key: cord-0770423-j5drurnj
authors: de Guadiana-Romualdo, Luis García; Martínez, Monica Martínez; Mulero, María Dolores Rodríguez; Torrella, Patricia Esteban; Olivo, Marta Hernández; García, María José Alcaraz; Campos-Rodríguez, Valerio; Sancho-Rodríguez, Natalia; Martínez, María Galindo; Alcaraz, Antonia; Braquehais, María Salome Ros; Perez-Crespo, Carlos Báguena; Arenas, Verónica Ramos; Jiménez, Cristina Tomás; Consuegra-Sánchez, Luciano; Conesa-Hernandez, Andrés; Piñera-Salmerón, Pascual; Bernal-Morell, Enrique
title: Circulating MR-proADM levels, as indicator of endothelial dysfunction, for early risk stratification of mid-term mortality in COVID-19 patients
date: 2021-08-28
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2021.08.058
sha: 183ff0fc968ad4cdbe112bc31b40bc45da0ba662
doc_id: 770423
cord_uid: j5drurnj

OBJECTIVES: Thromboinflammation, resulting from a complex interaction between trombocytopathy, coagulopathy and endotheliopathy, contributes to increased mortality in COVID-19 patients. MR-proADM, as a surrogate of adrenomedullin system dysruption 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. METHODS: Prospective, observational study enrolling COVID-19 patients from August to October 2020. A blood sample for laboratory test analysis was drawn on arrival to emergency department. The primary endpoint was 90-day mortality. Area under the curve (AUC) and Cox regression analysis were used to assess its discriminatory ability and association with the endpoint. RESULTS: A total of 359 patients were enrolled and 90-day mortality rate was 8.9%. ROC AUC for MR-proADM predicting 90-day mortality was 0.832. An optimal cut-off 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 11 potential confounders, were a independent predictor of 90-day mortality (HR: 0.162 [95% CI: 0.043-0.480]) CONCLUSIONS: Our data confirms that MR-proADM has a role for mid-term prognosis of COVID-19 patients and might assist to physicians for risk stratification.

In December 2019, an outbreak of pneumonia due to a novel coronavirus, named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Preliminary results in small scale studies including patients on first wave suggest a potential role for MR-proADM regarding prognosis García de Guadiana-Romualdo et al.,2021; Gregoriano et al., 2021; Sozio et al., 2021; Montrucchio et al., 2020, but In the present study, we aimed to evaluate the role of MR-proADM with regards 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 of second wave.

This was a two-centre 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 Guidance World Health Organization., 2020. Exclusion criteria were: (a) patients < 14 years; (b) pregnant women; (c) patients transferred from or to other hospital and (d) lack of samples for the measurement of biomarkers. Only a first episode of admission to 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 in accordance with 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 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, 9 dementia, immunosuppression, chronic obstructive pulmonary disease (COPD) or other non-asthma respiratory diseases, asthma and peptic ulcer), previous treatments (angiotensin converting enzyme inhibitors (ACEi), angiotension 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 enrolment was the primary outcome.

Patients were followed up from admission to 90 days after discharge or until death.

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 available according to clinical routine. For ferritin and interleukin-6 (IL-6), leftover serum was immediately frozen and 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 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 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 11 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 similar distribution of measured covariates, and in this was 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 were 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 in the Cox model due to a non-gaussian distribution. Risk of the 90-day all-cause mortality was expressed as 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, 6 patients transferred from or to other hospitals and one pregnant woman were excluded; in 5 cases aliquots for biomarker analysis were not available. Finally, the study population included 359 hospitalized patients by SARS-CoV-2 infection, 197

from Santa Lucía University Hospital and 162 from Reina Sofía University Hospital, respectively. Figure 2 provides an overview of the study flow.

Baseline characteristics in the overall cohort and stratified data according to 90day 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-ray 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 10 days (IQR: 6-17).

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 13 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).

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%). Table 2 ). According to 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 cut-offs 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 considered as endpoint.

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 in comparison to those with a MR-proADM ≤ 0.80 nmol/L (n=192) ( Figure 5 ).

In regression analysis, 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 thromboinflamation, a major cause of morbidity and mortality in infected patients 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 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; after adjusting by a propensity score, including 11 variables, MR-proADM was an independent predictor for mid-term mortality; and (4) Results in our study, including a cohort of 359 patients recruited during the second wave in two Spanish hospitals, confirms that MR-proADM levels may 18 help to early identify the risk for a poor outcome in patients presenting to the ED. Particularly, and due to the elevated negative predictive value, close to 100%, associated to 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 Gregoriano et al. 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 shows a number of 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 Wibowo et al.,

2021, were not measured. However, its routinely measurement in has been discouraged by the European Society of Cardiology, because it concludes that it is unlikely that cardiac troponin provides incremental value to other strong predictors of death The European Society of Cardiology., 2020.

In conclusion, our study confirms that MR-proADM levels, measured on arrival to the ED, have a potential role to establish the prognosis of patients infected by SARS-CoV-2 requiring admission to hospital. Low MR-proADM levels might assist to physicians in early identifying low-risk patients, with a high probability of survival, and clinical decision makings.

ThermoFisher Scientific, BRAHMS, Henningsdorf (Germany) supported the study providing reagents and other materials for measurement of MR-proADM.

ThermoFisher Scientific, BRAHMS, did not participate in the study design, data collection and analysis or writing of the manuscript.

Authors state no conflict of interest. 

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/mL FEU)

SOFA: Sequential Organ Failure Assessment; COPD: Chronic Obstructive Pulmonary Disease; LDH: Lactate dehydrogenase; CRP: C-reactive protein; IL-6: Interleukin 6; WBC: White blood cell; NLR: Neutrophil-tolymphocyte ratio; MR-proADM: Mid-regional proadrenomedullin

Sp: Specificity; LR: Likelyhood ratio; PPV: positive predictive value; NPV: Negative predictive value