Evaluation of the clinical contribution in sepsis risk assessment with MR-proADM as an early biomarker of endothelial dysfunction: preliminary data from a cohort of critically ill patients tested by the LIAISON® BRAHMS MR-proADM™ Assay

Evaluation of the clinical contribution in sepsis risk assessment with MR-proADM as an early biomarker of endothelial dysfunction: preliminary data from a cohort of critically ill patients tested by the LIAISON® BRAHMS MR-proADM™ Assay | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of the clinical contribution in sepsis risk assessment with MR-proADM as an early biomarker of endothelial dysfunction: preliminary data from a cohort of critically ill patients tested by the LIAISON® BRAHMS MR-proADM™ Assay Laura Grumiro, Simona Semprini, Emiliano Gamberini, Marina Terzitta, and 19 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9251510/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objectives: Sepsis is the leading cause of death in the ICU. Early recognition and immediate management of the causes of sepsis is the focus of this work, aimed at evaluating one of the early-onset biomarkers in the phases of organ dysfunction typical of sepsis. To evaluate the performance of mid-region pro-adrenomedullin (MR-proADM) as an early biomarker of endothelial dysfunction and prognosis in critically ill patients with suspected sepsis. Methods: In this prospective observational cohort, 150 adult patients admitted to the Intensive Care Units (ICU) of AUSL Romagna from April to October 2025 were enrolled. Plasmmatic MR-proADM was quantified at baseline (t0), 24 hours (t24), and 48 hours (t48) using the LIAISON® BRAHMS MR-PROADM™ chemiluminescent assay. Patients were stratified according to blood culture results: culture negative, Gram negative and Gram-positive bacteremia. The primary outcomes were MR-proADM kinetics and association with 7- and 28-day mortality. Secondary outcome included comparison with C-reactive protein (CRP) trends. Results: MR-proADM levels were significantly higher in Gram-negative bacteremia than in the Gram-positive and culture-negative groups at all time points. Non-survivors showed persistently elevated or increasing MR-proADMs, while survivors showed declining trends. CRP showed slower kinetics and poor discrimination between infection categories. Conclusions: MR-proADM identifies early endothelial dysfunction and predicts outcomes in sepsis. Its early kinetic changes outperform CRP for prognosis but require validation in larger cohorts to establish clinical cut-offs and utility in antimicrobial decision support. Sepsis MR-proADM Automatic immunoanalysis Prognostic biomarkers ICU Endothelial dysfunction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Sepsis is the systemic response to infection, generally due to common bacterial organisms such as Staphylococcus aureus , streptococci, Enterobacteriaceae , and Pseudomonas aeruginosa ( 1 ). Sepsis and septic shock remain a global health challenge with high mortality rates and increasing antibiotic resistance, underscoring the need for effective strategies for early recognition, risk stratification, and prognosis assessment ( 1 ). Sepsis is a fairly common condition and is one of the most frequent causes of death in most ICU (intensive care units) ( 2 ). In the ICU, there are two main challenges to consider: strategies to identify septic status early and moderate antibiotic use. In general, clinicians must empirically choose from a wide range of broad-spectrum agents, often without immediate microbiological guidance. In addition, despite timely empirical therapy, the patient's condition can still worsen. In addition, the use of non-targeted antibiotics leads to a progressive increase in the phenomenon of antibiotic resistance, reducing the ammunition that can be used for future infections ( 3 ). Methods for rapid identification of sepsis make use of clinical scores, standardized tools used to quantify disease severity, estimate prognosis, and support clinical decision-making ( 4 ). They integrate clinical, physiological and laboratory parameters, allowing an objective and reproducible assessment of the patient, particularly in emergency, intensive care and sepsis settings. However, the use of clinical scores alone could delay antibiotic treatment and worsen the patient's prognosis ( 5 ). In the 2019 Gonzalez del Castillo study , it is well highlighted that the use of clinical scores to manage a septic system patient is often a reductive and dangerous measure for the patient. In fact, the use of endothelial dysfunction biomarker MR-proADM and clinical scores such as NEWS (National Early Warning Score) in relation to antibiotic use was