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Updated: May 1, 2026

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A new ratio for protocol categorization.

Pierre Squara1

  • 1CERIC, Clinique Ambroise Paré, 27 boulevard Victor Hugo, 92200 Neuilly-sur-Seine, France.

Computational and Mathematical Methods in Medicine
|April 17, 2014
PubMed
Summary
This summary is machine-generated.

A new ratio "S" balances predictability and true/false positives/negatives for fluid bolus response prediction. This ratio, validated in cardiac output studies, offers improved clinical decision-making compared to traditional metrics.

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Area of Science:

  • Medical Statistics
  • Clinical Physiology
  • Predictive Modeling

Background:

  • Assessing fluid responsiveness is crucial in critical care.
  • Traditional metrics for predicting fluid responsiveness have limitations.
  • Balancing predictability and classification accuracy is essential for reliable clinical tools.

Purpose of the Study:

  • Introduce and validate a novel ratio, termed 'S'.
  • Evaluate the performance of ratio 'S' in predicting cardiac output response to fluid bolus.
  • Compare ratio 'S' with existing metrics for classification accuracy and precision.

Main Methods:

  • Applied ratio 'S' to existing data predicting fluid responsiveness from passive leg raise (PLR) tests.
  • Modeled 2x2 contingency tables for 1000 hypothetical patients to compare 'S' with traditional ratios.
  • Assessed the precision of 'S' against other ratios by analyzing random fluctuations.

Main Results:

  • Ratio 'S' demonstrated superior performance in predicting cardiac output response to fluid bolus compared to other ratios.
  • When true response proportions are high, 'S' uniquely balances true positives (TP) and true negatives (TN).
  • The precision of ratio 'S' was found to be comparable to the coefficient of correlation (CC).

Conclusions:

  • Ratio 'S' offers a balanced approach to categorization from quantitative variables.
  • It enhances predictability while ensuring a balance between TP and TN.
  • Ratio 'S' is recommended for clinical applications where predictability and classification balance are critical.