Artificial Intelligence-Based Disease Management in the Vulnerable Period of Heart Failure

Heart Failure Clinical Trial

— AIDMy-HF  

Official title:

Artificial Intelligence-Based Disease Management in the Vulnerable Period of Heart Failure, An Observational Study to Evaluate Patient Speech and Voice in the Vulnerable Phase of Heart Failure

Clinical Trial Details — Status: Enrolling by invitation

Administrative data

• NCT number: NCT05544006
• Other study ID #: 101052022
• Status: Enrolling by invitation
• Start date: October 26, 2022
• Est. completion date: April 2, 2023

Study information

• Verified date: November 2022
• Source: Albert Saglik Hizmetleri ve Ticaret A.S.
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The study aims to evaluate the effect of AI-based discharge training after acute decompensation of heart failure on the patient's quality of life and to examine the relationship between changes in voice and speech characteristics of patients and changes in hospitalization, discharge, and early post-discharge clinical status.

Description:

Heart failure (HF) is a progressive disease with a fluctuating course. From time to time, patients' symptoms and signs worsen enough to require hospitalization, and hospitalization occurs with acute decompensated HF. Acute HF decompensations are periods that worsen the prognosis of the patient. On the other hand, patients discharged after an acute decompensation have the highest risk during the first months after discharge. Patients get trained about lifestyle changes and medication management during the discharge period. Recent guidelines suggest that patients in the early post-discharge period be called for virtual/telephone or face-to-face control visits at short intervals(3rd, 7th, 14th, and 28th days ), then at 3-6 monthly intervals according to NYHA class.

In traditional cardiovascular practice, patients are called for outpatient control visit in the first month after discharge. However, the processes after the pandemic kept patients away from visiting the hospital at the frequency recommended in the American and European guidelines and caused them to stay at home not even following their routine visit schedules. Moreover, the risks and benefits of virtual visits in terms of patient prognosis are not well established.

This study aims to investigate relationships between routinely recorded findings, symptoms, and vocal biomarkers of heart failure patients in the hospitalization and in the post-discharge period and to investigate the effect of post-discharge education on patient-reported outcomes and re-hospitalization.

Recruitment information / eligibility

• Status: Enrolling by invitation
• Enrollment: 76
• Est. completion date: April 2, 2023
• Est. primary completion date: March 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 85 Years

Eligibility

Inclusion Criteria:

• Hospitalisation due to heart failure decompensation

• Having a smartphone with internet access

• Willingness to participate in the study

• NYHA 2-4 symptoms

Exclusion Criteria:

• Diagnosis of active malignancy

• Pregnancy

• Vision and hearing problems

• Moderate to severe cognitive impairment

• Dementia

Related Conditions & MeSH terms

• Heart Failure

Locations

Country	Name	City	State
Turkey	Dokuz Eylul University Research and Application Hospital	Izmir

Sponsors (2)

Lead Sponsor	Collaborator
Albert Saglik Hizmetleri ve Ticaret A.S.	Dokuz Eylul University

Country where clinical trial is conducted

Turkey, 

References & Publications (3)

Degertekin M, Erol C, Ergene O, Tokgözoglu L, Aksoy M, Erol MK, Eren M, Sahin M, Eroglu E, Mutlu B, Kozan O. [Heart failure prevalence and predictors in Turkey: HAPPY study]. Turk Kardiyol Dern Ars. 2012 Jun;40(4):298-308. doi: 10.5543/tkda.2012.65031. Turkish. — View Citation

McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, Burri H, Butler J, Celutkiene J, Chioncel O, Cleland JGF, Coats AJS, Crespo-Leiro MG, Farmakis D, Gilard M, Heymans S, Hoes AW, Jaarsma T, Jankowska EA, Lainscak M, Lam CSP, Lyon AR, McMurray JJV, Mebazaa A, Mindham R, Muneretto C, Francesco Piepoli M, Price S, Rosano GMC, Ruschitzka F, Kathrine Skibelund A; ESC Scientific Document Group. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021 Sep 21;42(36):3599-3726. doi: 10.1093/eurheartj/ehab368. Erratum in: Eur Heart J. 2021 Oct 14;:. — View Citation

Yilmaz MB, Celik A, Cavusoglu Y, Bekar L, Onrat E, Eren M, Kutlu M, Yalta K, Temizhan A, Kilicaslan B, Gungor H, Acikel M, Demir M, Akdemir R, Zoghi M, Tokgozoglu L. [Snapshot evaluation of heart failure in Turkey: Baseline characteristics of SELFIE-TR]. Turk Kardiyol Dern Ars. 2019 Apr;47(3):198-206. doi: 10.5543/tkda.2019.66877. Turkish. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Heart failure-related hospitalizations	The effect of acquired intermittent digital data including vocal biomarkers along with standardized discharge education on the HF-related hospitalization	At baseline, Four weeks after discharge, Three months after discharge
Primary	Change from baseline in health-related quality of life	The effect of acquired intermittent digital data including vocal biomarkers along with standardized discharge education on the patient's quality of life. SF-12(Short Form-12) will be used to evaluate the effect	At baseline, Four weeks after discharge, Three months after discharge
Secondary	Patient-reported outcomes	Multivariate logistic regression models of digital and vocal properties optimized for sensitivity to predict patient-reported outcomes, including dyspnea level (ranging from 1 to 4), edema(0 to +3) and HF-related hospitalization	At baseline, Four weeks after discharge, Three months after discharge