Evidence map›Paper›PMID 25763716›Full record

ArticleNPJ primary care respiratory medicine2015

Differences in spirometry interpretation algorithms: influence on decision making among primary-care physicians.

Xiao-Ou He, Anthony D'Urzo, Pieter Jugovic, Reuven Jhirad, Prateek Sehgal, Evan Lilly

Open access · goldAbstract read
In one paragraph

Article in NPJ primary care respiratory medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Xiao-Ou HeFaculty of Medicine, University of Toronto, Toronto, ON, Canada.
Anthony D'Urzo1] Faculty of Medicine, University of Toronto, Toronto, ON, Canada [2] Department of Family and Community Medicine at the University of Toronto, Toronto, ON, Canada.
Pieter JugovicDepartment of Family and Community Medicine at the University of Toronto, Toronto, ON, Canada.
Reuven JhiradDepartment of Family and Community Medicine at the University of Toronto, Toronto, ON, Canada.
Prateek SehgalFaculty of Medicine, University of Toronto, Toronto, ON, Canada.
Evan LillyFaculty of Medicine, University of Toronto, Toronto, ON, Canada.
University of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpirometry is recommended for the diagnosis of asthma and chronic obstructive pulmonary disease (COPD) in international guidelines and may be useful for distinguishing asthma from COPD. Numerous spirometry interpretation algorithms (SIAs) are described in the literature, but no studies highlight how different SIAs may influence the interpretation of the same spirometric data.

aimsWe examined how two different SIAs may influence decision making among primary-care physicians.

methodsData for this initiative were gathered from 113 primary-care physicians attending accredited workshops in Canada between 2011 and 2013. Physicians were asked to interpret nine spirograms presented twice in random sequence using two different SIAs and touch pad technology for anonymous data recording.

resultsWe observed differences in the interpretation of spirograms using two different SIAs. When the pre-bronchodilator FEV1/FVC (forced expiratory volume in one second/forced vital capacity) ratio was >0.70, algorithm 1 led to a 'normal' interpretation (78% of physicians), whereas algorithm 2 prompted a bronchodilator challenge revealing changes in FEV1 that were consistent with asthma, an interpretation selected by 94% of physicians. When the FEV1/FVC ratio was <0.70 after bronchodilator challenge but FEV1 increased >12% and 200 ml, 76% suspected asthma and 10% suspected COPD using algorithm 1, whereas 74% suspected asthma versus COPD using algorithm 2 across five separate cases. The absence of a post-bronchodilator FEV1/FVC decision node in algorithm 1 did not permit consideration of possible COPD.

conclusionsThis study suggests that differences in SIAs may influence decision making and lead clinicians to interpret the same spirometry data differently.

Indexed as

Decision MakingPhysicians, Primary CareSpirometryAlgorithmsAsthmaDiagnosis, DifferentialForced Expiratory VolumeHumansPulmonary Disease, Chronic ObstructiveVital Capacity

Identifiers

PMID25763716
PMCPMC4373504
OpenAlexW2065505334

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.