Evidence map›Paper›PMID 41195068›Full record

ArticleFrontiers in nutrition2025

The predictive value comparison of the different nutritional assessment tools for postoperative delirium in elderly patients after non-cardiac surgery.

Xuzhou Dang, Yefang Yang, Yu Liang, Yuting Liu, Wenjie Zhang, Xuesen Su

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Xuzhou DangThe College of Anesthesia, Shanxi Medical University, Taiyuan, Shanxi, China.
Yefang YangDepartment of Anesthesiology, Datong Third People's Hospital, Datong, Shanxi, China.
Yu LiangThe College of Anesthesia, Shanxi Medical University, Taiyuan, Shanxi, China.
Yuting LiuThe College of Anesthesia, Shanxi Medical University, Taiyuan, Shanxi, China.
Wenjie ZhangDepartment of Anesthesiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Xuesen SuThe Anesthesiology Department of Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, Shanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to evaluate and compare the predictive performance of various nutritional assessment tools. Methods: This prospective observational study enrolled 315 elderly patients (≥65 years) scheduled for non-cardiac surgery at Shanxi Medical University First Hospital between March and May 2025. Preoperative data collected included demographics, laboratory indices, Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), and Mini Nutritional Assessment (MNA). Postoperative delirium (POD) was diagnosed daily during the 7 days postoperatively using the 3-Minute Diagnostic Confusion Assessment Method (3D-CAM). Patients were stratified into Delirium ( Results: MNA and PNI scores were significantly lower in the delirium group compared to the non-delirium group ( Conclusion: MNA is the most effective standalone nutritional tool for predicting POD in elderly non-cardiac surgery patients. A combined model incorporating age, CRP, and MNA score (AUC = 0.810) shows higher accuracy and improved clinical usefulness for preoperative risk stratification. This allows targeted interventions for high-risk individuals.

Indexed as

C-reactive protein (CRP)elderlyMini nutritional assessment (MNA)non-cardiac surgerynutritional assessmentpostoperative deliriumpredictive model

Identifiers

PMID41195068
PMCPMC12584556

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.