Evidence map›Paper›PMID 32431495›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2020

Identification of Patient Profiles with High Risk of Hospital Re-Admissions for Acute COPD Exacerbations (AECOPD) in France Using a Machine Learning Model.

Arnaud Cavailles, Boris Melloni, Stéphane Motola, Florent Dayde, Marie Laurent, Katell Le Lay, Didier Caumette, Laura Luciani, Pierre Louis Lleu, Geoffrey Berthon and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Economic Burden of Uncontrolled COPD Under Triple Therapy: A Population-Based Study.International journal of chronic obstructive pulmonary disease · 2025
    Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. The Association with COPD Readmission Rate and Access to Medical Institutions in Elderly Patients.International journal of chronic obstructive pulmonary disease · 2021
    Article
  15. Review
  16. Remote Patient Monitoring for the Detection of COPD Exacerbations.International journal of chronic obstructive pulmonary disease · 2020
    Article
  17. Article
  18. 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

11 authors at 4 institutions in 1 country.

Arnaud CavaillesService de Pneumologie, Institut du Thorax, CHU de Nantes, Nantes, France.
Boris MelloniService de Pneumologie, CHU Dupuytren, Limoges, France.
Stéphane MotolaHEVA, Lyon, France.
Florent DaydeHEVA, Lyon, France.ORCID 0000-0002-9805-5864
Marie LaurentHEVA, Lyon, France.ORCID 0000-0003-4971-3784
Katell Le LayHEOR/RWE, Boehringer Ingelheim, Paris, France.
Didier CaumetteInstitutional and Hospital Partnership, Boehringer Ingelheim, Paris, France.
Laura LucianiHEOR/RWE, Boehringer Ingelheim, Paris, France.
Pierre Louis LleuMedical Affairs, Boehringer Ingelheim, Paris, France.
Geoffrey BerthonCHRU Tours, Tours, France.
Thomas FlamentService de Pneumologie, CHRU Bretonneau, Tours, France.
Boehringer Ingelheim (France) · FRCentre Hospitalier Universitaire de Tours · FRCentre Hospitalier Universitaire de Nantes · FRHôpital Dupuytren · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To characterise patients with chronic obstructive pulmonary disease (COPD) who are rehospitalised for an acute exacerbation, to estimate the cost of these hospitalisations, to characterise high risk patient sub groups and to identify factors potentially associated with the risk of rehospitalisation. Patients and Methods: This was a retrospective study using the French National Hospital Discharge Database. All patients aged ≥40 years hospitalised for an acute exacerbation of COPD between 2015 and 2016 were identified and followed for six months. Patients with at least one rehospitalisation for acute exacerbation of COPD constituted the rehospitalisation analysis population. A machine learning model was built to study the factors associated with the risk of rehospitalisation using decision tree analysis. A direct cost analysis was performed from the perspective of national health insurance. Results: A total of 143,006 eligible patients were hospitalised for an acute exacerbation of COPD (AECOPD) in 2015-2016 (mean age: 74 years; 62.1% men). 25,090 (18.8%) were rehospitalised for another exacerbation within six months. In this study, 8.5% of patients died during or immediately following the index hospitalisation and 10.5% died during or immediately after rehospitalisation ( Conclusion: Rehospitalisations for acute exacerbations of COPD carry a high epidemiological and economic burden. Since hospitalisation for an acute exacerbation is the most important determinant of future rehospitalisations, management of COPD needs to focus on interventions aimed at decreasing the rehospitalisation risk of in order to lower the burden of disease.

Indexed as

Patient ReadmissionPulmonary Disease, Chronic ObstructiveAgedDisease ProgressionFemaleFranceHospitalizationHospitalsHumansMachine LearningMaleRetrospective Studiescomorbiditycostdecision tree analysisrehospitalisation

Identifiers

PMID32431495
PMCPMC7198446
OpenAlexW3022044608

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.