Predictive Value of MR-proADM in the Risk Stratification of COVID-19 Patients Assessed at the Triage of the Emergency Department (preprint)

Background: In the last two pandemic years, the Emergency Departments (ED) have been overrun with COVID-19 suspicious patients, creating a pressing need to optimize resources through risk stratification for those patients. For this reason, the assessment of prognostic tools and biomarkers have been necessary. Some dataon the role played by laboratory biomarkers in the early risk stratification of COVID-19 patients have been recently published. The aim of this study is to assess the potential role of the new biomarker mid-regional proadrenomedullim (MR-proADM) in stratifying the in-hospital mortality risk of COVID-19 patients at the triage in order to help the emergency physician in the decision-making process. A further goal of the present study is to evaluate whether MR-proADM together with other biochemical markers could play a key role in assessing the correct care level of these patients by predicting who could need intensive care and ventilation. Methods Data from 321 consecutive patients admitted to the triage of the emergency department with a COVID-19 infection were analyzed. Epidemiological, demographic, clinical, laboratory, and outcome data were assessed. C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), d-dimer and MR-proADM blood levels were also evaluated. Results All the biomarkers evaluated showed significant increased values at admission in the emergency department in non-survivorsvs survivors as well in ventilated as compared to non-ventilated patients. Moreover, all the biomarkers analyzed showed animportant role in predicting mortality, need of invasive mechanical ventilation (IMV) and non-invasive mechanical ventilation (NIMV) in patients admitted at the emergency department with COVID-19 infection as analyzed by the univariate Cox regression analysis. Pooling together both clinical and laboratory variables in a multivariate analysis, all biomarkers, except for PCT, seem to play a significant role in the mortality risk stratification at admission in the emergency department. Similarly, an increase of MR-proADM level at ED admission resulted independently associated with a threefold times higher risk of IMV. LDH showed a smaller but still significant power. CRP only showed a significant predictive value for the need of NIMV. In patients COVID-19 positive, MR-proADM assessed at the admission in the triage showed a good discriminative performance both for in-hospital mortality (AUC 0,85) and for prediction of IMV (AUC 0,81), whereas it was less effective for NIMV prediction (AUC 0,71). ROC curves and AUC resulted significantly greater for MR-proADM as compared to other laboratory biomarkers for the primary endpoint, i.e. in-hospital mortality, with the exception of CRP. Conclusion This study shows that MR-proADM seems to be particularly effective for early predicting mortality and the need of ventilation in COVID-19 patients admitted to the emergency department.


