Mid-regional pro-adrenomedullin in patients with acute dyspnea: data. from the Akershus Cardiac Examination (ACE) 2 Study

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1 Mid-regional pro-adrenomedullin in patients with acute dyspnea: data from the Akershus Cardiac Examination (ACE) 2 Study Mohammad Osman Pervez MD 1 ; Magnus Nakrem Lyngbakken MD 1 ; Peder Langeland Myhre MD 1 ; Jon Brynildsen MD 1 ; Eva Camilla Langsjøen MD 2 ; Arne Didrik Høiseth MD, PhD 1 ; Geir Christensen MD, PhD, MHA 3 ; Torbjørn Omland MD, PhD, MPH 1 ; Helge Røsjø MD, PhD 1 1 Division of Medicine, Akershus University Hospital, Lørenskog, Norway and Center for Heart Failure Research, University of Oslo, Oslo, Norway; 2 Section for Medical Biochemistry, Division of Diagnostics and Technology, Akershus University Hospital, Lørenskog, Norway; 3 Institute for Experimental Medical Research, Oslo University Hospital, Ullevål, Oslo, Norway and Center for Heart Failure Research, University of Oslo, Oslo, Norway Corresponding author: Helge Røsjø, MD, PhD, Division of Medicine, Akershus University Hospital, Sykehusveien 25, 1478 Lørenskog, Norway. Tel: Fax: helge.rosjo@medisin.uio.no Short title: MR-proADM in patients with dyspnea Key words: MR-proADM, Biomarker, Cardiovascular, Heart failure, Prognosis Abstract: 247 Text: 3680 Tables: 2 Figures: 2 1

2 ABSTRACT Background: Mid-regional pro-adrenomedullin (MR-proADM) is a surrogate marker for adrenomedullin; a hormone that attenuates myocardial remodeling. Accordingly, we hypothesized that MR-proADM could provide diagnostic and prognostic information in patients with acute dyspnea. Methods and Results: We measured MR-proADM by a commercial ELISA on hospital admission in 311 patients with acute dyspnea and compared the utility of MR-proADM with N-terminal pro-b-type natriuretic peptide (NT-proBNP). Blood samples were also available after 24 h (n=232) and before discharge (n=94). The principal diagnosis of the index hospitalization was determined by an adjudication committee. MR-proADM concentrations on hospital admission were higher in patients with acute heart failure (HF; n=143) vs. patients hospitalized with non-hf-related dyspnea (n=168): 1.31 (Q ) vs ( ) nmol/l; p< The receiver-operating characteristics area under the curve (ROC-AUC) for MR-proADM to diagnose HF was 0.77 (95% CI ) and 0.86 ( ) for NTproBNP. During a median follow-up of 816 days, 66/143 patients (46%) with acute HF and 35/84 patients (42%) with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) died; p=0.58 between groups. In multivariate Cox regression analyses, admission MR-proADM concentrations were associated with mortality in patients with acute HF (HR 5.90 [ ], p<0.001), but not in patients with AECOPD. Admission MR-proADM concentrations also improved risk stratification in acute HF as assessed by the net reclassification index. MR-proADM concentrations decreased from admission to later time points. Conclusion: Admission MR-proADM concentrations provide strong prognostic information in patients with acute HF, but modest diagnostic information in patients with acute dyspnea. 2

