Prediction of hypocalcemia after using 1‐ to 6‐hour postoperative parathyroid hormone and calcium levels: An analysis of pooled individual patient data from 3 observational studies
Bibliographic record
Abstract
BACKGROUND: Parathyroid hormone (PTH) levels up to 6 hours postthyroidectomy have been shown to have excellent predictive power in determining hypocalcemia. In this study, we investigate the usefulness of combining calcium and PTH to increase the predictive power. METHODS: Individual patient data were obtained from 3 studies (152 patients) that fulfilled our criteria (using PTH assay within hours postthyroidectomy to predict symptomatic hypocalcemia). RESULTS: Changes in combined PTH and calcium threshold levels checked 1 to 6 hours after thyroidectomy were excellent in predicting postoperative hypocalcemia. A decrease in PTH of 60%, coupled with a simultaneous decrease in calcium of 10%, 5 to 6 hours postoperatively resulted in a sensitivity and specificity of 100%. However, combined PTH and calcium threshold changes were not significantly better than using PTH threshold changes alone. CONCLUSIONS: Threshold changes in serum calcium and PTH, checked hours after surgery, can be used together to accurately predict whether a patient will become hypocalcemic after thyroidectomy.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".