Predictability of Hypocalcemia Using Early Postoperative Serum Calcium Levels
Bibliographic record
Abstract
OBJECTIVE: In operations involving the thyroid or parathyroid glands, postoperative serum calcium levels are one contributing factor to patients' length of hospital stay. In this study, we wanted to determine whether early postoperative serum calcium levels could be used to predict hypocalcemia following operations of the thyroid or parathyroid glands. METHODS: A retrospective chart review was performed on 203 patients who had undergone operations involving risk to the parathyroid glands. This included patients who had bilateral thyroid operations or those who had one or more parathyroid glands removed for various disease processes. Postoperative calcium levels were plotted as a function of time, and the slope between the first two levels was examined. Both serum calcium levels were drawn within 12 hours after the operation. RESULTS: A positive slope predicted normocalcemia in 100% of patients undergoing thyroid or parathyroid procedures. A negative slope was predictive in magnitude. Patients who developed hypocalcemia had an average slope two to three times more negative than those remaining normocalcemic. CONCLUSIONS: It appears that early serum calcium levels may be predictive for postoperative hypocalcemia in operations that put the parathyroid glands at risk.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".