3 1. INTRODUCTION Heart failure (HF) is an increasing problem, and an important contributing factor is the aging population [1]. With more elderly subjects, the panorama of HF is changing and the prevalence of HF with preserved ejection fraction (HFpEF) is increasing [1]. This could be important also for biomarker selection as B-type natriuretic peptide (BNPs: i.e. BNP and N- terminal pro-b-type natriuretic peptide [NT-proBNP]) concentrations are lower and have inferior diagnostic accuracy in patients with HFpEF compared to HF patients with reduced ejection fraction (HFrEF) [2, 3]. Novel biomarkers may also improve risk prediction in HF patients by providing information on pathophysiology that is not reflected by the established biomarkers. Mid-regional pro-adrenomedullin (MR-proADM) is a promising biomarker that previously has been found to provide incremental prognostic information to the BNPs in patients with acute HF [4]. MR-proADM concentrations are detectable in healthy individuals and a mean concentration of 0.37 nmol/l (range nmol/l) has previously been reported in healthy subjects (5). MR-proADM concentrations have also been found elevated in patients with HF, respiratory infections, and sepsis [5]. The 47-amino acid peptide MR-proADM is stable in human plasma for one year when collected in EDTA tubes and stored at -20 C [6, 7], and MR-proADM directly reflects the release of the more unstable and biologically active adrenomedullin, a 52-amino acid vasodilatory peptide with important actions in the microcirculation and endothelium [8, 9]. Adrenomedullin is also known to influence left ventricular (LV) structure and function, thus linking adrenomedullin and MR-proADM directly to LV remodeling. Given the close association between LV remodeling and diagnosis and prognosis in patients with cardiovascular disease [10, 11], MR-proADM could be a promising biomarker in patients with suspected HF. This may especially be true for patients 3

4 with HFpEF as concentric LV hypertrophy is a hallmark of this condition [12-14]. Accordingly, in this study of unselected patients hospitalized with acute dyspnea we hypothesized that (i) MR-proADM provides diagnostic information concerning HF regardless of left ventricular ejection fraction and that (ii) MR-proADM provides additional prognostic information to established risk indices in patients with acute dyspnea. 2. METHODS Additional information can also be found in the Supplementary material. 2.1 Akershus Cardiac Examination (ACE) 2 Study The Akershus Cardiac Examination (ACE) 2 Study was a prospective, single-center study aiming to assess established and novel cardiac biomarkers. The study was conducted at Akershus University Hospital, a Norwegian teaching hospital with a catchment area of approximately subjects, and the details of the study has previously been reported [15]. In short, we evaluated patients presenting to the emergency department (ED) with dyspnea as their primary distress and eligibility criteria for study enrolment were age 18 y and the ability to provide informed consent. Blood sampling was performed within 24 hours of hospital admission and the recruitment period was from June 2009 to November The study complied with the Declaration of Helsinki and was approved by the Regional Ethics Committee. All study participants provided written informed consent before study commencement. 2.2 Data collection We used a standardized questionnaire to collect relevant data from the patients and the physicians in the ED as previously reported [15]. Analogous to previous studies on patients 4

5 with acute dyspnea [2-4], the ED physicians were asked to assess the probability of acute HF being the main cause of dyspnea from 0% (highly unlikely) to 100% (very likely) after their initial assessment of the patient and prior to results of NT-proBNP testing. The patient medical records were used for acquiring clinical data and the electrocardiogram (ECG). Clinical routine transthoracic echocardiography provided estimation of left ventricular ejection fraction (LVEF) and additional echocardiographic indices, including data on LV structure and diastolic function, and these data were grouped together as previously reported based on review of the patients' medical records [16]. Body mass index (BMI) was calculated by body weight/height height (kg/m 2 ). 2.3 Adjudication of diagnosis and follow-up data On the basis of medical records, including results of supplementary examinations and data on new events during follow-up (median follow-up 464 days [quartile days] before adjudication), two senior physicians that worked independently of each other determined the diagnosis of the index hospitalization. Diagnosis was determined according to guidelines and HF was defined as symptoms and clinical signs of HF and evidence of myocardial structural or functional impairment or injury [17]. Patients considered to have symptoms and signs of HF, but with estimated LVEF 50%, were classified as heart failure with preserved ejection fraction (HFpEF) if echocardiography or other modality demonstrated evidence of structural or functional myocardial dysfunction (e.g. left atrial enlargement, LV hypertrophy, inverted E/A ratio, etc.). LVEF was calculated by echocardiography as part of clinical routine and was available in all patients with acute dyspnea due to HF (n=143) and in 61% (n=103) of patients classified as hospitalized due to non-hf related dyspnea. 5

