Predictors of Hungry Bone Syndrome After Parathyroidectomy in Secondary Hyperparathyroidism: A Narrative Review of Bone Turnover Biomarkers and Risk Prediction Tools.

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.