Implementation of the cardiovascular assessment screening program (CASP) by nurse practitioners-it's time to focus on early identification of cardiovascular risk
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Newfoundland and Labrador Support for Patient-Oriented Research (NL SUPPORT) Background There is inconsistent utilization of clinical practice guidelines (CPGs) for cardiovascular disease (CVD) screening and management by advanced practice nurses/nurses practitioners (NPs) to identify CVD risk factors early and to intervene using current recommendations. To address this clinical practice issue and increase utilization of Canadian CPGs, an exploratory multiphase sequential mixed methods study was conducted and the Cardiovascular Assessment Screening Program (CASP) was developed, implemented, and evaluated. Objective Phase 2 of the mixed methods study, a cluster randomized controlled trial (cRCT), evaluated the implementation of CASP by NPs with individuals aged 40-74 years, without established CVD or vascular disease (VD), in order to identify CVD risk factors early, to determine the level of risk for a CV event, to calculate the Heart Age, and to set heart health priorities and management, according to current CPGs in Canada. Methods In a cRCT, block randomization randomly divided ten NPs into the intervention group clusters (IGCs) and the control group clusters (CGCs). In turn, eight NPs recruited 166 patients in their own communities; the four NP IGCs recruited patients (n=67) and the four NP CGCs recruited patients (n=99). The web-based CASP intervention was implemented with patients in the IGCs, and the CGCs received standard care. The CASP intervention consisted of four components: an electronic CVD Database, an NP toolkit, an educational resource for NPs and patients, and a website containing CPGs. The data on CVD risk factors, Framingham Risk Score (FRS), Heart Age, and priorities for heart health were recorded in the CVD Database utilized by the NP IGCs. Results Utilizing the CVD database, CVD risk factors were consistently identified in patients by NPs in the IGCs compared to the NP CGCs. The patients in the IGCs had a high number of risk factors for CVD documented by NPs, including family history of CVD, hypertension, diabetes, obesity, renal dysfunction, and dyslipidemia, and found that 62 patients (91%) were at moderate to high risk for having a CV event in the next 10 years using the FRS. In comparison, NPs in the CGCs did minimal documentation of risk factors; the level of CVD risk was largely unknown (96%) for control group patients as the FRS was only documented on 7 patients (4%). The Heart Age was calculated in the IGCs (92%); in the CGCs, the Heart Age was not calculated. The recommendations made by IGC NPs matched their patients’ priorities 94% of the time; 75% of the intervention group patients developed personalised goals that matched their top priorities for improving heart health. Conclusion The key benefit of the CASP implementation by NPs was the identification of CVD risk factors earlier in individuals without established CVD or VD. Engaging individuals to participate in screening to learn about their CVD risk encourages priority setting for heart health using a patient-focused approach.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".