Introduction
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has spread worldwide and reached catastrophic proportions in the last two years. The SARS-CoV-2 infection has been named coronavirus disease 2019 . The World Health Organization (WHO) declared the SARS-CoV-2 infection as 'Public Health Emergency of International Concern' due to its rapid transmission among humans. After two years of the pandemic, there have been more than 230 million cases worldwide and nearly 5 million deaths. The SARS-CoV-2can present different symptoms and levels of severity including asymptomatic infection, mild upper respiratory tract illness, and severe viral pneumonia with respiratory failure [1].
During the pandemic, the admissions to the hospitals greatly increased thus stressing out the capacity of public health systems and resulting in a high mortality rate. This situation has been complicated further due to nonspeci c clinical features of COVID-19 pneumonia making it di cult to distinguish from other causes of severe pneumonia [1].
The lack of immediate results from the current microbiological tests to con rm COVID-19, coupled with the reported suboptimal sensitivity of swab tests by real-time reverse transcription-polymerase chain reaction (RT-PCR) assays, made the situation worse [2]. As a result, the emergency departments have been overrun with suspicious COVID-19 patients, creating a pressing need to optimize resources through risk strati cation for those patients already upon entering the triage.Since predicting the course of this disease at symptom onset is di cult and very often clinical conditions tends to worsen abruptly, prognostic tools and/orbiochemical markers have been fundamental to address patients through the right clinical pathway in the emergency department (ED).However,althoughseveral laboratory biomarkers have been so far identi ed to diagnose more rapidly COVID-19 pneumonia,to date, there is no data on biomarkers with high speci city and sensibility able to early stratify the mortality risk of patients affected by viralpneumonia [3].
C-reactive protein (CRP) has been one of the most used biomarkers to assessthe evolution of COVID-19 in ammatory processes, even though its use is limited by a low sensitivity for community-acquired pneumonia (CAP). While a high CRP value (>100 mg/L) can indicate a severe bacterial infection, lower values are common in both viral infections and noninfectious diseases [4].
Another biomarker evaluated in COVID-19 patients has been the procalcitonin (PCT), since it has an important role in detecting a bacterial superinfection to manage antibiotic therapy [5]. As known, PCT can predict microbial etiology in pneumonia [6]. On the other hand, in patients with a high PSI (classes III-V), PCT has proven to be a good prognostic marker rather than a diagnostic marker [7].
Procalcitonin, CRP and white blood cell count have shown to be signi cantly higher in CAP patients with a typical bacterial etiology as compared to cases in which the pathogen was represented by an atypical bacterium or by a virus [8]. Mid-regional proadrenomedullin (MR-proADM), a more stable fragment of the rapidly degrading active adrenomedullin (ADM) peptide, has been proven a promising biomarker, particularly effective in detecting endothelial dysfunction thus predicting severity and long-term adverse outcomes in CAP. In fact, Christ-Crain et al. [9]demonstrated that the level of MR-proADM, in contrast to CRP levels and leukocytes, increased according to CAP severity.Valenzuela Sanchez et al. [10] reported that MR-proADMwas able to predict unfavorable outcomes in patients with in uenza virus-induced pneumonia.Furthermore, MR-proADMis able to stratify the clinical risk in patients affected by CAP [11]. It has also been reported that MR-proADMobtained within 6 hours of arrival at the hospital has considerable prognostic value, independently of the causal agent of CAP and, if associated with PSI and CURB-65, it improves prognostic accuracy [11,12].
Interestingly, when the microcirculatory integrity is deteriorating causing the capillary leak, an alteration of the endothelium barrier function can occur, as happens during sepsis. It has been demonstrated that in these conditions MR-proADM plasma concentrations tend to increase [13].
Accordingly, Hupf et al. [14] have recently reported signi cantly higher adrenomedullin RNA blood expression in patients with severe COVID-19 vs. patients with a mild disease.
In this context, Li et al. (15) hypothesized that the integrity of the epithelial-endothelial barrier was severely interrupted in critical patients with COVID-19-related pneumonia thus introducing the concept of "viral sepsis". Con rming this pathogenetic mechanism, recent studies have shown that proin ammatory cytokines and chemokines such as tumor necrosis factor-α (TNF-α) and interleukin-6(IL-6) increased in COVID- 19 [16,17] and that this cytokine storm might play a key role in the evolution of SARS-CoV-2 infection [18].
Despite recent studies have demonstrated a predictive value of MR-proADM in patients with COVID-19-related pneumonia [19][20][21], no data are actually available about risk strati cation of patients with a suspected SARS-CoV-2 infection at the triage in the emergency department.
Therefore, the aim of this study is to assess the role of MR-proADM,in comparison to other biochemical markers,in stratifying the inhospital mortality risk of COVID-19 patients admitted at the triage in order to help the emergency physician in the decision concerning the rule-in or rule-out of these patients. A further goal of the present study is to evaluate whether the laboratory biomarkers can play a key role in predicting also the correct care level of these patients thus contributing to optimize the hospital resources.

