An Optimal Algorithm for Intraoperative Parathyroid Hormone Monitoring

Background: A minimally invasive approach to primary hyperparathyroidism is equivalent to bilateral exploration when intraoperative parathyroid hormone (IOPTH) monitoring is used. The optimal strategy for the monitoring has been debated. Hypothesis: There exists an optimal strategy for IOPTH monitoring. Design: Retrospective study. Setting: Tertiary referral hospital. Patients and Methods: A total of 1882 patients underwent parathyroidectomy for primary hyperparathyroidism with IOPTH monitoring. Successful exploration was defined as a 50% or more decline in IOPTH level from baseline and a normal or near-normal IOPTH level at 10 minutes postexcision. These results were compared with those of alternative strategies for IOPTH monitoring, including a 50% decline at 10 minutes, 50% decline at 5 minutes, and normal IOPTH levels at 10 minutes, using the preoperative parathyroid level as baseline. Results: A curative operation was performed in 1830 patients (97.2%). The current strategy had a sensitivity of 96% and an accuracy of 95%. Multiglandular disease was present in 271 patients (14.5%); 134 of 1858 patients (7.2%) whose outcomes failed to reach curative criteria had confirmed multiglandular disease. Using only a 50% decline from baseline as the curative criterion would result in a failed operation in 22.4% of patients with multiglandular disease. A 50% decline at 10 minutes was 96% sensitive and 94% accurate. A 5-minute value was 79% sensitive and 80% accurate. With use of the 5-minute value, unnecessary bilateral exploration would have been performed in 272 of 1460 patients (18.6%) compared with 62 of 1750 patients (3.5%) when using a 10-minute value. A normal 10-minute value is 91% sensitive and 90% accurate. Conclusions: A 10-minute postexcision IOPTH level that decreased 50% from baseline and is normal or near normal is highly successful. Relying on a 50% decrease alone increases the rate of operative failure in patients with multiglandular disease.