Hematological Findings in Medical Professionals Involved at Intraoperative Fluoroscopy
Bibliographic record
Abstract
Medical professionals involved at intraoperative fluoroscopy are exposed to low doses of the occupational radiation exposures. The biological effects of chronic low-dose radiation on human health are complex and have not been well established. The aim of the present study is to follow up hematological parameter changes during 2 years in medical professionals exposed to ionization radiation in operating rooms. 22 medical professionals (medical specialists and technicians), chronically exposed to ionizing radiation of mobile C-Arm X ray machine, were selected. The seven hematological parameters were examined each time. The statistical analyses were done by Student’s t test and one way ONOVA test. The data analysis led to the following observations: (1) the present study incorporated that the basic hematological parameters including the mean value of red blood cells (P=0.90), white blood cells (P=0.68), and platelets count (P=0.45) did not show a significant difference between two years. (2) The mean values corpuscular hemoglobin concentration, corpuscular hemoglobin, and hematocrit parameters were found disturbed low or high in some of medical professionals but their means were not significantly different between two measurements. (3)A statistically significant relation in mean value of RBCs with the duration of exposure and sex were observed. It seems that, hematological parameters survey could not be a reliable test as the biological indicator of long term exposure to very low dose of radiation exposure in medical professionals which their physical dosimetry values are lower than dose limits.
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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 | 0.000 |
| 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) | 0.001 | 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".