6 In the case of disagreement between the members of the adjudication committee, the decision regarding diagnosis was made by consensus. Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) was diagnosed according to guidelines and required evidence of worsening of the patient s symptoms (dyspnea, cough and/or sputum production) beyond day-to-day variation leading to a change in medication. We obtained data on survival from the electronic hospital records, which are synchronized with Statistics Norway. Follow-up ended November 1 st, Biochemical analysis Blood samples were obtained within 24 h of hospital admission, after 24 h (n=232), and before discharge in a subset of patients (n=94). After centrifugation, plasma was immediately frozen and stored at -80 C prior to biomarker analyses. MR-proADM was analysed in 2015 in EDTA plasma on a KRYPTOR system using a commercially available sandwich chemiluminescence immunoassay (B.R.A.H.M.S GmbH, Thermo Fisher Scientific, Hennigsdorf, Germany) and previously validated by Caruhel P. et al in 2009 [5]. The detection limit was 0.05nmol/L and the assay has an intra assay coefficient of variation of <10%. Quality controls were supplied by B.R.A.H.M.S GmbH. NT-proBNP concentrations were measured in 2012 by the probnp II assay on an Elecsys platform (Roche Diagnostics, Basel, Switzerland). Creatinine clearance was calculated according to the Cockcroft-Gault formula [18]. 2.5 Statistical analysis Normally distributed data are presented as means with standard deviations (SD) and compared by the Student s t-test. Due to non-normal distribution of biomarkers, as assessed by the Kolmogorov-Smirnov test, these values are expressed as median (quartile [Q] 1-3) and 6

7 compared by the Mann-Whitney U-test and the related-samples Wilcoxon signed rank test. Correlations were calculated by Spearman rank correlation and we also explored associations of MR-proADM concentrations by multivariate linear regression analysis (forward selection). Survival curves were constructed by the Kaplan-Meier method and compared by the log-rank test. Receiver-operating characteristics (ROC) analysis with area under the curve (AUC) was used to determine diagnostic and prognostic accuracy, and is presented as recently recommended with 95% CI [19]. Optimal cut-off values of MR-proADM were estimated by the Youden index J. We calculated Cox proportional hazards regression models to evaluate the prognostic utility of MR-proADM. Due to collinearity, closely correlated variables (rho >0.5) were also tested in separate regression models. Significant values in the univariate analyses were explored further in multivariate models (forward selection). Biomarker concentrations and creatinine clearance were transformed using the natural logarithm prior to regression analyses due to non-normal distribution. We calculated C statistics by combining MR-proADM on top of the other variables that were significantly associated with mortality in the multivariate Cox regression models (basic model). Furthermore, we also calculated the net reclassification index (NRI) [20] by adding MR-proADM concentrations to the basic model as previously reported [15]. All analyses were considered statistically significant at the threshold value of p<0.05. We used SPSS for Windows version 22.0 (SPSS, Chicago, IL) for all statistical analyses, except for comparison of ROC curves and calculation of C statistics, which was performed with MedCalc for Windows version (Broekstraat, Mariakerke, Belgium) and calculation of NRI, which was performed with R (R Foundation for Statistical Computing, Vienna, Austria). 7

