Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Modeling longitudinal data in acute illness.

Gilles Clermont

Critical Care (London, England)

|August 11, 2007

Summary

This summary is machine-generated.

Biomarkers for sepsis enable early identification of high-risk patients for life-saving interventions. Advanced modeling of biomarker profiles is crucial for personalized immunomodulatory therapies and clinical trial design.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Cardiovascular and Autonomic Phenotypes Reveal Distinct Mechanisms of Sepsis Decompensation via Deep Learning.

Research square·2026

Same author

A comprehensive cross-sectional study of bedside monitor alarm characteristics and alarm load across hospital units.

Scientific reports·2026

Same author

Development and evaluation of a prediction model for adult ICU hemorrhage using only continuous cardiorespiratory data.

Physiological measurement·2026

Same author

How much information is needed to predict outcomes after cardiac arrest?

Resuscitation·2025

Same author

Adversarial Debiasing for Equitable and Fair Detection of Acute Coronary Syndrome Using 12-Lead ECG.

IEEE transactions on bio-medical engineering·2025

Same author

A Machine Learning Trauma Triage Model for Critical Care Transport.

JAMA network open·2025

Same journal

Comparative performance of mitral E/e' versus inferior vena cava variability for predicting fluid responsiveness in mechanically ventilated adults with shock.

Critical care (London, England)·2026

Same journal

Different lungs or different patients? Insights into postoperative ARDS.

Critical care (London, England)·2026

Same journal

Predictive validity of SOFA-2: analytical and contextual considerations.

Critical care (London, England)·2026

Same journal

Interpreting elevated FRAP in critical illness: beyond antioxidant capacity.

Critical care (London, England)·2026

Same journal

Cytokine-based strategies to improve prognostic enrichment of pediatric ARDS.

Critical care (London, England)·2026

Same journal

Genomic dynamics of antimicrobial resistance transmission between bacteria from intensive care unit surfaces and from critically ill patients.

Critical care (London, England)·2026

See all related articles

Area of Science:

Critical care medicine
Biostatistics
Computational biology

Background:

Sepsis biomarker discovery is key for early risk stratification.
Immunomodulatory therapies offer potential life-saving interventions for sepsis.
Personalized treatment requires understanding longitudinal biomarker profiles.

Discussion:

Advanced modeling techniques are essential for interpreting complex biomarker data.
Longitudinal biomarker profiles need to be analyzed in relation to patient characteristics, disease progression, and treatment.
Developing patient-specific models is crucial for optimizing immunomodulatory therapies.

Key Insights:

Biomarker-driven, individualized interventions can improve sepsis outcomes.
Sophisticated statistical and mathematical models are needed for biomarker profile analysis.

Related Experiment Videos

Critical illness settings are ideal for applying and validating these emerging modeling techniques.

Outlook:

Validated models can guide rational clinical trial design and interpretation.
Point-of-care testing enhances the feasibility of real-time biomarker monitoring.
Emerging modeling techniques promise to revolutionize critical care and personalized medicine.