investigated. ICU admission was delayed by 1.5 days in patients with elevated MR-proADM values and low NEWS values compared to matched patients with high NEWS values, despite similar mortality rates at 28 days (13.5% vs. 16.5%). Antibiotics were discontinued in 17.4% of patients with elevated MR-proADM and low NEWS values, with higher rates of ICU admission (27.3% vs. 4.8%) and infection-related hospital admission (54.5% vs. 14.3%) ( 5 ). Alongside the early management of sepsis through the use of clinical scores, biomarkers are also used, molecules secreted early or during the septic event, the most used are C-Reactive Protein (CRP) and Procalcitonin (Pct) ( 6 ). Often, however, these methods do not disregard therapeutic failure, and it becomes necessary to understand what leads to therapeutic failure with the eventual exitus of the patient. It should be considered that treatment failure underlies a complex pathophysiological process of sepsis in which the host response is dysregulated and causes cellular, tissue and organ damage. Rapid diagnosis of bacterial infection and early assessment of a poor prognosis are essential for septic septic patients and for all levels of clinical patient management, which is why biochemical values that can help the clinician in the therapeutic decision of a critically ill patient are always sought. The favorable effects that follow the choice of the appropriate time to start and stop antibiotic therapy could also concern the reduction of health costs, both by avoiding the administration of inadequate antibiotic therapies and by reducing the duration of hospitalization. Numerous literature reviews have emphasized the importance of biomarker assessment in the management of sepsis ( 7 ). Circulating biomarkers that reflect endothelial stress may increase early risk stratification ( 7 ). MR-proADM is a stable surrogate for adrenomedullin, implicated in the regulation of vascular tone and barrier integrity ( 8 ). ADM is a 52-amino acid peptide hormone isolated in 1993 from extracts of human pheochromocytoma ( 9 , 10 ). ADM belongs to the calcitonin gene peptide superfamily: calcitonin, PCT, calcitonin-related peptide (CGRP), Amylin, and ADM. The ADM molecule has a 27% similarity to CGRP ( 10 , 11 ). The gene for human ADM is located on a single locus on chromosome 11. The mRNA encodes information for the synthesis of a prehormone known as preproadrenomedullin, which is composed of 185 amino acids, which is subsequently degraded into the 164-amino acid peptide called proadrenomedullin via pooping of the signal peptide. Proadrenomedullin has three vasoactive peptides: ADM, aminoterminal peptide proadrenomedullin (PAMP), and adrenotensin ( 9 ). Studies show that the ADM protein possesses antimicrobial and anti-inflammatory properties, participating in the body's defense mechanism against bacterial invasion ( 8 ). This makes it a candidate as an early indicator of organ dysfunction which is the exacerbation of an ongoing deep or systemic infection. ADM has homeostatic and regulatory roles, influencing the physiological functions of the cardiovascular system and kidneys. However, circulating ADM is extremely difficult to detect in blood samples because it degrades rapidly from the circulation in about 22 minutes thanks to plasma proteases ( 12 ). For this reason, it is decided to dose MR-proADM, which derives from the proteolytic cleavage of the polypeptide that leads to the formation of ADM in a 1:1 ratio. Numerous studies have investigated the possible role of ADM in septic processes, but none have yet correlated the value of the biomarker and its temporal trend with respect to the microorganism causing the septic event. In this work, we have chosen to investigate the properties of the biochemical marker MR-proADM as a support for ICU clinicians, providing them with a valid parameter together with the etiological diagnosis of sepsis through the Blood Culture reference model. The automated LIAISON® BRAHMS MR-proADM™ chemiluminescent immunoassay system offers standardized quantification of MR-proADM in plasma. This study investigates MR-proADM trends related to microbial etiology and clinical outcomes and compares its prognostic utility to CRP. The study was approved by the Ethics Committee of Romagna with Resolution no. 198 of 22/01/2025. Methods Study design and context : This prospective observational study enrolled 150 adult ICU patients from the AUSL Romagna network, Emilia Romagna, Italy, between April and October 2025. Informed consent to participate in the study was obtained from all patients as required by the Declaration of Helsinki. Patient inclusion criteria included: adulthood, intensive cure admission after