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Journal of nephrology · 2025

Primary hyperoxaluria type 1 diagnosis in adult dialysis patients: prediction model assessment in a group of Italian patients.

СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Ferraro Pietro Manuel, Arbustini Eloisa, Bellino Diego, Caletti Chiara, Capelli Irene, Capolongo Giovanna, Caruso Maria Rosa, Cianfrone Paola, D'Alessandro Maria Michela, Di Luca Marina, Gambaro Giovanni, Palmisano Alessandra, Ranghino Andrea, Santagostino Barbone Gaia, Viazzi Francesca, Zambianchi Loretta, Mandrile Giorgia

Аннотация

BACKGROUND: To increase the diagnostic rate of primary hyperoxaluria type 1 (PH1) in the adult dialysis setting, a prediction model based on five readily available clinical parameters was recently developed and validated in an adult hemodialysis population. To further test the prediction model in clinical practice, this case series describes the retrospective application of the diagnostic algorithm in a group of adult dialysis patients with PH1 treated at different Italian nephrology centers.

METHODS: Between January and May 2023, adult patients (≥ 18 years) undergoing chronic hemodialysis with a genetic diagnosis of PH1, followed at 14 Italian nephrology centers, were selected for the retrospective application of the prediction model.

RESULTS: The presence of at least one red flag of the diagnostic algorithm was reported in most patients (14 out of 15; 93%), two red flags were present in four patients (27%), and three red flags in two patients (13%). A history of active nephrolithiasis was the most common clinical feature (87% of patients), followed by early dialysis initiation, nephrocalcinosis and a family history of CKD (20-27%).

CONCLUSIONS: Our study provides further evidence on the real-world application of a simple algorithm, implemented by easily accessible clinical parameters, to be used as a screening tool for diagnosing PH1 in adult patients undergoing dialysis. The successful implementation of this prediction model has the potential to facilitate timely diagnosis, improve patient outcomes, and inform targeted therapeutic interventions in this patient setting.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты