Evidence map›Paper›PMID 31469745›Full record

ArticleAnnals of surgery2021

Readmission After Lobectomy for Lung Cancer: Not All Complications Contribute Equally.

Lisa M Brown, Dylan P Thibault, Andrzej S Kosinski, David T Cooke, Mark W Onaitis, Henning A Gaissert, Patrick S Romano

Open access · greenAbstract read
In one paragraph

Article in Annals of surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
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  3. Nonagenarians: Outcomes after lung cancer surgery.Lung cancer (Amsterdam, Netherlands) · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 7 institutions in 1 country.

Lisa M BrownSection of General Thoracic Surgery, University of California Davis Health, Sacramento, CA.
Dylan P ThibaultDuke Clinical Research Institute, Duke University, Durham, NC.
Andrzej S KosinskiDuke Clinical Research Institute, Duke University, Durham, NC.
David T CookeSection of General Thoracic Surgery, University of California Davis Health, Sacramento, CA.
Mark W OnaitisDivision of Cardiovascular and Thoracic Surgery, University of California San Diego Medical Center, San Diego, CA.
Henning A GaissertDivision of Thoracic Surgery, Massachusetts General Hospital, Boston, MA.
Patrick S RomanoCenter for Healthcare Policy and Research, University of California Davis Health, Sacramento, CA.
Center For Policy Research · USClinical Research Institute · USDuke University · USMassachusetts General Hospital · USUC Davis Health System · USUniversity of California, Davis · USUniversity of California San Diego Medical Center · US

Funding

UC Davis Clinical and Translational Science CenterUL1TR001860 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KENYON, NICHOLAS J., LYLES, COURTNEY REES · 2016 to 2025
$47.3M
Institutional Career Development Core (KL2)KL2TR001859 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI HOLMES, JAMES F. · 2016 to 2025
$10.1M
NCATS NIH HHS KL2 TR001859NCATS NIH HHS UL1 TR001860
6 · The paper itself

Abstract

objectiveThe aim of this study was to identify independent predictors of hospital readmission for patients undergoing lobectomy for lung cancer. SUMMARY BACKGROUND DATA: Hospital readmission after lobectomy is associated with increased mortality. Greater than 80% of the variability associated with readmission after surgery is at the patient level. This underscores the importance of using a data source that includes detailed clinical information.

methodsUsing the Society of Thoracic Surgeons (STS) General Thoracic Surgery Database (GTSD), we conducted a retrospective cohort study of patients undergoing elective lobectomy for lung cancer. Three separate multivariable logistic regression models were generated: the first included preoperative variables, the second added intraoperative variables, and the third added postoperative variables. The c statistic was calculated for each model.

resultsThere were 39,734 patients from 277 centers. The 30-day readmission rate was 8.2% (n = 3237). In the final model, postoperative complications had the greatest effect on readmission. Pulmonary embolus {odds ratio [OR] 12.34 [95% confidence interval (CI),7.94-19.18]} and empyema, [OR 11.66 (95% CI, 7.31-18.63)] were associated with the greatest odds of readmission, followed by pleural effusion [OR 7.52 (95% CI, 6.01-9.41)], pneumothorax [OR 5.08 (95% CI, 4.16-6.20)], central neurologic event [OR 3.67 (95% CI, 2.23-6.04)], pneumonia [OR 3.13 (95% CI, 2.43-4.05)], and myocardial infarction [OR 3.16 (95% CI, 1.71-5.82)]. The c statistic for the final model was 0.736.

conclusionsComplications are the main driver of readmission after lobectomy for lung cancer. The highest risk was related to postoperative events requiring a procedure or medical therapy necessitating inpatient care.

Indexed as

PneumonectomyAdultAgedDatabases, FactualFemaleHumansLogistic ModelsLung NeoplasmsMaleMiddle AgedPatient ReadmissionPerioperative PeriodPostoperative ComplicationsRetrospective StudiesRisk Factors

Identifiers

PMID31469745
PMCPMC11292111
OpenAlexW2970916906

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.