Biochemical Markers Present in a Population Susceptible to Suffering From Metabolic Syndrome
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of metabolic syndrome (SM) according to Adult Treatment Panel III ATPIII and its relation with uric acid concentration and C-reactive protein, in people aged from 45 to 60 years old from the Getsemaní neighborhood of Cartagena city, Colombia.MATERIALS AND METHODS: Type of study: Observational, Descriptive-Correlation. Population of 802 inhabitants from the Getsemaní neighborhood of Cartagena city. We analyzed 302 inhabitants from a random sample with 95% confidence level and 5% of error level. The ATP III diagnostic criteria were applied, the applied instrument had basic data about the general context (social, demographic, economic aspects, family history, work activity and its physical characteristics: weight, waist circumference, blood pressure, calculation of BMI), as well diagnostic tests as: glycaemia, total cholesterol, triglycerides, HDLc, LDLc, uric acid, ultrasensitive C-reactive protein. RESULTS: The population susceptible to metabolic syndrome presented a prevalence of 18%. The most prevalent metabolic syndrome factor was abdominal obesity with 85%, followed by an increase in triglycerides by 76%.CONCLUSION: When applying the ATP III criteria, the prevalence of metabolic syndrome was considered high. There was no significant association of C-reactive protein values with the possibility of developing metabolic syndrome in both men and women, but uric acid results were found to be correlated in the group of women susceptible to MS with a p = 0.0022.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".