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Record W2094030052 · doi:10.1016/j.otohns.2007.11.021

Cost savings associated with post‐thyroidectomy parathyroid hormone levels

2008· article· en· W2094030052 on OpenAlexaff
Valérie Côté, Noah Sands, Michael P. Hier, Martin J. Black, Michael Tamilia, Elizabeth MacNamara, Xun Zhang, Richard J. Payne

Bibliographic record

VenueOtolaryngology · 2008
Typearticle
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsMcGill UniversityMontreal Children's HospitalJewish General Hospital
Fundersnot available
KeywordsMedicineParathyroid hormoneThyroidectomyInternal medicineVitamin D and neurologyHypoparathyroidismCalciumEndocrinologyUrologyThyroid

Abstract

fetched live from OpenAlex

OBJECTIVES: A 1-hour post-thyroidectomy parathyroid hormone (PTH) level of < or =8 ng/L is predictive of patients who will develop hypocalcemia and guides early supplementation with calcium and vitamin D. However, most hypocalcemic patients fail to meet this criterion. The goal of this study was to determine whether PTH < or = 15 ng/L could be used as a better predictor of hypocalcemia. STUDY DESIGN, SUBJECTS, AND METHODS: This retrospective study involved 270 thyroidectomy patients (2004-2006). PTH and calcium levels, length of admission, supplementation, and rates of hypocalcemia were recorded. RESULTS: Forty-three percent (26/60) of patients developing hypocalcemia met the PTH < or = 8 ng/L cut-off. In contrast, 80% (48/60) of patients developing hypocalcemia had a PTH < or = 15 ng/L. Two point two percent of patients had a 1-hour PTH < or = 15 ng/L and failed to develop hypocalcemia, for a specificity of 97%. CONCLUSIONS: A 1-hour PTH cut-off of < or =15 ng/L for prophylactic supplementation should allow the prevention of the majority of cases of hypocalcemia, leading to significant cost savings by shortening hospital stays.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.044
GPT teacher head0.269
Teacher spread0.225 · 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.

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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