Association between biomarkers and COVID-19 severity and mortality: a nationwide Danish cohort study

Abstract

ObjectiveTo evaluate the association between common biomarkers, death and intensive care unit (ICU) admission in patients with COVID-19.DesignRetrospective cohort study. From electronic national registry data, we used Cox analysis and bootstrapping to evaluate associations between baseline levels of biomarkers and standardised absolute risks of death/ICU admission, adjusted for age and gender.SettingAll hospitals in Denmark.Participants1310 patients aged ≥18 years admitted to hospital with COVID-19 from 27th of February to 1st of May 2020, with available biochemistry data.Main outcome measuresA composite of death/ICU admission occurring within 30 days.ResultsOf the 1310 patients admitted to hospital (54.6% men; median age 73.6 years), 352 (26.9%) experienced the composite endpoint and 263 (20.1%) died. For the composite endpoint, the absolute risks for moderately and severely elevated C reactive protein (CRP) were significantly higher, 21.5% and 39.2%, respectively, compared with 5.0% for those with normal CRP. Moderately and severely elevated leucocytes were significantly higher, 34.5% and 46.6% risk, respectively, compared with 23.2% for those with normal leucocytes. Moderately and severely decreased estimated glomerular filtration rates (eGFR) were significantly higher, 41.5% and 45.9% risk, respectively, compared with 30.4% for those with normal/mildly decreased eGFR. Normal and elevated ureas were significantly higher, 22.3% and 40.6% risk, respectively, compared with 7.3% for those with low urea. Elevated D-dimer was significantly higher, 31.8% risk, compared with 17.5% for those with normal D-dimer. Moderately and severely elevated troponins were significantly higher, 27.7% and 57.3% risk, respectively, compared with 9.4% for those with normal troponin. Elevated procalcitonin was significantly higher, 52.1% risk, compared with 28.0% for those with normal procalcitonin.ConclusionIn this nationwide study of patients admitted with COVID-19, elevated levels of CRP, leucocytes, procalcitonin, urea, troponins and D-dimer, and low levels of eGFR were associated with higher standardised absolute risk of death/ICU admission within 30 days.

Prognostic Value of Bioactive Adrenomedullin in Critically Ill Patients with COVID-19 in Germany: An Observational Cohort Study

“…Several publications from China addressed the prognostic value of different parameters in predicting disease severity and short-term survival in COVID-19 patients [ 41 , 42 , 43 , 44 , 45 , 46 ]. Of note, although limited by a small size and the single center character, our data show significantly elevated bio-ADM levels in non-survivors compared to survivors with a moderate predictive value for 28-day mortality.…”

Epidemiology and microbiology of ventilator-associated pneumonia in COVID-19 patients: a multicenter retrospective study in 188 patients in an un-inundated French region

“…Procalcitonin was not routinely measured in the ICUs that participated in our study, although it could be a helpful tool in the decision regarding early use of antibiotics. However, procalcitonin levels are generally elevated in COVID-19 ICU inpatients [22], and data are needed to assess a possible specific threshold.…”

An Online Risk Calculator for Rapid Prediction of In-hospital Mortality from COVID-19 Infection

“…11,21,22 While previous studies have identified other laboratory values, such as red cell distribution width and D-dimer levels, as significant predictors, they did not contribute to this algorithm. 3,14 BUN was the only laboratory value in the algorithm and a missing value did not influence the score. This suggests that clinicians do not need to order or wait for other test results to estimate a patient’s probability of dying.…”

“…Previous studies of predictors of dying from COVID-19 infection have had a small number of deaths; [1][2][3][4][5][6][7] used comorbid conditions, diagnoses ,and severity indices from electronic medical records that may not be known at the time of admission; 4,[8][9][10][11][12][13] or included specialized laboratory tests-such as levels of C-reactive protein, troponin, and D-dimers-that are not readily available for urgent triage of patients for hospital admission or intensive care. 14 Some studies were done in ethnically homogenous populations such as Wuhan, China 1 or Italy, 15 in specific populations such as nursing home residents, 16 or among patients already being treated in an intensive care unit (ICU) 6,9 Although some studies applied machine learning methods to develop predictive models, 1,5,17,18 none have been based on measurements available at the time of triage in a large diverse population, nor have they been translated into calculators that can be used in clinical settings.…”