surgery or trauma, and clinical picture of sepsis clinically assessed via clinical scores and haematological parameters according to Sepsis-3 guidelines. Blood samples for MR-proADM were collected in plasma tube with separator gel and K2_EDTA at three time points: admission (t0), 24 hours (t24), and 48 hours (t48). The blood culture was performed at the same time as the t0 of MR-proADM, in time of clinical suspicion of sepsis, in special bottles containing the culture medium and incubated at 37°C for up to 5 days. The results of the blood culture were used to classify patients into three groups: Blood culture negative Gram-negative bacteremia Gram-positive bacteremia Clinical data included age, sex, and 7- and 28-days mortality. Biomarker measurement: MR-proADM was quantified from gel-separated EDTA plasma samples that were centrifuged and frozen at -20°C until assay. Subsequently, the biomarker test was performed using the LIAISON® BRAHMS MR-proADM™ test (DiaSorin S.p.A., Saluggia (VC) - Italy). It is a sandwich chemiluminescent assay with anti-MR-proADM capture and isoaluminum-labeled detection antibodies on an automated platform. The assay range is 0.21–10 nmol/L. Unbound materials were removed by automatic washing; chemiluminescent signal correlated with the concentration of MR-proADM by light emission detection. The reference values indicated by the test provide a cut-off of 0.87 nmol/L for the assessment of the risk of progression to a severe pathological condition. If the value is > 1.50 nmol/L the risk of progression to a more severe disease condition increases, and if < 2.25 nmol/L a clinically stable patient can be safely discharged from the intensive care unit at a lower level of care. Other laboratory markers C-reactive protein (CRP) was routinely measured by Roche Diagnostics S.p.A. (Monza (MB), Italy). Results are expressed in mg/L. Procalcitonin has been excluded from statistical considerations because it is used clinically downstream in the management of sepsis, to monitor the effectiveness of antibiotic treatment rather than roll in in therapy as is the case for CRP and MR-proADM. Identification of isolates: The causative agent of sepsis was detected by blood culture examination in dedicated Culture Media bottles with positivity detected by the BacT/Alert Virtuo system (bioMérieux, Marcy l'Etoile, France). Subsequently, in positive aerobic/anaerobic bottles, the culture was examined by microscopic examination with Gram staining and species identification by mass spectrometry (MALDI-ToF). Statistical analysis: Given the preliminary sample size, analyses focused on descriptive statistics and exploratory comparisons without inferential testing. Descriptive statistics summarized biomarker levels across groups and outcomes. Statistical analysis was carried out using Microsoft Excel statistical programs and one-way ANOVA tests and ANOVA tests for independent measures (Social Science Statistics). It was also used Wilcoxon signed-rank test is a non-parametric statistical test for to compare two related samples (paired data) or repeated measurements. A statistical analysis was performed considering the time course of MR-proADM concentrations according to microbiological category, survival status and age. Median MR-proADM levels were assessed at baseline (t0), 24 hours (t24), and 48 hours (t48). Results Cohort characteristics: Of the 150 patients enrolled in the study, 96 had a negative microbiological result, 29 positive for Gram-negative microorganisms, and 25 positive for Gram-positive microorganisms (Table 1 ). 64 female and 86 male subjects were enrolled, with an average age of 71 and 68 years, respectively. Table 1 Distribution of blood culture results and microorganisms isolated Blood culture Count Gram - 29 Gram + 25 Negative 96 Total 150 Microorganism isolated in culture G+ Count Bacillus sp. 1 E. faecium 2 S. agalactiae gr. B 1 S. aureus 4 S. capitis 1 S. epidermidis 7 S. epidermidis/hominis. 2 S. hominis 4 S. mitis 1 S. pneumoniae 2 Total 25 Microorganism isolated in culture G- Count A. baumannii 1 Citrobacter koseri 1 E. coli 12 E.coli/K.pneumoniae 2 Enterobacter aerogenes; E. faecalis 1 Enterococcus faecium; Klebsiella oxytoca; Enterococcus avium 1 H. influenzae/K. Pneumoniae 1 K. Oxytoca 1 K. Pneumoniae 5 Morganella morganii 1 Neisseria subflava 1 P. aeruginosa 1 S. marcescens 1 Total 29 MR-proADM kinetics: In Fig. 1 it is possible to observe the average trend of MR-proADM in the three categories considering the values ​​obtained from 150 enrolled patients. Gram-negative bacteremia was associated with the highest MR-proADM values at all time points, while culture-negative patients showed intermediate levels and Gram-positive