8 3. RESULTS 3.1 Study population Over a period of 18 months, 468 patients with acute dyspnea were evaluated and 314 patients were included into the ACE 2 Study (Fig. 1). Three patients had missing EDTA samples for MR-proADM measurements, leaving 311 patients for this substudy. Of these patients, 143 patients (46%) were classified as hospitalized due to acute HF. In HF patients, 91 patients (64%) had LVEF<50% and were categorized as HFrEF, while 52 patients (36%) had LVEF 50% and evidence of structural or functional diastolic dysfunction and were classified as HFpEF (Fig. 1). A comparison of clinical characteristics among patients with dyspnea stratified according to the adjudicated diagnosis of HF vs. non-hf-related dyspnea is presented in Table 1. Compared to the patients with non-hf-related dyspnea, HF patients had higher prevalence of risk factors for cardiovascular disease and exhibited more clinical signs related to congestion. LVEF was also significantly lower among the HF group compared to the patients with non-hf-related dyspnea (Table 1). Separating HF patients according to a LVEF of 50% is presented in the Supplementary Table 1 and patients with preserved LVEF were older and more often female. 8

9 Fig. 1. Flow chart of study inclusion. HFrEF, heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; AECOPD, acute exacerbation of chronic obstructive pulmonary disease. Table 1. Clinical demographic and biological characteristics of the patients with dyspnea according to diagnosis Acute HF (n=143) Non-HF-related dyspnea (n=168) p Age (y) 75±1 66±1 <0.001 Male sex 90 (63%) 74 (42%) <

10 Body mass index (kg/m 2 ) 27±1 26± NYHA functional class IV 65 (46%) 71 (42%) 0.45 Heart rate, admission (bpm) 92±2 94± Systolic blood pressure (mmhg) 147±3 145± Diastolic blood pressure ( mmhg) 82±2 78± Creatinine clearance (ml/min) 66±3 89±4 <0.001 LVEF (%) 41±1 56±1 <0.001 HF, systolic dysfunction 91 (64%) HF, preserved ejection fraction 52 (36%) History of: Heart failure 87 (61%) 14 (8%) <0.001 Coronary artery disease 78 (55%) 32 (19%) <0.001 Myocardial infarction 65 (46%) 29 (17%) <0.001 PCI 33 (23%) 18 (11%) CABG 35 (25%) 5 (3%) <0.001 Hypertension 69 (48%) 51 (30%) Atrial fibrillation 68 (48%) 27 (16%) <0.001 Diabetes mellitus 43 (30%) 24 (14%) COPD 61 (43%) 94 (56%) 0.02 Asthma 6 (4%) 22 (13%) 0.01 Examination variables: Elevated JVP 17 (12%) 8 (5%) 0.02 Edema 77 (54%) 45 (27%) <0.001 Rales (58%) 78 (46%)

11 MR-proADM (nmol/l) 1.31 ( ) 0.85 ( ) <0.001 NT-proBNP (pg/ml) 3600 ( ) 348 ( ) <0.001 Data presented as numbers (%) or median (interquartile range 1-3). NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; HF, heart failure; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft ; COPD, chronic obstructive pulmonary disease; JVP, jugular venous pressure; MR-proADM, Mid-regional pro-adrenomedullin; NTproBNP, N-terminal pro-b-type natriuretic peptide. 3.2 MR-proADM concentrations and association with HF diagnosis MR-proADM concentrations ranged between 0.26 to 6.77 nmol/l with median concentration of 1.01 (Q ) nmol/l in the total study cohort. Admission MR-proADM concentrations correlated significantly with several variables, including baseline NT-proBNP concentrations (rho=0.76; p<0.001) (Supplementary Table 2). In multivariate linear regression analysis, reduced creatinine clearance, low LVEF, and history of hypertension and diabetes mellitus were significantly associated with higher MR-proADM concentrations and explained 50% of the variance in MR-proADM concentrations among HF patients (r 2 =0.50; Supplementary Table 3). Analogously; age, C-reactive protein, and previous history of atrial fibrillation and HF were associated with higher concentrations of MR-proADM in patients classified as hospitalized due to non-hf-related dyspnea (r 2 =0.46; Supplementary Table 3). Plasma concentrations of MR-proADM were higher in patients who were hospitalized with acute HF compared to patients hospitalized due to non-hf-related dyspnea: median 1.31 ( ) vs ( ) nmol/l; p<0.001 (Table 1). Assessing diagnostic accuracy by ROC analysis, the AUC of MR-proADM concentrations to diagnose acute HF was 0.77 (95% CI ). The corresponding AUC of NT-proBNP to discriminate between patients with acute HF and other causes of dyspnea was 0.86 ( ). 11

