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Record W2039496939 · doi:10.1016/j.otohns.2008.08.014

Incidence and Histopathological Behavior of Papillary Microcarcinomas: Study of 429 cases

2008· article· en· W2039496939 on OpenAlexaff
Michael N. Pakdaman, Louise Rochon, Olguta Gologan, Michael Tamilia, Natasha Garfield, Michael Hier, Martin J. Black, Richard J. Payne

Bibliographic record

VenueOtolaryngology · 2008
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsRoyal Victoria HospitalJewish General HospitalMcGill University
Fundersnot available
KeywordsIncidence (geometry)MedicineSignificant differenceMalignancyStatistical significanceExact testInternal medicineGastroenterologyMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: We aim to present papillary microcarcinoma (PMC) incidence at a university teaching hospital, to compare characteristics of PMC in relation to size, and to assess for significant difference in PMC incidence among patients with non-PMC thyroid malignancies. MATERIALS AND METHODS: Pathology results were reviewed for consecutive total thyroidectomies between 2002 and 2007 (n = 860). Statistical significance was calculated using chi(2) or, when unavailable, Fisher exact test. RESULTS: PMC was found in 429 cases, which is 49.9 percent of all total thyroidectomies. In PMC > or =5 mm, 25.1 percent had extrathyroidal extension vs 9.1 percent for <5 mm (P < 0.001). When 4 mm is used as a threshold, P value was 300-fold smaller. Incidence in patients with any non-PMC thyroid malignancy was 51.6 percent against 47.2 percent in all other patients (P = 0.203). CONCLUSIONS: In this study, PMC was found in 49.9 percent of patients, which, to our knowledge, is higher than any other reported incidence. A threshold of > or =4 mm was more significant than 5 mm for carrying increased risk for extrathyroidal spread. There was no significant difference in PMC incidence in patients with malignant vs benign disease.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.348

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 head0.033
GPT teacher head0.282
Teacher spread0.250 · 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

Citations33
Published2008
Admission routes1
Has abstractyes

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