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Effects of Autonomic Nervous System Modulation by Heart Rate Variability Biofeedback Training With Resonant Frequency Breathing on Glucose Metabolism in Individuals With Prediabetes (RwHRVBFinPD)

J

Johannes Gutenberg University (JGU)

Status

Enrolling

Conditions

Prediabetes

Treatments

Behavioral: Anti-Stress program
Behavioral: Resonance frequency breathing with heart rate variability biofeedback training

Study type

Interventional

Funder types

Other

Identifiers

NCT06739993
2022-16489
540546352 (Other Grant/Funding Number)

Details and patient eligibility

About

Approximately 20% of adults have prediabetes in Germany. Prediabetes is defined as a condition with glucose levels outside the normal range but not yet meeting the criteria for type 2 diabetes. The pathogenesis of prediabetes, as well as of type 2 diabetes, involves whole-body insulin resistance associated with inadequate insulin secretion. These two central processes of glucose regulation are modulated by the brain. The brain communicates via the autonomic nervous system (ANS) with metabolically important organs in the periphery to modulate insulin sensitivity and insulin secretion. These processes are impaired in individuals with prediabetes and diabetes. An ANS sympathovagal imbalance has also been observed in individuals with prediabetes. There are no specific therapeutic approaches to improve ANS sympathovagal imbalance. It is assumed that resonant frequency breathing (RFB) maximizes heart rate variability (HRV) through rhythmization of breathing, heartbeat, and blood pressure. Through this state of coherence, the activity of the parasympathetic nervous system is upregulated, and the activity of the sympathetic nervous system is suppressed, leading to an increase in modulation of ANS activity. Several studies have demonstrated that heart rate variability-biofeedback (HRV-BF) interventions improve HRV, reduce stress and anxiety, and alleviate symptoms in patients with various medical conditions. To the best of current knowledge, no study has investigated the effect of HRV-BF-RFB on glucose metabolism. Therefore, the proposed randomized controlled non-blinded trial aims to gain evidence about the effect of HRV-BF-RFB compared to an anti-stress program on glucose metabolism in individuals with prediabetes. Glucose metabolism is characterized using the 75 g oral glucose tolerance test. There are two potential mechanisms by which HRV-BF-RFB may improve glucose metabolism in individuals with prediabetes: (a) a 0°-phase relationship between heart oscillations and breathing, maximizing the amplitude of respiratory sinus arrhythmia (RSA), and (b) activation of the cholinergic anti-inflammatory pathway. The investigators hypothesized that in individuals with prediabetes, the HRV-BF-RFB intervention will improve glucose metabolism and glucose variability.

Enrollment

60 estimated patients

Sex

All

Ages

18 to 65 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Presence of prediabetes Fasting glucose: 100-125 mg/dl (5.6-6.9 mmol/L) and/or HbA1c in %: 5.7-6.4 (39-47 mmol/mol Hb) and/or 2-hour value of the 75 g OGTT: 140-199 mg/dl (7.8-11.0 mmol/L)

    • This is checked using a 75 g OGTT in a screening visit.
  • Age between 18 and 65 years

  • BMI between 20 and 40 kg/m²

Exclusion criteria

  • Diabetes mellitus
  • Malignant diseases within the last 5 years before randomization
  • History of gastrointestinal surgery
  • Pancreatic diseases other than pancreatic lipomatosis
  • Acute diseases or infections
  • Regular intake of cardiac drugs that affect heart rate within the last 4 weeks before the first measurement (e.g. beta-receptor blockers, antiarrhythmics, etc.)
  • Intake of centrally acting drugs
  • Medical contraindications to a meaningful interpretation of the heart rate analysis (e.g. patients with pacemakers, atrial fibrillation or other arrhythmias)
  • Chronic diseases (particularly metabolic diseases, heart diseases, blood diseases)
  • Endocrinological disease other than substituted hypothyroidism
  • Mental illnesses
  • Intake of drugs that can affect blood sugar metabolism (e.g. steroids)

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

60 participants in 2 patient groups

Resonance frequency breathing with heart rate variability biofeedback training (RFB-HRV-BF)
Experimental group
Description:
The mobile system "eSense Pulse" by Mindfield Biosystems Ltd. (Gronau, Germany) was used for RFB-HRV-BF training. The participants sat in an upright position, started the training via the eSense app on their smartphone, and were instructed to practice breathing at their individually determined resonance frequency.During training, a ball that expands (breathe in) and shrinks (breathe out) on the screen specified the breathing frequency goal to a value of six cycles per minute (five seconds inspiration, five seconds expiration). The HRV was visualized by new symbols varying in color depending on the respectively measured values, which appeared every ten seconds.
Treatment:
Behavioral: Resonance frequency breathing with heart rate variability biofeedback training
Anti-Stress program
Active Comparator group
Description:
The mobile system eSense Pulse from Mindfield Biosystems is used for the digital anti-stress program. To do this, the participants put on a chest strap with a sensor and can start training via the eSense app. The anti-stress program is carried out using a procedure generated for the study. During the anti-stress program units, the participants receive application-related information and tips to better understand the topic of stress, identify stressors in their own lives and reduce stress. The active control intervention of the anti-stress program was selected to investigate the effect of a specific stress level reduction without the direct modulation of physiological mechanisms of action as with HRV-BF-RFA.
Treatment:
Behavioral: Anti-Stress program

Trial contacts and locations

2

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Central trial contact

Martin Heni, Prof. Dr. med.; Benedict Herhaus, Ph.D.

Data sourced from clinicaltrials.gov

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