Background&#xa0; <p>Pediatric sepsis exhibits marked heterogeneity. Early integration of clinical, biomarker, and microcirculatory data may refine risk stratification and identify reproducible phenotypes associated with distinct outcomes.</p> Methods <p>We performed a secondary analysis of a prospective sepsis cohort (2018–2024). A temporal split defined derivation (2018–2022) and validation (2023–2024) cohorts, including demographics, clinical variables, biomarkers, and sublingual videomicroscopy (GlycoCheck<sup>®</sup>). Dimensionality reduction was performed using Factorial Analysis of Mixed Data, followed by unsupervised clustering with Ward.D2. The primary outcome was persistence of multiple organ dysfunction syndrome (MODS) at 72&#xa0;h after admission.</p> Results <p>Among 239 patients (median age 2.1 years [IQR 0.5–11.1]; 52% female), three distinct microvascular phenotypes were identified: Preserved (<i>n</i> = 52), Partially Compensated (<i>n</i> = 75), and Decompensated (<i>n</i> = 112). Patients in the Preserved phenotype were older, required less organ support, and exhibited favorable microvascular indices, characterized by higher capillary density and mild glycocalyx alteration. Partially Compensated patients exhibited marked inflammatory activation, requiring greater vasoactive and ventilatory support and longer PICU stays. Microcirculatory assessment showed moderate reductions in capillary density and subtle glycocalyx changes, indicating a partially compensated response to inflammatory stress. Decompensated patients were predominantly younger and had more frequent multi-organ dysfunction, acute kidney injury, and universal mechanical ventilation, with the lowest capillary density and evidence of global microvascular failure. The risk of MODS within 72&#xa0;h was highest in the Decompensated phenotype compared with the Preserved group (aHR 2.47; 95% CI 1.04–8.44; <i>p</i> = 0.042), with corresponding MODS rates of 42% and 10%, respectively, independent of age, infection focus, and the need for invasive mechanical ventilation. Mortality followed a stepwise gradient (Preserved 1.9%, Partially Compensated 12.1%, Decompensated 17.2%; <i>p</i> = 0.023). Internal validation analyses reproduced phenotype assignments and outcome associations, confirming their temporal stability. </p> Conclusions <p>Three reproducible microvascular phenotypes in pediatric sepsis—Preserved, Partially Compensated, and Decompensated—were identified using bedside clinical, biomarker, and microcirculation data. These phenotypes represent distinct pathophysiologic and prognostic patterns, from preserved states with favorable outcomes to decompensated forms linked to higher risk of organ dysfunction and death. Early microvascular phenotyping is feasible and enhances risk stratification.</p> Graphical abstract <p></p>

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Microvascular phenotypes in pediatric sepsis identified by machine learning: prognostic implications for organ dysfunction and mortality

  • Juan Carlos Beltrán,
  • Jaime Fernández-Sarmiento,
  • Alvaro David Orjuela-Cañón,
  • L. Nelson Sanchez-Pinto,
  • Juan Pablo Fernández-Sarta,
  • Isabella La Rotta,
  • Daniel Fernández-Sarta,
  • Alejandro Coutin,
  • Juan Esteban Godoy,
  • Hans Vink,
  • Sainath Raman,
  • Niranjan Kissoon,
  • María Paula Cardona,
  • Tatiana Bernal Sierra,
  • Juanita Buelvas-Pérez,
  • Laura Sofia Rodriguez,
  • Maria José Barrera Suárez

摘要

Background 

Pediatric sepsis exhibits marked heterogeneity. Early integration of clinical, biomarker, and microcirculatory data may refine risk stratification and identify reproducible phenotypes associated with distinct outcomes.

Methods

We performed a secondary analysis of a prospective sepsis cohort (2018–2024). A temporal split defined derivation (2018–2022) and validation (2023–2024) cohorts, including demographics, clinical variables, biomarkers, and sublingual videomicroscopy (GlycoCheck®). Dimensionality reduction was performed using Factorial Analysis of Mixed Data, followed by unsupervised clustering with Ward.D2. The primary outcome was persistence of multiple organ dysfunction syndrome (MODS) at 72 h after admission.

Results

Among 239 patients (median age 2.1 years [IQR 0.5–11.1]; 52% female), three distinct microvascular phenotypes were identified: Preserved (n = 52), Partially Compensated (n = 75), and Decompensated (n = 112). Patients in the Preserved phenotype were older, required less organ support, and exhibited favorable microvascular indices, characterized by higher capillary density and mild glycocalyx alteration. Partially Compensated patients exhibited marked inflammatory activation, requiring greater vasoactive and ventilatory support and longer PICU stays. Microcirculatory assessment showed moderate reductions in capillary density and subtle glycocalyx changes, indicating a partially compensated response to inflammatory stress. Decompensated patients were predominantly younger and had more frequent multi-organ dysfunction, acute kidney injury, and universal mechanical ventilation, with the lowest capillary density and evidence of global microvascular failure. The risk of MODS within 72 h was highest in the Decompensated phenotype compared with the Preserved group (aHR 2.47; 95% CI 1.04–8.44; p = 0.042), with corresponding MODS rates of 42% and 10%, respectively, independent of age, infection focus, and the need for invasive mechanical ventilation. Mortality followed a stepwise gradient (Preserved 1.9%, Partially Compensated 12.1%, Decompensated 17.2%; p = 0.023). Internal validation analyses reproduced phenotype assignments and outcome associations, confirming their temporal stability.

Conclusions

Three reproducible microvascular phenotypes in pediatric sepsis—Preserved, Partially Compensated, and Decompensated—were identified using bedside clinical, biomarker, and microcirculation data. These phenotypes represent distinct pathophysiologic and prognostic patterns, from preserved states with favorable outcomes to decompensated forms linked to higher risk of organ dysfunction and death. Early microvascular phenotyping is feasible and enhances risk stratification.

Graphical abstract