12 In total, 52 HF patients were classified as having HFpEF. MR-proADM concentrations did not differ between patients with HFrEF and HFpEF: 1.31 ( ) vs ( ) nmol/l; p=0.33 (Supplementary Table 1). In contrast, NT-proBNP concentrations were significantly higher in patients with HFrEF compared to HFpEF: 4308 ( ) vs 2293 ( ) ng/l; p= In line with this result, the correlation coefficient between MRproADM concentrations and LVEF in HF patients was rho= (p=0.036), while the correlation coefficient for NT-proBNP concentrations and LVEF was (p<0.001). Assessing the accuracy of the biomarkers to identify HFpEF and HFrEF separately, ROC- AUC of MR-proADM to separate patients with HFrEF from non-hf-related dyspnea was 0.79 ( ) and the AUC for separating HFpEF from non-hf-related dyspnea was 0.73 ( ). The corresponding ROC-AUC of NT-proBNP for HFrEF vs. non-hf-related dyspnea was 0.89 ( ) and HFpEF vs. non-hf-related dyspnea was 0.80 ( ). 3.3 MR-proADM concentrations and prognosis in patients with acute dyspnea During a median follow-up of 816 (Q ) days, 114 of the 311 patients died (37%). The mortality rate differed according to etiology of dyspnea as 46% (n=66) of patients with acute HF died, while 29% (n=48) of patients with non-hf related dyspnea died during followup (p=0.001 between groups). MR-proADM concentrations separated patients with a poor and favourable outcome in the total cohort (Supplementary Fig. 1; p<0.001 by the log-rank test). To study whether MR-proADM measurements provide similar prognostic information across important subgroups of patients with acute dyspnea, we assessed the prognostic value of MRproADM in patients with acute HF and AECOPD separately as these diagnoses had comparable mortality rates during follow-up (46% (n=66) vs 42% (n=35), p=0.58). MR- 12

13 proadm concentrations on study inclusion were higher in the acute HF patients who died during follow-up than in survivors: 1.70 (Q ) vs ( ) nmol/l, p< In contrast, MR-proADM concentrations did not significantly differ between patients with a poor and favourable outcome in the AECOPD group: 0.94 ( ) vs ( ) nmol/l, p= NT-proBNP concentrations also separated between nonsurvivors and survivors in patients with acute HF (2593 [Q ] vs [ ] ng/l, p<0.001), but not in patients with AECOPD (419 [ ] vs. 339 [ ] ng/l, p=0.27). Supplementary Fig. 2 demonstrates concentrations of NT-proBNP and MRproADM in the total cohort, in groups according to adjudicated diagnosis, and outcomes after 2 years of follow-up. Stratifying the acute HF patients into quartiles based on admission, MRproADM concentrations separated patients with a poor and a favourable outcome (Fig. 2; p<0.001 by the log-rank test). In contrast, mortality rates did not significantly differ across quartiles of MR-proADM in patients with AECOPD (Fig. 2; p=0.12 by the log-rank test). Additionally, optimal cut-off values of MR-proADM to predict mortality was estimated by the Youden index J (see Supplementary Table 4 for values with corresponding sensitivity and specificity). 13

