The potential effects of untreated sleep-related breathing disorders on neuropathic pain, spasticity, and cardiovascular dysfunction following spinal cord injury: A cross-sectional prospective study protocol
Bibliographic record
Abstract
INTRODUCTION: Sleep-related breathing disorders (SRBDs), neuropathic pain, spasticity and cardiovascular autonomic dysfunction are common after spinal cord injury (SCI). Prior studies suggest that systemic inflammation following SCI may be implicated in the development of neuropathic pain, spasticity and cardiovascular dysfunction. Given that SRBDs also cause a systemic inflammatory response, we hypothesized that individuals with SCI who develop more severe SRBDs would experience more intense neuropathic pain, more severe spasticity and more significant cardiovascular autonomic dysfunction. METHODS: This cross-sectional prospective study will explore the previously understudied hypothesis that SRBDs are associated with increased neuropathic pain, spasticity, and cardiovascular autonomic dysfunction in adult individuals with low-cervical/high-thoracic (injury level at C5 to T6), complete/incomplete (ASIA Impairment Scale A, B, C or D) SCI. DISCUSSION: To our knowledge, no prior study has addressed this clinically relevant question on whether the degree of SRBDs affects the intensity of neuropathic pain, spasticity, and cardiovascular autonomic dysfunction in individuals with SCI. We anticipate that the results of this original study will provide key information for a future clinical trial on the use of continuous positive airway pressure (CPAP) therapy for moderate-to-severe SRBDs, which may better control neuropathic pain, spasticity, and cardiovascular autonomic dysfunction among individuals with SCI. TRIAL REGISTRATION: The research protocol for this study was registered in the ClinicalTrials.gov website (NCT05687097). https://clinicaltrials.gov/ct2/show/NCT05687097.
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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".