Evidence map›Paper›PMID 39685810›Full record

ReviewJournal of clinical medicine2024

Interstitial Lung Disease Epidemiology in the Past Three Decades: A Narrative Review.

Francesco Puppo, Roberto G Carbone

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2024. 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. COVID-19 and Interstitial Lung Disease.Medicina (Kaunas, Lithuania) · 2025
    Review
  3. Article
  4. Review
  5. Article
  6. 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

2 authors.

Francesco PuppoDepartment of Internal Medicine, University of Genoa, 16132 Genoa, Italy.ORCID 0000-0002-5393-0071
Roberto G CarboneDepartment of Internal Medicine, University of Genoa, 16132 Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current epidemiological data on interstitial lung disease (ILD) are still poor. The principal cause of the discordant data is associated with a heterogeneous group of respiratory diseases that includes a large number, about 200 families, with low frequency, distinct and sometimes unknown etiology, and different progression. In fact, some conditions spontaneously resolve, whereas others, such as IPF and most non-IPF ILDs, progress to respiratory failure and death despite treatment. Furthermore, epidemiological data are limited. The scope of the narrative review is to report ILD incidence and prevalence in registries from different countries in the last three decades. We identified 20 ILD registries (17 prospective and 3 retrospective) from major countries in Europe (n = 10), Asia (n = 7), North America (n = 2), and Oceania (n = 1). Significant discrepancies in ILD and ILD subtype prevalence and incidence among countries are reported in registries. These discrepancies could be determined by different ethnicities and socioeconomic conditions as well as by updates in disease diagnosis and classification. ILD epidemiological registries are progressively ameliorating through better adherence to updated guidelines and classification codes. An accurate and definite diagnosis and compilation of ILD epidemiological registries will be useful for a more precise monitoring of disease progression and treatment. Future research to identify the populations with the highest risk factors, including genetic and molecular studies, and implementation of disease progression scores are needed to improve ILD clinical assessment.

Indexed as

epidemiologyincidenceinterstitial lung diseaseprevalenceregistries

Identifiers

PMID39685810
PMCPMC11641969

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.