BACKGROUND: The optimal strategy for identification of hemodynamically stable patients with acute pulmonary embolism (PE) at risk for death and clinical deterioration remains undefined.
OBJECTIVES: We aimed to assess the performances of currently available models/scores for identifying hemodynamically stable patients with acute, symptomatic PE at risk of death and clinical deterioration.
METHODS: This was a prospective multicenter cohort study including patients with acute PE (NCT03631810). Primary study outcome was in-hospital death within 30 days or clinical deterioration. Other outcomes were in-hospital death, death, and PE-related death, all at 30 days. We calculated positive and negative predictive values, c-statistics of European Society of Cardiology (ESC)-2014, ESC-2019, Pulmonary Embolism Thrombolysis (PEITHO), Bova, Thrombo-embolism lactate outcome study (TELOS), fatty acid binding protein, syncope and tachicardia (FAST), and National Early Warning Scale 2 (NEWS2) for the study outcomes.
RESULTS: In 5036 hemodynamically stable patients with acute PE, positive predictive values for the evaluated models/scores were all below 10%, except for TELOS and NEWS2; negative predictive values were above 98% for all the models/scores, except for FAST and NEWS2. ESC-2014 and TELOS had good performances for in-hospital death or clinical deterioration (c-statistic of 0.700 and 0.722, respectively), in-hospital death (c-statistic of 0.713 and 0.723, respectively), and PE-related death (c-statistic of 0.712 and 0.777, respectively); PEITHO, Bova, and NEWS2 also had good performances for PE-related death (c-statistic of 0.738, 0.741, and 0.742, respectively).
CONCLUSION: In hemodynamically stable patients with acute PE, the accuracy for identification of hemodynamically stable patients at risk for death and clinical deterioration varies across the available models/scores; TELOS seems to have the best performance. These data can inform management studies and clinical practice.
| Discipline Area | Score |
|---|---|
| Physician |  |
Physician rater
This comparison of different risk models in PE is important and may be useful to some clinicians. The complexity of some of the scoring systems and the lack of complete data in the validation set are important limitations.
Physician rater
Although the authors conclude that TELOS is the most predictive, data found all models were able to define cohorts at low-, intermediate-, and high-risk for death. There seems no clear evidence for adopting any specific model.
, McMaster University