Evidence map›Paper›PMID 36836204›Full record

ArticleJournal of clinical medicine2023

Clinical Profile of Patients with Idiopathic Pulmonary Fibrosis in Real Life.

Diego Morena, Jesús Fernández, Carolina Campos, María Castillo, Guillermo López, María Benavent, José Luis Izquierdo

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Observational
  3. Article
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  6. 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

7 authors.

Diego MorenaServicio de Neumología, Hospital Universitario de Guadalajara, 19002 Guadalajara, Spain.
Jesús FernándezServicio de Neumología, Hospital Universitario de Guadalajara, 19002 Guadalajara, Spain.
Carolina CamposServicio de Neumología, Hospital Universitario de Guadalajara, 19002 Guadalajara, Spain.
María CastilloServicio de Neumología, Hospital Universitario de Guadalajara, 19002 Guadalajara, Spain.
Guillermo LópezSAVANA, 28013 Madrid, Spain.
María BenaventSAVANA, 28013 Madrid, Spain.ORCID 0000-0002-9248-748X
José Luis IzquierdoServicio de Neumología, Hospital Universitario de Guadalajara, 19002 Guadalajara, Spain.ORCID 0000-0002-1671-2243

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective of this study is to define the real-life clinical profile and therapeutic management of patients with idiopathic pulmonary fibrosis using artificial intelligence.

methodsWe have conducted an observational, retrospective, non-interventional study using data from the Castilla-La Mancha Regional Healthcare Service (SESCAM) in Spain between January 2012 and December 2020. The Savana Manager 3.0 artificial intelligence platform was used to collect information from electronic medical records by applying natural language processing.

resultsOur study includes 897 subjects whose diagnosis was compatible with idiopathic pulmonary fibrosis; 64.8% were men, with a mean age of 72.9 years (95% CI 71.9-73.8), and 35.2% were women, with a mean age of 76.8 years (95% CI 75.5-78). Patients who had a family history of IPF (98 patients; 12%) were younger and predominantly female (53.1%). Regarding treatment, 45% of patients received antifibrotic therapy. Patients who had undergone lung biopsy, chest CT, or bronchoscopy were younger than the patient population in whom these studies were not completed.

conclusionsThis study has used artificial intelligence techniques to analyze a large population over a 9-year period and determine the situation of IPF in standard clinical practice by identifying the patient clinical profile, use of diagnostic tests and therapeutic management.

Indexed as

artificial intelligenceIPFreal life

Identifiers

PMID36836204
PMCPMC9959732

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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.