Relationship between Bone Mineral Density and Maturity Index in Cervical Smears, Serum Estradiol Levels and Body Mass Index
Bibliographic record
Abstract
OBJECTIVES: Osteoporosis is a systemic skeletal disease with a consequent increased risk of fracture, decreased quality of life and economic burdens for both the patients and health care system. While Dual energy X-Ray absorptiometry remains the gold standard for assessment of bone mineral density, it cannot be requested for all patients for obvious reasons. By determining other variables that may correlate with osteoporosis, we can identify individuals who may be at risk for osteoporosis earlier. Then, they can be treated at the earlier stages of the disease. In the present study, relationships between bone mineral density, maturity index in cervical smear, serum estradiol level and body mass index were examined. MATERIALS & METHODS: The present study performed on 128 women, who had been referred for bone mineral densitometry. Blood samples were obtained for determination of serum estradiol level. Cervical smear was taken for assessment of cell's maturity. Cervical smears were examined by a pathologist and were sorted as atrophic or mature. Body mass index was calculated too. Relationships among Body mass index, serum estradiol level, and maturity index and bone mineral densitometry were analyzed using proper statistical tests. RESULTS: Maturity index had significant relationship with T Score in the spine and femoral neck (P<0.001). Significant relationships were found between serum estradiol level and femoral neck T Score (P<0.004) and spine T Score (P<0.008). Also a significant relationship was found between body mass index and bone mineral density. CONCLUSION: Pap smear is a routine examination which is performed mainly for screening purposes in gynecology. It is non-invasive, simple and low-priced. Results of current study suggest that women with atrophic cervical smear should be examined more rigorously for osteoporosis. If any patient has atrophic maturity index in her cervical smear, she will be at much higher risk of osteoporosis.
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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 | 0.000 | 0.000 |
| 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".