Abstract 1244: Lipid Goals among Patients with Diabetes or the Metabolic Syndrome: The Lipid Treatment Assessment Project (L-TAP) 2
Bibliographic record
Abstract
Background: Achievement of lipid targets is particularly important in individuals with diabetes mellitus (DM) and the metabolic syndrome (MS) because their cardiovascular (CV) risk is high. This analysis of the L-TAP 2 population compared goal attainment by DM status and number of MS components. Methods: In L-TAP 2, patients aged ≥20 years with dyslipidemia on stable lipid lowering therapy were assessed at investigation sites in 9 countries (US, Spain, Canada, Netherlands, Korea, France, Taiwan, Mexico, and Brazil) between September 2006 and April 2007. Lipid levels were determined once in each patient at time of enrollment. Achievement of LDL-C success (according to National Cholesterol Education Program Adult Treatment Panel III guidelines), triglycerides (TG) goals (<150 mg/dL), and HDL-C success (>40 mg/dL in men or >50 mg/dL in women) was compared using logistic regression by DM status and number of MS components (BMI ≥30 kg/m 2 , TG ≥150 mg/dL, HDL-C <40 mg/dL in men or <50 mg/dL in women, blood pressure ≥130/≥85 mm Hg, fasting glucose ≥110 mg/dL). Lipid and CRP levels were compared by DM status using ANOVA. Results: A total of 9955 patients were evaluated. Patients with DM, compared with those without DM, had significantly lower achievement of LDL-C success (67% vs 75%), TG goals (55% vs 64%), and HDL-C success (62% vs 75%; P <0.0001 for all comparisons). However, significantly more DM patients had LDL-C <70 mg/dL (28% vs 16%; P <0.0001). As the number of MS components increased, success rates significantly decreased for both LDL-C (81%, 75%, 71%, 69%, 69%, and 69% for 0, 1, 2, 3, 4, and 5 MS components respectively; P <0.0001) and HDL-C (91%, 74%, 50%, and 24% for 1, 2, 3, and 4 MS components respectively; P <0.0001). Patients with DM, compared with those without DM, had significantly higher CRP levels (1.86 vs 1.52 mg/L), significantly lower total cholesterol (175 vs 188 mg/dL), LDL-C (91 vs 104 mg/dL), HDL-C (49 vs 54 mg/dL), and non-HDL-C (125 vs 134 mg/dL), and higher TG (177 vs 155 mg/dL; P <0.0001 for all comparisons). Conclusions: This analysis indicates that despite their increased CV risk, patients with DM remain undertreated. Furthermore, as the number of MS components increases, lipid goal success rates decrease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".