Hungry bone syndrome after parathyroid surgery
Bibliographic record
Abstract
INTRODUCTION: Data on the incidence rates of hungry bone syndrome after parathyroidectomy in patients on dialysis are inconsistent, as the published rates vary from 15.8% to 92.9%. METHODS: Between 2009 and 2019, 120 hemodialysis patients underwent parathyroidectomy for secondary hyperparathyroidism at the Chang Gung Memorial Hospital. The patients were stratified into two groups based on the presence (n = 100) or absence (n = 20) of hungry bone syndrome after parathyroidectomy. FINDINGS: Subtotal parathyroidectomy was the most common surgery performed (76.7%), followed by total parathyroidectomy with autoimplantation (23.3%). Pathological examination revealed parathyroid hyperplasia. Hungry bone syndrome developed within 0.3 ± 0.3 months and lasted for 11.1 ± 14.7 months. After surgery, compared with patients without hungry bone syndrome, patients with hungry bone syndrome had lower levels of nadir corrected calcium (P < 0.001), as well as lower nadir (P < 0.001) and peak (P < 0.001) intact parathyroid hormone levels. During 59.3 ± 44.0 months of follow-up, persistence and recurrence of hyperparathyroidism occurred in 25 (20.8%) and 30 (25.0%) patients, respectively. Furthermore, patients with hungry bone syndrome had a lower rate of persistent hyperparathyroidism than those without hungry bone syndrome (P < 0.001). Four patients (3.3%) underwent a second parathyroidectomy. Patients with hungry bone syndrome received fewer second parathyroidectomies than those without hungry bone syndrome (P < 0.001). Finally, a multivariate logistic regression model revealed that the preoperative blood ferritin level was a negative predictor of the development of hungry bone syndrome (P = 0.038). DISCUSSION: Hungry bone syndrome is common (83.3%) after parathyroidectomy for secondary hyperparathyroidism in patients undergoing hemodialysis, and this complication should be monitored and managed appropriately.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".