Subtotal Parathyroidectomy and Relocation of the Parathyroid Remnant for Renal Hyperparathyroidism: Modification of a traditional operation
Bibliographic record
Abstract
BACKGROUND: We describe a modification of the conventional subtotal parathyroidectomy operation where the parathyroid gland(s) remnant is repositioned with intact vascular supply to a plane superficial to the infrahyoid strap muscles and immediately under the skin incision. This technique called Subtotal Parathyroidectomy and Remnant Relocation (SPARE) retains all the metabolic advantages of the conventional operation with the added advantage of easier identification of a recurrent hyperplastic remnant if re-exploration becomes necessary. METHODS: In the SPARE technique, four parathyroid glands were identified and the quality of each gland and the length of each vascular pedicle to the parathyroid glands were assessed. The optimal parathyroid gland was relocated to a plane superficial to the strap muscles. The remainder of the glands were removed. RESULTS: In total, 30 patients with hyperparathyroidism secondary to renal failure (HSRF) underwent parathyroidectomy with the SPARE technique. The mean age was 53.1±12.5 years and median follow-up was 17.1 months (range 1-78.9 months). There were no recurrent laryngeal nerve (RLN) injuries or hematomas. The pre- and post-operative value for corrected calcium and PTH were 158.4±109.4 pmol/L and 11.4±12.1 pmol/L, respectively (p < 0.05). Three recurrences were noted (10.0%), with a mean time to recurrence of 15.3±6.6 months. One patient had excision of the remnant parathyroid glands performed under local anaesthetic (29 min); one had re-exploration performed under general anaesthetic (81 min), and one was managed medically. CONCLUSION: We described a novel parathyroidectomy technique for patients with HSRF, which provides the advantages of conventional subtotal parathyroidectomy while mitigating the challenges of thyroid bed re-exploration when recurrences arise.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".