Improved automatic analysis of ambulatory blood pressure data based on precise detection of individual night-time from diurnal profile of heart rate
- Resource Type
- Authors
- Victor F. Mordovin; Galina Semke; S. Pekarski; Margarita V Kolodina; Sergei V Triss
- Source
- Blood Pressure Monitoring. 7:117-121
- Subject
- Adult
Male
medicine.medical_specialty
Ambulatory blood pressure
Diastole
Blood Pressure
Assessment and Diagnosis
Stage ii
Standard deviation
Internal medicine
Heart rate
Internal Medicine
medicine
Humans
Advanced and Specialized Nursing
Reproducibility
business.industry
Reproducibility of Results
General Medicine
Blood Pressure Monitoring, Ambulatory
Middle Aged
Sleep time
Circadian Rhythm
Blood pressure
Cardiology
Female
Sleep
Cardiology and Cardiovascular Medicine
business
Algorithms
Software
- Language
- ISSN
- 1359-5237
Background Software programs sold with ambulatory blood pressure monitoring (ABPM) devices are designed to use some set 'typical' night-time (e.g. 2300-0700) to estimate daytime/night-time blood pressure (BP) with limited accuracy. Alternative use of individual periods of sleep/wakefulness from patient diaries is time consuming and subjective. We developed a simple mathematical algorithm for the detection of the 'night-time' as a period of low values in diurnal profiles of heart rate (HR) allowing accurate automatic analysis of daytime/night-time blood pressure. To test this technique we designed a software application allowing automatic analysis of ABPM data based on the different night-time definitions, including the developed algorithm and compared reproducibility of the degree of BP dipping produced by the different methods across two days of 48-h ABPM. Methods A 48-h ABPM study was performed in 33 patients with uncomplicated stage II hypertension. Means and standard deviations (SD) of the differences in the degree of BP dipping between two 24-h periods of 48-h ABPM were obtained separately for three methods of night-time definition: automatic detection from individual HR profiles, fixed 2300-0700 h interval and sleep time from patient diaries. Results Reproducibility of the BP dip estimation across 2 days of BP monitoring was significantly better for night-time detected from individual HR profiles than for the fixed 2300-0700 h interval or sleep time from diary. The SD of the differences was 6.7/8.2 compared with 13.5/18.3 and 13.0/14.8 respectively (systolic BP/diastolic BP, mmHg). Conclusions Implementation of the developed method of night-time definition may significantly improve automatic analysis of ABPM data.