Utility of P Wave Indices on Electrocardiography in Predicting the Left Atrial Volume Index in Chronic Kidney Disease Patients

Our study suggests that electrocardiographic (ECG) parameters such as p wave peak time can predict LAVI in CKD and ECG is an easily available tool; thus, this could help stratify cardiovascular risk, especially left ventricular diastolic dysfunction.

Authors

Institutions

Publication Details

Journal
Cureus
Published
2025-01-22
DOI
https://doi.org/10.7759/cureus.77809
Citations
1
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
1.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Utility of P Wave Indices on Electrocardiography in Predicting the Left Atrial Volume Index in Chronic Kidney Disease Patients

Nikhil Chaudhary, Shivendra Singh, Umesh Kumar Pandey
1 citations
Cureus
Cardiovascular Function and Risk Factors
1.39
article

Utility of P Wave Indices on Electrocardiography in Predicting the Left Atrial Volume Index in Chronic Kidney Disease Patients

Nikhil Chaudhary, Shivendra Singh, Umesh Kumar Pandey
article en
1 citations

Abstract

Our study suggests that electrocardiographic (ECG) parameters such as p wave peak time can predict LAVI in CKD and ECG is an easily available tool; thus, this could help stratify cardiovascular risk, especially left ventricular diastolic dysfunction.

CureusVol. 17(1)
Pediatric Nephrology of Alabama (US), Banaras Hindu University (IN)
Good health and well-being
Openalex Percentile: Top 23%
Cardiovascular Function and Risk Factors
1.39
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.