Predicting Calcium Status Post Thyroidectomy with Early Calcium Levels
Bibliographic record
Abstract
OBJECTIVE: The study goals were to predict postoperative normocalcemia and hypocalcemia after total thyroidectomy using calcium levels and to assess the value of a standardized protocol in managing the total thyroidectomy patient. STUDY DESIGN: We conducted a prospective study encompassing 68 patients undergoing a total thyroidectomy using a standardized protocol. Blood to measure postoperative calcium levels was drawn at 6, 12, and 20 hours and then twice daily thereafter. Calcium slope was calculated from the 6- and 12-hour serum corrected calcium levels. RESULTS: Logistic regression analysis allowed the comparison of the 6- and 12-hour calcium slope versus proportion of normocalcemic patients postoperatively. A slope of +0.02 had a 97% chance of remaining normocalcemic (p = 0.0007). CONCLUSION: Successful prediction of calcium status post total thyroidectomy can be achieved using the slope of the 6- and 12-hour calcium levels. The risk of developing severe hypocalcemia can also be predicted with these slope values. Implementation of the protocol resulted in a significant reduction in the duration of hospital stay for patients who remain normocalcemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".