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Record W2318790812 · doi:10.1097/brs.0b013e31824a8314

Relationship Between Ambulatory Performance and Self-Rated Disability in Patients With Lumbar Spinal Stenosis

2012· article· en· W2318790812 on OpenAlexaff
Rob Pryce, Michael G. Johnson, Michael Goytan, Steven Passmore, Neil Berrington, Dean Kriellaars

Bibliographic record

VenueSpine · 2012
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineLumbar spinal stenosisPhysical therapyPhysical medicine and rehabilitationLumbarLow back painAmbulatoryStepwise regressionCross-sectional studyOswestry Disability IndexSpinal stenosisBack painSurgery

Abstract

fetched live from OpenAlex

In Brief Study Design. A cross-sectional study. Objective. To identify the relationship between performance measures derived from accelerometry and subjective reports of pain, disability, and health in patients with lumbar spinal stenosis (LSS). Summary of Background Data. Accelerometers have emerged as a measure of performance, providing the ability to characterize the pattern and magnitude of real-life activity, and sedentarism. Pain and loss of function, particularly ambulation, are common in LSS. The extent to which pain, perceived disability, and self-rated health relate to performance in patients with LSS is not well known. Methods. Data regarding self-reported pain, disability (Oswestry Disability Index, Roland-Morris Disability Questionnaire, and Disabilities of the Arm, Shoulder, and Hand), and health (36-Item Short Form Health Survey [SF-36]) were collected from patients with LSS (n = 33). Physical activity, ambulation, and inactivity performance measures were derived from 7-day accelerometer records. Correlation and stepwise regression were used. Results. The physical function subscale of the SF-36, a non–pathology-specific outcome, had the best overall correlation to physical activity and ambulation (average r = 0.53) compared with pain (average r = 0.32) and disability (average r = −0.45) outcomes. Stepwise regression models for performance were predominantly single-variable models (4 of 8 models); pain was not selected as a predictor. A second non–pathology-specific outcome, the Disabilities of Arm Shoulder and Hand, improved the prediction of performance in 5 of 8 models. Conclusion. Subjective measures of pain and disability had limited ability to account for real-life performance in patients with LSS. Future research is required to identify determinants of performance in patients with LSS because barriers to activity may not be disease-specific. The relationship of pain and disability with performance was evaluated in patients with lumbar spinal stenosis, using accelerometry. Domain-specific measures provided improved explanatory ability above disease-specific disability and pain assessments for ambulatory behavior. Outcome assessments should include performance measures, and interventional approaches need to address non-diseasespecific barriers.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.263
Teacher spread0.250 · 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

Citations37
Published2012
Admission routes1
Has abstractyes

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