Does Radiating Spinal Pain Determine Future Work Disability? A Retrospective Cohort Study of 22,952 Danish Twins
Bibliographic record
Abstract
STUDY DESIGN: Population-based, retrospective cohort. OBJECTIVE: To determine whether radiating spinal pain from the low back, mid back, and neck is associated with future use of health-related benefits and their duration as compared with those with nonradiating spinal pain. SUMMARY OF BACKGROUND DATA: Studies on the socioeconomic consequences of radiating pain have primarily focused on the low back and to a lesser extent on the neck and mid back. In addition, few studies report on the incidence of health-related benefit use after any radiating spinal pain. METHODS: A cohort of 22,952 subjects was formed from the 2002 survey of the Danish Twin Registry. The survey contained information on spinal pain and important confounding factors. Work disability for an 8-year period was determined through data linkage with the Danish Register-Based Evaluation of Marginalization (DREAM) register of government transfer payments. We determined the incidence rate ratio for receipt of sickness benefit and the mean duration of the first and total sickness benefit periods by radiating and nonradiating spinal pain. Relative risks for the occurrence and number of sickness benefit episodes were calculated by radiating spinal pain status. RESULTS: The incidence of sickness benefit was greater for those with radiating spinal pain (89.6 per 1000 person-years [95% confidence interval: 86.0, 93.2]) than those with nonradiating spinal pain (60.4 per 1000 person-years [95% confidence interval: 57.7, 63.1]). However, the duration of time off work, conditional on 1 day or more off work, was the same between those with and without radiating spinal pain. CONCLUSION: Radiating spinal pain is an important risk factor for future sickness benefit. Radiating spinal pain was not associated with the duration of sickness benefit. These findings were independent of the effects of pain duration at baseline. The results highlight the need for interventions to prevent the onset of work disability, especially for those with radiating pain.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".