bacteremia the lowest (Fig. 1 .A). At baseline, MR-proADM concentrations differed significantly between Gram-negative bacteremia and other microbiological categories, with no significant difference between Gram-positive and culture-negative patients (Fig. 1 .B). To assess temporal changes in MR-proADM levels, the primary analysis included only patients with comprehensive biomarker measurements at all three predefined time points, resulting in a cohort of 105 patients (Table 2 ; Fig. 2 .A). A one-way repeated measures ANOVA was then performed to assess changes within the group over time in association with a non-parametric statistical test Wilcoxon signed-rank. Table 2 Pro-adrenomedullin (pro-ADM) levels according to blood culture result Blood culture result n t0 mean ± SD (95% CI) t24 mean ± SD (95% CI) t48 mean ± SD (95% CI) Negative 69 3.70 ± 3.00 (3.05–4.35) 3.80 ± 3.50 (3.05–4.55) 3.49 ± 2.90 (2.84–4.14) Gram-positive 20 3.19 ± 3.00 (2.10–4.28) 2.63 ± 2.50 (1.65–3.61) 2.43 ± 2.20 (1.55–3.31) Gram-negative 16 5.97 ± 7.50 (3.10–8.84) 4.25 ± 4.50 (2.35–6.15) 4.13 ± 4.00 (2.25–6.01) Overall 105 3.95 ± 4.50 (3.10–4.80) 3.65 ± 3.90 (2.85–4.45) 3.39 ± 3.50 (2.60–4.18) Among the 105 patients included in the analysis, MR-proADM levels were measured at baseline (t0), 24 hours (t24), and 48 hours (t48) and stratified according to blood culture results (Table 2 ). Overall, mean MR-proADM values showed a progressive decrease over time, from 3.95 ± 4.50 nmol/L at t0 to 3.39 ± 3.50 nmol/L at t48. Patients with Gram-negative bacteremia (n = 16) exhibited the highest MR-proADM concentrations at all time points, with mean values decreasing from 5.97 ± 7.50 nmol/L at t0 to 4.13 ± 4.00 nmol/L at t48. In the Gram-positive group (n = 20), MR-proADM levels were lower and showed a reduction from 3.19 ± 3.00 nmol/L at baseline to 2.43 ± 2.20 nmol/L at 48 hours. In contrast, patients with negative blood cultures (n = 69) displayed relatively stable MR-proADM concentrations over time, with no clear downward trend. Wilcoxon signed-rank tests demonstrated statistically significant reductions in MR-proADM levels between t0 and t48 in both Gram-negative (p = 0.012) and Gram-positive (p = 0.045) groups, whereas no significant change was observed in the blood culture–negative group (p = 0.32) (Fig. 2 .A). Because only a limited number of Gram-negative patients had complete measurements at all three time points, a secondary analysis was conducted including patients with at least two-time measurements available. This approach increased the Gram-negative sample size to 23 patients obtaining the mean reduction of 33.1% in Gram values was observed from baseline (t0: 7.37) to 24 hours (t24: 4.93) in the study population (n = 23). (Fig. 2 .B). MR-proADM in survivor and dead categories When stratified by blood culture results and short- and mid-term mortality, MR-proADM levels showed marked differences between non-survivors and survivors across all time points (t0, t24, t48) (Fig. 3 ). Blood culture–negative patients At 7 days, patients who died exhibited substantially higher MR-proADM values than survivors at all time points, with a + 189% difference at t0 (10.0 vs 3.46), + 185% at t24 (5.4 vs 3.51), and + 84% at t48 (5.9 vs 3.2). A similar pattern was observed for 28-day mortality, where non-survivors had MR-proADM levels 153% higher at t0 (8.33 vs 3.29), 148% higher at t24 (7.28 vs 2.93), and 174% higher at t48 (7.1 vs 2.59) compared with survivors. Gram-negative bacteremia Gram-negative non-survivors displayed the highest absolute MR-proADM concentrations. At 7 days, MR-proADM levels were + 146% higher at t0 (17.3 vs 7.02), + 249% at t24 (10.2 vs 2.92), and + 618% at t48 (13.0 vs 1.81) compared with survivors. Comparable differences were observed for 28-day mortality, with increases of + 108% at t0 (14.6 vs 7.02), + 184% at t24 (8.3 vs 2.92), and + 430% at t48 (9.6 vs 1.81) in non-survivors versus survivors. Gram-positive bacteremia In Gram-positive infections, MR-proADM levels were overall lower and showed a less consistent association with early mortality. At 7 days, non-survivors had 61% lower MR-proADM at t0 compared with survivors (1.53 vs 3.90), while differences at t24 and t48 were modest (+ 5% and − 46%, respectively). Conversely, at 28 days, non-survivors exhibited higher MR-proADM levels than survivors, with increases of + 73% at t0 (4.75 vs 2.75), + 80% at t24 (3.75 vs 2.08), and + 69% at t48 (3.47 vs 2.05). Age-stratified analysis and the comparison with CRP: Age-stratified analysis showed lower and stable levels of MR-proADM in younger patients, while older patients had higher baseline values at all observation points (Fig. 4 ). CRP showed a nonspecific increase between