Evidence map›Paper›PMID 38668299›Full record

ArticlePathogens (Basel, Switzerland)2024

Trends in Non-Tuberculous Mycobacterial Lung Disease and Treatment Outcomes in a Low-Tuberculosis Prevalence Setting: A Retrospective Analysis.

Biplob Kumar Mohanty, Tomas Mikal Lind Eagan, Bernt Bøgvald Aarli, Dag Harald Skutlaberg, Tehmina Mustafa

Open access · goldAbstract read
In one paragraph

Article in Pathogens (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 92% 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

3 citing papers in PubMed, 0 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
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

5 authors at 2 institutions in 1 country.

Biplob Kumar MohantyCentre for International Health, Department of Global Public Health and Primary Care, University of Bergen, 5020 Bergen, Norway.ORCID 0009-0007-5420-7188
Tomas Mikal Lind EaganDepartment of Thoracic Medicine, Haukeland University Hospital, 5021 Bergen, Norway.
Bernt Bøgvald AarliDepartment of Thoracic Medicine, Haukeland University Hospital, 5021 Bergen, Norway.
Dag Harald SkutlabergDepartment of Microbiology, Haukeland University Hospital, 5021 Bergen, Norway.ORCID 0000-0003-3434-6715
Tehmina MustafaCentre for International Health, Department of Global Public Health and Primary Care, University of Bergen, 5020 Bergen, Norway.ORCID 0000-0001-9822-1191
Haukeland University Hospital · NOUniversity of Bergen · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInformation on the management of non-tuberculous mycobacterial (NTM) lung infection and disease is scarce. The aim of this study was to investigate the trends in NTM lung infections, and the factors associated with the initiation of treatment and treatment outcomes.

methodsA retrospective analysis was carried out on patient medical records from Haukeland University Hospital, Bergen, Norway, from 2000 to 2021.

resultsAmong 154 patients with NTM lung infection, the majority (70%) were older than 65 years, and 49% had an underlying pulmonary comorbidity. The most frequently observed mycobacterial species was

conclusionA favourable response to treatment was seen in 74% of patients with a high relapse rate.

Indexed as

Anti-Bacterial AgentsMycobacterium Infections, NontuberculousNontuberculous MycobacteriaAdultAgedAged, 80 and overFemaleHumansLung DiseasesMaleMiddle AgedNorwayPrevalenceRetrospective StudiesTreatment OutcomeAnti-Bacterial Agentsmycobacterium aviumnon-tuberculous mycobacteriarelapsetreatment response

Identifiers

PMID38668299
PMCPMC11053999
OpenAlexW4395001118

What OpenQuestion holds

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LicenceCC BY
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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.