Potentially harmful drug–drug interactions in the therapeutic regimens of persons with spinal cord injury
Bibliographic record
Abstract
OBJECTIVES: Individuals with spinal cord injury deal with multiple health complications that require them to use many medications. The purpose of this paper was to find the most common potentially harmful drug-drug interactions (DDIs) in therapeutic regimens of persons with spinal cord injury, and the risk factors associated with it. We further highlight the relevance of each of the DDIs specific to spinal cord injury population. DESIGN: Observational design and cross-sectional analysis. SETTING: Community; Canada. PARTICIPANTS: = 108). MAIN OUTCOME MEASURES/ANALYSIS: The main outcome was the presence of one or more potential DDIs that can lead to an adverse outcome. All the reported drugs were classified as per the World Health Organization's Anatomical Therapeutic Chemical Classification system. Twenty potential DDIs were selected for the analysis based on the most common medications prescribed to people with spinal cord injury and severity of clinical consequences. The medication lists of study participants were analyzed for selected DDIs. RESULTS: Among the 20 potential DDIs analyzed in our sample, the top 3 prevalent DDIs were Opioids + Skeletal Muscle Relaxants, Opioids + Gabapentinoids, and Benzodiazepines + ≥ 2 other central nervous system (CNS)-active drugs. Of the total sample of 108 respondents, 31 participants (29%) were identified with having at least one potential DDI. The risk of having a potential DDI was highly associated with polypharmacy, though no associations were found between the presence of a drug interaction and age, sex, level of injury, time since injury, or cause of injury among the study sample. CONCLUSION: Almost three out of ten individuals with spinal cord injury were at risk of having a potentially harmful drug interaction. Clinical and communication tools are needed that facilitate identification and elimination of harmful drug combinations in the therapeutic regimens of patients with spinal cord injury.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".