Medication-related problems in individuals with spinal cord injury in a primary care-based clinic
Bibliographic record
Abstract
OBJECTIVE: To determine the frequency of medical problems, reason for referral/primary complaint, products used, medication-related problems, and polypharmacy in patients with spinal cord injury (SCI) seen at an interprofessional primary care mobility clinic. DESIGN: Retrospective review of medical records of patients with SCI for patient visits between August 2012 and March 2013. METHODS: Data were abstracted from medical records of patients with SCI. RESULTS: Of 74 patients who presented to the clinic, 19 had an SCI. Mean age was 46.7 years and 74% were male. Most frequent medical problems were depression/anxiety (37%), osteoporosis/osteopenia (26%), hypertension (21%), dyslipidemia (21%), and osteoarthritis (21%). Most common presenting complaints were pain (23%) and bowel/bladder issues (13%). Most common medication-related problems were untreated conditions (41%), ineffective medications (21%), adverse drug reactions (18%), and under- and over-dosage (each 9%). Patients with SCI most frequently used products to treat pain (68%), constipation (42%), muscle spasm (42%), hypertension (42%), and depression (37%). When including natural health products, vitamins and minerals, polypharmacy was seen in 74% of patients with SCI (63% when limited to prescription and over-the-counter medications). For patients with SCI in whose care a pharmacist collaborated, a mean of 3.2 medication-related problems per patient were identified compared with 1 per patient when the pharmacist was not involved. CONCLUSION: This study is the first to describe medication use, polypharmacy and medication-related problems in patients with SCI seen at an interprofessional primary care clinic. Use of high-risk medications, polypharmacy, and medication-related problems in patients with SCI suggest the need for collaborative interprofessional care that includes a pharmacist.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".