Study design
The present study has an observational, retrospective single-center design. Data from 321 consecutive patients admitted to the Emergency Department of the University Hospital Tor Vergata (Rome, Italy) from Aprilto December 2020 with a con rmedCOVID-19 infectionwere analyzed. A diagnosis of COVID-19 was made by a positive real-time reverse transcription polymerase chain reaction (RT-PCR) taken from nasopharyngeal swabs and through radiological imaging, where indicated, in accordance with WHO interim guidelines.
Adult patients aged more than 18 yearswith a positive swab test were enrolled.
The epidemiological, demographic and clinicaldata were extracted from the electronic clinical records (Tab. 1).
Either chest X-rays or computed tomography scans were performed, depending on the physician's clinical assessment, and these were further reviewed by the emergency department's radiologist. When necessary, analyses of blood culture, sputum, urine, bronchial aspirate, and/or bronchoalveolar samples were also assessed.
The nal diagnosis was considered as that provided by the emergency department physician. A patient follow-up was performed up to 45 days.
The study was approved by the Local Ethics Committee (approval number 87/20) and was performed in accordance with the Declaration of Helsinki. Written informed consent was waived due to the rapid emergence of this infectious disease.

Blood sample collection
All baseline blood samples were immediately collected immediately at the triage admission. For serum and plasma specimens, blood samples were rapidly centrifuged upon arrival to the laboratory at 4500 xg for 5 minutes.

Statistical analysis
The primary endpoint was the overall in-hospital mortality;the secondary endpoints were the need of NIMV and IMV.
Continuous variables were expressed as mean (standard deviation) or median (interquartile ranges), according to data distribution, and were compared using the Student's t-test or the Mann-Whitney U test, when appropriate; categorical variables were expressed as counts and percentages and compared using the Chi-square or Fisher's exact tests, as appropriate.
Associations between candidate variables and endpointswere assessed using both univariate and multivariate Cox regression analyses, and hazard ratios were calculated. We have evaluated survivors compared with non-survivors and patients who needed ventilation (both invasive and non-invasive) compared with patients without ventilation.
The discriminatory power of the analyzed variables for predicting mortality was tested by means of a receiver operating characteristic (ROC) curve analysis with area under the ROC curve (AUC) determination.
For the regression analysis, variables were dichotomized according to cut-off values derived during the data analysis for this study, using the Youden index arising from the ROC curve analysis.
Kaplan-Meier curves were created to estimate the overall survival and compared using the log-rank test.
All analyses were performed with SPSS software. Tests were considered statistically signi cant if they yielded two-tailed p-values<0.05. For the multivariate analysis, we used variables resulting statistically signi cant in the univariate analysis.

