White blood cell count and clustered components of metabolic syndrome: A study in western Iran.
Bibliographic record
Abstract
BACKGROUND: White blood cell count (WBC) is one of the objective parameters of systemic inflammation. The aim of present study was to evaluate the relationship between WBC count and metabolic syndrome. METHODS: In this study on Lor population in Borujerd province (West of Iran), from 2011 to 2013, 800 persons were enrolled. MetS was defined based on ATP III criteria. Differences among the quartiles of WBC were examined by one-way analysis of variance. RESULTS: Only 14.7% did not have any of the five components and 43% of all subjects had metabolic syndrome. The means of WBC count in MetS group were significantly higher than the control group (p<0.0001). In subjects without any MetS components, the means of WBC was 5.321 /µL, and it was 5.664, 5.714, 5.961, 6.302, and 6.572 /µL in subjects with 1, 2, 3, 4, and 5 components, respectively. These differences show a significant increasing trend (p<0.0001). CONCLUSION: WBC count was associated with clustered components of metabolic syndrome. It seems that WBC counts could be considered as a predictive factor for metabolic syndrome in preventive medicine.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".