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Record W2113093883 · doi:10.1002/pbc.22575

Imaging in pediatric patients: Time to think again about surveillance

2010· article· en· W2113093883 on OpenAlexaff
Amy Lee Chong, Ronald Grant, Bilal Ashfaq Ahmed, Karen E. Thomas, Bairbre Connolly, Mark Greenberg

Bibliographic record

VenuePediatric Blood & Cancer · 2010
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHospital for Sick Children
FundersSociety for Pediatric Radiology
KeywordsMedicinePediatricsMedical physicsMedical emergencyIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Despite concerns regarding ionizing radiation exposures from diagnostic imaging procedures in pediatric patients, many are deemed unavoidable or even mandated by treatment protocols. A prior review at our institution found patients with lymphoma had a higher median cumulative radiation exposure (191 mSv) versus other oncology subgroups (61 mSv). PURPOSE: Estimations of cumulative diagnostic radiation exposures were tabulated for 5 years from the first diagnostic scan for 30 consecutive lymphoma patients diagnosed in 2001. Each individual imaging procedure was reviewed and classified as protocol mandated or discretionary (for disease surveillance, good patient care or radiologist request). RESULTS: Almost all patients (28/29) received chemotherapy; one had surgery only. Individual cumulative radiation exposures ranged from 10 to 642 mSv. Over 5 years, 690 procedures were performed; 303 (44%) X-rays, 203 (29%) CTs, 157 (23%) radionucleotide, and 27 (4%) interventional procedures. Of these, 238 (34%) were protocol required and 452 (66%) discretionary (224 as part of good patient care for a co-morbid illness and 228 for evaluation of possible disease progression/surveillance). A total of 86/217 (40%) studies (including 43 CTs and 38 radionucleotide scans) were performed when the recurrence risk was low (>2 years off therapy). CONCLUSIONS: The majority of ionizing radiation procedures in this lymphoma cohort were discretionary. Given the excellent outcome of this group and the long-term risks; rational use of discretionary surveillance procedures is necessary. Guidelines for the appropriate use of surveillance imaging based on probability of risk recurrence must be developed in order to minimize ionizing radiation exposure.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.242
Teacher spread0.239 · 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.

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

Citations38
Published2010
Admission routes1
Has abstractyes

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