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Record W2087587163 · doi:10.1186/1471-2431-14-162

Variability of physicians’ thresholds for neuroimaging in children with recurrent headache

2014· article· en· W2087587163 on OpenAlexafffundabout
Carrie Daymont, Patrick J. McDonald, Kristy Wittmeier, Martin H. Reed, Michael Moffatt

Bibliographic record

VenueBMC Pediatrics · 2014
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsGeorge & Fay Yee Centre for Healthcare InnovationChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersManitoba Health Research Council
KeywordsMedicineNeuroimagingGuidelineMagnetic resonance imagingNeurologyFamily medicineNeurosurgeryClinical PracticePediatricsPsychiatryRadiologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: We sought to determine the extent to which physicians agree about the appropriate decision threshold for recommending magnetic resonance imaging in a clinical practice guideline for children with recurrent headache. METHODS: We surveyed attending physicians in Canada practicing in community pediatrics, child neurology, pediatric radiology, and pediatric neurosurgery. For children in each of six risk categories, physicians were asked to determine whether they would recommend for or against routine magnetic resonance imaging of the brain in a clinical practice guideline for children with recurrent headache. RESULTS: Completed surveys were returned by 114 physicians. The proportion recommending routine neuroimaging for each risk group was 100% (50% risk), 99% (10% risk), 93% (4% risk), 54% (1% risk), 25% (0.4% risk), 4% (0.01% risk). Community pediatricians, physicians in practice >15 years, and physicians who believed they ordered neuroimaging less often than peers were less likely to recommend neuroimaging for the 1% risk group (all p < 0.05). CONCLUSIONS: There is no consensus among pediatric specialists regarding the appropriate decision threshold for neuroimaging in a clinical practice guideline for children with recurrent headache. Because of the impact that individual threshold preferences may have on guidelines, these findings support the need for careful composition of guideline committees and consideration of the role of patient and family preferences. Our findings also support the need for transparency in guidelines regarding how evidence was translated into recommendations and how conflicts were resolved.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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

Citations3
Published2014
Admission routes3
Has abstractyes

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