Evidence mapPaperPMID 40604666Full record

ArticleBMC oral health2025

Development and validation of a nomogram model for predicting postoperative delirium in elderly patients with oral cancer: a retrospective study.

Chen Ying, Liu Xiaona, Zhang Aili, Wang Zengxiang, Wu Ying, Pu Yu, Zhang Hongbo, Wang Danni, Jiang Meiping, Dai Hongyuan

Abstract readValidation Study
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Review
  3. Article
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

10 authors.

Chen Ying *Oral and Maxillofacial Head and Neck Oncology Surgery Ward II, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China. chenyingYZU@163.com.
Liu Xiaona *Department of Nursing, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Zhang AiliOral and Maxillofacial Head and Neck Oncology Surgery Ward II, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Wang ZengxiangDepartment of Nursing, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Wu YingDepartment of Nursing, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Pu YuOral and Maxillofacial Head and Neck Oncology Surgery Ward II, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Zhang HongboOral and Maxillofacial Trauma Orthognathic Plastic Surgery Ward IV, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Wang DanniOral and Maxillofacial Trauma Orthognathic Plastic Surgery Ward IV, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Jiang MeipingOral Anaesthesia Department, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
Dai HongyuanOrthodontic Department, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to develop and internally validate a dynamic a nomogram model by analysing the risk factors for postoperative delirium (POD) in elderly patients with oral cancer.

methodsThis was a single-centre, retrospective study. We used the convenience sampling method to select 359 elderly oral cancer patients from January 2020-August 2023 in Nanjing Stomatological Hospital. The original dataset was randomly divided into a training group (n = 252) and a validation group (n = 107) by a computer-generated random number sequence in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator Regression (LASSO regression) were used to screen the best predictor variables. Logistic regression was used to build the model and visualized by nomogram. The performance of the model was evaluated by area under the curve (AUC), calibration curve and decision curve analysis (DCA).

resultsOur predictive model showed that seven variables, age, sex, alcohol consumption history, marriage, preoperative anxiety, preoperative sleep disorder, and ICU length of stay, were associated with POD. The nomogram showed high predictive accuracy with an AUC of 0.82 (95% CI: 0.76-0.87) for the training group and 0.84 (95% CI: 0.76-0.92) for the internal validation group. In two groups, there was good agreement between the predicted results and the true observations. DCA showed that the predictive model had a good net clinical benefit.

conclusionWe developed a new predictive model to predict risk factors for POD in elderly oral cancer patients. The nomogram can help physicians assess POD quickly and effectively.

Indexed as

DeliriumMouth NeoplasmsNomogramsPostoperative ComplicationsAgedAged, 80 and overAge FactorsFemaleHumansMaleRetrospective StudiesRisk FactorsFree flap reconstructionPredictive modelPreoperative anxietyPreoperative sleep disorderRisk factors

Identifiers

PMID40604666
PMCPMC12220587

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.