Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Mixed Reality Technology in Laparoscopic Partial Nephrectomy

St. Petersburg State Pavlov Medical University · 2020
ClinicalTrials.gov · Datasets · License: Public Domain · 2020
Open Source ↗
na
The aim of our study was: a) to evaluate the usefulness of the MR model for renal pedicle exposure and identification of the tumor's exact location during LPN, and b) to evaluate the subjective utility of the MR model as an intraoperative reference tool. Investigators prospectively enrolled 47 patients with LPN between June 2020 and February 2021. Patients were randomly assigned into two groups: the control group (24 patients), who underwent operation with an intraoperative ultrasound (US) control and the experimental group (23 patients), who underwent operation with the aid of the MR model. Randomization was performed using a computerized randomization program and sealed envelopes. Patients were included in the study if they were 18 years of age or older, were able to sign informed consent, and had T1a renal tumors amenable to LPN. Patients were excluded if they were unwilling to participate or did not meet the inclusion criteria. For each patient, investigators prospectively collected demographic data including age, body mass index, clinical tumor size, side, location, and complexity score according to the PADUA scoring system; perioperative data (including time for renal pedicle exposure and time for renal tumor detection and duration of ischemia); pathological data; data on postoperative functional outcome and complications, classified according to the Clavien-Dindo system.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 800708
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive