Evidence map›Paper›PMID 38882972›Full record

ReviewCureus2024

Phenotype to Treatable Traits-Based Management in Chronic Obstructive Pulmonary Disease.

Ankit Kumar, Surya Kant, Vijeta Niranjan

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Ankit KumarRespiratory Medicine, King George's Medical University, Lucknow, IND.
Surya KantRespiratory Medicine, King George's Medical University, Lucknow, IND.
Vijeta NiranjanPathology, T.S. Misra Medical College and Hospital, Lucknow, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic obstructive pulmonary disease (COPD), a heterogeneous respiratory disease driven by various genetic and environmental factors, presents significant challenges in diagnosis and management. Traditional approaches focused on phenotypic classification, but recent paradigms emphasize identifying and addressing treatable traits to personalize treatment strategies. Treatable traits facilitate personalized interventions, optimizing symptom control, and reducing exacerbation risk. Dyspnea and exacerbations, recognized as key traits, guide treatment decisions and follow-up management. Various interventions, including bronchodilators, corticosteroids, and lifestyle modifications, target specific traits like airway inflammation, mucus overproduction, and emphysema. Strategies for assessing and addressing treatable traits during initial encounters and follow-up visits enhance disease monitoring and treatment efficacy. Comprehensive trait assessment demands resources and specialized monitoring, posing barriers to widespread implementation. The lack of standardized protocols and evolving evidence further complicates decision-making and clinical practice. Despite these challenges, the shift toward treatable traits-based management signifies a pivotal advancement in COPD care, emphasizing holistic approaches tailored to individual patient needs. Recognizing and addressing treatable traits offers personalized interventions, enhancing symptom control and disease management. Embracing treatable traits-based approaches holds promise for improving clinical outcomes and enhancing the quality of life for individuals living with COPD.

Indexed as

bronchiectasischronic bronchitiscopd (chronic obstructive pulmonary disease)dyspneaemphysemaexpectorationfixed airflow limitationpulmonary exacerbationtreatable trait

Identifiers

PMID38882972
PMCPMC11179745

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.