Evidence map›Paper›PMID 38111768›Full record

ArticleWorld journal of gastrointestinal surgery2023

Nomogram for predicting early complications after distal gastrectomy.

Biao Zhang, Qing Zhu, Zhi-Peng Ji

Open access · diamondAbstract read
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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. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 20% of its field
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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 4 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Biao ZhangDepartment of Gastrointestinal Surgery, Second Hospital of Shandong University, Jinan 250033, Shandong Province, China.
Qing ZhuDepartment of Gastrointestinal Surgery, Second Hospital of Shandong University, Jinan 250033, Shandong Province, China.
Zhi-Peng JiDepartment of Gastrointestinal Surgery, Second Hospital of Shandong University, Jinan 250033, Shandong Province, China. 17660081217@163.com.
Second Hospital of Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReducing or preventing postoperative morbidity in patients with gastric cancer (GC) is particularly important in perioperative treatment plans.

aimTo identify risk factors for early postoperative complications of GC post-distal gastrectomy and to establish a nomogram prediction model.

methodsThis retrospective study included 131 patients with GC who underwent distal gastrectomy at the Second Hospital of Shandong University between January 2019 and February 2023. The factors influencing the development of complications after distal gastrectomy in these patients were evaluated using univariate and multivariate logistic regression analysis. Based on the results obtained, a predictive nomogram was established. The nomogram was validated using internal and external (

resultsMultivariate logistic regression analysis showed that hypertension, diabetes, history of abdominal surgery, and perioperative blood transfusion were independent predictors of postoperative complications of distal gastrectomy. The modeling and validation sets showed that the area under the curve was 0.843 [95% confidence interval (CI): 0.746-0.940] and 0.877 (95%CI: 0.719-1.000), the sensitivity was 0.762 and 0.778, respectively, and the specificity was 0.809 and 0.944, respectively, indicating that the model had good sensitivity and specificity. The C-indexes of the modeling and validation datasets were 0.843 (95%CI: 0.746-0.940) and 0.877 (95%CI: 0.719-1.000), respectively. The calibration curve (Hosmer Lemeshow test:

conclusionThe nomogram prediction model based on independent risk factors related to postoperative complications of distal gastrectomy can facilitate perioperative intervention for high-risk populations and reduce the incidence of postoperative complications.

Indexed as

Blood transfusionGastroenterostomyNomogramsPostoperative complicationsRisk factorsStomach neoplasms

Identifiers

PMID38111768
PMCPMC10725534
OpenAlexW4389010774

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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.