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Record W2055007095 · doi:10.2310/7070.2005.34505

Postoperative Parathyroid Hormone Levels in Conjunction with Corrected Calcium Values as a Predictor of Post-Thyroidectomy Hypocalcemia: Review of Outcomes 1 Year after the Implementation of a New Protocol

2005· article· en· W2055007095 on OpenAlexaffvenue
Richard J. Payne, Michael P. Hier, Valérie Côté, Michael Tamilia, Elizabeth MacNamara, Martin J. Black

Bibliographic record

VenueThe Journal of Otolaryngology · 2005
Typearticle
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineParathyroidectomyParathyroid hormoneThyroidectomyCalciumUrologySurgeryHypoparathyroidismThyroidInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the effectiveness of post-thyroidectomy parathyroid hormone (PTH) levels in conjunction with corrected calcium values as predictors of patients at risk of developing hypocalcemia. METHODS: This is a follow-up study reviewing the results of a newly implemented post-thyroidectomy algorithm. The changes in management from the previous protocol involve decision making based on the 12-hour corrected calcium and PTH levels, as well as the 1-hour PTH value. The study involved 120 patients separated into two groups: 60 prior to implementation of the protocol and 60 following the implementation of the protocol. Patients having completion thyroidectomy, neck dissections, or parathyroidectomy were excluded. RESULTS: Since the implementation of the new protocol, there has been a reduction in the rate of transient hypocalcemia (25% to 12%; p = .059), fewer blood tests (23 to 15 per patient), and earlier patient discharges. CONCLUSIONS: The new algorithm is effective in detecting patients who are not at risk of developing hypocalcemia at 12 hours. This has led to significant cost savings at our institution. Moreover, calcium supplementation based on the 1-hour PTH level has coincided with a reduction in cases of transient hypocalcemia.

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)0.000
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 score0.624
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.330
Teacher spread0.311 · 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

Citations30
Published2005
Admission routes2
Has abstractyes

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