Remote Multichannel Monitoring of Patients With Chronic DIseAses Using Speech technoLogies Based On Artificial intelliGence

NCT06644339 | Not Yet Recruiting DMC

• 1 other identifier: DIALOG2024
• Study Type: interventional
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

DIALOG is a study to assess the efficacy and safety of remote patient monitoring using virtual operator voice technologies and a business intelligence (BI) system for timely detection, prevention of early complications, worsening of the condition, and other adverse events in patients who have been discharged from the hospital.

Conditions

Heart Failure; Diabetes Mellitus; Arterial Hypertension; Lymphoproliferative Disease; Total Knee Replacement

Keywords

heart failure; diabetes mellitus; arterial hypertension; lymphoproliferative diseases; knee replacement; remote monitoring; mHealth; telemedicine; voice assistant

Outcome Measures

Primary Outcomes (3)

• cardiovascular mortality

  mortality rate

  an average, 1 month after randomization

• all-cause mortality

  mortality rate

  an average, 1 months after randomization

• complications, decompensations

  rate of complications and exacerbations of the main disease

  an average, 1 month after randomization

Secondary Outcomes (3)

• achievement target or maximally tolerated doses

  an average, 1 month after randomization

• satisfaction

  an average, 1 month after randomization

• changes in medical adherence

  an average, 1 month after randomization

Study Arms (5)

Heart Failure

EXPERIMENTAL

Patients with chronic heart failure who was hospitalized due to decompensation of their condition. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, weight) related to heart failure.

Device: Voice assistant

Diabetes mellitus

EXPERIMENTAL

Patients with diabetes mellitus who was hospitalized with unstable glucose level. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, weight, glucose) related to diabetes mellitus.

Device: Voice assistant

Arterial hypertension

EXPERIMENTAL

Patients with arterial hypertension who was hospitalized with unstable arterial pressure. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, hypotension sings, signs of damage to target organs).

Device: Voice assistant

Lymphoproliferative diseases

EXPERIMENTAL

Patients with any lymphoproliferative disease who is undergoing chemotherapy. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate) related to chemotherapy complications.

Device: Voice assistant

Total knee replacement

EXPERIMENTAL

Patients who underwent total knee replacement. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (pain, fever) related to replacement complications.

Device: Voice assistant

Interventions

Voice assistant DEVICE

Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands on the "question-answer" principle. It allows us to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, weight) depending on disease. Follow-up and management of disease provided by specialists at participating institutions.

Arterial hypertension; Diabetes mellitus; Heart Failure; Lymphoproliferative diseases; Total knee replacement

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Disease diagnosed according to the latest Clinical practice guidelines
• Stable condition at the time of discharge from the hospital
• Written informed consent to participate in the study
• Diagnosed dementia or severe cognitive impairment
• The inability to use automatic devices to register blood pressure at home, a blood glucose meter
• Alcohol or drug abuse
• Inability to contact a voice assistant and other study requirements, due to major co-morbidities, social or financial issues, or a history of noncompliance with medical regimens, that might compromise the patient's ability to understand and/or comply with the protocol instructions or follow-up procedures

You may not qualify if:

• Unwillingness of the patient to continue participating in the study

Sponsors & Collaborators

• I.M. Sechenov First Moscow State Medical University: lead
• PJSC VimpelCom: collaborator

Study Sites (1)

Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), University Clinical Hospital No.1

Moscow, 119048, Russia

Location

MeSH Terms

Conditions

Heart Failure; Diabetes Mellitus; Hypertension; Lymphoproliferative Disorders

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Vascular Diseases; Lymphatic Diseases; Hemic and Lymphatic Diseases; Immunoproliferative Disorders; Immune System Diseases

Study Officials

• Maria Kozhevnikova, Professor

  The Sechenov First Moscow State Medical University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Maria Kozhevnikova, Professor

CONTACT

+79265605019; kozhevnikova_m_v@staff.sechenov.ru

Aleksei Emelianov, Assistant

CONTACT

+79998305785; emelyanov_a_v@staff.sechenov.ru

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 3, 2024
• First Posted: October 16, 2024
• Study Start: October 15, 2024
• Primary Completion: February 28, 2025
• Study Completion: April 30, 2025
• Last Updated: October 16, 2024

Record last verified: 2024-10

Data Sharing

• IPD Sharing: Will not share

Locations

RU (1)