Evidence map›Paper›PMID 32249767›Full record

ArticleNPJ primary care respiratory medicine2020

Data-driven questionnaire-based cluster analysis of asthma in Swedish adults.

Marta A Kisiel, Xingwu Zhou, Josefin Sundh, Björn Ställberg, Karin Lisspers, Andrei Malinovschi, Hanna Sandelowsky, Scott Montgomery, Anna Nager, Christer Janson

Abstract read
In one paragraph

Article in NPJ primary care respiratory medicine, 2020. 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. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Asthma phenotypes in primary care.NPJ primary care respiratory medicine · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Marta A KisielDepartment of Medical Sciences: Environmental and Occupational Medicine, Uppsala University, Uppsala, Sweden. marta.kisiel@medsci.uu.se.ORCID http://orcid.org/0000-0002-0410-1509
Xingwu ZhouDepartment of Medical Sciences: Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden.
Josefin SundhDepartment of Respiratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Björn StällbergDepartment of Public Health and Caring Sciences, Family Medicine and Preventive Medicine, Uppsala University, Uppsala, Sweden.
Karin LisspersDepartment of Public Health and Caring Sciences, Family Medicine and Preventive Medicine, Uppsala University, Uppsala, Sweden.
Andrei MalinovschiDepartment of Medical Sciences: Clinical Physiology, Uppsala University, Uppsala, Sweden.
Hanna SandelowskyNVS, Section for Family Medicine and Primary Care, Karolinska Institute, Stockholm, Sweden.
Scott MontgomeryClinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden.
Anna NagerNVS, Section for Family Medicine and Primary Care, Karolinska Institute, Stockholm, Sweden.
Christer JansonDepartment of Medical Sciences: Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden.

Funding

Medical Research Council MC_PC_19009
6 · The paper itself

Abstract

The aim of this study was to identify asthma phenotypes through cluster analysis. Cluster analysis was performed using self-reported characteristics from a cohort of 1291 Swedish asthma patients. Disease burden was measured using the Asthma Control Test (ACT), the mini Asthma Quality of Life Questionnaire (mini-AQLQ), exacerbation frequency and asthma severity. Validation was performed in 748 individuals from the same geographical region. Three clusters; early onset predominantly female, adult onset predominantly female and adult onset predominantly male, were identified. Early onset predominantly female asthma had a higher burden of disease, the highest exacerbation frequency and use of inhaled corticosteroids. Adult onset predominantly male asthma had the highest mean score of ACT and mini-AQLQ, the lowest exacerbation frequency and higher proportion of subjects with mild asthma. These clusters, based on information from clinical questionnaire data, might be useful in primary care settings where the access to spirometry and biomarkers is limited.

Indexed as

Disease ProgressionQuality of LifeSeverity of Illness IndexAdministration, InhalationAdultAgedAge of OnsetAsthmaBody Mass IndexCardiovascular DiseasesCluster AnalysisComorbidityCost of IllnessDiabetes MellitusFemaleGlucocorticoidsGlucocorticoids

Identifiers

PMID32249767
PMCPMC7136224

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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.