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Record W2413394839

Change in patient doses from radiological examinations at the Vancouver General Hospital, 1991-2002.

2005· article· en· W2413394839 on OpenAlexaffabout
John E. Aldrich, J R Williams

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineRadiological weaponNuclear medicineEffective dose (radiation)Radiation doseRadiology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: Much concern has been expressed over the radiation doses and potential harm from x-ray examinations. However, there have been few longitudinal studies in North America. A survey of doses from radiological examinations in Canada was last carried out in 1995. This study was undertaken to estimate the change in the number of patient examinations and patient dose since this last Canadian survey. METHODS: The number of radiological examinations and numbers of patients for the years 1991 to 2002 were obtained from workload statistics, which are reported to the Canadian government each year. Radiological examinations were of the following type: general, gastrointestinal or genitourinary, angiography, and computed tomography (CT). Average doses were calculated for each group of examinations. RESULTS: From 1991 to 2002 there was an increase of 28% in the total number of x-ray examinations performed. The proportion of most types of examination has stayed fairly constant, except for CT, which has increased fourfold in the last 8 years. The striking change is the increased contribution to patient effective dose from CT since 1996, these examinations now comprising nearly 60% of the total patient dose. The average annual effective dose per patient has nearly doubled-from 3.3 mSv in 1991 to 6.0 mSv in 2002. CONCLUSION: This paper provides a simple method for any Canadian hospital to estimate the radiation dose to its patients. At the Vancouver General Hospital (VGH), the number of patient examinations has increased by 28%, but the average annual patient effective dose has almost doubled. CT is now by far the largest contributor to patient dose in diagnostic radiology. Efforts need to be made to reduce patient dose by such methods as reduction in unnecessary exams, substitution of nonionizing techniques where possible, and optimization of dose.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.240
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2005
Admission routes2
Has abstractyes

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