Further observations on reverse-dipper or riser patterns identified with ambulatory blood pressure monitoring

Introduction:Despite debate over definitions, patterns like reverse-dipper phenotypes (RDPs) are determined solely by the nightto-day mean systolic blood pressure (mSBP) ratio, without considering variations in nighttime SBP load and hyperbaric impact (HBI).Objective: This study aims to describe the potential spectrum of RDP phenotypes.Materials and methods: This was a cross-sectional observational study of adults diagnosed with RDP using 24-hour ambulatory blood pressure monitoring (ABPM).Clinical information was extracted from electronic medical records and ABPM.The systolic hyperbaric impact (SHBI) at night, the ratio of nighttime mSBP/daytime mSBP, isolated nocturnal hypertension (INHTN), and sustained hypertension (SHTN) (day and night) were recorded.Results: A total of 136 RDP patients were included.Three subgroups were identified based on ratio, SBP load, day/night mSBP difference, SHTN, INHTN, and SHBI.These subgroups showed different ABPM values, characterizing distinct phenotypes with statistical significance.Conclusion: This study revealed diverse phenotypes within RDP, marked by a varying nighttime SBP load and HBI, alongside day to night SBP gradients and the presence or absence of INHTN/SHTN.These subtypes may exhibit different clinical behaviors and prognoses, offering a fresh perspective on RDP classification.

Authors

Publication Details

Journal
Revista Colombiana de Cardiología (English Edition)
Published
2024-12-06
DOI
https://doi.org/10.24875/rccare.m24000114
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Further observations on reverse-dipper or riser patterns identified with ambulatory blood pressure monitoring

Linda Ibatá, Diego I. Vanegas-Cadavid, Andrés F. Blanco-Ruiz
Revista Colombiana de Cardiología (English Edition)
ECG Monitoring and Analysis
article

Further observations on reverse-dipper or riser patterns identified with ambulatory blood pressure monitoring

Linda Ibatá, Diego I. Vanegas-Cadavid, Andrés F. Blanco-Ruiz
article en

Abstract

Introduction:Despite debate over definitions, patterns like reverse-dipper phenotypes (RDPs) are determined solely by the nightto-day mean systolic blood pressure (mSBP) ratio, without considering variations in nighttime SBP load and hyperbaric impact (HBI).Objective: This study aims to describe the potential spectrum of RDP phenotypes.Materials and methods: This was a cross-sectional observational study of adults diagnosed with RDP using 24-hour ambulatory blood pressure monitoring (ABPM).Clinical information was extracted from electronic medical records and ABPM.The systolic hyperbaric impact (SHBI) at night, the ratio of nighttime mSBP/daytime mSBP, isolated nocturnal hypertension (INHTN), and sustained hypertension (SHTN) (day and night) were recorded.Results: A total of 136 RDP patients were included.Three subgroups were identified based on ratio, SBP load, day/night mSBP difference, SHTN, INHTN, and SHBI.These subgroups showed different ABPM values, characterizing distinct phenotypes with statistical significance.Conclusion: This study revealed diverse phenotypes within RDP, marked by a varying nighttime SBP load and HBI, alongside day to night SBP gradients and the presence or absence of INHTN/SHTN.These subtypes may exhibit different clinical behaviors and prognoses, offering a fresh perspective on RDP classification.

Revista Colombiana de Cardiología (English Edition)Vol. 31(5)
Openalex Percentile: Top 59%
ECG Monitoring and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.