Depression following Traumatic Spinal Cord Injury
Bibliographic record
Abstract
OBJECTIVES: To describe the epidemiology of depression following traumatic spinal cord injury (SCI) and identify risk factors associated with depression. METHODS: This population-based cohort study followed individuals from date of SCI to 6 years after injury. Administrative data from a Canadian province with a universal publicly funded health care system and centralized databases were used. A Cox proportional hazards model was developed to identify risk factors. RESULTS: Of 201 patients with SCI, 58 (28.9%) were treated for depression. Individuals at highest risk were those with a pre-injury history of depression [hazard rate ratio (HRR) 1.6; 95% CI: 1.1-2.3], a history of substance abuse (HRR 1.6; 95% CI: 1.2-2.3) or permanent neurological deficit (HRR 1.6; 95% CI: 1.2-2.1). CONCLUSION: Depression occurs commonly and early in persons who sustain an SCI. Both patient and injury factors are associated with the development of depression. These should be used to target patients for mental health assessment and services during initial hospitalization and following discharge into the community.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".