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Record W4200401915 · doi:10.1111/cen.14653

Revisiting the role of surgery in the treatment of Graves’ disease

2021· review· en· W4200401915 on OpenAlexaff
Oded Cohen, Ohad Ronen, Avi Khafif, Juan P. Rodrigo, Ricard Simó, Pia Pace‐Asciak, Gregory W. Randolph, Lauge Hjorth Mikkelsen, Luiz Paulo Kowalski, Kerry D. Olsen, Álvaro Sanabria, Ralph P. Tufano, Silvia Babighian, Ashok R. Shaha, Mark Zafereo, Alfio Ferlito

Bibliographic record

VenueClinical Endocrinology · 2021
Typereview
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineGraves' diseaseDiseaseInternal medicineEndocrinologySurgery

Abstract

fetched live from OpenAlex

Graves' disease (GD) can be managed by antithyroid drugs (ATD), radioactive iodine (RAI) and surgery. Thyroidectomy offers the highest success rates for both primary and persistent disease, yet it is the least recommended or utilized option reaching <1% for primary disease and <25% for persistent disease. Several surveys have found surgery to be the least recommended by endocrinologists worldwide. With the development of remote access thyroidectomies and intraoperative nerve monitoring of the recurrent laryngeal nerve, combined with current knowledge of possible risks associated with RAI or failure of ATDs, revaluation of the benefit to harm ratio of surgery in the treatment of GD is warranted. The aim of this review is to discuss possible reasons for the low proportion of surgery in the treatment of GD, emphasizing an evidence-based approach to the clinicians' preferences for surgical referrals, surgical indications and confronting traditional reasons and concerns relating to the low referral rate with up-to-date data.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.188
GPT teacher head0.444
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations21
Published2021
Admission routes1
Has abstractyes

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