Use of fluorescent angiography with indocyanine green for prediction of hypocalcemia development after thyroidectomy
Bibliographic record
Abstract
Introduction. The future of thyroid gland fast-track surgery depends largely on early hypocalcemia prediction. We describe our experience of using intraoperative indocyanine green fluorescent angiography (IGFA) of parathyroid glands to access their function in the early postoperative period.The study objective is to evaluate the possibility of prediction of early postoperative hypocalcemia after thyroidectomy using intraoperative indocyanine green fluorescent angiography.Materials and methods. Thirty five (35) patients with benign and malignant thyroid tumors eligible for thyroidectomy were included in the study. Intraoperative IGFA was performed using the SPY SP2000 (Novadaq Technologies Inc., Canada) device and visual assessment of vascularization of the parathyroid glands. The glands without fluorescence were considered ischemic. Ionized calcium test was performed 4, 8, and 18–24 hours after the surgery. Significance of the difference in its levels in patients with normal and ischemic parathyroid glands was evaluated.Results. In 26 patients, vascularization was considered sufficient, in 9 patients the glands were ischemic per the fluorescent examination.Statistically significant difference of ionized calcium levels were observed between groups with ischemic and normal glands at 18 hours after the surgery (mean 1.060 ± 0.53 in ischemic vs. 1.110 ± 0.56 in normal group, p 0.05).Conclusion. Intraoperative IGFA of the parathyroid glands can successfully predict early postoperative hypocalcemia. Further studies for accessing correlation with permanent hypocalcemia are required.
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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 | 0.001 |
| 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 | 0.000 | 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".