Evidence map›Paper›PMID 29147917›Full record

ReviewGeneral thoracic and cardiovascular surgery2018

Recommendations for perioperative management of lung cancer patients with comorbidities.

Hiroyoshi Tsubochi, Tomoki Shibano, Shunsuke Endo

Open access · hybridAbstract readReview
In one paragraph

Review in General thoracic and cardiovascular surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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.

Hiroyoshi TsubochiDepartment of Thoracic Surgery, Jichi Medical University, Tochigi, Japan.
Tomoki ShibanoDepartment of Thoracic Surgery, Jichi Medical University, Tochigi, Japan.
Shunsuke EndoDepartment of Thoracic Surgery, Jichi Medical University, Tochigi, Japan. tcvshun@jichi.ac.jp.
Jichi Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo improve surgical outcomes, clinicians must provide optimal perioperative care for comorbidities identified as significant factors in risk models for patients undergoing lung cancer surgery.

methodsWe reviewed trends in perioperative care for idiopathic pulmonary fibrosis, cardiovascular diseases, and end-stage renal diseases in patients undergoing lung cancer surgery, as large clinical databases indicate that these comorbidities are significant risk factors for lung cancer surgery. Articles identified by keyword searches were included in the analysis.

resultsSignificant predictive factors for acute exacerbation of idiopathic pulmonary fibrosis were identified. However, no effective perioperative care was identified for prevention of acute exacerbation of interstitial pneumonia. The timing of coronary revascularization and antithrombotic management for cardiovascular diseases are subjects of ongoing research, and acid-base balance is essential in the management of hemodialysis patients with end-stage renal diseases.

conclusionsTo improve surgical outcomes for lung cancer patients, future studies should continue to study optimal perioperative management of comorbidities.

Indexed as

Cardiovascular DiseasesComorbidityHumansIdiopathic Pulmonary FibrosisKidney Failure, ChronicLung NeoplasmsPerioperative CarePneumonectomyRisk FactorsCardiovascular disordersEnd-stage renal diseaseIdiopathic pulmonary fibrosisLung cancerPulmonary resection

Identifiers

PMID29147917
PMCPMC5794844
OpenAlexW2768859308

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.