Evidence map›Paper›PMID 34330250›Full record

ArticleBMC musculoskeletal disorders2021

Higher psychological distress in patients seeking care for a knee disorder is associated with diagnostic discordance between health care providers: a secondary analysis of a diagnostic concordance study.

Véronique Lowry, Alec Bass, Tatiana Vukobrat, Simon Décary, Patrick Bélisle, Marie-Pierre Sylvestre, François Desmeules

Open access · goldAbstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2021. 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
1.0field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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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

7 authors at 3 institutions in 1 country.

Véronique LowrySchool of Rehabilitation, Faculty of Medicine, University of Montreal, Montreal, QC, Canada. veronique.lowry@umontreal.ca.
Alec BassSchool of Rehabilitation, Faculty of Medicine, University of Montreal, Montreal, QC, Canada.
Tatiana VukobratOrthopaedic Clinical Research Unit, Maisonneuve-Rosemont Hospital Research Center, Centre Intégré Universitaire de Santé Et de Services Sociaux de L'Est-de-L'Île-de-Montréal, 5415 Blvd L'Assomption, Pav. Rachel Tourigny, Montréal, QC, H1T 2M4, Canada.
Simon DécarySchool of Rehabilitation, Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, QC, Canada.
Patrick BélisleMontreal Health Innovations Coordinating Center, Montreal Hearth Institute, Montreal, QC, Canada.
Marie-Pierre SylvestreDepartment of Social Preventive Medicine, School of Public Health, Université de Montréal, Montreal, QC, Canada.
François DesmeulesSchool of Rehabilitation, Faculty of Medicine, University of Montreal, Montreal, QC, Canada.
Université de Montréal · CAHôpital Maisonneuve-Rosemont · CAUniversité de Sherbrooke · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnee disorders are highly prevalent and may be a disabling condition. An accurate diagnosis is necessary to guide toward a rapid and efficient management of knee disorders. However, the ability to make a valid diagnosis is often complex for clinicians and evidence is mainly focused on clinician cognitive biases or errors produced during clinical reasoning. The aim of this secondary exploratory analysis is to identify patient-specific characteristics associated with diagnostic discordance between health care providers in making a diagnosis for a new knee disorder.

methodsWe performed a secondary analysis of a diagnostic study comparing the diagnostic ability of a physiotherapist to medical musculoskeletal specialists. Patients' socio-demographic, psychosocial and clinical characteristics were compared between the concordant and discordant diagnostic groups. Psychosocial symptoms were evaluated using the validated Kessler 6 (K6) questionnaire. We performed multivariable logistic regressions using the Bayesian Information Criterion to identify the most probable model including patients' characteristics associated with diagnostic discordance. Overall probability of identified variables to explain diagnostic discordance and associated odd ratios (OR) with 95% credibility intervals (95% CrI) were calculated.

resultsOverall, 279 participants were evaluated by a physiotherapist and medical musculoskeletal specialists. The mean age of the participants was 49.1 ± 15.8 years and 57.7% were female. The most common disorder was osteoarthritis (n = 117, 18.8% of cases were discordant). The most probable model explaining diagnostic discordance (11.13%) included having depressive symptoms, which was associated with an increased probability of diagnostic discordance (OR: 3.9; 95% CrI: 1.9 - 8.0) and having a higher number of comorbidities, which was associated with a decreased probability of diagnostic discordance (OR: 0.6; 95% CrI: 0.5 - 0.9). The depression item of the K6 questionnaire had a 99.4% chance to be included in a model explaining diagnostic discordance. Other variables taken separately had less than 50% chance to be included in a model explaining diagnostic discordance and cannot be considered significant.

conclusionOur results suggest that depressive symptoms may increase the risk of knee diagnostic discordance. Clinicians may be more likely to make diagnostic errors and should be more cautious when evaluating patients with knee disorders suffering from psychological distress.

Indexed as

OsteoarthritisPhysical TherapistsPsychological DistressAdultBayes TheoremFemaleHumansKnee JointMiddle AgedBayesian information criterionConcordanceDepressive symptomsDiagnosisKneePsychosocial

Identifiers

PMID34330250
PMCPMC8325325
OpenAlexW3184737981

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.