Evidence map›Paper›PMID 29225786›Full record

ReviewF1000Research2017

Recent advances in managing idiopathic pulmonary fibrosis.

Chiara Scelfo, Antonella Caminati, Sergio Harari

Abstract readReview
In one paragraph

Review in F1000Research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Comorbidities in idiopathic pulmonary fibrosis: an underestimated issue.European respiratory review : an official journal of the European Respiratory Society · 2019
    Review
  10. 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

3 authors.

Chiara ScelfoUnità Operativa di Pneumologia e Terapia Semi-Intensiva Respiratoria, Servizio di Fisiopatologia Respiratoria ed Emodinamica Polmonare, Ospedale San Giuseppe, Multimedica IRCCS, Milan, Italy.
Antonella CaminatiUnità Operativa di Pneumologia e Terapia Semi-Intensiva Respiratoria, Servizio di Fisiopatologia Respiratoria ed Emodinamica Polmonare, Ospedale San Giuseppe, Multimedica IRCCS, Milan, Italy.ORCID https://orcid.org/0000-0002-6414-3460
Sergio HarariUnità Operativa di Pneumologia e Terapia Semi-Intensiva Respiratoria, Servizio di Fisiopatologia Respiratoria ed Emodinamica Polmonare, Ospedale San Giuseppe, Multimedica IRCCS, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Idiopathic pulmonary fibrosis (IPF) is a rare pulmonary disease with a poor prognosis and severe impact on quality of life. Early diagnosis is still challenging and important delays are registered before final diagnosis can be reached. Available tools fail to predict the variable course of the disease and to evaluate response to antifibrotic drugs. Despite the recent approval of pirfenidone and nintedanib, significant challenges remain to improve prognosis and quality of life. It is hoped that the new insights gained in pathobiology in the last few years will lead to further advances in the diagnosis and management of IPF. Currently, early diagnosis and prompt initiation of treatments reducing lung function loss offer the best hope for improved outcomes. This article aims at providing an overview of recent advances in managing patients with IPF and has a particular focus on how to reach a diagnosis, manage comorbidities and lung transplantation, care for the non-pharmacological needs of patients, and address palliative care.

Indexed as

idiopathic pulmonary fibrosisnintedanibpathogenesispirfenidone

Identifiers

PMID29225786
PMCPMC5710314

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.