Prospective Study on Individualized Dose Adjustment of Tolvaptan Based on Urinary Osmolality in Patients With ADPKD

Roca Oporto, F.J.; Andrades Gómez, C.; Montilla Cosano, G.; Aguilera, A. Luna; Rocha, José L.

doi:10.1016/j.ekir.2024.01.020

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…For patients with ADPKD, this measure can vary significantly due to factors affecting kidney function [53] and treatment effects [54,55]. Clinical trials have noted marked increases in the 24 h urine volume to a median of 6 L/day during tolvaptan treatment [54][55][56]. Furthermore, increased hydration-recommended at approximately 2 to 3 L daily-can suppress vasopressin levels and potentially slow ADPKD progression [57].…”

Section: Urine Output and Ureteral Jet Effectmentioning

confidence: 99%

A Primer for Utilizing Deep Learning and Abdominal MRI Imaging Features to Monitor Autosomal Dominant Polycystic Kidney Disease Progression

Zhu,

He,

Blumenfeld

et al. 2024

Biomedicines

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Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment’s efficacy. Deep learning for segmenting the kidneys has improved these measurements’ speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease.

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