14 Fig. 2. Survival curves for patients with acute heart failure and acute exacerbation of chronic obstructive pulmonary disease. Cumulative survival in patients with adjudicated diagnoses of acute heart failure (n=143) and acute exacerbation of chronic obstructive pulmonary disease (n=84) stratified by quartiles of MR-proADM on hospital admission. Increasing MR-proADM concentrations in patients with acute HF were also associated with increasing risk of mortality during follow-up in univariate Cox proportional hazard regression analysis: HR 3.59 (95% CI ), p<0.001 (Table 2). Moreover, adjusting for other clinical and biochemical variables that were associated with mortality in univariate Cox regression analysis, which included NT-proBNP concentrations, MR-proADM concentrations were still significantly associated with mortality during follow-up in patients with acute HF: HR 5.90 ( ); p<0.001 (Table 2). In contrast, NT-proBNP concentrations were not significantly associated with mortality in the multivariate model that included MR-proADM. The AUC for MR-proADM to predict mortality in patients with acute HF was 0.73 ( ) 14

15 and the AUC of NT-proBNP was 0.67 ( ). Of note, assessing MR-proADM and NTproBNP in separate multivariate models due to collinearity, both biomarkers were associated with mortality during follow-up after adjustment for other variables (Supplementary Table 5). However, the Wald score was higher and the -2 log likelihood ratio was lower for the model with MR-proADM concentrations compared to the model that included NT-proBNP concentrations (Supplementary Table 5). The ROC-AUCs of MR-proADM to separate patients with a favourable and poor outcome in HFrEF and HFpEF were 0.71 ( ) and 0.79 ( ), respectively. The corresponding ROC-AUCs of NT-proBNP in HFrEF and HFpEF were 0.72 ( ) and 0.71 ( ). The C statistic of the basic risk model of BMI, history of COPD, and diastolic blood pressure was 0.73 ( ) and the C statistic for the basic risk model plus MR-proADM was 0.81 ( ). Adding MR-proADM to the basic risk model also improved risk stratification in patients with acute HF as assessed by category-free NRI: 0.92 (95% CI ), p< Neither admission MR-proADM concentrations (HR 1.94 [ ], p=0.11) nor NT-proBNP concentrations (HR 1.11 [ ], p=0.40) were associated with mortality during follow-up in patients hospitalized with AECOPD in multivariate Cox proportional hazard regression analysis (Supplementary Table 8). The ROC-AUCs of admission MR-proADM and NT-proBNP concentrations to separate survivors from non-survivors in AECOPD were 0.61 ( ) and 0.56 ( ), respectively. Table 2. Cox proportional hazard regression analysis: predictors for mortality during followup in patients with adjudicated heart failure (n=143). Univariate HR 95 % CI p Wald 15

16 Age, per 1 y increase Male sex Body mass index, per 1 kg/ m2 increase Creatinine clearance, per 1 unit increase < Heart rate admission, per 1/min Systolic blood pressure, admission per 1 mmhg increase Diastolic blood pressure, admission, per 1 mmhg increase NYHA functional class IV vs. II/III LVEF, per 1 % increase History of COPD History of CAD Hypertension Atrial fibrillation Diabetes mellitus lnnt-probnp, admission, per 1 unit increase < lnmr-proadm, admission, per 1 unit increase < Multivariate HR 95 % CI p Wald Body mass index, per 1 unit increase < History of COPD

17 Diastolic blood pressure, admission, per 1mmHg increase lnmr-proadm, per 1 unit increase < NT-proBNP and MR-proADM levels were transformed by the natural logarithm before analysis and these hazard ratios are reported as log-unit increase. ln, natural logarithm. Other abbreviations as reported for Table MR-proADM concentrations during admission for acute HF In patients with acute HF, the median MR-proADM concentration after 24 h was 1.22 (Q ) nmol/l, which was lower compared to MR-proADM concentration on study admission (median 1.31 [Q ] nmol/l, p=0.001). Analogous to the results for MR-proADM on hospital admission, we found no significant difference between patients with HFrEF and HFpEF for MR-proADM concentrations measured after 24 h: 1.19 ( ) vs ( ) nmol/l, p=0.68. The correlation coefficient between admission MRproADM concentrations and MR-proADM concentrations after 24 h was rho=0.95 (p<0.001) and the ROC-AUC of MR-proADM concentrations measured after 24 h to identify nonsurvivors during follow-up was 0.72 (95% CI ). The ROC-AUC for NT-proBNP measurements to predict mortality after 24 h was 0.69 ( ). In the subgroup of acute HF patients with blood sampling on hospital discharge (n=47), MRproADM concentrations were 1.11 ( ) nmol/l, which was lower than MR-proADM concentrations on admission (<0.001). MR-proADM concentrations showed a median decrease of 0.22 ( ) nmol/l, p<0.001 from admission to discharge during the hospitalization for acute HF. The corresponding decrease was 987 ( ) ng/l for NTproBNP concentrations (p<0.001). The ROC-AUC of discharge MR-proADM concentrations to separate patients with a favourable and poor outcome during follow-up was 0.66 ( ) 17

18 and the ROC-AUCs to predict mortality for changes in MR-proADM concentrations during the hospitalization was 0.56 ( ) for baseline to day 2 and 0.60 ( ) for baseline to discharge. 4. DISCUSSION This study demonstrates that MR-proADM concentrations provide strong prognostic information in patients with acute dyspnea. The association was especially strong in patients hospitalized with acute HF. ROC-AUCs of MR-proADM to diagnose HF were lower than ROC-AUCs of NT-proBNP, regardless of LVEF among the HF patients. Adrenomedullin is a hormone produced by several organs in the body, including neuroendocrine tissue, the heart, pulmonary tissue, and the vasculature [21]. Inflammation and activation of the sympathetic nervous system are two of many factors that increase adrenomedullin synthesis and the actions of adrenomedullin include vasodilatation and antiproliferative, anti-apoptotic [22], and inotropic effects [23]. Accordingly; adrenomedullin is generally considered to be cardio-protective, and adrenomedullin has also been found to improve cardiac structure and function via inhibition of the renin-angiotensin-aldosterone system and the adrenergic system. The precise release mechanisms of adrenomedullin have not been established, but previous investigations have shown that hypoxia and mechanical stretching and shear stress in cardiomyocytes and vascular smooth muscle cells increase adrenomedullin synthesis [24-26]. Circulating MR-proADM has also previously been demonstrated to correlate closely with circulating adrenomedullin and the greater stability of MR-proADM in plasma and serum makes MR-proADM a potentially interesting biomarker [6, 8]. 18

19 Accordingly; we wanted to compare the diagnostic utility of MR-proADM concentrations with the accuracy of NT-proBNP, which has a prominent position in the algorithm to assess probability of HF in patients with dyspnea [17]. Among patients with dyspnea in this cohort, MR-proADM displayed moderately strong diagnostic properties. Still, NT-proBNP concentrations demonstrated higher ROC-AUCs to separate HF patients from non-hf patients, thus, MR-proADM measurements do not seem to add to established diagnostic biomarkers in patients with acute dyspnea. This result is in line also with previous studies [27]. The influence of non-cardiac factors such as inflammation and comorbidities on MRproADM concentrations may explain the suboptimal diagnostic ability of MR-proADM as these variables will distort the association between circulating MR-proADM concentrations and LV remodeling. MR-proADM concentrations on hospital admission provided strong prognostic information in patients with acute dyspnea and especially in the patients adjudicated as hospitalized with acute HF, with higher C statistic and improved risk stratification by adding MR-proADM concentrations to the basic risk model. Moreover, hazard ratios and the Wald scores for MRproADM was higher than for NT-proBNP in multivariate Cox models. ROC-AUCs for separating survivors from non-survivors were also higher for MR-proADM concentrations compared to the ROC-AUCs for NT-proBNP concentrations in patients with acute HF. In contrast, neither MR-proADM nor NT-proBNP concentrations were associated with mortality during follow-up in the multivariate Cox model in AECOPD patients, although there was a trend for MR-proADM quartiles to separate AECOPD patients with a poor and favourable outcome as presented in the Kaplan-Meier plots. Accordingly, MR-proADM concentrations seem to provide strong prognostic information in patients with acute dyspnea, and especially in the subgroup of patients with acute HF. We believe this may reflect upon the association 19

