Frequency of Testing for Dyslipidemia: An Evidence-Based Analysis.
Bibliographic record
Abstract
BACKGROUND: Dyslipidemias include high levels of total cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides and low levels of high-density lipoprotein (HDL) cholesterol. Dyslipidemia is a risk factor for cardiovascular disease, which is a major contributor to mortality in Canada. Approximately 23% of the 2009/11 Canadian Health Measures Survey (CHMS) participants had a high level of LDL cholesterol, with prevalence increasing with age, and approximately 15% had a total cholesterol to HDL ratio above the threshold. OBJECTIVES: To evaluate the frequency of lipid testing in adults not diagnosed with dyslipidemia and in adults on treatment for dyslipidemia. RESEARCH METHODS: A systematic review of the literature set out to identify randomized controlled trials (RCTs), systematic reviews, health technology assessments (HTAs), and observational studies published between January 1, 2000, and November 29, 2012, that evaluated the frequency of testing for dyslipidemia in the 2 populations. RESULTS: Two observational studies assessed the frequency of lipid testing, 1 in individuals not on lipid-lowering medications and 1 in treated individuals. Both studies were based on previously collected data intended for a different objective and, therefore, no conclusions could be reached about the frequency of testing at intervals other than the ones used in the original studies. Given this limitation and generalizability issues, the quality of evidence was considered very low. No evidence for the frequency of lipid testing was identified in the 2 HTAs included. Canadian and international guidelines recommend testing for dyslipidemia in individuals at an increased risk for cardiovascular disease. The frequency of testing recommended is based on expert consensus. CONCLUSIONS: Conclusions on the frequency of lipid testing could not be made based on the 2 observational studies. Current guidelines recommend lipid testing in adults with increased cardiovascular risk, with the frequency of testing based on individual cardiovascular risk.
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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 | 0.034 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.018 |
| Bibliometrics | 0.019 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".