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Record W1964448586 · doi:10.1148/radiol.2015140620

Thyroid Biopsy Specialists: A Quality Initiative to Reduce Wait Times and Improve Adequacy Rates

2015· article· en· W1964448586 on OpenAlexaff
Sangeet Ghai, Stefanie Lee, P M Bret, Ravi Menezes, Scott Boerner, Yongheng Jia, Kulsoom A. Maan, Rudolf Boci, Wasim Javed, Mostafa Atri

Bibliographic record

VenueRadiology · 2015
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsToronto General HospitalWomen's College HospitalUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineThyroid nodulesCytopathologyBiopsyInstitutional review boardWaiverThyroidRadiologyFine-needle aspirationSurgeryCytologyInternal medicinePathology

Abstract

fetched live from OpenAlex

PURPOSE: To develop and implement a program where selected sonographers would be trained to perform thyroid biopsies independently under the supervision of a radiologist, with the goal of improving efficiency and quality. MATERIALS AND METHODS: Institutional research ethics board approval was obtained for this retrospective study, with waiver of informed consent. After approval from the relevant regulatory bodies, four sonographers successfully completed a training program and began to perform all thyroid biopsies (with informed consent) in a room adjacent to the main radiologist-run biopsy room, where the radiologist was available for backup as needed. In the preimplementation period (January 2010 to April 2011), 1321 nodules were biopsied, 29 of which included on-site cytopathology assessment. In the postimplementation period (August 2011 to July 2012), 1347 nodules were biopsied, 103 of which underwent on-site cytopathology assessment. Wait times and adequacy rates were calculated for both periods. RESULTS: Patient wait times decreased from a mean of 80-90 days before implementation of the thyroid biopsy specialist program to 20-30 days afterward. The percentage of adequate samples improved from 74.6% (985 of 1321 nodules) to 78.6% (1059 of 1347 nodules), with a P value of .015 (74.1% [957 of 1292 nodules] to 77.5% [964 of 1244 nodules] when excluding nodules with on-site cytopathology assessment, P = .0497). The percentage of malignant samples showed no significant change in the two time periods, 5.1% (68 of 1321 nodules) before implementation of the program versus 5.4% (73 of 1347 nodules) after implementation, P = .823 (5.1% [66 of 1292 nodules] vs 5.3% [66 of 1244 nodules] in the respective time periods when excluding nodules with on-site cytopathology assessment, P = .888). No major procedural complications occurred. CONCLUSION: Sonographers can be successfully trained to perform ultrasonography-guided thyroid biopsies safely under the supervision of a radiologist, which can improve wait times and adequacy rates.

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 score0.532
Threshold uncertainty score0.548

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 head0.064
GPT teacher head0.364
Teacher spread0.300 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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