SUN-756 Diagnosing and Treating Hereditary Hypophosphatemia Rickets with Hypercalciuria
Notice bibliographique
Résumé
Abstract Disclosure: S. Dickerman: None. F.A. Al-Khayer: None. Introduction: Hereditary hypophosphatemia rickets with hypercalciuria (HHRH) is a rare autosomal recessive disorder with an estimated prevalence of 1 in 250,000 caused by mutations in the SLC34A3 gene that clinically manifests as rickets, bone pain, and hypercalciuria. This disorder may present similarly to more common disease states such as osteomalacia or osteoporosis, making its diagnose difficult and often tenuous. Clinical Case: This is the case of a 39-year-old female patient with a complex past medical history significant for renal stones since childhood and pancreatoduodenectomy in 2022 due to a dysplastic pancreatic lesion who initially presented to the office in 2024 with low phosphate, normal alkaline phosphatase, normal B6, high calcitriol, and hypercalciuria. Initial diagnoses considered based on these results included Fanconi syndrome, x-linked hypophosphatemia, nutritional or tumor-induced osteomalacia, and hereditary Vitamin D resistance. However, none of these conditions were consistent with her presenting symptoms and lab values. To work up the etiology of her presentation, the tubular reabsorption of phosphorus (TRP) was calculated using TRP=100(1-[quarinePO4/UCr])(serum Cr/serum PO4). When serum phosphate is low, it is expected that renal phosphate absorption and TRP will increase, yet this patient had a calculated TRP of 15. The tubular maximum reabsorption of phosphate (TmP) was then calculated using TmP=(TRP)(serum PO4), yielding 27. The ratio of TmP/eGFR was calculated to be 0.4, with a normal ratio for females being 3-4.45, 5-4 standard deviations below the age-related mean. Further, the upper limit of normal calcium excretion in 24 hours is 4mg/kg and this patient’s excretion was calculated to be 9.4mg/kg. An excretion rate greater than 8.6mg/kg is consistent with HHRH, as is the low ratio of Tmp/eGFR. The patient was treated with potassium phosphate supplementation. This successfully led to the correction of all the above abnormalities except for the decreased TmP/eGFR ratio and improvement of her symptoms. The diagnosis was later confirmed by detecting the pathogenic SLC34A3 mutation. Conclusion: Making the diagnosis of HHRH is challenging and requires an extensive and often timely workup. This case details the diagnostic process and key findings associated with HHRH: phosphate wasting which causes an appropriately elevated level of calcitriol, increased calcium intestinal absorption, suppression of PTH, hypercalciuria, and phosphate deficiency acting as a potent and direct stimulus to renal 25-hydroxyvitamin D-1-alpha hydroxylase (CYP27B1) activity. Treatment of HHRH and correction of these abnormalities may be accomplished utilizing phosphate supplementation. This case report offers a diagnostic schema for making an obscure diagnosis. Presentation: Sunday, July 13, 2025
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».