Prescribing for common complications of spinal cord injury
Bibliographic record
Abstract
OBJECTIVE: To describe prescribing patterns for 3 common complications associated with spinal cord injury (SCI) and to provide family doctors with strategies for optimizing the care of patients with SCI. SOURCES OF INFORMATION: Results of a nationwide survey of prescription medication use among people with SCI in Canada and a longitudinal study of secondary complications associated with SCI. MAIN MESSAGE: Altered neurologic and cardiometabolic function in patients with SCI make it difficult for family physicians to predict optimal medication regimens for these patients. Three common problems seen in primary care among patients with SCI that require pharmacologic treatment are pain (treated in 57% of survey respondents), muscle spasms (54%), and recurrent urinary tract infections (43%). Pain management may require multiple medications, depending on the source or nature of the pain. Some prescription medications recommended for treating pain may be underused in this population, such as amitriptyline, while others may be overused in this population, such as antibiotics for urinary tract infections. Spasticity is often related to an underlying problem such as pain, and treatment of concomitant conditions may also reduce spasticity. Short-acting benzodiazepines were found to have been prescribed for spasticity outside the recommended treatment paradigm at a surprisingly high rate. The longitudinal study of secondary complications associated with SCI led to the development of Actionable Nuggets, an innovative knowledge translation tool for primary care providers. CONCLUSION: To provide optimal treatment to patients with SCI, family doctors are encouraged to engage in open communication with them about prescription medications, including aspects of cost, polypharmacy, and therapeutic substitutions. Family physicians should also explore interprofessional collaboration with SCI specialists and allied health providers to provide patients with nonpharmacologic strategies tailored to their activity levels and nutritional needs. The Actionable Nuggets mobile app provides family doctors with brief, actionable, evidence-based information on the top 20 health concerns associated with SCI.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".