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Corresponding author: Enrique Bernal-Morell, Infectious Disease Unit, Hospital General Universitario Reina Sofía, Murcia and the Instituto Murciano de Investigación Biosanitaria (IMIB), Spain. Avda. Intendente Jorge Palacios Avenue, 1, CP 30003.
Endotheliopathy is a pathological feature associated with thromboinflammation.
Endothelial biomarkers may help the stratification of risk in COVID-19.
Disruption of the adrenomedullin system contributes to endothelial dysfunction.
MR-proADM might be useful for early risk stratification of COVID-19.
Thromboinflammation, resulting from a complex interaction between thrombocytopathy, coagulopathy, and endotheliopathy, contributes to increased mortality in COVID-19 patients. MR-proADM, as a surrogate of adrenomedullin system disruption, leading to endothelial damage, has been reported as a promising biomarker for short-term prognosis. We evaluated the role of MR-proADM in the mid-term mortality in COVID-19 patients.
A prospective, observational study enrolling COVID-19 patients from August to October 2020. A blood sample for laboratory test analysis was drawn on arrival in the emergency department. The primary endpoint was 90-day mortality. The area under the curve (AUC) and Cox regression analyses were used to assess discriminatory ability and association with the endpoint.
A total of 359 patients were enrolled, and the 90-day mortality rate was 8.9%. ROC AUC for MR-proADM predicting 90-day mortality was 0.832. An optimal cutoff of 0.80 nmol/L showed a sensitivity of 96.9% and a specificity of 58.4%, with a negative predictive value of 99.5%. Circulating MR-proADM levels (inverse transformed), after adjusting by a propensity score including eleven potential confounders, were an independent predictor of 90-day mortality (HR: 0.162 [95% CI: 0.043-0.480])
Our data confirm that MR-proADM has a role in the mid-term prognosis of COVID-19 patients and might assist physicians with risk stratification.
In December 2019, an outbreak of pneumonia due to a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan (Hubei Province, China). The disease caused by this virus was called Coronavirus disease 19 (COVID-19), resulting in a pandemic affecting millions of people globally (
Emerging advances in understanding the pathophysiology of infection by SARS-COV-2 have been crucial to improving the treatment and management of COVID-19. The most severe forms of this disease are not limited to the respiratory system but is a multisystem syndrome in which the vascular endothelium is the primary damaged organ, characterized by inflammation and immunothrombosis within microvessels (
). Because the vascular endothelium constitutes a cellular barrier playing a crucial role in the maintenance of vessel integrity, endothelial damage and dysfunction may also be prominent features of COVID-19 induced severe illness (
). Finally, differences in the predictive accuracies of biomarkers as D-dimer or IL-6 between the first and second wave have been reported, reflecting a different disease stage of patients on arrival to the hospital (
), conditions both affecting to the accuracy of biomarkers.
In the present study, we aimed to evaluate the role of MR-proADM with regards to the prediction of severity in hospitalized patients by SARS-CoV-2 infection, focusing on a longer period after the index event (90 days), in a large cohort including patients in the second wave.
Material and methods
Study design and patient selection
This was a two-center prospective observational study recruiting consecutive adult (≥ 14 years) COVID-19 patients admitted to Reina Sofía University Hospital (Murcia, Spain) and Santa Lucía University Hospital (Cartagena, Spain) between September and October 2020, during the second wave in Spain. Infection by SARS-CoV-2 was diagnosed by a positive result of real-time reverse transcriptase-polymerase chain reaction testing of a nasopharyngeal or lower respiratory tract specimen, according to WHO Guidelines (
). Exclusion criteria were: (a) patients < 14 years; (b) pregnant women; (c) patients transferred from or to other hospitals and (d) lack of samples for the measurement of biomarkers. Only a first episode of admission to the hospital was considered for inclusion in the study.
The study protocol was approved by the local Ethics Committee of both hospitals and was performed under a waiver of informed consent and following the Declaration of Helsinki ethical guidelines.
