Pamidronate: Treatment for Severe Hypercalcemia in Neonatal Subcutaneous Fat Necrosis
Bibliographic record
Abstract
BACKGROUND: Subcutaneous fat necrosis (SCFN) of the newborn is an uncommon disorder that occurs in the first weeks of life after foetal distress. It can be complicated by potentially life-threatening hypercalcemia. Treatments of hypercalcemia have included hydration, furosemide and corticosteroids. Only one report has described the use of intravenous bisphosphonates for this condition. We propose that pamidronate could be the first line therapy for severe hypercalcemia in SCFN. PATIENTS AND RESULTS: Four newborns presented between 2001 and 2004 with SCFN complicated by severe hypercalcemia. At diagnosis, ionized calcium levels were higher than 1.4 mmol/l and were associated with high urinary calcium/creatinine ratios and high 1,25-dihydroxyvitamin D levels. Despite treatment with IV fluids, low calcium diet and furosemide, calcium levels remained high. The patients were given 3-4 doses (0.25-0.50 mg/kg/dose) of pamidronate. Urinary calcium/creatinine ratios and calcium levels decreased within 48-96 h. 1,25-dihydroxyvitamin D levels normalized with resolution of the skin lesions. No persistent nephrocalcinosis was observed. CONCLUSION: Pamidronate is effective, well-tolerated in the short-term and obviates the need for prolonged treatment with furosemide and corticosteroids. To prevent nephrocalcinosis, pamidronate might be considered as first line treatment for severe hypercalcemia in SCFN.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".