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NCT05350423COMPLETEDanonymous

Use of Urinary Biomarkers to Quantify Degree of Renal, Parenchymal and Urothelial Damage During Ureteroscopy

Sponsor

Source record

Icahn School of Medicine at Mount Sinai

Phase

Source record

NA

Modality

AI-normalized

medical device

Target

AI-normalized

Thulium Fibre Laser, Holmium:Yttrium-Aluminum-Garnet

Indication / condition

AI-normalized

Nephrolithiasis

Intervention

Source record

Thulium Fibre Laser, Holmium:Yttrium-Aluminum-Garnet

Source & freshness

Source record

NCT ID

NCT05350423

Original source

ClinicalTrials.gov

Source last updated

Dec 07, 2023

Ingested at

Jun 11, 2026

Internal sync

Jun 11, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

Open original registry record
View original source fields

NCT ID

NCT05350423

Title

Use of Urinary Biomarkers to Quantify Degree of Renal, Parenchymal and Urothelial Damage During Ureteroscopy

Sponsor

Icahn School of Medicine at Mount Sinai

Status

COMPLETED

Phase

NA

Condition raw

Nephrolithiasis

Condition normalized

Nephrolithiasis

Modality raw

medical device

Modality normalized

medical device

Target raw

Thulium Fibre Laser, Holmium:Yttrium-Aluminum-Garnet

Target normalized

Thulium Fibre Laser, Holmium:Yttrium-Aluminum-Garnet

Interventions

Thulium Fibre Laser, Holmium:Yttrium-Aluminum-Garnet

Public preview

Source record

This is an ongoing randomized controlled trial of patients undergoing URSLL with unilateral non-obstructing renal stones. Patients are randomized to undergo URSLL with either the TFL or Ho:YAG laser. Each patient's urine is collected immediately pre-op (V1), 1 hour post-op (V2), and 10 days post-op (POD#10, V3). Samples are analyzed by enzyme-linked immunosorbent assay (ELISA) for the following biomarkers: Kidney injury molecule-1 (KIM-1), Neutrophil gelatinase-associated lipocalin (NGAL), and β2-microglobulin (β2M), then normalized to urine creatinine.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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