Results
The study population ranged from 321 to 284 patients according to the different analysisdue to missed biomarkers data and one patient who died after 45 days as detailed in Table 3.
Among the comorbidities reported, obesity did not show signi cant differences between survivors and non-survivors, whereas malignancy showed a statistical level close to the signi cance. All the other comorbidities showed a signi cant difference between the two groups considered. Evaluating the secondary outcomes, cardiovascular disease and malignancy did not show signi cant differences between IMV and no-IMV, whereas all the other comorbidities showed a signi cant difference. For the last group of patients, only hypertension and renal disease showed signi cant differences between NIMV and no-NIMV patients.
All the biomarkers evaluated just after triage showed increased values in non-survivors as compared to survivors as well as in IMV and NIMV compared to no-IMV and no-NIMVreaching always a statistically signi cant level (Tab.2). Table 3 shows the results of the univariate Cox regression analysis performed to investigate the possible predictive role of clinical and demographic characteristics in patients with suspected COVID-19 infections. In addition, obesity does not seem to predict 45 days mortality, whereas malignancy showed a statistical level close to the signi cance in patients evaluated at the triage in the Emergency Department. All the other clinical features have shown signi cant odds ratio value to predict mortality in this group of patients.
Concerning the possible role in predicting need of IMVwithin 28 days in these patients, all the clinical features reached the statistical signi cance except for cardiovascular disease and malignancy, whereas only hypertension and renal diseases showed a signi cantodds ratio value for NIMV within 28 days (Tab. 3).
All the biomarkers analyzed showed a signi cant role in predicting mortality, need of IMV and NIMV in patients admitted at the ED with COVID-19 infection as analyzed by the univariate Cox regression analysis (Tab. 3).
Pooling together bothclinical and laboratory variables in a multivariate analysis and considering the whole observation period (mortality at 45 days, IMV and NIMV at 28 days), all biomarkers, except PCT, seem to play a key role in the mortality risk strati cation at the admission in the emergency department (Tab. 4). In fact, patients with avalue of MR-proADM higher than the cut-off value of 1.105 show an increase of mortality of almost three times(OR 2,97, IC 1,7-5,28);also CRP levels were independently associated with a higher risk of in-hospital mortality in patients with COVID 19 (OR 2,85, IC 1,73-4,69).Similarly, an increase in the admission MR-proADM level was independently associated with almost three times (OR 2,83, IC 1,49-5,36) higher risk of the need of IMV as well as for LDH which showed a smaller but still signi cant risk (OR 2,18, IC 1,33-3,57). Only CRP showed a signi cant predictive value (OR 2, IC 1-3,7) for the need of NIMV.
In COVID-19 patients,MR-proADM assessed at the ER admission showed a good discrimination performance both for in-hospital mortality (AUC 0,85) and for prediction of IMV (AUC 0,81), whereas it was less effective for NIMV prediction (AUC 0,71) with the optimal cut-off of 1,105 as obtained with the Youden index. ROC curves and AUC resulted signi cantly greater for MR-proADM as compared to the other biomarkers for the primary endpoint, i.e. in-hospital mortality,except for CRP (Tab. 5 and Fig. 1).
In particular, MR-proADM showed the better PPV (65%) and especially NPV (87%) in predicting mortality as well as for IMV and NIMV regarding NPV (both 88%) as compared to the other biomarkers with only CRP that showed similar values (Tab. 5).
The good discrimination performance of MR-proADM for the primary and secondary endpoint is also showed by the survival curves (Fig. 2). In fact, a higher survival rate and a reduced mechanical ventilation risk were evident for patients with values less than 1,05nmol/L at the admission in the ED.
Similar results have been found for CRP (Fig. 2), whereas the performance was lower for PCT, d-dimer and LDH, as shown in Figure  3, where it is evident a poor discrimination power.

Discussion
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has heavily affected the worldwide population in the last two years. Although most patients infected by SARS-CoV-2 had only a mild illness, about 5% of them suffered severe lung injury or even multiorgan dysfunction [22], requiring admission at intensive care unit (ICU).
Consequently, emergency departments have seen a dramatic increase in their workload, triggering the need to optimize resources and the decision to hospitalize only seriously ill patients, in order to face the more adequate care level.
The utilization of biomarkers at the admission to the emergency department to quickly stratify risksfor patients with pneumonia and other diseases has been largely reported [12,23,24]. We have shown, in previous studies, that MR-proADM is effective in risk strati cation for patients affected by community-acquired pneumonia (CAP), as well as in promptly determining the appropriate level of care in the emergency department [11,25].
To our knowledge, this is the rst study focused on the ability of new, as MR-proADM, and traditional biomarkers in the risk strati cation of patients with COVID-19 infections at the emergency department admission.
Previous studies performed with a smaller number of patients have reported that MR-pro ADM can play a role in predicting outcome in already hospitalized patients affected by COVID-19-related pneumonia [19,20].
In particular, our group has recently reported that MR-proADM seems to represent the most powerful biomarker for predicting death in critical patients at ICU, where the outcome can happen earlier, within one week, thus representing a good predictor for disposition of patients from emergency department to ICU [21].
In line with these previous studies, the median admission levels of all biomarkers checked in our studies showed signi cant higher values for all the endpoints considered, i.e. non-survivors vs survivors, IMV vs no-IMV and NIMV vs no-NIMV. This result suggests that these biomarkers might play a predictive role in the early risk strati cation of patients with COVID-19 infections.In fact, all the biomarkers considered showed a signi cant predictive value for the endpoints considered when analyzed with a univariate analysis.
Considering the possible confounding effect of the demographic and clinical features of patients, a multivariate analysis was performed pooling together both the clinical characteristics and the biomarkers assessed in the study. MR-proADM showed the best predictive value for the primary endpoints and for the need of IMV, whereas did not show signi cant predictive role for the need of NIMV.
In particular, it is notable that MR-proADM showed the best negative predictive value for all the endpoints considered thus giving a relevant support to the emergency physician in the eventual decision of the patient rule-out or rule-in and of the adequate clinical setting of patients affected by COVID-19 since it is able to predict also the possibility of ventilation need. This relevant information might greatly contribute to optimize the hospital resources and to hasten the decision-making process of the emergency physician.
The great power of MR-proADM in the mortality risk strati cation of COVID-19 patients has been further con rmed by the analysis of the ROC curves, which showed a signi cant greater AUC as compared to the other biomarkers. Similarly, the survival curves showed a primary role of MR-proADM as predictive factor in patients affected by COVID-19 in the emergency department.
Our novel data are in line with previous studies in which the predictive role of MR-proADMhas been evaluated in hospitalized COVID-19 patients [19][20][21].
Some differences among present and previous studies need to be highlighted. First, the clinical setting. In fact, in previous studies only critical patients admitted in the hospital wards have been enrolled. Our study, instead, have been primarily focused on patients admitted to the emergency department and therefore with different degrees of impairment ranging from asymptomatic to critical conditions. In these populations, the goal is to predict the trajectory of the illness at the symptoms onset and very often this is not easy.
The second important aspect of our study was the number of patients enrolled that was considerably greateras compared to previous studies.
Our data are also in line with previous studies in which the predictive value of biomarkers was tested in patients affected by CAP. Infact, while MR-proADM has been considered a useful tool for risk strati cation in patients affected by bacterial pneumonia [9,11,12], PCT proved to be less effective in predicting death and it was therefore considered as a useful diagnostic tool for tailoring antibiotic therapy [9,26,27].
CRP is usually considered as a non-speci c marker of acute in ammation that may possibly be in uenced by several other factors [9,27,28].
The results of our novel study emphasize the role of biomarkers as a useful tool for emergency physicians in the early risk strati cation of patients presenting to the ED, even in the age of COVID-19. Diagnostic and predictive value is likely to increase only after the most effective combination of scores and biomarkers has been established, or even by utilizing a panel of biomarkers [29][30][31]. For these reasons, it is important to know how biomarkers behave in response to de ned diseases such as SARS-CoV-2.
The limit of our study is that patients were recruited in only one hospital.Therefore, it would be desirable to extend the study to multiple centers to increase the number of enrolled patients, in order to con rm our results.

Conclusions
This study, which to our knowledge is the rst to evaluate the behavior of the MR-proADM compared to traditional biomarkers in COVID-19 patients at the admission in the ED, shows that all the biomarkers utilized can help the physician in the decisions making process. However,MR-proADM seems to represent the most powerful biomarker for predicting mortality and the need of ventilation in patients admitted at the emergency department. This is particularly useful for helping the emergency physician in the rule-in or ruleout of COVID-19 patients.Furthermore, this study can help in deciding the adequate clinical setting according to the possible need of ventilation thus contributing to optimize the hospital resources.
It is evident, however, that biomarkers will always oversimplify the interpretation of important variables and they complement, rather than supersede, a clinician judgment and/or validated severity scores.
In conclusion, MR-proADM appears to be particularly effective, among other biomarkers, in the risk strati cation for COVID-19 patients admitted to the emergency department thus helping the making decision process of emergency physician.  MR-proADM, mid-regional proadrenomedullin; CRP, C-reactive protein; PCT procalcitonin; LDH, lactate dehydrogenase AUC analysis for 45-day mortality prediction and for 28-day IMV or NIMV prediction of study population P value: differences between area of each biomarker vs MR-pro-ADM.

List Of Abbreviations
Cut-off derived from ROC (Receiver Operating Characteristic) using the Youden index.

Figure 2
Kaplan-Meier survival curve. Strati cation of patients with mid-regional proadrenomedullin (MR-proADM) levels greater or less than 1,105 nmol/L and C-reactive protein (CRP) levels greater or less than 95,5 mg/L at admission in the emergency department. IMV, invasive mechanical ventilation; NIMV, non-invasive mechanical ventilation.