Do patients with psychosis receive guideline appropriate care for acute myocardial infarction
Bibliographic record
Abstract
Background: Circulatory disease, not suicide, is the major cause of excess death in psychiatric patients. Data from Australia and Canada suggest that people with mental illness, especially psychosis, do not receive equitable levels of specialised procedures such as percutaneous transluminal coronary angioplasty and coronary artery bypass grafts. We investigated whether patients admitted for myocardial infarction with a history of psychosis (ICD9 295, 297‐8) received equitable levels of the following guideline‐consistent treatments compared to non‐psychiatric controls: beta‐blockers, ACE inhibitors, statins, clopidogrel and angiotensin receptor blockers (ARBs)Method: A population‐based case‐control study of 49,248 Nova Scotians admitted with myocardial infarction (MI). Of these, 11,139 had previous contact with primary or secondary care for psychiatric problems from 1995 to 2001. 1285 patients had a history of psychosis. We adjusted for confounders including age, gender, income and medical comorbidity.Results: Patients with a history of psychosis had a higher 1‐year mortality compared to controls (ORadj=1.3 95%CI =1.1‐1.5). However, on either univariate or multivariate analyses (significance p<0.05), these patients had only a 25 to 80% chance of receiving any of the guideline‐consistent treatments during, or on discharge, from their admission for MI compared to controls: e.g. cardiac catheterisation (ORadj=0.12 95%CI=0.1‐0.2), beta‐blockers (ORadj= 0.79, 95%CI=0.7‐0.9), statins (ORadj=0.24, 95%CI=0.1‐0.4), ARBs (ORadj=0.22, 95%CI=0.1‐0.9), and clopidogrel (ORadj=0.68,95%CI=0.5‐0.99). Conclusions: People with a history of psychosis do not receive equitable levels of evidence‐based treatment for acute MI, even under universal health care. Possible explanations include reduced patient adherence to treatment, difficulties in communication or accessing health care, and stigma.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".