Literature DB >> 23102677

Calculating an individual maxPTH to aid diagnosis of normocalemic primary hyperparathyroidism.

Judy Jin1, Jamie Mitchell, Joyce Shin, Eren Berber, Allan E Siperstein, Mira Milas.   

Abstract

BACKGROUND: We aimed to validate a nomogram for diagnosing primary hyperparathyroidism (PHP), particularly when normocalcemic PHP and vitamin D (VitD25) deficiency coexist.
METHODS: The nomogram calculates maximal upper limit of normal PTH unique for each person by maxPTH = 120 - [6*calcium] - [½*VitD25] + [¼*age]. PHP is suspected when serum PTH exceeds maxPTH. Normocalcemic PHP (NCPHP) was defined as always normal serum calcium (8.5-10.5 mg/dL) with PTH >60 pg/mL preoperatively and VitD25 deficiency as <31 ng/mL.
RESULTS: A total of 477 patients had operatively and histologically proven PHP. Overall and including those with classical presentation (high serum levels of calcium and PTH), the nomogram predicted PHP in 97% patients. A total of 66 had NCPHP: 47 with low VitD25 levels (20 ± 0.4 ng/mL) made initial PHP diagnosis challenging; 19 had normal VitD25 status. Although the level of serum calcium concentrations were equivalent in these 2 groups (10.1 ± 0.4 mg/dL), PTH was greater in patients with concurrent VitD25 deficiency (129 vs 97 pg/mL, P = .04). However, when used to calculate maxPTH, the nomogram predicted PHP correctly in all 66 NCPHP patients (100%).
CONCLUSION: The maxPTH nomogram functions as expected to classify patients with PHP and may aid in the diagnosis of NCPHP regardless of vitamin D status and repletion, reassuring primary providers and surgeons alike to embark on appropriate and timely PHP management.
Copyright © 2012 Mosby, Inc. All rights reserved.

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Year:  2012        PMID: 23102677     DOI: 10.1016/j.surg.2012.08.013

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  2 in total

1.  Use of Calcium and Parathyroid Hormone Nomogram to Distinguish Between Atypical Primary Hyperparathyroidism and Normal Patients.

Authors:  Olga A Lavryk; Allan E Siperstein
Journal:  World J Surg       Date:  2017-01       Impact factor: 3.352

2.  Improving diagnostic recognition of primary hyperparathyroidism with machine learning.

Authors:  Yash R Somnay; Mark Craven; Kelly L McCoy; Sally E Carty; Tracy S Wang; Caprice C Greenberg; David F Schneider
Journal:  Surgery       Date:  2016-12-15       Impact factor: 3.982

  2 in total

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