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Screening of Sleep Apnea by Holter Electrocardiography: Validation of Heart Rate Variability Analysis Algorithm

NCT05435001 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 107

Last updated 2023-02-21

No results posted yet for this study

Summary

Obstructive sleep apnea syndrome (OSAS) is a growing health concern affecting up to 60 % of population with cardiovascular disease. Despite the high cardiovascular morbidity and mortality associated with this syndrome, the substantial inconvenience and cost of polysomnography recordings may delay routine evaluation. Polysomnography (PSG) is the gold standard for diagnosis. However, this is a costly and time-consuming examination. Sympathoadrenergic balance obtained from the routine Holter monitoring suggesting the presence of OSAS, can enable patients to be guided and their PSGs to be primarily held.Abnormalities in nocturnal cyclical heart rate (HR) variations have previously been described in sleep-related breathing disorders. Compared with PSG, holter electrocardiogram has the advantages of pervasion, lower cost, no need for overnight hospitalization, greater similarity to normal conditions, and good compliance. The observation of changes in heart rate associated with apneic events has a potential to be used as an alternative technique for identification of subjects with OSAS. In regard to the feasibility of screening OSAS by HRV analysis by holter electrocardiogram monitoring, it has already been reported that a 24-h electrocardiographic monitoring might be useful to diagnose OSAS. It became a more feasible technique to use following the development of a convenient recorder for OSAS screening by analyzing changes in heart rate.

Conditions

  • Sleep Apnea Syndromes

Interventions

DEVICE

Holter ECG Monitoring

Holter electrocardiogram monitoring will be carried out for 24 h simultaneously with the PSG monitoring using a 2- lead ambulatory electrocardiograph (Fysiologic; kind courtesy: MedTech Company, Amsterdam, Holland). We will calculate the time-domain, frequency-domain and non-linear indices by HRV. Several parameters describing the differences between RR intervals will be calculated: the square root of the mean of the sum of the squares of differences between adjacent normal RR intervals (r-MSSD), SD of NN intervals (SDNN), SD of the averages of NN intervals in all 5-minute segments of the recording (SDANN), and mean of the SD of all NN intervals for all consecutive 5-minute segments of the recording (SDNN index). All variables will be calculated for the 24-hour, daytime (2:00 to 9:00 PM), and nighttime (midnight to 7 AM) periods, and the differences between daytime and nighttime values (D\[D/N\]) will be computed.

Sponsors & Collaborators

  • Amatis Software and Fysiologic Smart ECG Solutions

    collaborator UNKNOWN

  • Izmir Dr Suat Seren Chest Diseases and Surgery Education and Research Hospital

    lead OTHER

Principal Investigators

  • Zeynep Z Ucar, Prof Dr · Izmir Dr Suat Seren Chest Disease and Surgery Training and Research Hospital

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-05-05
Primary Completion
2022-07-01
Completion
2022-08-01

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05435001 on ClinicalTrials.gov