For eligible patients, clinical variables at admission and during the stay were extracted from electronic medical records. Admission variables were as follows: age, gender, SOFA score as an indicator for organ dysfunction, time from symptoms onset, the type of radiological pneumonia seen in chest X-ray or CT (absent, unilateral, or bilateral), comorbidities (hypertension, dyslipidemia, diabetes mellitus, obesity, current smoking, chronic kidney injury, cardiovascular disease, cerebrovascular disease, active cancer, liver disease, dementia, immunosuppression, chronic obstructive pulmonary disease (COPD) or other non-asthma respiratory diseases, asthma, and peptic ulcer), previous treatments (angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), non-steroidal anti-inflammatory drugs, statins, immunosuppressors, systemic corticoids, and oral anticoagulants, including vitamin K antagonists and direct oral anticoagulants. In-hospital treatments were also recorded. Additionally, data from routine hematological, biochemical, and coagulation tests were collected from laboratory information systems.
Ninety-day all-cause mortality following enrollment was the primary outcome. Patients were followed up from admission to 90 days after discharge or until death.
Blood sampling and laboratory analysis
In all patients, blood samples for biochemical analysis, including creatinine, albumin, bilirubin, C-reactive protein (CRP), procalcitonin and lactate dehydrogenase (LDH), hematological analysis, including cell blood counts, and coagulation markers, including D-dimer, were drawn on arrival to the Emergency Department and results were made available according to clinical routine. For ferritin and interleukin-6 (IL-6), leftover serum was immediately frozen and stored at -80°C until testing. For the measurement of MR-proADM, blood samples collected in tubes containing EDTA K3 as anticoagulant were centrifuged at 2000 g for 10 min, and plasma was subsequently frozen and stored to -80°C until testing, according to stability results previously reported (
Plasma MR-proADM levels were measured by a homogeneous sandwich immunoassay with fluorescent detection using a time-resolved amplified cryptate emission (TRACE) technology assay (KRYPTOR® Gold, Brahms ThermoFisher Scientific Inc., Hennigsdorf, Berlin, Germany). According to the manufacturer's data, the detection limit, functional sensitivity, and quantification limit were 0.05 nmol/L, 0.23 nmol/L, and 0.25 nmol/L; intra-assay coefficient of variation (CV) and inter-assay CV were ≤ 10% and ≤ 20%, for a level ranging from 0.2 to 0.5 nmol/L, respectively.
The normality of continuous variables was tested by Kolmogorov-Smirnov or Shapiro-Wilk test, and they are reported as median (interquartile range [IQR]) or mean (standard deviation [SD]). Categorical variables are presented as frequency and percentage in each category. The Mann-Whitney U test and chi-squared test were used to compare continuous and categorical data between survivors and nonsurvivors as was the Kruskal-Wallis test and chi-squared test across quartiles of MR-proAMP and SOFA score on admission to the ED.
The discriminatory ability for 90-day mortality was evaluated by calculating the area under the receiver operating characteristic curve (ROC AUC). Youden's criterion was used to establish the optimal cutoff value, with sensitivity, specificity, negative and positive predictive values (NPV, PPV), negative and positive likelihood ratios (LR-, LR+) also reported. Furthermore, we validated the prognostic value of different reported MR-proADM cutoffs based on previous studies in other populations (
). Kaplan-Meier curves and log-rank tests were used to compare survival time stratified by an optimal cutoff.
We developed a full non-parsimonious logistic regression model to derive a propensity-score for the prediction of high circulating MR-proADM levels (above the median, 0.76 nmol/L) with eleven independent variables (age, hypertension, diabetes mellitus, dyslipidemia, obesity, COPD, CKD, cardiovascular disease, cerebrovascular disease, dementia and SOFA score). Our propensity score analysis attempted to compare outcomes for patients with COVID-19 that exhibited high vs. low MR-proADM levels, who had a similar distribution of measured covariates, and in this way approximated the condition of random assignment (
). The C-statistic of the propensity score was 0.885 (95% CI 0.850–0.919). We then divided subjects into four equal-size groups using the quartiles of the estimated propensity score. Seven (1.9%) patients were excluded from multivariable and propensity scores analyses because of missing values. The independent effect of circulating MR-proADM levels was determined using the estimated regression coefficient from the fitted regression models; thus, we conducted adjusted analyses using Cox proportional hazard models, entering the propensity score as a covariate. MR-proADM was inverse-transformed before being entered into the Cox model, due to a non-gaussian distribution. The risk of the 90-day all-cause mortality was expressed as a hazard ratio (HR) and 95% confidence intervals (CI). To test for consistency, CIs were calculated with a 3000-iterations bootstrapped method.
