Age-Adjusted Endothelial Activation and Stress Index for Coronavirus Disease 2019 at Admission Is a Reliable Predictor for 28-Day Mortality in Hospitalized Patients With Coronavirus Disease 2019.

Endothelial Activation and Stress Index (EASIX) predict death in patients undergoing allogeneic hematopoietic stem cell transplantation who develop endothelial complications. Because coronavirus disease 2019 (COVID-19) patients also have coagulopathy and endotheliitis, we aimed to assess whether EASIX predicts death within 28 days in hospitalized COVID-19 patients. We performed a retrospective study on COVID-19 patients from two different cohorts [derivation ( = 1,200 patients) and validation ( = 1,830 patients)]. The endpoint was death within 28 days. The main factors were EASIX [(lactate dehydrogenase creatinine)/thrombocytes] and aEASIX-COVID (EASIX age), which were log-transformed for analysis. Log-EASIX and log-aEASIX-COVID were independently associated with an increased risk of death in both cohorts ( < 0.001). Log-aEASIX-COVID showed a good predictive performance for 28-day mortality both in the derivation cohort (area under the receiver-operating characteristic = 0.827) and in the validation cohort (area under the receiver-operating characteristic = 0.820), with better predictive performance than log-EASIX ( < 0.001). For log aEASIX-COVID, patients with low/moderate risk (<6) had a 28-day mortality probability of 5.3% [95% confidence interval (95% CI) = 4-6.5%], high (6-7) of 17.2% (95% CI = 14.7-19.6%), and very high (>7) of 47.6% (95% CI = 44.2-50.9%). The cutoff of log aEASIX-COVID = 6 showed a positive predictive value of 31.7% and negative predictive value of 94.7%, and log aEASIX-COVID = 7 showed a positive predictive value of 47.6% and negative predictive value of 89.8%. Both EASIX and aEASIX-COVID were associated with death within 28 days in hospitalized COVID-19 patients. However, aEASIX-COVID had significantly better predictive performance than EASIX, particularly for discarding death. Thus, aEASIX-COVID could be a reliable predictor of death that could help to manage COVID-19 patients.