Establishing hematological reference intervals in healthy adults: Ravansar non‐communicable disease cohort study, Iran
Bibliographic record
Abstract
INTRODUCTION: It is necessary to establish hematological reference intervals (RIs) in each population to improve disease management and healthcare quality. This study aimed to establish age- and sex-specific hematological RIs in a healthy adult Kurdish population and evaluate the influence of select lifestyle factors. METHODS: Hematological parameters were studied in 6518 individuals (3006 females, 3512 males) from Ravansar Non-Communicable Disease (RaNCD) cohort study. Hematological parameters were measured by Beckman Coulter HmX Analyzer. After combined application of exclusion criteria and statistical outlier removal, RIs for all partitions were calculated using nonparametric methods. RESULTS: The present study established hematological RIs for 14 parameters in a healthy adult Iranian population. Reference values for some analytes demonstrated significant age- and sex-specific differences and were slightly different when compared to RIs determined in other populations. Furthermore, the current smokers had higher levels of white blood cells (WBCs), red blood cells (RBCs), hemoglobin, hematocrit, mean corpuscular hemoglobin (MCH), and mean corpuscular volume than ex- and nonsmokers. Also, in the presence of high physical activity, elevated levels of RBC, hemoglobin, hematocrit, monocytes, and MCH were observed, as well as lower WBC levels. Further, a significant positive association was observed between body mass index (BMI) and WBC, red cell distribution width, and plateletcrit levels. CONCLUSION: Our study suggests hematological parameters are influenced by age, sex, and lifestyle factors such as physical activity and BMI. Additionally, discrepancies when compared to other population studies suggest that ethnic-specific differences need to be considered when establishing RIs for hematological parameters.
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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 | 0.002 |
| 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 | 0.001 | 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".