Low-density lipoprotein cholesterol goal attainment and treatment patterns in a cohort of >143,000 patients with atherosclerotic cardiovascular disease in Ontario, Canada
Bibliographic record
Abstract
Abstract Background/Introduction Limited real-world data are available on attainment of low-density lipoprotein cholesterol (LDL-C) treatment goals in patients with atherosclerotic cardiovascular disease (ASCVD) in Canada. Purpose A retrospective observational study was conducted to describe types of ASCVD events/procedures, time between events and use of lipid lowering treatment (LLT) in patients who did not achieve LDL-C goal. Methods Patients in Ontario ≥65 years with a primary ASCVD event/procedure between 1 Apr 2005 and 31 Mar 2016, treated with an LLT and with index and follow up LDL-C values were identified from claims data at the Institute for Clinical Evaluative Sciences data repository. Patients were assessed over a 1-year follow up period for LDL-C goal attainment (<2.0 mmol/L or 50% reduction from index LDL-C) and analysed by LLT and by index event type. Results Overall, 28% of 143,302 patients ≥65 years on LLT failed to attain LDL-C goal at follow up (Figure). The proportion of patients failing to achieve LDL-C goal decreased from 35% to 22% over the 11-year study period. Mean time between index and follow up LDL-C (based on lowest score >2 weeks and up to 1 year after index LDL-C) was 203±97 days. When analysed by low-, moderate- or high-intensity statin, 57%, 30%, and 22% of patients failed to achieve LDL-C goal at follow up, respectively. Conclusions In this study, more than 1 in 4 patients with ASCVD in Ontario failed to achieve guideline recommended LDL-C goal despite treatment. In particular, ∼1 in 3 patients with cerebral and peripheral arterial disease were not at goal. An opportunity exists to better manage these high risk ASCVD patients with further statin intensification and additional LLTs This study made use of de-identified data from the ICES Data Repository, which is managed by the Institute for Clinical Evaluative Sciences with support from its funders and partners: Canada's Strategy for Patient-Oriented Research (SPOR), the Ontario SPOR Support Unit, the Canadian Institutes of Health Research and the Government of Ontario. The opinions, results and conclusions reported are those of the authors. No endorsement by ICES or any of its funders or partners is intended or should be inferred. Parts of this material are based on data and/or information compiled and provided by CIHI. However, the analyses, conclusions, opinions and statements expressed in the material are those of the author(s), and not necessarily those of CIHI Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Amgen Canada Inc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".