Evidence map›Paper›PMID 37046562›Full record

ArticleDiagnostics (Basel, Switzerland)2023

The Role of Multidimensional Indices for Mortality Prediction in Chronic Obstructive Pulmonary Disease.

Stanislav Kotlyarov

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. The Disproportionate Burden of Cardiovascular Disease in Mild-to-Moderate COPD.International journal of chronic obstructive pulmonary disease · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Observational
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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

1 author at 1 institution in 1 country.

Stanislav KotlyarovDepartment of Nursing, Ryazan State Medical University, 390026 Ryazan, Russia.ORCID 0000-0002-7083-2692
Ryazan State Medical University named after Academician I.P. Pavlov · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: Chronic obstructive pulmonary disease (COPD) is one of the most important respiratory diseases. It is characterised by a progressive course with individual differences in clinical presentation and prognosis. The use of multidimensional indices such as the BODE, eBODE, BODEX, CODEX, ADO, and Charlson Comorbidity Index has been proposed to predict the survival rate of COPD patients. However, there is limited research on the prognostic significance of these indices in predicting long-term survival rates in patients with COPD. The aim of this prospective cohort study was to investigate the prognostic value of the BODE, eBODE, BODEX, CODEX, ADO, COTE and Charlson Comorbidity Index in predicting 5- and 10-year survival in patients with COPD. (2) Methods: A total of 170 patients were included in the study and their clinical and functional characteristics of COPD progression, such as dyspnoea, body mass index and spirometry data, were evaluated. A Kaplan-Meier survival analysis was used to calculate 5- and 10-year survival rates. The predictive value of each index was assessed using Cox proportional hazards regression models. (3) Results: The 5-year survival rate was 62.35% and the 10-year survival rate was 34.70%. The BODE, eBODE, BODEX, CODEX, ADO, COTE and Charlson Comorbidity Index were all significantly associated with the 10-year survival rate of COPD patients (

Indexed as

ADOBODEBODEXCharlson Comorbidity IndexCODEXCOPDCOTEeBODEprognosissurvival

Identifiers

PMID37046562
PMCPMC10093710
OpenAlexW4362638015

What OpenQuestion holds

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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.