Neuropathic Pain, Depression, and Cardiovascular Disease: A National Multicenter Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Individuals with spinal cord injury (SCI) have a more than twofold increased risk of heart disease and stroke compared with able-bodied individuals. The increased risk appears to be in excess of the risk conferred by several well-established risk factors, including diabetes, hypertension, and sex. This raises the question whether other factors, secondary to SCI, are also contributing to the development of cardiovascular disease (CVD). Two potential factors associated with SCI and CVD are pain and depression. Both are frequently reported among individuals with SCI, develop in the acute stages of injury, and are commonly described as severe. Therefore, the primary aim of this study was to examine the relationship between pain (and types of pain) and depression with CVD among individuals with SCI. METHODS: A total of 1,493 individuals (referred sample) with chronic SCI participated in a self-report cross-sectional multicenter Canada-wide survey from 2011-2012 (mean age ± standard deviation: 49.6 ± 13.9 years). RESULTS: After adjustment for age, sex, and injury characteristics, neuropathic pain and depression were significantly and independently associated with CVD (adjusted odds ratio and 95% confidence interval: 2.27 (1.21, 4.60) for neuropathic pain; 4.07 (2.10, 7.87) for depression). In contrast to neuropathic pain, non-neuropathic pain was not significantly associated with CVD (p = 0.13). CONCLUSION: In conclusion, these data illustrate important interrelationships between secondary complications following SCI, as well as raise the possibility of neuropathic pain (versus nociceptive pain) as a novel and emerging risk factor for CVD.
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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 | 0.007 | 0.046 |
| 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