Cardiovascular

Early Risk Stratification in Acute Pulmonary Embolism using Inflammatory and Hematologic Biomarkers.

TL;DR

Red blood cell distribution width, white blood cell count, and neutrophil-to-lymphocyte ratio independently predict in-hospital adverse events in acute pulmonary embolism, and their combined use may enhance early risk stratification.

Key Findings

In-hospital adverse events occurred in 14.8% of acute PE patients, including four deaths.

  • The study included 88 patients diagnosed with acute PE between 2023 and 2024.
  • Adverse events occurred in 13 patients (14.8%).
  • Adverse events were defined as hemodynamic instability, cardiac arrest, or death during hospitalization.
  • Four deaths were recorded among the 13 patients with adverse events.
  • This was a retrospective study design.

Patients with adverse events had significantly higher levels of all five inflammatory and hematologic markers compared to those without adverse events.

  • RDW was significantly higher in patients with adverse events (p = 0.008).
  • WBC count was significantly higher in patients with adverse events (p = 0.002).
  • NLR was significantly higher in patients with adverse events (p = 0.001).
  • PLR was significantly higher in patients with adverse events (p = 0.001).
  • CRP was significantly higher in patients with adverse events (p = 0.028).

Multivariable logistic regression identified RDW, WBC, and NLR as independent predictors of in-hospital adverse events in acute PE.

  • RDW was an independent predictor with OR 1.48 (95% CI 1.12–1.96; p = 0.006).
  • WBC was an independent predictor with OR 1.20 (95% CI 1.02–1.41; p = 0.032).
  • NLR was an independent predictor with OR 1.14 (95% CI 1.02–1.27; p = 0.018).
  • PLR and CRP, while significant on univariable analysis, were not identified as independent predictors in the multivariable model.

The combination of RDW, WBC, and NLR showed improved discriminative performance for in-hospital adverse events with an AUC of 0.880.

  • ROC analysis was used to assess discriminative performance of the markers.
  • The combined model of RDW, WBC, and NLR achieved an AUC of 0.880.
  • The combined AUC of 0.880 represented improved discrimination compared to individual markers alone.
  • Clinical, echocardiographic, and laboratory data were all analyzed as part of the broader assessment.

Accurate early risk stratification in acute PE remains challenging, particularly in intermediate-risk patients, and readily available hematologic and inflammatory markers may provide additional prognostic value.

  • The study evaluated RDW, WBC count, NLR, PLR, and CRP as candidate prognostic markers.
  • These markers were selected because they are readily available in clinical practice.
  • The study context highlights a gap in prognostic tools specifically for intermediate-risk PE patients.
  • Both clinical and echocardiographic data were incorporated alongside laboratory markers.

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Citation

Pocesta B, Poposka L, Vrajnko E, Konjanovski T, Bosevski M, Georgievska-Ismail L. (2026). Early Risk Stratification in Acute Pulmonary Embolism using Inflammatory and Hematologic Biomarkers.. Prilozi (Makedonska akademija na naukite i umetnostite. Oddelenie za medicinski nauki). https://doi.org/10.2478/prilozi-2026-0004