20 between adrenomedullin, and thus also MR-proADM, and specific myocardial pathology that includes LV remodelling. Our data is also supported by previous reports that found MRproADM concentrations to improve risk prediction in patients with acute HF [4, 27-29]. Renal dysfunction influenced admission MR-proADM concentrations in our study and the inverse association between MR-proADM concentrations and creatinine clearance may add to the prognostic value of MR-proADM in acute HF. MR-proADM concentrations also provided potent prognostic information across the different time points for blood sampling in our study, although MR-proADM concentrations decreased significantly already on day 1 after hospital admission. Accordingly; MR-proADM concentrations provided potent prognostic information in acute HF patients regardless of LVEF and time of blood sampling. Thus, circulating MRproADM concentrations reflect cardiac and extra-cardiac pathology of relevance for survival in acute HF. This study has some strengths and limitations. A strength is the uniform adjudication of all diagnosis as we employed an adjudication committee to determine the diagnosis of the index hospitalization, which is the preferred strategy in studies of patients with unselected dyspnea [30, 31]. Pertinent to this point, our adjudication committee demonstrated higher proportion of agreement (95%) between the two experts than reported in other studies with analogous design [32]. Collection of information from the patient and blood sampling were also performed in a standardized way in our study. In contrast, we did not have dedicated investigators to perform the echocardiograms, thus, we do not have detailed and uniform information about specific echocardiographic indices for our patients, which is a limitation to our study. However, all of the patients who were diagnosed with HF in our study had evidence of myocardial structural or functional abnormality or cardiac injury, thus, lack of standardized echocardiography probably did not result in patients without HF being classified 20

21 in the HF group. In contrast, as not all patients characterized as hospitalized with non-hfrelated dyspnea were subjected to echocardiography, we cannot exclude that some patients in this group may actually have suffered from myocardial dysfunction and HF. Still, NTproBNP concentrations separated nicely between patients with HF and non-hf-related dyspnea in our study, and the ROC-AUC of NT-proBNP to separate HF and non-hf patients were similar to data previous reported for NT-proBNP in large multicentre studies of patients with unselected dyspnea [33]. The sample size of the study was moderate due to the singlecenter design and relative short-term patient inclusion with recruitment restricted to weekdays and only day-time. This is a limitation, especially when assessing association between biomarkers and mortality in subgroup analysis like acute HF and AECOPD separately. CONCLUSION MR-proADM concentrations do not seem to add information to NT-proBNP concentrations for diagnosing acute HF in patients presenting with acute dyspnea in the ED. In contrast, we found MR-proADM concentrations to provide excellent prognostic information in patients with acute dyspnea and especially in the subgroup with acute HF. 21

22 ACKNOWLEDGMENTS We would like to acknowledge the contribution by the Clinical Trial Unit, Division of Medicine, Akershus University Hospital, for patient inclusion and especially thank Vigdis Bakkelund, RN; Annika Lorentzen, RN; and Marit Holmefjord Pedersen, BSc. We also acknowledge the skilful work by Heidi Strand, BSc, Section for Medical Biochemistry, Division for Diagnostics and Technology, Akershus University Hospital to the MR-proADM analyses. FUNDING The ACE 2 Study was funded by a research grant from the Norwegian Research Council to TO and HR and by internal grants from Akershus University Hospital. DISCLOSURES Thermo Fisher Scientific, Clinical Diagnostics, BRAHMS GmbH, Hennigsdorf, Germany, Tel: provided MR-proADM reagents free of charge for this study. NT-proBNP kits were supplied at reduced price by Roche Diagnostics. 22

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