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Updated: Aug 29, 2026
Establishment of a Simple and Effective Rat Model for Intraoperative Parathyroid Gland Imaging
Published on: August 17, 2022
An alternative analysis of intraoperative parathyroid hormone data may improve the ability to detect multiglandular
Paul G Gauger1, Michelle H Mullan, Norman W Thompson
1Division of Endocrine Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, USA. pgauger@umich.edu
Hypothesis:
A nomogram based on regression analysis of intraoperative parathyroid hormone level decay discriminates single gland disease from multiglandular (MG) disease more accurately than the currently used 50% rule.
Design:
Retrospective case series.
Setting:
Academic health center.
Patients:
Two hundred thirty-five patients (222 patients with single gland disease and 13 patients with MG disease) who underwent parathyroidectomy.
Interventions:
Intraoperative parathyroid hormone level analysis at baseline, time 1 (about 5 minutes), and time 2 (about 10 minutes) after excision of the first gland.
Main Outcome Measures:
The mean slope was calculated at time 1 and time 2 and analyzed using one-way analysis of variance and the Fisher least significance difference post hoc tests using data normalized to baseline intraoperative parathyroid hormone levels to compare patients with single gland disease with patients with MG disease. A regression-based nomogram was created to analyze individual kinetic decay data.
Results:
The mean (SEM) single gland disease slope was significantly steeper than the MG disease slope at both time 1 (-0.91 [0.02] vs -0.66 [0.05]; P<.01) and time 2 (-0.77 [0.01] vs -0.56 [0.05]; P<.01). When the standard threshold rule of a 50% decrease from baseline was used, only 23% of the patients with MG disease were correctly predicted by intraoperative parathyroid hormone values (77% false-positive result rate) at time 1. However, the nomogram correctly predicted 54% of the patients with MG disease at time 1 (46% false-positive result rate). At time 2, the standard threshold 50%-rule method correctly predicted 38% of the patients with MG disease (62% false-positive result rate), while the nomogram still correctly classified 54% of the patients with MG disease (46% false-positive result rate).
Conclusions:
A regression-based nomogram incrementally improves prediction of MG disease compared with the standard 50%-rule method and accounts for variability in the exact timing of samples. Slope analysis suggests that the earliest time point best isolates the kinetics of the excised gland. The nomogram will need to be validated prospectively.
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