Lifetime exposure to radiation from imaging investigations.
Bibliographic record
Abstract
OBJECTIVE: To assess levels of radiation exposure from diagnostic imaging among family practice patients, the degree to which these levels exceed recommended levels, and whether radiation exposure level is associated with a diagnosis of cancer. DESIGN: Chart abstraction. SETTING: Six practices in an academic family medicine centre and 1 family practice in the community. PARTICIPANTS: Two hundred fifty patients between the ages of 45 and 65 years with at least 20 years' information on their charts. MAIN OUTCOME MEASURES: All x-ray procedures, the dates they were performed, the amount of radiation exposure from each procedure based on standard charts, and whether diagnosis of any form of cancer was noted on the chart. RESULTS: Mean lifetime radiation exposure was 14.94 mSv. No patients had exceeded the lifetime occupational limit of 400 mSv; however, 4.4% of patients had exceeded the annual occupational exposure limit of 20 mSv at some point in their lives. Mean lifetime exposure of those with cancer was found to be significantly higher than exposure of those without cancer. This difference was due to the extra radiation exposure after the cancer was diagnosed; hence a causal relationship was not shown. Mean level of annual radiation exposure from diagnostic imaging has been slowly increasing since the 1960s. CONCLUSION: The current lifetime level of radiation to which patients are exposed by diagnostic imaging appears to be far below the maximum recommended level. Some patients do exceed the maximum recommended annual level, but this overexposure is generally warranted due to serious medical illness or injury, and the benefit outweighs the risk. We found no evidence of an association between these low levels of radiation and development of cancer.
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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 | 0.010 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".