Evidence map›Paper›PMID 39272015›Full record

ArticleBMC surgery2024

Predictive factors for intrathoracic anastomotic leakage and postoperative mortality after esophageal cancer resection.

Jian Zhu, Tianxiao Tao, Gengxin Zhang, Shenhui Dai

Abstract read
In one paragraph

Article in BMC surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

4 authors.

Jian ZhuCardiothoracic Surgery Department, the first Affiliated Hospital of Anhui University of Science & Technology (Huainan First People's Hospital), Huainan, 232001, Anhui Province, China.
Tianxiao TaoCardiothoracic Surgery Department, the first Affiliated Hospital of Anhui University of Science & Technology (Huainan First People's Hospital), Huainan, 232001, Anhui Province, China.
Gengxin ZhangCardiothoracic Surgery Department, the first Affiliated Hospital of Anhui University of Science & Technology (Huainan First People's Hospital), Huainan, 232001, Anhui Province, China.
Shenhui DaiCardiothoracic Surgery Department, the first Affiliated Hospital of Anhui University of Science & Technology (Huainan First People's Hospital), Huainan, 232001, Anhui Province, China. 2427112534@qq.com.

Funding

Science Plan Project of Huainan City 2021175
6 · The paper itself

Abstract

backgroundEsophageal cancer is currently one of the high-risk malignant tumors worldwide, posing a serious threat to human health. This study aimed to analyse the causes of postoperative mortality and intrathoracic anastomotic leakage(IAL) after esophagectomy.

methodsA retrospective analysis was conducted on 172 patients with esophageal cancer resection and focused on the preoperative and postoperative indicators. Cox regression analysis was performed to identify factors affected IAL and evaluated the potential factors on postoperative mortality. The Kaplan-Meier curve was applied to evaluate the effect of leakage on postoperative mortality after propensity score matching.

resultsUnivariable and multivariable Cox regression analysis showed that infection and high BMI were significant risk factors for IAL, patients with BMI over 24 kg/m

conclusionIAL was a significant cause of death in patients underwent esophageal cancer resection. Patients with high BMI over 24 kg/m

Indexed as

Anastomotic LeakEsophageal NeoplasmsEsophagectomyAgedChinaEsophagusFemaleHumansMaleMiddle AgedProportional Hazards ModelsRetrospective StudiesRisk FactorsAnastomotic leakageEsophagectmyMortalityRisk factors

Identifiers

PMID39272015
PMCPMC11395224

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.