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Related Concept Videos

Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Clearance Models: Compartment Models01:25

Clearance Models: Compartment Models

Clearance measures drug elimination from the central compartment, including plasma and highly perfused organs like kidneys and liver. Its calculation varies depending on pharmacokinetic models and administration routes. The one-compartment model, for instance, portrays the pharmacokinetics of polar drugs such as aminoglycoside antibiotics administered intravenously and readily excreted in urine. In this case, clearance is influenced by the terminal rate constant (λz) and the total volume of...

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Related Experiment Video

Updated: Jun 20, 2026

Evolution of Staircase Structures in Diffusive Convection
07:28

Evolution of Staircase Structures in Diffusive Convection

Published on: September 5, 2018

Marginal DCS events: their relation to decompression and use in DCS models.

Laurens E Howle1, Paul W Weber, Richard D Vann

  • 1Mechanical Engineering Dept., Duke Univ., Durham, NC 27708-0300, USA. laurens.howle@duke.edu

Journal of Applied Physiology (Bethesda, Md. : 1985)
|August 22, 2009
PubMed
Summary

Marginal decompression sickness (DCS) events should not be included when optimizing decompression models. Counting these events as no-DCS improves model accuracy and conservativeness for diving safety.

Related Experiment Videos

Last Updated: Jun 20, 2026

Evolution of Staircase Structures in Diffusive Convection
07:28

Evolution of Staircase Structures in Diffusive Convection

Published on: September 5, 2018

Area of Science:

  • Diving Medicine
  • Physiological Modeling
  • Risk Assessment

Background:

  • Marginal decompression sickness (DCS) events are often included in probabilistic decompression models with fractional weights.
  • Previous methods aimed to make model predictions more conservative by incorporating these marginal events.

Purpose of the Study:

  • To determine the utility and nature of marginal DCS events in probabilistic decompression models.
  • To investigate if marginal DCS events correlate with decompression exposure.
  • To evaluate the impact of including marginal DCS events on model optimization and accuracy.

Main Methods:

  • Developed and compared three null models against a known decompression model.
  • Tuned models using dive trial data containing only marginal DCS and non-DCS events.
  • Analyzed the effects of fractional weighting and combined data on probabilistic DCS model optimization.

Main Results:

  • Marginal DCS events are correlated with decompression exposure.
  • Empirical data with both marginal and full DCS events cannot be combined into a single DCS model.
  • The optimal analytical weight for a marginal DCS event is 0.

Conclusions:

  • Marginal DCS events should be treated as no-DCS events during probabilistic model optimization.
  • Including marginal DCS events is counterproductive, worsening model fit to full DCS data.
  • Excluding marginal DCS events leads to more accurate and conservative decompression models.