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Updated: Jan 11, 2026

Generation of Hypoparathyroid Rats via Carbon-Nanoparticle-Assisted Parathyroidectomy
Published on: July 14, 2023
Predictors of Hungry Bone Syndrome After Parathyroidectomy in Secondary Hyperparathyroidism: A Narrative Review of
Adina Coman1,2,3, Cristi Tarta1, Alexandru Isaic1
1Researching Future Surgery II Research Center, Department X, Discipline of General Surgery II, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy Timisoara, E. Murgu Square, No. 2, 300041 Timisoara, Romania.
Abstract:
Background/Objectives: Secondary hyperparathyroidism (SHPT) affects 30-50% of end-stage renal disease patients. Parathyroidectomy (PTX), while effective for medication-refractory SHPT, carries 20-70% risk of hungry bone syndrome (HBS)-severe sustained hypocalcemia requiring intensive care and prolonged hospitalization. Accurate preoperative risk stratification using biochemical markers and validated prediction tools is critical for optimal preventive management. Methods: We conducted a comprehensive narrative review synthesizing evidence on HBS predictors after PTX in SHPT, evaluating traditional and novel bone turnover markers, clinical risk factors, and multivariate prediction models, through a structured literature search and analysis. Results: Preoperative bone turnover status represents the strongest contributor to HBS risk. Traditional biomarkers-particularly parathyroid hormone (PTH > 1000-2400 pg/mL) and alkaline phosphatase (ALP > 150-300 U/L)-demonstrate moderate-to-strong individual predictive power. Novel bone turnover markers (bone-specific ALP, P1NP, TRAP-5b) offer incremental value, especially in CKD populations where renal clearance affects traditional markers. Combined risk prediction models substantially outperform single biomarkers, achieving area under curve values of 0.87-0.95. The simple NYU 2-point score (ALP > 150 U/L + PTH > 1000 pg/mL) showed 96.8% accuracy, with 100% negative predictive value. More complex tools like nomograms (C-index 0.92-0.94) and machine-learning algorithms (AUC 0.88) provide enhanced discrimination by integrating multiple continuous parameters. Additional clinical factors-younger age (<48 years), prolonged dialysis (≥5 years), low preoperative calcium, high gland weight, and absence of autotransplantation-further refine risk assessment. Postoperative calcium typically reaches nadir at 48-72 h, defining the critical monitoring window. Conclusions: High-turnover bone biomarkers and combined risk models effectively identify high-risk SHPT patients. Risk-stratified protocols (i.e., prophylactic supplementation, intensive monitoring, and selective ICU admission) can substantially reduce HBS-related morbidity. Ongoing efforts should focus on validating these predictive tools across diverse populations and integrating them into clinical practice, thereby facilitating real-time HBS risk assessment and protocol-driven care.
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