Evidence map›Paper›PMID 28442016›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2017

[Analysis of Postoperative Complications and Risk Factors of Patients with Lung Cancer through Clavien-Dindo Classification].

Pengfei Li, Yutian Lai, Kun Zhou, Guowei Che

Abstract read
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

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0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. [Establishment and Optimization of Enhanced Recovery after Surgery System 
for Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2017
    Review
  11. [Enhanced Lung Recovery after Surgery, Is It A Necessary for Precision Therapy?]Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2017
    Review
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.

Pengfei LiDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu 610041, China.
Yutian LaiDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu 610041, China.
Kun ZhouDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu 610041, China.
Guowei CheDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu 610041, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPostoperative complications (PCs) are contributing factors to patient mortality following lung resection. In this retrospective study, the Clavien-Dindo classification was used to analyze the current incidence of PCs and identify the risk factors of different grades of PCs.

methodsA total of 966 lung cancer patients who underwent lobectomy in our department between June 2013 and December 2014 were retrospectively enrolled. Patients were divided into two groups depending on the occurrence of PCs. The PCs were classified into four grades through the Clavien-Dindo classification, and the related risk factors of different grades were evaluated.

resultsApproximately 15.0% (145/966) of patients had PC (total incidence: 39.3%, 380/966). Among the 380 cases with PCs, the proportions of Clavien-Dindo grade I, grade II, grade III and grade IV or above complications were 6.8%, 75.3%, 15.0% and 2.9%, respectively. Binary Logistic regressions showed that preoperative forced expiratory volume in one second (FEV1), diffusion capacity for carbon monoxide of the lung (single breath)(DLco SB), and preoperative combined chronic obstructive pulmonary disease were the significant independent factors for PCs. FEV1 in preoperative pulmonary function was the significant risk factor for complications at Clavien-Dindo grade I, grade II, grade III, and above.

conclusionsClavien-Dindo grade II complications are the most common complications within 30 days after lung cancer lobectomy. FEV1 is closely related to the occurrence of PCs and may potentially be one of the practical variables to assess the risk of occurrence of PCs.

Indexed as

AgedChinaFemaleHumansLogistic ModelsLungLung NeoplasmsMaleMiddle AgedNeoplasm StagingPostoperative ComplicationsRetrospective Studies

Identifiers

PMID28442016
PMCPMC5999680

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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.