A Positive Parathyroid Washout May Obviate the Need for Nuclear Scintigraphy in Parathyroid Adenoma Localization: A Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Minimally invasive parathyroidectomy (MIP) in patients with a parathyroid adenoma (PA) requires imaging modalities for precise localization. Parathyroid hormone assay on ultrasound-guided fine-needle aspiration washout, or PTH washout, can be used for this purpose. It is unclear whether PTH washout complements traditional PA localization techniques such as a sestamibi (MIBI) scan or diminishes its need. This study aims to determine whether a positive PTH washout obviates the need for an MIBI scan in the preoperative localization of a PA. METHOD: A multi-center retrospective, comparative review comprised adult patients who underwent MIP at 2 McGill University teaching hospitals between 2018 and 2022. Patients who had both PTH washout and MIBI scan for preoperative localization of PA, final histopathology reports available, and preoperative/postoperative results recorded were included in the final analysis. RESULTS: Of the 193 patients' charts reviewed, 87 were included in this study. Of these 87 patients, 74.7% (65/87) had a positive PTH washout result. Among those, MIBI correctly detected 90.8% (59/65) of the PAs. The MIBI scan did not contribute meaningful information for any of the 65 patients who had positive PTH washout results. CONCLUSION: These findings strongly support the use of preoperative dedicated ultrasound as the initial standard procedure. When a PA candidate on ultrasound is found, a PTH washout should be performed. If positive, it could suffice as the sole localization method for MIP surgery. When a PA was identified on ultrasound and confirmed with PTH washout, the MIBI scan did not add more information. Benefits include fewer patient tests, less exposure to ionizing radiation, and reduced healthcare expenses.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".