Metabolic syndrome in a family practice population: prevalence and clinical characteristics.
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence and clinical characteristics of metabolic syndrome in a family practice population. DESIGN: Chart abstraction and patient interviews. SETTING: Family Medicine Centre in Kingston, Ont. PARTICIPANTS: Five hundred one men and women between 40 and 60 years old registered at the Family Medicine Centre. Based on the number of risk factors for metabolic syndrome recorded on their charts (except for waist circumference), participants were stratified into 3 groups. Group 1 were patients without the syndrome (0 or 1 risk factor). Group 2 were patients who might have the syndrome, depending on subsequent measurement of waist circumference (2 risk factors). Group 3 were patients with metabolic syndrome (3 or more risk factors). Patients in group 2 were invited to attend the clinic for an assessment of waist circumference. MAIN OUTCOME MEASURES: Presence of metabolic syndrome, as defined by the Third Adult Treatment Panel of the National Institutes of Health, based on waist circumference; blood pressure; and serum triglyceride, high-density lipoprotein, and glucose levels. RESULTS: Prevalence of metabolic syndrome in this population was 33% (35% among men and 32% among women). Hypertension was the most prevalent component of the syndrome (81.6%). The most common combination of 3 components of the syndrome was central obesity, hypertriglyceridemia, and hypertension (43.7%). CONCLUSION: Metabolic syndrome was prevalent among patients in the family practice studied. One in every 3 patients between 40 and 60 years old met the criteria for the syndrome.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".