The Audit Of Using Of Statins Following A Diagnosis Of Acute Coronary Syndrome (ACS) In The Royal Alexandra Hospital
Bibliographic record
Abstract
Background Statins are well-founded for the acute coronary syndrome as a secondary prevention therapy. Recent GGC guidelines recommend the use of maximum atorvastatin dose (80 mg). Methodology An audit was performed on all patients who had a clear diagnosis of ACS during admission at RAH within three weeks period(August 2019). Data collected from patient's medications chart, electronic system and medical note. IT included age, gender, statin before admission, statin during admission, lipid profiles, contraindication to statin use. Results 72 patients were diagnosed with ACS through the audit period at an average age of 64 years. 61% (n=44) were men and 39% (n=28) were women. 60% (n=43) of the patients before admission on a statin. although of known ACS, 8% (n=6) of all patients had no lipid-lowering treatment. During admission, 33 per cent (n=24) of patients with ACS were measured the lipid profile. 61% (n=44) of cases received maximum atorvastatin dose. Only 22 % of those not licensed for the GGC guideline dose had clear side effects. Conclusion The current audit showed that 39 per cent of patients diagnosed with ACS did not receive a maximum dose of atorvastatin during admission, with only a 22 per cent of patients having side effects from using a statin. The results indicate non-compliance with GGC guidelines regarding the use of appropriate statin following a diagnosis of ACS during admission. future Plans will include applying new GGC guidance and medical team training sessions to emphasize evidence-based practices.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".