Community pharmacist surveillance of hypertension in pregnancy
Bibliographic record
Abstract
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are associated with serious maternal and perinatal complications. For nonsevere hypertension, there is a lack of consensus regarding treatment during pregnancy and while breastfeeding. Further, there is considerable variability in guidelines for antihypertensive drug choices. As part of a Drug Safety and Effectiveness Network (DSEN)-funded project, we piloted a novel surveillance strategy in which community pharmacists recruited pregnant and breastfeeding women to monitor their blood pressure and medication use and to provide education on HDP. METHODS: Participating pharmacists were required to complete a certified training program, identify and recruit patients who were pregnant or breastfeeding, obtain informed consent, administer a patient questionnaire and complete an initial case report form for enrolled patients. Study outcomes included the feasibility of community pharmacists to enroll patients and carry out study-related documentation and follow-up. The criteria for success in this pilot study included the ability of pharmacists to recruit 10 participants per pharmacy. RESULTS: 178 community pharmacies across British Columbia agreed to participate in this feasibility study, of which 63 pharmacists completed the study training. Of these, only 21 pharmacists recruited at least 1 patient and 1 pharmacist met the success criteria. Overall, 51 patients were enrolled, 2 withdrew from the study and 7 patients were diagnosed with HDP. Antihypertensive medications used by patients included methyldopa and labetalol. CONCLUSIONS: While postmarketing surveillance is an important tool for the assessment of drug safety in the pregnant and breastfeeding patient population, the feasibility of community pharmacists taking on this role was not successfully demonstrated.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".