Related Experiment Video
Updated: Jun 13, 2026
06:41
Veno-Venous Extracorporeal Membrane Oxygenation in a Mouse
Published on: October 24, 2018
12.5K
Prognostic models for mortality risk in patients requiring ECMO
Lara C A Pladet1, Jaimie M M Barten2, Lisette M Vernooij2
1Department of Intensive Care Medicine, University Medical Center Utrecht, Utrecht, The Netherlands. c.l.a.pladet@umcutrecht.nl.
Intensive Care Medicine
|January 4, 2023
Summary
Mortality prediction models for extracorporeal membrane oxygenation (ECMO) patients show moderate performance and poor quality, with limited external validation. These models are not suitable for guiding ECMO initiation decisions.
Area of Science:
- Critical Care Medicine
- Cardiovascular Research
- Respiratory Medicine
Background:
- Extracorporeal membrane oxygenation (ECMO) is a life-support technology for severe cardiocirculatory or respiratory failure.
- Accurate mortality prediction is crucial for managing ECMO patients and optimizing resource allocation.
Conclusions:
- Despite numerous models, few are externally validated, and their predictive performance and methodological quality are generally poor.
- Current mortality prediction models for ECMO patients are not applicable for clinical decision support in selecting patients for ECMO initiation.
- Further research is needed to develop and validate robust prediction models suitable for guiding ECMO therapy decisions.
Related Concept Videos
01:15Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
01:20Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
01:21Cancer Survival Analysis
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...