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Biomarker-based risk model to predict persistent multiple organ dysfunctions after congenital heart surgery â€" A prospective observational cohort study.
Benscoter, Alexis L; Alten, Jeffrey A; Atreya, Mihir R; Cooper, David S; Byrnes, Jonathan W; Nelson, David P; Ollberding, Nicholas J; Wong, Hector R.
Affiliation
  • Benscoter AL; University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center.
  • Alten JA; University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center.
  • Atreya MR; University of Cincinnati, Cincinnati Children's Hospital Medical Center.
  • Cooper DS; University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center.
  • Byrnes JW; University of Alabama at Birmingham.
  • Nelson DP; University of Kentucky.
  • Ollberding NJ; University of Cincinnati, Cincinnati Children's Hospital Medical Center.
  • Wong HR; University of Cincinnati, Cincinnati Children's Hospital Medical Center.
Res Sq ; 2023 Jan 27.
Article in En | MEDLINE | ID: mdl-36747744
ABSTRACT

Background:

Multiple organ dysfunction syndrome (MODS) is an important cause of post-operative morbidity and mortality for children undergoing cardiac surgery requiring cardiopulmonary bypass (CPB). Dysregulated inflammation is widely regarded as a key contributor to bypass-related MODS pathobiology, with considerable overlap of pathways associated with septic shock. The pediatric sepsis biomarker risk model (PERSEVERE) is comprised of seven protein biomarkers of inflammation, and reliably predicts baseline risk of mortality and organ dysfunction among critically ill children with septic shock. We aimed to determine if PERSEVERE biomarkers and clinical data could be combined to derive a new model to assess the risk of persistent CPB-related MODS in the early post-operative period.

Methods:

This study included 306 patients <18 years old admitted to a pediatric cardiac ICU after surgery requiring cardiopulmonary bypass (CPB) for congenital heart disease. Persistent MODS, defined as dysfunction of two or more organ systems on postoperative day 5, was the primary outcome. PERSEVERE biomarkers were collected 4 and 12 hours after CPB. Classification and Regression Tree methodology was used to derive a model to assess the risk of persistent MODS.

Results:

The optimal model containing interleukin-8 (IL-8), chemokine ligand 3 (CCL3), and age as predictor variables, had an area under the receiver operating characteristic curve (AUROC) of 0.86 (0.81-0.91) for differentiating those with or without persistent MODS, and a negative predictive value of 99% (95-100). Ten-fold cross-validation of the model yielded a corrected AUROC of 0.75.

Conclusions:

We present a novel risk prediction model to assess the risk for development of multiple organ dysfunction after pediatric cardiac surgery requiring CPB. Pending prospective validation, our model may facilitate identification of a high-risk cohort to direct interventions and studies aimed at improving outcomes via mitigation of post-operative organ dysfunction. Clinical Trial Registration Number This study does not meet criteria for a clinical trial per the WHO International Clinical Trials Registry Platform as no intervention was performed.

Full text: 1 Database: MEDLINE Type of study: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Res Sq Year: 2023 Type: Article

Full text: 1 Database: MEDLINE Type of study: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Res Sq Year: 2023 Type: Article