Observational studyScientific reports2025
Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.
Observational study in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Microwave Radar Sensing for Non-Invasive Intra-Abdominal Pressure Monitoring: A Simulation-Based Analysis with Phantom Testing.Sensors (Basel, Switzerland) · 2026Article
- Variation and accuracy of intra-abdominal pressure measurement in different body positions: a prospective study.World journal of emergency surgery : WJES · 2025Article
- The accuracy of a new noninvasive approach using physical examination combined with ultrasonography to detect intraabdominal hypertension.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Almost one in four critically ill patients suffer from intra-abdominal hypertension (IAH). Currently, the gold standard for measuring intra-abdominal pressure (IAP) is via the bladder. Measurement of IAP is important to identify IAH early and thus implement appropriate management in order to avoid complications. It may be possible to use anthropometric parameters to predict IAP and thus identify IAH non-invasively. This retrospective observational study investigated how the most relevant body parameters evolve in relation to IAP, and whether IAP can be predicted based on anthropometric parameters. The IAP and 28 body parameters of 96 critically ill patients were recorded. Following statistical analyses such as Pearson's and mutual information correlation, the collected data were used to train a simulation model to examine reliable relationships between IAP, predict IAP values, and detect IAH. Three metrics were shown to sufficiently predict intra-bladder pressure (IBP) with a Pearson's correlation of 0.75 (R
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