the two groups, Gram-negative and Gram-positive, as shown in Fig. 5 a and b, respectively. Furthermore, it should be noted that for MR-proADM, a trend can be observed that provides early indications, unlike CRP, which peaks 24 hours after suspected sepsis and then declines, assuming values ​​that are not indicative of the patient's infectious status. Discussion In this prospective observational study, we evaluated the temporal kinetics and prognostic value of MR-proADM measured using a fully automated chemiluminescent assay in critically ill patients with suspected sepsis, stratified by microbiological etiology and clinical outcome. One of the most relevant results of this study is the consistent observation of higher concentrations of MR-proADM in patients with Gram-negative bacteremia at all measured time points compared to Gram-positive and culture-negative patients. This pattern likely reflects the profound endothelial activation and vascular dysfunction induced by Gram-negative pathogens, whose lipopolysaccharide (LPS) triggers a potent innate immune response via Toll-like receptor 4 signaling, leading to widespread cytokine release, nitric oxide production, and capillary leakage ( 13 – 16 ). Adrenomedullin plays a central role in maintaining the integrity of the endothelial barrier and regulating vascular tone during inflammatory stress ( 16 ). Elevated MR-proADM concentrations in Gram-negative sepsis may therefore represent a compensatory response to severe endothelial injury, rather than a simple indicator of infection burden. This interpretation is consistent with previous studies that have demonstrated higher levels of MR-proADM in patients with septic shock and severe organ dysfunction, particularly in settings characterized by distributional shock and vasoplegia ( 8 , 17 , 18 ). Intriguingly, culture-negative patients showed intermediate MR-proADM values, suggesting that even in the absence of microbiological confirmation, a subset of these patients may experience significant endothelial stress. This observation is consistent with previous evidence indicating that blood culture can remain negative in up to 40–50% of septic patients despite a true infection, often due to previous antibiotic exposure or low bacterial load ( 19 ). MR-proADM can therefore provide pathophysiological information complementary to microbiological diagnostics. Longitudinal evaluation of MR-proADM revealed distinct kinetic patterns among microbiological categories. A statistically significant decline over 48 hours was observed exclusively in Gram-positive bacteremia when complete serial measurements were available, while values remained stable in culture-negative patients and declined more slowly in Gram-negative infections. These findings suggest that the kinetics of MR-proADM may reflect differences in the reversibility of endothelial dysfunction depending on the pathogen type. Gram-positive infections, often characterized by localized infectious sources and a lower endotoxin burden, may allow for faster restoration of endothelial homeostasis once appropriate antimicrobial therapy has been initiated ( 20 ). Conversely, Gram-negative sepsis may be associated with sustained endothelial activation and explain the slower or incomplete decline in MR-proADM observed in this group. The persistence of elevated MR-proADM values has been previously linked to ongoing microcirculatory dysfunction and poor outcome, even in patients showing apparent clinical stabilization ( 21 ). Our results reinforce the concept that MR-proADM kinetics, rather than isolated measurements, provide clinically meaningful information regarding the disease pathway. Non-survivors consistently showed higher, non-decreasing levels of MR-proADM over time than survivors, who showed a progressive reduction. This result is in line with numerous studies identifying MR-proADM as a strong independent predictor of short- and medium-term mortality in sepsis and septic shock ( 17 , 22 , 23 ). From a mechanistic perspective, elevated persistent MR-proADM likely reflects irreversible endothelial injury, loss of vascular barrier function, and progression to multiorgan failure. The association between declining MR-proADM levels and survival supports its role as a dynamic indicator of recovery rather than a static indicator of disease severity. Age-stratified analysis revealed higher baseline concentrations of MR-proADM in elderly patients, consistent with previous reports showing that MR-proADM increased with age, even in non-septic populations ( 24 ). This phenomenon may reflect age-related endothelial dysfunction, increased vascular rigidity, and reduced compensatory capacity during systemic inflammation. These