Evidence map›Paper›PMID 37901722›Full record

ArticleWorld journal of gastrointestinal surgery2023

Prediction model of stress ulcer after laparoscopic surgery for colorectal cancer established by machine learning algorithm.

Dong-Mei Yu, Chun-Xiao Wu, Jun-Yi Sun, Hui Xue, Zhe Yuwen, Jiang-Xue Feng

Open access · diamondAbstract read
In one paragraph

Article in World journal of gastrointestinal surgery, 2023. 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
0.2field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

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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

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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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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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 at 2 institutions in 1 country.

Dong-Mei YuSchool of Nursing, Hebei University of Traditional Chinese Medicine, Shijiazhuang 050000, Hebei Province, China.
Chun-Xiao WuDepartment I of Anorectal, Hebei Traditional Chinese Medicine Hospital, Shijiazhuang 050000, Hebei Province, China.
Jun-Yi SunDepartment of Inspection Center, Hebei Traditional Chinese Medicine Hospital, Shijiazhuang 050000, Hebei Province, China.
Hui XueSchool of Nursing, Hebei University of Traditional Chinese Medicine, Shijiazhuang 050000, Hebei Province, China.
Zhe YuwenDepartment of Perivascular, Hebei Traditional Chinese Medicine Hospital, Shijiazhuang 050000, Hebei Province, China.
Jiang-Xue FengDepartment I of Anorectal, Hebei Traditional Chinese Medicine Hospital, Shijiazhuang 050000, Hebei Province, China. fengjiangxue0330@163.com.
Hospital of Hebei Province · CNHebei University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with colorectal cancer (CRC) are prone to stress ulcer after laparoscopic surgery. The analysis of risk factors for stress ulcer (SU) in patients with CRC is important to reduce mortality and improve patient prognosis.

aimTo identify risk factors for SU after laparoscopic surgery for CRC, and develop a nomogram model to predict the risk of SU in these patients. METHODSThe clinical data of 135 patients with CRC who underwent laparoscopic surgery between November 2021 and June 2022 were reviewed retrospectively. They were divided into two categories depending on the presence of SUs: The SU group (

resultsAmong the 135 patients with CRC, 23 patients had postoperative SU, with an incidence of 17.04%. The SU group had higher levels of heat shock protein (HSP) 70, HSP90, and gastrin (GAS) than the non-SU group. Age, lymph node metastasis, HSP70, HSP90, and GAS levels were statistically different between the two groups, but other indicators were not statistically different. Logistic regression analysis showed that age ≥ 65 years, lymph node metastasis, and increased levels of HSP70, HSP90 and GAS were all risk factors for postoperative SU in patients with CRC (

conclusionPatients with CRC aged ≥ 65 years, with lymph node metastasis and elevated HSP70, HSP90, GAS levels, are prone to post-laparoscopic surgery SU. Our nomogram model shows good predictive value.

Indexed as

Colorectal cancerLaparoscopeNomogramRisk factorsStress ulcer

Identifiers

PMID37901722
PMCPMC10600766
OpenAlexW4386921909

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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.