About LV Mass Scaling Tools

What This Site Does

This web site provides tools to explore different methods of scaling left ventricular mass (LVM) and wall thickness for body size and composition. These scaling methods are important for accurately diagnosing LVH across different populations.

Inspiration

This work was inspired by the editorial by Dewey et al. (2008), and their admonition:

'Reliance on parameters ratiometrically scaled to BSA for clinical decision making should be discouraged.'

I wanted to explore the implications of this statement. LV mass and wall thickness seemed the perfect place to start, as these are commonly used in clinical practice and have significant implications for patient care.

The Driving Question

How is the problem of ratiometric scaling manifest? What does the problem look like in practice?

It's one thing to read that "ratiometric BSA scaling is problematic," but it's another to see exactly how problematic it can be. This tool makes the abstract visible by showing the same patient data through different scaling lenses.

Other Questions

In addition to the core question, this application explores several other important questions related to body size scaling:

• •If we use BSA as a scaling variable, does the BSA equation matter?
• •Height has been proposed as a better scaling parameter than BSA, but to which allometric power?
• •Lean body mass (LBM) has been proposed as perhaps the ultimate body size scaling variable. Yet routine, practical measurement of body composition has not been adopted. Do LBM prediction equations perform adequately?
• •What about the influence of age and ethnicity? Are the differences pratical— or just theoretical?

How I Generate Patient Data

The data for these visualizations use systematically generated patient populations to show how scaling methods perform across diverse body habitus. Here's how I create realistic, representative datasets:

Understanding the 95th Percentile Approach

These visualizations use the 95th percentile as the cutoff for defining abnormal values (like LVH). This means that 95% of healthy individuals fall below this threshold, while 5% fall above it. I used the percentiles provided in the source articles to set the upper limit for each scaling method.

This Percentile Explorer helps demonstrate how I generated these upper limits if the source article instead provided a mean and standard deviation.

Clinical Impact

The choice of scaling method isn't just academic—it has real clinical consequences. A patient might be diagnosed with LVH using one method but not another. This is particularly important for:

• ✓Patients with obesity, where BSA-based methods may be imperfect
• ✓Different ethnic populations with varying body compositions
• ✓Athletes with high lean body mass
• ✓Elderly patients with different body composition patterns

By visualizing these differences, clinicians can make more informed decisions about which scaling method is most appropriate for their specific patient population.

Available Tools