Viewing Study NCT06645548



Ignite Creation Date: 2024-10-26 @ 3:43 PM
Last Modification Date: 2024-10-26 @ 3:43 PM
Study NCT ID: NCT06645548
Status: NOT_YET_RECRUITING
Last Update Posted: None
First Post: 2024-10-15

Brief Title: Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care Study 3
Sponsor: None
Organization: None

Study Overview

Official Title: Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care Study 3 - Measure the Accuracy of Weight Estimations by The 3D Camera System in Acutely Ill or Injured Emergency Department Patients and Compare This Accuracy Against That of Standard Care
Status: NOT_YET_RECRUITING
Status Verified Date: 2024-10
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: No
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: None
Brief Summary: The goal of this randomized controlled clinical trial is to compare standard methods of weight estimation and drug dose calculations against weight estimates and dose calculations using a 3D camera weight estimation system in critically ill or injured cohorts of patients presenting to the Emergency Department The main questions it aims to answer are

Are weight estimates from a 3D camera system more accurate than standard methods of weight estimation Do patients who receive weight estimates with a 3D camera system have fewer drug dosing errors than patients receiving standard care

Participants will either receive a weight estimate using a 3D camera system or standard methods of care

Researchers will compare the 3D camera group to those with standard care to see if the weight estimates are more accurate to see if drug dosing is more accurate and to compare the incidence of adverse events related to medications in each group
Detailed Description: Drug dosing errors can have a catastrophic effect in acutely ill patients such as stroke patients needing thrombolytic therapy or patients requiring urgent sedation In an acutely ill patient inaccurate weight estimates are a significant cause of dosing errors and weight estimates that deviate by 10 from actual weight could make treatment itself life threatening Inaccurate weight estimates lead to inaccurate drug doses which can result in potentially fatal treatment failure from subtherapeutic doses or potentially fatal adverse events from supratherapeutic doses Nearly 75 of treatment failures in obese patients may be related to errors in weight estimation When clinical care is time-sensitive it may be impossible to obtain a measured weight in 50 of patients In these circumstances a rapid accurate method for estimating weight is critical One recent innovation is the use of a low-cost 3D camera system to estimate weight The 3D camera device eg Intel RealSense D415 is used to obtain a point cloud map of the patients body from which a weight estimate can be estimated based on algorithms derived using convoluted neural network analysis Initial studies have been extremely promising in terms of the accuracy achievable by this system in estimating Total Body Weight TBW

The primary aim of this study is to measure the accuracy of weight estimations by the 3D camera system in acutely ill or injured ED patients and compare this accuracy against that of standard care The researchers will compare the performance and downstream effects of weight estimation using the 3D camera system against standard care in a randomized controlled trial of acutely ill or injured adults presenting to the ED

The key hypothesis is that the 3D camera system will provide real-time estimates of TBW IBW and LBW in an emergency setting and will exceed the accuracy of existing methods of weight estimation

Supporting non-clinical trial studies will establish the accuracy of the 3D camera system in laboratory conditions and in simulated medical emergencies However its performance and its impact on downstream drug dosing accuracy needs to be established during emergency care in a real clinical setting This study will provide an essential perspective about the accuracy and functioning of the 3D camera system as well as real-world weight estimation during emergency care It will also describe the ability to measure weight using in-bed scales and to obtain weight estimations from patients themselves and family members in ED patients The secondary objective to determine the accuracy of drug doses in each arm of the study will provide critical information on the need for alternative weight scalars in obese and morbidly obese patients presenting to the ED The study will establish the need for standards and policies to guide dose scaling in obese patients in the ED Information on the actual usage of drugs that should be scaled to TBW and those that should be scaled to LBW will provide useful real-world insight into the magnitude of the problem in the threat to patient safety by using a one size fits all approach to drug dose calculations for all patients irrespective of weight status

Acutely ill patients presenting to the ED of a large regional hospital and who require weight-based drug therapy will be enrolled in the study They will be randomised to either receive a weight estimation using a 3D camera system which will provide estimates of TBW IBW and LBW or to receive standard care All other interventions and medical care will be standard care

These patients will be followed for the first 72 hours of their hospital stay The accuracy of the weight estimates will be compared between the groups as will the drug dose accuracy and any adverse events related to drug therapy

Study Oversight

Has Oversight DMC: None
Is a FDA Regulated Drug?: None
Is a FDA Regulated Device?: None
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: None