results highlight the importance of interpreting MR-proADM values in the clinical and demographic context and oppose rigid threshold values without age adjustment. CRP showed slower kinetics and failed to discriminate between microbiological categories or survival outcomes. Although CRP remains a widely used inflammatory marker, its hepatic origin and delayed response limit its usefulness in early risk stratification and prognostic assessment ( 25 ). In contrast, MR-proADM directly reflects endothelial stress, capturing a critical pathophysiological component of sepsis that precedes organ visual failure. The early divergence of MR-proADM trajectories observed in our cohort underscores their potential superiority over traditional inflammatory markers for early prognostic assessment. The LIAISON® BRAHMS MR-proADM™ automated assay enables standardized and reproducible measurement of MR-proADM, making it easy to integrate into routine laboratory workflows. Early identification of patients with persistently elevated or increasing MR-proADM levels could support clinical decision-making, including escalation of monitoring, optimization of hemodynamic support, and re-evaluation of therapeutic strategies. Moreover, MR-proADM may complement clinical scores, which alone can underestimate the risk in certain subgroups of patients, as previously demonstrated in studies combining MR-proADM with early warning scores ( 5 , 26 , 27 ). However, our findings caution against using MR-proADM as a standalone tool, emphasizing the need for integrated clinical interpretation. Our results support MR-proADM as an early marker of endothelial dysfunction and adverse prognosis, overcoming CRP in discriminating between disease severity and outcome, and provide new insights into its behaviour according to the pathogen category. This study has several limitations, including the single-network design, the limited sample size in subgroup analyses, and the exploratory nature of the statistical approach. The absence of systematic measurements of procalcitonin prevented direct comparison with other biomarkers for sepsis. Future multicenter studies with larger cohorts are needed to validate these findings, establish clinically actionable threshold values, and evaluate the role of MR-proADM-guided therapeutic algorithms, including antimicrobial stewardship strategies. Conclusion MR-proADM measured on the LIAISON® platform is a promising early biomarker of endothelial dysfunction and adverse outcome in sepsis. It shows a stronger early prognostic value than CRP. Larger studies are needed to validate clinical cut-offs and integrate MR-proADM into therapeutic algorithms. Abbreviations CGRP (calcitonin-related peptide); CRP (C Reactive Protein); ICU (Intensive Care Unit ); MR-proADM (mid-region pro-adrenomedullin); NEWS (National Early Warning Score). Declarations ● Ethics approval and consent to participate The study was approved by the Ethics Committee of Romagna with Resolution no. 198 of 22/01/2025. Informed consent to participate in the study was obtained from all patients as required by the Declaration of Helsinki. ● Consent for publication Informed consent for data publication in the study was obtained from all patients. ● Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available because they are owned by AUSL Romagna and subject to confidentiality agreements, but are available from the corresponding author upon reasonable request. ● Competing Interests The authors declare that they have no competing interests. ● Funding This study was supported by research funding from Local Health Authority of Romagna. ● Authors' contributions Conceptualization: LG, VS; Data Curation: LG, SS; Formal Analysis: ABS, LG, FB, MEP; Investigation: LG; Funding acquisition: VS; Methodology: LG, VS, MT, EG; Project administration: LG; Resources: LG; Software: LG, ABS; Supervision: VS, MC, AMDP; Validation: LG; Visualization: LG, MB; Writing — original draft: LG; Writing — revision and editing: LG, SS, EG, MT, CG, FB, GG, PF, MEP, ABS, MB, MG, GG, CC, LI, LD, GD, SZ, MSM, AM, AMDP, MC, VS. ● Clinical trial number Not applicable. ● Acknowledgments We thank the laboratory staff for their practical support, clinical analyses, and sample management. Special thanks to the technicians of the Unit of Microbiology the Greater Romagna Area Hub Laboratory: Rosario Romano, Lorena Esposito, Sara Cappucci, Vilma Sternini, Barabara Ceccarelli, Barbara Marchini, Lorella Mazzotti, Alfonso Sacconi. References Bauer M, Gerlach H, Vogelmann T, Preissing F, Stiefel J, Adam D. Mortality in sepsis and septic shock in Europe, North America and Australia between 2009 and 2019— results from a systematic review and meta-analysis. Crit Care. 2020;24(1):239. Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348(16):1546–54. Garnacho-Montero J, Ortiz-Leyba C, Herrera-Melero I, Aldabo-Pallas T, Cayuela-Dominguez A, Marquez-Vacaro JA, et al. Mortality and morbidity attributable to inadequate empirical antimicrobial therapy in patients admitted to the ICU with sepsis: a matched cohort study. J Antimicrob Chemother. 2007;61(2):436–41. Vincent JL, Moreno R. Clinical review: Scoring systems in the critically ill. Crit Care. 2010;14(2):207. del Gonzalez J, Wilson DC, Clemente-Callejo C, Román F, Bardés-Robles I, Jiménez I, et al. Biomarkers and clinical scores to identify patient populations at risk of delayed antibiotic administration or intensive care admission. Crit Care. 2019;23(1):335. Chuang CL, Yeh HT, Niu KY, Chen CB, Seak CJ, Yen CC. Diagnostic performances of procalcitonin and C-reactive protein for sepsis: a systematic review and meta-analysis. Eur J Emerg Med. 2025;32(4):248–58. Ahuja N, Mishra A, Gupta R, Ray S. Biomarkers in sepsis-looking for the Holy Grail or chasing a mirage! World J Crit Care Med. 2023;12(4):188–203. Christ-Crain M, Morgenthaler NG, Struck J, Harbarth S, Bergmann A, Müller B. Mid-regional pro-adrenomedullin as a prognostic marker in sepsis: an observational study. Crit Care. 2005;9(6):R816. Ishimitsu T, Kojima M, Kangawa K, Hino J, Matsuoka H, Kitamura K, et al. Genomic Structure of Human Adrenomedullin Gene. Biochem Biophys Res Commun. 1994;203(1):631–9. Kitamura K, Kangawa K, Kawamoto M, Ichiki Y, Nakamura S, Matsuo H, et al. Adrenomedullin: A Novel Hypotensive Peptide Isolated from Human Pheochromocytoma. Biochem Biophys Res Commun. 1993;192(2):553–60. Pierrakos C, Vincent JL. Sepsis biomarkers: a review. Crit Care. 2010;14(1):R15. Meeran K, O’Shea D, Upton PD, Small CJ, Ghatei MA, Byfield PH, et al. Circulating Adrenomedullin Does Not Regulate Systemic Blood Pressure but Increases Plasma Prolactin after Intravenous Infusion in Humans: A Pharmacokinetic Study 1. J Clin Endocrinol Metab. 1997;82(1):95–100. Angus DC, van der Poll T. Severe Sepsis and Septic Shock. N Engl J Med. 2013;369(9):840–51. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801. Opal SM, van der Poll T. Endothelial barrier dysfunction in septic shock. J Intern Med. 2015;277(3):277–93. Wang P. ADRENOMEDULLIN IN SEPSIS AND SEPTIC SHOCK. Shock. 1998;10(5):383–4. Suberviola B, Castellanos-Ortega A, Llorca J, Ortiz F, Iglesias D, Prieto B. Prognostic value of proadrenomedullin in severe sepsis and septic shock patients with community-acquired pneumonia. Swiss Med Wkly. 2012. Elke G, Bloos F, Wilson DC, Brunkhorst FM, Briegel J, Reinhart K, et al. The use of mid-regional proadrenomedullin to identify disease severity and treatment response to sepsis - a secondary analysis of a large randomised controlled trial. Crit Care. 2018;22(1):79. Lamy B, Dargère S, Arendrup MC, Parienti JJ, Tattevin P. How to Optimize the Use of Blood Cultures for the Diagnosis of Bloodstream Infections? A State-of-the Art. Front Microbiol. 2016;7. Cohen J. The immunopathogenesis of sepsis. Nature. 2002;420(6917):885–91. Joffre J, Hellman J, Ince C, Ait-Oufella H. Endothelial Responses in Sepsis. Am J Respir Crit Care Med. 2020;202(3):361–70. Andaluz-Ojeda D, Nguyen HB, Meunier-Beillard N, Cicuéndez R, Quenot JP, Calvo D, et al. Superior accuracy of mid-regional proadrenomedullin for mortality prediction in sepsis with varying levels of illness severity. Ann Intensive Care. 2017;7(1):15. Saeed K, Wilson DC, Bloos F, Schuetz P, van der Does Y, Melander O, et al. The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study. Crit Care. 2019;23(1):40. Önal U, Valenzuela-Sánchez F, Vandana KE, Rello J. Mid-Regional Pro-Adrenomedullin (MR-proADM) as a Biomarker for Sepsis and Septic Shock: Narrative Review. Healthcare. 2018;6(3):110. Pepys MB, Hirschfield GM. C-reactive protein: a critical update. J Clin Invest. 2003;111(12):1805–12. Valenzuela-Sánchez F, Valenzuela-Méndez B, Rodríguez-Gutiérrez JF, Estella-García Á, González-García MÁ. New role of biomarkers: mid-regional pro-adrenomedullin, the biomarker of organ failure. Ann Transl Med. 2016;4(17):329–329. Miller JM, Binnicker MJ, Campbell S, Carroll KC, Chapin KC, Gilligan PH, et al. A Guide to Utilization of the Microbiology Laboratory for Diagnosis of Infectious Diseases: 2018 Update by the Infectious Diseases Society of America and the American Society for Microbiologya. Clin Infect Dis. 2018;67(6):e1–94. