Manuscript Title:

EXAMINING ECHOCARDIOGRAPHIC PERCENTILE VALUES AND CURVES: A COMPARATIVE ANALYSIS BETWEEN LMS AND QR TECHNIQUES IN FEMALE RESIDENTS OF MULTAN, PAKISTAN

Author:

MUHAMMAD IMRAN MUSHTAQ, MUHAMMAD AHMED SHEHZAD

DOI Number:

DOI:10.5281/zenodo.10940441

Published : 2024-04-10

About the author(s)

1. MUHAMMAD IMRAN MUSHTAQ - PhD Scholar, Department of Statistics, Bahauddin Zakariya University Multan- Pakistan.
2. MUHAMMAD AHMED SHEHZAD - Associate Professor, Department of Statistics, Bahauddin Zakariya University, Multan Pakistan.

Full Text : PDF

Abstract

There is scanty literature on percentile curves for echocardiographic measures in Pakistan particularly for women. This study adds to the existing literature by examining echocardiographic percentile values and curves corresponding to body surface area through LMS and QR techniques in female residents of Multan, Pakistan. To achieve this goal, a survey was conducted through a questionnaire among 685 female patients at the Chaudhry Pervaiz Elahi (CPE) Institute of Cardiology Multan to get the data. We have applied Lambda-Mu-Sigma (LMS) and Quantile Regression (QR) methods to compute percentile values of echocardiographic measures. The study suggests that when estimating certain measurements, like AR (mm), the LMS method might give more varied results than quantile regression, especially for people with larger body sizes. The trends for LA (mm) measurements at the 50th percentile are different. EF (mm) measurements are mostly alike though there are some exceptions. LVIDD measurements do not vary much with LMS, but these are more consistent with quantile regression. With LVIDS, quantile regression tends to give slightly higher results as compared to LMS for most body sizes. LMS provides more detailed information for LVISD (mm) while quantile regression offers a broader view. Lastly, LVPWD (mm) percentiles between LMS and quantile regression for each body size are similar.


Keywords

Quantile Regression, Lambda-Mu-Sigma Method, Percentile Curves, Female Patients.