NICE guidelines for new chest pain: comparison of new and old services
Bibliographic record
Abstract
In 2000 the National Service Framework for Coronary Artery Disease (CAD) prompted the development of rapid-access chest pain clinics (RACPCs). The aim of such clinics is to provide prompt assessment of chest pain to identify CAD with the use of an exercise tolerance test. In 2010, the National Institute for Health and Clinical Excellence (NICE) guidelines recommended using imaging studies based on CAD risk scoring and not an exercise tolerance test to exclude angina in patients with no previous history of known CAD. A comparison of the use of the 2010 NICE guidelines for the management of new-onset chest pain within a well-established exercise-based RACPC service is undocumented. The new recommendation moves the focus towards discharging low-risk patients, imaging studies/invasive procedure (angiogram) for the moderate-risk group and initiating anti-anginal treatment for the high-risk group. To phase the new recommendations into clinical practice in a district general hospital, the new guidelines were implemented in one out of three RACPC sessions per week. A retrospective assessment was carried out over a 4-month period to evaluate the new service implementation. A total of 160 patients attended the RACPC service, of which 56 (35%) were offered treatments according to the newer NICE guidelines and 104 (65%) were managed with the aim of exercising on the treadmill. This review gives an insight into the benefits of the new recommendations in practice, as well as highlighting some of the immediate limitations and barriers encountered.
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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 | 0.023 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".