Secondary Hyperparathyroidism Presenting with Vocal Cord Paralysis
Bibliographic record
Abstract
ABSTRACT The association of vocal cord paralysis with tumors in the neck generally raises the suspicion of an underlying malignancy. We report the clinical course, imaging and operative findings in a patient with secondary hyperparathyroidism presenting with vocal cord paralysis. The related literature is also reviewed. A 45-year-old man with end-stage renal failure was awaiting surgical treatment for secondary hyperparathyroidism. Ultrasound of the neck demonstrated hypoechoic nodules consistent with enlarged parathyroid glands. Several months later, just before the scheduled date for parathyroid surgery, he developed increasing hoarseness and vocal fatigue. Direct laryngoscopy revealed an immobile left vocal cord (VC). Neck examination and further imaging did not reveal the source of VC palsy. A presumptive diagnosis of thyroid or parathyroid malignancy involving the recurrent laryngeal nerve (RLN) was made. Intraoperatively, four enlarged parathyroid glands were encountered. The left superior gland was seen stretching and displacing the RLN without evidence of direct invasion. This was successfully dissected off while preserving the RLN. The remaining three parathyroid glands were subsequently removed with autotransplantation of a parathyroid remnant. In addition, a left thyroid lobectomy and ipsilateral level VI dissection was performed. Final pathology revealed parathyroid hyperplasia and thyroid follicular adenoma. No malignancy was seen. Three weeks later, the patient's biochemistry had normalized and his voice improved. Laryngoscopy confirmed a mobile left VC. Benign parathyroid tumors are rarely associated with RLN compression leading to VC paralysis. Such diagnoses are difficult to make preoperatively. In the absence of malignant invasion, the RLN should be preserved during surgery as it is likely to recover once the compression is relieved.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".