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Record W2090724727 · doi:10.1002/hed.10165

Correlation of biochemical parameters with single parathyroid adenoma weight and volume

2002· article· en· W2090724727 on OpenAlexaff
Vinita Bindlish, Jeremy L. Freeman, Ian Witterick, L. Sylvia

Bibliographic record

VenueHead & Neck · 2002
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsPrimary hyperparathyroidismParathyroid adenomaAdenomaHyperparathyroidismParathyroid hormoneInternal medicineMedicineEndocrinologyCalciumUrology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the relationship of the biochemical parameters serum phosphate, serum calcium, and serum parathyroid hormone levels with respect to parathyroid adenoma weight and volume in primary hyperparathyroidism. STUDY DESIGN: Retrospective review of 63 cases of primary hyperparathyroidism from 1992 to 1998. METHODS: Single parathyroid adenomas were identified from surgical pathology reports. Preoperative calcium, phosphate, and parathyroid hormone levels were collected from charts. The volume of the adenoma was calculated using a mathematical equation for the volume of an ellipsoid object. The data were analyzed using a multiple analysis of variance, and a correlation coefficient was calculated. The level of significance was set at p < or = .05. RESULTS: With respect to adenoma volume, there was a significant correlation with serum calcium and parathormone levels (p = .0001 and p = .0001, respectively). There was no significant correlation between serum phosphate and adenoma volume. With respect to adenoma weight, there was a significant correlation with serum calcium and parathormone levels (p = .0001 and p = .0001, respectively). There was no significant correlation between serum phosphate and adenoma weight. CONCLUSIONS: Preoperative serum calcium and parathormone levels may be able to predict adenoma weight and volume in primary hyperparathyroidism for a single adenoma.

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 score0.057
Threshold uncertainty score0.377

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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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

Citations69
Published2002
Admission routes1
Has abstractyes

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