Statistical analysis was performed using SPSS vs. 22 (SPSS Inc) and MedCalc 15.0 (MedCalc Software).
During the enrolment period, a total of 373 COVID-19 patients were recruited. Two patients were still hospitalized at the time of the analysis and therefore excluded from the data set. According to exclusion criteria, six patients transferred from or to other hospitals and one pregnant woman were excluded; in five cases, aliquots for biomarker analysis were not available. Finally, the study population included 359 hospitalized patients with SARS-CoV-2 infection, 197 from Santa Lucía University Hospital, and 162 from Reina Sofía University Hospital. Figure 2 provides an overview of the study flow.
Patients' characteristics and biomarkers stratified by the primary endpoint
Baseline characteristics in the overall cohort and stratified data according to 90-day mortality are summarized in Table 1. Median age was 59 years (Interquartile range [IQR]: 47-71) and 64.1% (n=230) were male. The most prevalent comorbidities were hypertension (46.0%), obesity (n=240 [45.0%]) and diabetes mellitus (25.3%). Radiographic signs of infiltrates were recorded in 331 patients (92.2%) on chest X-rays at admission. In the overall cohort, 36.5% were on ACEI/ARBs and 31.5% on statins. Forty-three patients (12.0%) required invasive mechanical ventilation, 106 (29.5%) were admitted to ICU, and 32 (8.9%) died within the first 90 days of follow-up. Overall, patients hospitalized due to SARS-CoV-2 infection had a median length of hospital stay (LOS) of ten days (IQR: 6-17).
Table 1Baseline characteristics in overall population and in groups according to 90-day mortality
During hospitalization, the most common complication was ARDS (45.4%), followed by liver (21.2%) and acute kidney injury (KDIGO stage 1 acute kidney injury or worse) (18.7%). In addition, 23 (6.4%) patients developed an episode of bacteremia. Concerning the in-hospital treatments, low molecular weight heparin, corticosteroids (methylprednisolone and/or dexamethasone), antimicrobials drugs (azithromycin or others), and remdesivir were frequently used (97.5%, 93.6%, 79.1%, and 25.6%, respectively).
Laboratory findings in the overall cohort and stratified according to survival status are summarized in Table 1. Creatinine, procalcitonin, IL-6, and MR-proADM were significantly higher and, in contrast, albumin and lymphocyte count significantly lower, in deceased patients. Median admission MR-proADM levels were two-fold higher in non-survivors compared to survivors (1.50 nmol/L [IQR: 0.98-2.31] vs. 0.73 nmol/L [IQR: 0.56-1.06]).
Patients' characteristics stratified by MR-proADM levels
The median level of MR-proADM in our cohort was 0.76 nmol/L (IQR: 0.57-1.15 nmol/L). When patients were stratified according to MR-proADM quartiles (Supplementary Table 1), those with higher levels upon admission were older and had a higher rate of hypertension, diabetes mellitus, obesity, cardiovascular disease, chronic kidney disease, and dementia. All-cause 90-day mortality increased significantly from the first quartile (n=0) to the fourth quartile (n=20 [22.2%]).
Association of MR-proAMP with disease severity on admission
SOFA, as an indicator of severity on arrival to the ED, was calculated in 352 patients (98%) and was significantly associated with higher concentrations of MR-proANP, ranging from 0.63 nmol/L (IQR: 0.50-0.83) in patients with SOFA < 2 to 2.28 (IQR: 1.22-3.91) in patients with SOFA ≥ 7 (Figure 3).
