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Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.

Salar Tayebi¹, Rob Wise^2,3,4, Niels Van Regenmortel^5,6

¹Department of Electronics and Informatics, Vrije Universiteit Brussel, Brussels, 1050, Belgium.

Scientific Reports

|March 20, 2025

Summary

Intra-abdominal hypertension (IAH) affects critically ill patients. Researchers found specific body measurements can predict intra-abdominal pressure (IAP) non-invasively, aiding early IAH detection and management.

Keywords:

Anthropometric parameters Intra-abdominal pressure Predictive models Statistical analyses

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Area of Science:

Critical Care Medicine
Medical Measurement
Patient Monitoring

Background:

Intra-abdominal hypertension (IAH) affects nearly 25% of critically ill patients.
Accurate intra-abdominal pressure (IAP) measurement is crucial for early IAH detection and complication avoidance.
Current IAP measurement relies on invasive bladder techniques.

Purpose of the Study:

To investigate the relationship between anthropometric parameters and IAP.
To determine if IAP and IAH can be predicted non-invasively using body measurements.
To identify reliable anthropometric predictors for IAP and IAH.

Main Methods:

Retrospective observational study of 96 critically ill patients.
Recorded IAP and 28 body parameters.
Utilized statistical analyses (Pearson's correlation, mutual information) and simulation modeling.

Main Results:

Three anthropometric parameters (difference between convex and horizontal xiphoid-pubis distance, sagittal abdominal diameter, abdominal compliance) predicted intra-bladder pressure (IBP) with R²=0.56.
The difference between convex and horizontal xiphoid-pubis distance and sagittal abdominal diameter reliably predicted IAH (R²=0.79).

Conclusions:

Specific anthropometric measurements can reliably predict IAP and IAH non-invasively.
The difference between convex and horizontal xiphoid-pubis distance is a key predictor for IAH.
Further research with larger, diverse populations is needed to validate these findings.