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
Section of Nephrology, Department of Medicine, Università degli Studi di Verona, Piazzale L.A. Scuro 10, 37134, Verona, Italy.
Center for Inherited Cardiovascular Diseases, Scientific Department, IRCCS Foundation, Policlinico San Matteo, Pavia, Italy.
J Nephrol. 2025 Jun 4. doi: 10.1007/s40620-025-02243-3.
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.
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.
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%).
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.
为提高成人透析患者中1型原发性高草酸尿症（PH1）的诊断率，最近开发了一种基于五个易于获得的临床参数的预测模型，并在成人血液透析人群中进行了验证。为了在临床实践中进一步测试该预测模型，本病例系列描述了诊断算法在一组于意大利不同肾脏病中心接受治疗的成年PH1透析患者中的回顾性应用。
在2023年1月至5月期间，选择了在14个意大利肾脏病中心接受随访、经基因诊断为PH1的成年慢性血液透析患者（≥18岁），以回顾性应用该预测模型。
大多数患者（15例中的14例；93%）报告存在诊断算法的至少一个警示信号，4例患者（27%）存在两个警示信号，2例患者（13%）存在三个警示信号。活动性肾结石病史是最常见的临床特征（87%的患者），其次是早期开始透析、肾钙质沉着症和慢性肾脏病家族史（20 - 27%）。
我们的研究为一种简单算法在现实世界中的应用提供了进一步证据，该算法由易于获取的临床参数组成，可作为诊断接受透析的成年患者PH1的筛查工具。该预测模型的成功应用有可能促进及时诊断、改善患者预后，并为该患者群体的靶向治疗干预提供依据。
