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MR-proADM as Prognostic Factor of Outcome in COVID-19 Patients
Paolo Cameli1, Elena Pordon1, Miriana d'Alessandro1
1Respiratory Diseases Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, 53100 Siena, Italy.
Background:
Serum mid-regional proadrenomedullin (MR-proADM) has emerged as a marker of organ failure (mainly lungs and kidneys) and poor prognosis in patients admitted to intensive care (IC); some reports also suggest it and other markers, such as Krebs von den Lungen-6 (KL-6) and interleukin-6 (IL-6), as a prognostic biomarker of COVID-19. The aim of the study was to evaluate the performance MR-proADM in hospitalized COVID-19 patients for predicting in-hospital mortality and need for non-invasive or invasive respiratory support.
Methods:
We enrolled 74 patients hospitalized in the COVID Unit of Siena Hospital from March to May 2020, for whom serum samples were available on admission for assay of MR-proADM, KL-6 and IL-6. Demographic data, comorbidities, medical history and clinical laboratory data on days 1-3 of admission and Simplified Acute Physiology Score and Simplified Organ Failure Assessment scores calculated at day 1 were collected retrospectively, as well as mortality and IC admission data.
Results:
12 patients died in hospital (16%) and 14 patients were admitted to IC (19%). Serum concentrations of MR-proADM on admission and on day 1 were higher among non-survivors than among survivors (p = 0.015 and p = 0.045, respectively), while those on day 3 were not significantly different. Patients needing respiratory support had higher MR-proADM concentrations on admission than the others (p = 0.046), and those requiring invasive mechanical ventilation had higher MR-proADM on day 1 (p = 0.017). Serum concentrations of KL-6 and IL-6 were significantly higher in non-survivors (p = 0.03 and p = 0.004, respectively). ROC curve analysis showed that serum MR-proADM on day 1 had the best accuracy in predicting death and/or IC admission (AUC = 0.9583, p = 0.0006); the combination of all three biomarkers further improved the accuracy of prediction of death or IC admission (AUC = 0.9793; p = 0.00004).
Conclusions:
Our data sustain the potential of serum MR-proADM as a reliable prognostic biomarker of hospitalized COVID-19 patients and confirms the utility of the three markers in the management and risk stratification of hospitalized patients. The markers are collected mini-invasively and are quick to analyze and cost-effective.
Insights
Serum mid-regional proadrenomedullin (MR-proADM) effectively predicts mortality and respiratory support needs in hospitalized COVID-19 patients. Combining MR-proADM with KL-6 and IL-6 further enhances prognostic accuracy for better patient risk stratification.
Area of Science:
- Biochemistry
- Clinical Medicine
- Critical Care Medicine
Background:
- Serum mid-regional proadrenomedullin (MR-proADM) is a marker for organ failure and poor prognosis in intensive care.
- MR-proADM, KL-6, and IL-6 are investigated as potential prognostic biomarkers for COVID-19.
Purpose of the Study:
- To evaluate MR-proADM's performance in predicting in-hospital mortality.
- To assess MR-proADM's ability to predict the need for respiratory support in hospitalized COVID-19 patients.
Main Methods:
- Retrospective analysis of 74 hospitalized COVID-19 patients.
- Serum samples analyzed for MR-proADM, KL-6, and IL-6 on admission and days 1-3.
- Collection of demographic, clinical, and outcome data, including mortality and intensive care unit (ICU) admission.
Main Results:
- Non-survivors and patients requiring respiratory support showed higher MR-proADM levels on admission and day 1.
- MR-proADM on day 1 demonstrated high accuracy (AUC=0.9583) in predicting death and/or ICU admission.
- Combining MR-proADM, KL-6, and IL-6 improved prediction accuracy (AUC=0.9793).
Conclusions:
- Serum MR-proADM is a reliable prognostic biomarker for hospitalized COVID-19 patients.
- MR-proADM, KL-6, and IL-6 aid in managing and stratifying risk for hospitalized patients.
- These biomarkers are mini-invasively collected, quick to analyze, and cost-effective.
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