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Related Concept Videos

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...

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Related Experiment Video

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A Recovery Cardiopulmonary Bypass Model Without Transfusion or Inotropic Agents in Rats
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Multivariable Modeling of Postoperative Risk in Infant Cardiac Surgery: Integrating Clinical Variables and 20

Rúnar Bragi Kvaran1,2, Andreas Skagervik1,2, Fredrik Pernbro2

  • 1Department of Anesthesiology and Intensive Care Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Acta Anaesthesiologica Scandinavica
|June 10, 2025
PubMed
Summary

Inflammatory biomarkers may improve prediction of outcomes like acute kidney injury after infant cardiac surgery. Combining biomarkers with clinical data offers enhanced risk stratification for better patient management.

Keywords:
biomarkerscongenital heart defectsinflammationinflammation mediatorsoutcomespediatric heart surgerysystemic inflammatory response syndrome

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Area of Science:

  • Cardiology
  • Pediatric Surgery
  • Biomarker Research

Background:

  • Infant cardiac surgery frequently induces a significant inflammatory response.
  • The predictive utility of biomarkers for clinical outcomes in this population remains a subject of ongoing research.
  • Acute kidney injury (AKI), duration of mechanical ventilation, and inotropic support are critical postoperative concerns.

Purpose of the Study:

  • To evaluate the predictive value of 20 inflammatory biomarkers, alongside clinical data, for key postoperative outcomes in infants undergoing cardiac surgery.
  • To develop and compare three predictive models: Clinical-Data-Only, Biomarker-Only, and a Combined model.

Main Methods:

  • Secondary analysis of the MiLe-1 study involving infants who underwent surgery with cardiopulmonary bypass (CPB).
  • Measurement of 20 inflammatory biomarkers pre- and post-CPB.
  • Development and comparison of multivariable logistic regression models (Clinical-Data-Only, Biomarker-Only, Combined) using BIC-guided selection.
  • Model performance assessed via c-statistics and p-contrast tests.

Main Results:

  • For AKI prediction, the Combined model (c-statistic=0.78) showed a statistically significant improvement over the Clinical-Data-Only model (c-statistic=0.60).
  • The Biomarker-Only model demonstrated strong predictive capability for AKI (c-statistic=0.79).
  • For inotropic score prediction, the Combined model (c-statistic=0.85) significantly outperformed the Clinical-Data-Only model (c-statistic=0.77).

Conclusions:

  • Inflammatory biomarkers show potential for enhancing risk stratification of postoperative outcomes in infant cardiac surgery.
  • The study highlights the added value of incorporating biomarkers into predictive models.
  • Further validation in larger, diverse patient cohorts is recommended to confirm these findings.