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Record W2036369627 · doi:10.1097/dcr.0000000000000123

Development and Implementation of a Synoptic MRI Report for Preoperative Staging of Rectal Cancer on a Population-Based Level

2014· article· en· W2036369627 on OpenAlexaffabout
Erin Kennedy, Laurent Milot, Mark Fruitman, Eisar Al‐Sukhni, G Dimitri N Heine, Selina Schmocker, Gina Brown, Robin S. McLeod

Bibliographic record

VenueDiseases of the Colon & Rectum · 2014
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsLunenfeld-Tanenbaum Research InstituteSt Joseph's Health CentreUniversity of TorontoSunnybrook Health Science CentreMount Sinai Hospital
FundersNational Institute for Health and Care Research
KeywordsMedicineColorectal cancerSurgical oncologyColorectal surgeryGeneral surgeryProctoscopyRadiologyCancerPopulationRectumMedical physicsSurgeryAbdominal surgeryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Colorectal cancer physician champions across the province of Ontario, Canada, reported significant concern about appropriate selection of patients for preoperative chemoradiotherapy because of perceived variation in the completeness and consistency of MRI reports. OBJECTIVE: The purpose of this work was to develop, pilot test, and implement a synoptic MRI report for preoperative staging of rectal cancer. DESIGN: This was an integrated knowledge translation project. SETTINGS: This study was conducted in Ontario, Canada. PATIENTS: Surgeons, radiologists, radiation oncologists, medical oncologists, and pathologists treating patients with rectal cancer were included in this study. INTERVENTIONS: A multifaceted knowledge translation strategy was used to develop, pilot test, and implement a synoptic MRI report. This strategy included physician champions, audit and feedback, assessment of barriers, and tailoring to the local context. A radiology webinar was conducted to pilot test the synoptic MRI report. MAIN OUTCOME MEASURES: Seventy-three (66%) of 111 Ontario radiologists participated in the radiology webinar and evaluated the synoptic MRI report. RESULTS: A total of 78% and 90% radiologists expressed that the synoptic MRI report was easy to use and included all of the appropriate items; 82% noted that the synoptic MRI report improved the overall quality of their information, and 83% indicated they would consider using this report in their clinical practice. An MRI report audit after implementation of the synoptic MRI report showed a 39% improvement in the completeness of MRI reports and a 37% uptake of the synoptic MRI report format across the province. LIMITATIONS: Radiologists evaluating the synoptic MRI report and participating in the radiology webinar may not be representative of gastroenterologic radiologists in other geographic jurisdictions. The evaluation of completeness and uptake of the synoptic MRI reports is limited because of unmeasured differences that may occur before and after the MRI. CONCLUSIONS: A synoptic MRI report for preoperative staging of rectal cancer was successfully developed and pilot tested in the province of Ontario, Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.371
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2014
Admission routes2
Has abstractyes

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