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Record W2395895478

Incidence of parathyroid tissue in level VI neck dissection.

2011· article· en· W2395895478 on OpenAlexaff
Cavanagh Jp, Martin Bullock, Hart Rd, Trites, Taylor Sm

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineNeck dissectionHypoparathyroidismParathyroidectomyThyroidIncidence (geometry)ThyroidectomyThyroid diseaseSurgeryParathyroid hormoneDissection (medical)Parathyroid glandCarcinomaPathologyInternal medicineCalcium
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Level VI central neck dissections are commonly completed with thyroidectomy. This procedure involves risk of damage to, or incidental excision of, one or more of the parathyroid glands. METHODS: This study examined the pathology reports of patients undergoing thyroid surgery to determine the incidence of parathyroid tissue associated with level VI neck dissections and the risk factors associated with incidental parathyroidectomy. RESULTS: Ninety pathology specimens were analyzed. The incidence of parathyroid tissue associated with level VI neck dissections was 41.4%. We discovered that a higher frequency of incidental parathyroid tissue was located in level VI neck dissections among patients discovered to have malignant thyroid disease. There was no significant association between incidental parathyroidectomy and the sex of the patient, the age of the patient, the type of thyroid surgery, or transient or permanent hypoparathyroidism. CONCLUSION: A large percentage of level VI neck dissections in thyroid surgery were associated with incidental parathyroid tissue. A more detailed examination of surgical specimens may decrease this possibly preventable surgical complication.

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 score0.104
Threshold uncertainty score0.505

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 head0.078
GPT teacher head0.261
Teacher spread0.183 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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