Evidence map›Paper›PMID 39994560›Full record

ArticleBMC gastroenterology2025

A validation study of three early warning scores in early identification of gastric cancer patients with deteriorating condition after gastrectomy.

Xinli Shi, Huijuan Jie, Naifa Li, Qiongshan Liu, Yue Wang, Changquan Wu, Wenwen Jiang, Bolin Zhang, Shurong Lai, Honglu Xu

Abstract readValidation Study
In one paragraph

Article in BMC gastroenterology, 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

10 authors.

Xinli Shi *Department of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Huijuan Jie *Department of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Naifa Li *Department of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Qiongshan LiuDepartment of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Yue WangDepartment of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Changquan WuDepartment of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Wenwen JiangDepartment of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China.
Bolin Zhang *Department of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China. burningjump@gmail.com.
Shurong Lai *Department of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangdong, 510080, China. laishr@mail.sysu.edu.cn.
Honglu XuDepartment of Nursing, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, China. xuhonglu@sysush.com.

Funding

Nursing Research Fund of the Seventh Affiliated Hospital of Sun Yat-sen University ZSQYHLKYJJ202001
6 · The paper itself

Abstract

objectivesEarly warning scores (EWS) aim to rapidly identify patients at risk of critical illness or life-threatening events before deterioration occurs in clinical settings. This study aims to validate the ability of three commonly used early warning scores, namely the National Early Warning Score (NEWS), the Early Warning Score (SEWS), and the Modified Early Warning Score (MEWS), to identify patients with deterioration after gastric cancer resection in general wards.

methodsThis retrospective case-control study included 110 patients who experienced clinical deterioration after gastrectomy for gastric cancer as case group, and 745 patients without deterioration as control group from a tertiary hospital in Guangdong Province, China. The discriminating ability (receiver operating characteristic curves), calibration (goodness-of-fit test) and net benefit (clinical decision curves) of the three EWS (NEWS, SEWS, MEWS) were explored to compare their early warning performance for patients at risk of post-operative deterioration.

resultsMEWS (goodness-of-fit p = 0.123 > 0.05) and SEWS (goodness-of-fit p = 0.235 > 0.05) both demonstrate good calibration and good discrimination ability (AUC 0.710, 95% CI 0.654-0.766;AUC 0.756, 95% CI 0.701-0.811). In contrast, NEWS not only has good calibration (goodness-of-fit p = 0.283 > 0.05) but also exhibits the best discrimination ability among the three scoring systems (AUC 0.835, 95% CI 0.785-0.884) and the highest net benefit.

conclusionOverall, NEWS may be more suitable for identifying gastric cancer patients at risk of post-operative clinical deterioration, as the early warning scoring model with best performance currently for post-gastrectomy observation.

Indexed as

Clinical DeteriorationEarly Warning ScoreGastrectomyPostoperative ComplicationsStomach NeoplasmsAgedCase-Control StudiesChinaFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentROC CurveComplicationsEarly warning scoresGastric cancerPostoperative

Identifiers

PMID39994560
PMCPMC11849142

What OpenQuestion 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 OpenQuestion graph.