Receiver operating curves for prediction of 90-day mortality by MR-proADM and other biomarkers and Kaplan-Meier analysis
Concerning predictive ability, circulating levels of MR-proADM showed the highest discrimination ability for 90-day mortality (ROC AUC: 0.832; 95% [CI]: 0.770-0.894) (Table 2 and Figure 4), although a significant difference was not detected in comparison to procalcitonin (ROC AUC: 0.795; 95% CI: 0.716-0.874) (Table 2). According to the Youden Index, we found an optimal cut-off at 0.80 nmol/L, with a sensitivity of 96.9% (95% CI: 83.8-99.9%) and a specificity of 58.4% (95% CI: 52.9-63.8%) yielding a very high negative predictive value of 99.5% (95% CI: 97.1-100%). When higher cutoffs were analyzed, such as 1.54 and 1.8 nmol/L, a higher specificity was reached, as expected, but with positive predictive values below 40% (Table 3). MR-proADM achieved a similar accuracy (ROC AUC; 0.832; 95%CI: 0.763-0.901; p<0.001) when short-term (30 day) mortality was taken as the endpoint.
Table 2ROC curve and AUC analysis for 90-day mortality prediction
ROC AUC, 95% CI
p-value of comparison vs. MR-proADM
0.832 (0.770-0.894; p<0.001)
0.795 (0.716-0.874; p<0.001)
0.751 (0.660-0.842; p<0.001)
0.712 (0.618-0.806; p<0.001)
0.698 (0.605-0.791; p<0.001)
0.689 (0.591-0.788; p<0.001
0.634 (0.542-0.726; p<0.001)
Only biomarker levels or blood cell counts with a significant ROC AUC were included in this table
Abbreviations: ROC: Receiver Operating Characteristics; AUC: Area under the curve; CI: Confidence interval; MR-proADM: Mid-regional proadrenomedullin; IL-6: Interleukin 6
Kaplan-Meier curves using the optimized MR-proADM cut-off identified a higher mortality (18.6% vs. 0.5%; p<0.001) in patients with MR-proADM > 0.80 (n=167) in comparison to those with a MR-proADM ≤ 0.80 nmol/L (n=192) (Figure 5).
Association of MR-proADM with 90-day mortality
In regression analyses, after adjusting by a propensity score, inverse transformed MR-proADM levels showed an independent association with the study endpoint (HR:0.162 [95% CI: 0.043-0.480]; p=0.002).
Recent research into the underlying mechanisms of coronavirus-mediated diseases suggests that a complex interaction between coagulopathy, thrombocytopathy, and endotheliopathy contribute to COVID-19-associated thromboinflammation, a significant cause of morbidity and mortality in infected patients by SARS-CoV-2 (
Because identifying early factors related to COVID-19 severity could provide valuable information about the appropriate clinical care for these patients as well as the allocation of health resources, the characterization of endothelial damage by the measurement of endothelial biomarkers may help to enable stratification of COVID-19 patients with the highest pro-thrombotic risk (
) in COVID-19 patients, the methodologies used are cumbersome and not applicable for its implementation as a STAT laboratory test. In this sense, the automated measurement of MR-proADM, as a surrogate of ADM activity, which plays a key role in reducing vascular (hyper) permeability and promoting endothelial stability and integrity following severe infection, could be of interest to characterize COVID-19 induced endothelial damage (
This prospective study aimed to analyze the value of MR-proADM as a surrogate biomarker of ADM activity for predicting mid-term mortality in confirmed COVID-19 patients during the second wave of the pandemic. The main findings were: (1) MR-proADM was the biomarker with the highest performance for predicting 90-day mortality; (2) a low MR-proADM level (0.80 nmol/L) showed a very high negative predictive value to rule-out mid-term mortality, which might contribute to decision-making by clinicians in combination with the clinical evaluation; (3) after adjusting by a propensity score, including eleven variables, MR-proADM was an independent predictor for mid-term mortality; and (4) similar to other studies recently published (
) and the likelihood of further disease progression in patients with suspected infection presenting to the ED, to either initiate, escalate or intensify early treatment strategies, or identify patients suitable for safe outpatient treatment (
). Fewer studies have evaluated the prognostic role of MR-proADM in viral infections, mainly by the influenza virus, and the results reported are controversial, with ROC AUC ranging from 0.68 for a composite of death, ICU admission, and prolonged stay (
