Evidence map›Paper›PMID 34831485›Full record

SynthesisCells2021

Treatable Traits in Chronic Respiratory Disease: A Comprehensive Review.

Yong Qin Lee, Asvin Selvakumar, Kay Choong See

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

9 citing papers in PubMed, 10 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Yong Qin LeeYong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore.
Asvin SelvakumarYong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore.
Kay Choong SeeYong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore.ORCID 0000-0003-2528-7282
National University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic respiratory diseases are major contributors to the global burden of disease. While understanding of these diseases has improved, treatment guidelines have continued to rely on severity and exacerbation-based approaches. A new personalised approach, termed the "treatable traits" approach, has been suggested to address the limitations of the existing treatment strategies. We aim to systematically review the current evidence regarding treatable traits in chronic respiratory diseases and to identify gaps in the current literature. We searched the PubMed and Embase databases and included studies on treatable traits and chronic respiratory diseases. We then extracted information on prevalence, prognostic implications, treatment options and benefits from these studies. A total of 58 papers was included for review. The traits identified were grouped into five broad themes: physiological, biochemical, psychosocial, microbiological, and comorbidity traits. Studies have shown advantages of the treatable traits paradigm in the clinical setting. However, few randomised controlled trials have been conducted. Findings from our review suggest that multidisciplinary management with therapies targeted at treatable traits has the potential to be efficacious when added to the best practices currently implemented. This paradigm has the potential to improve the holistic care of chronic respiratory diseases.

Indexed as

Quantitative Trait, HeritableAnimalsChronic DiseaseComorbidityHumansRespiratory Tract Diseaseschronic respiratory diseasemultidisciplinarypersonalised medicinetreatable trait

Identifiers

PMID34831485
PMCPMC8624727
OpenAlexW3216328680

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.