Evidence map›Paper›PMID 33485347›Full record

ArticleWorld journal of surgical oncology2021

Preoperative Controlling Nutritional Status (CONUT) score predicts short-term outcomes of patients with gastric cancer after laparoscopy-assisted radical gastrectomy.

Yun Qian, Huaying Liu, Junhai Pan, Weihua Yu, Jiemin Lv, Jiafei Yan, Jiaqi Gao, Xianfa Wang, Xiaolong Ge, Wei Zhou

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
3.8field-weighted citation impact, top 6% 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

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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 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

10 authors at 2 institutions in 1 country.

Yun Qian *Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Huaying Liu *Department of Medicine, GuangXi Medical College, Nanning, China.
Junhai PanDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Weihua YuDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Jiemin LvDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Jiafei YanDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Jiaqi GaoDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Xianfa WangDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China. 3195011@zju.edu.cn.
Xiaolong GeDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China. gxlmed@zju.edu.cn.ORCID http://orcid.org/0000-0002-7396-1174
Wei ZhouDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, China.
Sir Run Run Shaw Hospital · CNGuangxi Medical University · CN

Funding

Natural Science Foundation of Zhejiang Province 2017C33159
6 · The paper itself

Abstract

backgroundAn emerging prediction tool, the Controlling Nutritional Status (CONUT) score, has shown good assessment ability of postoperative outcomes in cancer patients. This study evaluated the role of the preoperative CONUT score regarding the short-term outcomes of gastric cancer (GC) after laparoscopic gastrectomy.

methodsThree hundred and nine GC patients undergoing laparoscopic gastrectomy from January 2016 to June 2019 were analysed, retrospectively. The patients were divided into two groups according to the CONUT optimal cut-off value. Clinical characteristics and postoperative complications in the two groups were analysed and evaluated. Risk factors for complications were identified by univariate and multivariate analyses.

resultsA total of 309 patients underwent laparoscopic gastrectomy; 91 (29.4%) patients experienced postoperative complications. The preoperative CONUT score showed a good predictive ability for postoperative complications (area under the curve (AUC) = 0.718, Youden index = 0.343) compared with other indices, with an optimal cut-off value of 2.5. Patients with high CONUT score had a significantly higher incidence of overall complications (P < 0.001). Age, haemoglobin, C-reactive protein, red blood cell levels, CONUT scores, surgical procedure type, T1, T4, N0 and N3 pathological TNM classification, and pathological stages of I and III were associated with postoperative complications (P < 0.05). Furthermore, the preoperative CONUT score was identified as an independent risk predictor of postoperative complications (P = 0.012; OR = 2.433; 95% CI, 1.218-4.862) after multivariate analysis.

conclusionsThe preoperative CONUT score is a practical nutritional assessment for predicting short-term outcomes in GC patients after laparoscopy-assisted gastrectomy.

Indexed as

LaparoscopyStomach NeoplasmsGastrectomyHumansNutritional StatusPrognosisRetrospective StudiesControlling Nutritional Status scoreGastric cancerLaparoscopic surgeryPostoperative complications

Identifiers

PMID33485347
PMCPMC7827975
OpenAlexW3107292414

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.