Nurse-led PrEP-RN clinic: a prospective cohort study exploring task-Shifting HIV prevention to public health nurses
Bibliographic record
Abstract
OBJECTIVE: To report the results of a nurse-led pre-exposure prophylaxis (PrEP) delivery service. DESIGN: testing. Those significant in bivariate analysis were retained and entered into a binary multiple logistic regression. Hierarchical modelling was used, and only significant factors were retained. SETTING: This study occurred in an urban public health unit and community-based sexually transmitted infection (STI) clinic in Ottawa, Canada. PARTICIPANTS: Of all persons who were diagnosed with a bacterial STI in Ottawa and everyone who presented to our STI clinic during the study period, there were 347 patients who met our high-risk criteria for PrEP; these criteria included patients who newly presented with any of the following: HIV contacts, diagnosed with a bacterial STI or single use of HIV PEP. Further, eligibility could be determined based on clinical judgement. Patients who met the foregoing criteria were appropriate for PrEP-RN, while lower-risk patients were referred to elsewhere. Of the 347 patients who met our high-risk criteria, 47% accepted and 53% declined. Of those who accepted, 80% selected PrEP-registered nurse (RN). PRIMARY AND SECONDARY OUTCOME MEASURES: Uptake, acceptance, engagement and attrition factors of participants who obtained PrEP through PrEP-RN. FINDINGS: 69% of participants who were eligible attended their intake PrEP-RN visit. 66% were retained in care. Half of participants continued PrEP and half were lost to follow-up. We found no significant differences in the uptake, acceptance, engagement and attrition factors of participants who accessed PrEP-RN regarding reason for referral, age, ethnicity, sexual orientation, annual income, education attainted, insurance status, if they have a primary care provider, presence or absence of depression or anxiety and evidence of newly acquired STI during the study period. CONCLUSIONS: Nurse-led PrEP is an appropriate strategy for PrEP delivery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".