radical prostatectomy.

Indexed as

DeliriumPostoperative ComplicationsProstatectomyProstatic NeoplasmsAgedAged, 80 and overAge FactorsHumansLogistic ModelsMaleMiddle AgedNomogramsProspective StudiesRisk FactorsSleep Wake DisordersElderly patientsNomogramPostoperative deliriumProstate cancerRisk factors

Identifiers

PMID40063281

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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.