MétaCan
Menu
Back to cohort
Record W4396592927 · doi:10.1093/ptj/pzae066

Prognostic Factors and Treatment Effect Modifiers for Physical Health, Opioid Prescription, and Health Care Utilization in Patients With Musculoskeletal Disorders in Primary Care: Exploratory Secondary Analysis of the STEMS Randomized Trial of Direct Access to Physical Therapist–Led Care

2024· article· en· W4396592927 on OpenAlexaff
James Zouch, Nazim Bhimani, André Bussières, Manuela L. Ferreira, Nadine E. Foster, Paulo H. Ferreira

Bibliographic record

VenuePhysical Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité du Québec à Trois-RivièresMcGill University
FundersMedical Research CouncilKeele UniversityNational Health and Medical Research CouncilChartered Society of Physiotherapy Charitable Trust
KeywordsMedicineRandomized controlled trialMedical prescriptionExploratory analysisPhysical therapyHealth carePrimary careAlternative medicineFamily medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: The aims of the study were to identify prognostic factors associated with health care outcomes in patients with musculoskeletal (MSK) conditions in primary care and to determine whether characteristics associated with choice of care modify treatment effects of a direct-access physical therapist-led pathway in addition to general practitioner (GP)-led care compared to GP-led care alone. METHODS: A secondary analysis of a 2-parallel-arm, cluster randomized controlled trial involving general practices in the United Kingdom was conducted. Practices were randomized to continue offering GP-led care or to also offer a direct-access physical therapist-led pathway. Data from adults with MSK conditions who completed the 6-month follow-up questionnaire were analyzed. Outcomes included physical health, opioid prescription, and self-reported health care utilization over 6 months. Treatment effect modifiers were selected a priori from associations in observational studies. Multivariable regression models identified potential prognostic factors, and interaction analysis tested for potential treatment effect modifiers. RESULTS: Analysis of 767 participants indicated that baseline pain self-efficacy, pain severity, and having low back pain statistically predicted outcomes at 6 months. Higher pain self-efficacy scores at baseline were associated with improved physical health scores, reduced opioid prescription, and less health care utilization. Higher bodily pain at baseline and having low back pain were associated with worse physical health scores and increased opioid prescription. Main interaction analyses did not reveal that patients' age, level of education, duration of symptoms, or MSK presentation influenced response to treatment, but visual trends suggested those in the older age group proceeded to fewer opioid prescriptions and utilized less health care when offered direct access to physical therapy. CONCLUSIONS: Patients with MSK conditions with lower levels of pain self-efficacy, higher pain severity, and presenting with low back pain have less favorable clinical and health care outcomes in primary care. Prespecified characteristics did not modify the treatment effect of the offer of a direct-access physical therapist-led pathway compared to GP-led care. IMPACT: Patients with MSK conditions receiving primary care in the form of direct-access physical therapist-led or GP-led care who have lower levels of self-efficacy, higher pain severity, and low back pain are likely to have a less favorable prognosis. Age and duration of symptoms should be explored as potential patient characteristics that modify the treatment response to a direct-access physical therapist-led model of care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.328
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePhysical TherapySame topicMusculoskeletal pain and rehabilitationFrench-language works237,207