Trajectories of Physical Function and Disability Over 12 Months in Older Adults With Chronic Low Back Pain
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Understanding prognosis is critical for clinical care and health policy initiatives. The purpose of this study was to determine whether distinct prognostic trajectories of physical function and disability exist in a cohort of 245 community-dwelling older adults with chronic low back pain (LBP), and to characterize the demographic, health, and pain-related profiles of each trajectory subgroup. METHODS: All participants underwent standard clinic examinations at baseline, 3 months, 6 months, and 12 months. At each time point, the Late Life Function & Disability Instrument (LLFDI) was used to measure general physical function (LLFDI Function) and disability (LLFDI Disability-Limitation); the Quebec LBP Disability Questionnaire was used to measure disability due to pain. Growth mixture modeling (GMM) was performed on each outcome to identify distinct trajectory classes/subgroups; baseline demographic (eg, age and sex), health (eg, comorbidities, depressive symptoms, and physical activity level), and pain-related (eg, LBP intensity, pain-related fear, and pain catastrophizing) characteristic profiles were compared across subgroups. RESULTS: GMM statistics revealed an optimal number of 3 to 4 trajectory subgroups, depending on the outcome examined. Subgroups differed across demographic, health, and pain-related characteristics; the classes with the most favorable prognoses had consistent profile patterns: fewer depressive symptoms, fewer comorbidities, higher physical activity levels, lower LBP intensities, less pain-related fear, and less pain catastrophizing. CONCLUSION: Our findings indicate that several distinct trajectory subgroups exist that would have been masked by observing mean cohort change alone. Furthermore, subgroup characteristic profiles may help clinicians identify likely prognostic trajectories for their patients. Future research should focus on identifying modifiable risk factors that best predict group membership, and tailoring interventions to mitigate the risk of poor prognosis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it