[PP.27.02] SCREENING FOR HYPERTENSION DURING CONSULTATION IN A WALK-IN SERVICE; LITERATURE REVIEW AND PROPOSED ALGORITHM
Bibliographic record
Abstract
Objective: In Canada, 17% of people with high blood pressure (BP) are unaware of their status and another 17% has high blood pressure but is not getting treated which represents close to 2.5 million individual that could benefit from proper BP screening and treatment. Walk-in clinics present a definite appeal for hypertension screening. A large number of patients are seen there every day and blood pressure (BP) is measured routinely. However, these routine measures are often not standardised and the patient could have pain or other factors that temporarily affect the BP. Moreover, there seems to be no valid algorithm available on how to integrate BP screening in a valid and reproducible way in order to diagnose HTN. A literature review was undertaken to identify all studies that addressed BP screening for HTN in a walk-in or emergency services. Design and method: MEDLINE and CINHAL Databases were searched for this review. Primary studies and reviews either in French and English were included from start date to November 2015. Additional citations from reference lists were retrieved. Results: A total of 600 articles were identified and further analysis resulted in the decision to include 7 papers that corresponded to the criteria. Results show that between 22 and 76% of patient with an elevated BP in the emergency were diagnosed with hypertension on follow-up. Many patients were lost after the initial visit and having an immediate reference for ambulatory measurements was more effective (87%) than other type of follow-up (54%). Conclusions: Weak predictive value were found between emergency BP measurements and further evaluation for hypertension when routine or poorly standardised BP measurement was used. Having patient return for follow-up presented a challenge and a way to improve this was to be able to make an immediate reference for ambulatory BP monitoring. A protocol is now proposed to include a formal algorithm for BP screening in the emergency including automated blood pressure measurement and ambulatory measurements. Characteristic of the patient and the impact of the health care system when implementing this algorithm will also be analysed.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.026 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".