). The main limitations in these studies are the small sample size and the inclusion of patients recruited in the first wave, in which the role of laboratory tests has been recently disputed, with differences in the prognostic value of some thromboinflammation markers in comparison to the first wave. Noteworthy, in our study, differences between survivors and nonsurvivors for D-dimer or CRP were not detected, as Mollinedo-Gajate et al. reported (
). Furthermore, most of these studies focused on a short follow-up period (28/30 days) from ED admission to the endpoint. Although 28 or 30-day mortality is an outcome commonly used in studies in ED to evaluate the impact of an intervention on patients, COVID-19 patients, particularly those admitted to ICU, have required a prolonged hospital length of stay, so death could occur after 30 days from arrival to ED (
Results of our study, including a cohort of 359 patients recruited during the second wave in two Spanish hospitals, confirm that MR-proADM levels may help to identify the risk for a poor outcome in patients presenting to the ED. Notably, and due to a elevated negative predictive value close to 100%, associated with the chosen optimal cutoff (0.8 nmol/L), low MR-proADM levels would allow recognizing patients with low mortality risk who could benefit from less intensive treatment. This finding, also reported by
), MR-proADM was the biomarker with the highest prognostic accuracy for short-term (30-day) mortality (ROC AUC: 0.832) and mid-term (90-day) mortality, although without a significant difference in comparison to procalcitonin (ROC AUC: 0.795), a bacterial infection biomarker, for this second outcome. Unfortunately, the presence of bacterial co-infection on arrival in the ED was not recorded in this study, and therefore it could not be excluded. It is unclear that the reported low co-infection rate is the result of large scale empirical antimicrobial administration or the limitation of the overwhelmed microbiological tests in health systems during the pandemic (
). Finally, multivariate analysis showed the value of MR-proADM as an independent predictor for 90-day mortality (HR for inverse transformed MR-proADM: 0.162 [95% CI: 0.043-0.480; p=0.002]) even after a bootstrap replication with 3000-iterations. Our results confirm the association of endothelial damage, characterized by MR-proADM levels, with COVID-19 severity.
Although this is the study with a larger sample size evaluating the role of MR-proADM for prognosis of severity in COVID-19 patients, it has some limitations. First, only one measurement of MR-proADM on arrival to ED was performed, and the impact of serial measurements was not evaluated. However, a single determination has been sufficient to reliably predict the evolution of these patients in both the short and mid-term. Second, other biomarkers previously reported as predictors of severity, such as troponin (
), were not measured. However, the European Society of Cardiology discouraged its routine measurement in COVID-19 because it concludes that it is unlikely that cardiac troponin provides incremental value to other strong predictors of death (
In conclusion, our study confirms that MR-proADM levels, measured on arrival to the ED, have a potential role in establishing the prognosis of patients infected by SARS-CoV-2 requiring hospital admission. Low MR-proADM levels might assist physicians in the early identification of low-risk patients with a high probability of survival in clinical decision-making.
ThermoFisher Scientific, BRAHMS, Henningsdorf (Germany) supported the study by providing reagents and other materials for the measurement of MR-proADM. ThermoFisher Scientific, BRAHMS, did not participate in the manuscript's study design, data collection, and analysis or writing.
Conflict of interest
The authors state no conflict of interest.
EGB and LGGR designed the study, analyzed the data, and wrote the manuscript. LCS provided statistical advice. PET and NSR measured MR-proADM in plasma samples. MMM, MJA, AA, CBPC, CTJ, MDRM, MHO, MGM, VCR, ACH, PPS and MSRB contributed to the enrollment of patients and clinical data collection. PET, NSR, and VRA managed the laboratory investigations. All authors reviewed and approved the final manuscript. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.