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 09 Apr, 2026 Editor assigned by journal 09 Apr, 2026 Editor invited by journal 09 Apr, 2026 Submission checks completed at journal 08 Apr, 2026 First submitted to journal 08 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9251510","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624166667,"identity":"69088e0a-ec7e-4e26-b317-6751e49ef669","order_by":0,"name":"Laura Grumiro","email":"data:image/png;base64,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","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":true,"prefix":"","firstName":"Laura","middleName":"","lastName":"Grumiro","suffix":""},{"id":624166668,"identity":"ed2d06ff-e8bf-4c98-aad4-5654666a4fbf","order_by":1,"name":"Simona Semprini","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Simona","middleName":"","lastName":"Semprini","suffix":""},{"id":624166669,"identity":"2b639a42-e3b8-4a96-862f-193dd5d12cea","order_by":2,"name":"Emiliano Gamberini","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Emiliano","middleName":"","lastName":"Gamberini","suffix":""},{"id":624166670,"identity":"13cd8be8-f679-43aa-880f-3c05cc8adaf0","order_by":3,"name":"Marina Terzitta","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Terzitta","suffix":""},{"id":624166671,"identity":"e0b280d2-16b6-4ef5-a26c-ddb3637da6e8","order_by":4,"name":"Claudio Gecele","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Claudio","middleName":"","lastName":"Gecele","suffix":""},{"id":624166672,"identity":"f213bece-b3f5-444d-8211-15b9f1955319","order_by":5,"name":"Federico Biondi","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Federico","middleName":"","lastName":"Biondi","suffix":""},{"id":624166673,"identity":"daedea2a-41f2-497d-8f28-24e76900553e","order_by":6,"name":"Guido Gambetti","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Guido","middleName":"","lastName":"Gambetti","suffix":""},{"id":624166674,"identity":"78eb400f-9920-49e5-b5ef-185d5712d16b","order_by":7,"name":"Paolo Farolfi","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Paolo","middleName":"","lastName":"Farolfi","suffix":""},{"id":624166675,"identity":"64708de1-6f3c-480a-8f6f-dcbc394838fb","order_by":8,"name":"Maria Eleonora Petroni","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Eleonora","lastName":"Petroni","suffix":""},{"id":624166676,"identity":"ccb18b37-371f-41cd-be88-f133e3328165","order_by":9,"name":"Anna Bartoletti Stella","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"Bartoletti","lastName":"Stella","suffix":""},{"id":624166677,"identity":"0f1d89ff-bd5e-456e-b88b-480d814700b2","order_by":10,"name":"Martina Brandolini","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Brandolini","suffix":""},{"id":624166678,"identity":"07542bd3-3717-4721-b327-a940dc557b88","order_by":11,"name":"Massimiliano Guerra","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Massimiliano","middleName":"","lastName":"Guerra","suffix":""},{"id":624166679,"identity":"40636162-7288-43f6-8cd7-de08f1a8176e","order_by":12,"name":"Giulia Gatti","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Gatti","suffix":""},{"id":624166680,"identity":"fc07a425-278c-45ae-a655-8a073d627f70","order_by":13,"name":"Claudia Colosimo","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"","lastName":"Colosimo","suffix":""},{"id":624166681,"identity":"8113faaf-bebf-4188-9f5f-986f6fa4a62d","order_by":14,"name":"Ludovica Ingletto","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Ludovica","middleName":"","lastName":"Ingletto","suffix":""},{"id":624166682,"identity":"84d13ac1-7a56-415c-8baa-6e2266d6d21a","order_by":15,"name":"Laura Dionisi","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Dionisi","suffix":""},{"id":624166683,"identity":"1a6ee28a-4972-48dd-a3ea-c9c9ae3a0d54","order_by":16,"name":"Giorgio Dirani","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Giorgio","middleName":"","lastName":"Dirani","suffix":""},{"id":624166684,"identity":"d97a562c-5455-4fe6-a8f7-013547489b8d","order_by":17,"name":"Silvia Zannoli","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Silvia","middleName":"","lastName":"Zannoli","suffix":""},{"id":624166685,"identity":"b8dcdaba-5f0e-4253-a1c8-2362d6de0869","order_by":18,"name":"Maria Sofia Montanari","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Sofia","lastName":"Montanari","suffix":""},{"id":624166686,"identity":"638ccacc-7e4f-4d45-a636-5484891140fc","order_by":19,"name":"Anna Marzucco","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Della Romagna","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Marzucco","suffix":""},{"id":624166688,"identity":"8de36c14-de33-4942-b96b-0610257a9ba5","order_by":20,"name":"Alessandra Mistral Pascali","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Alessandra","middleName":"Mistral","lastName":"Pascali","suffix":""},{"id":624166690,"identity":"3c512d92-1f19-4ae6-a9a1-d01a662dec14","order_by":21,"name":"Monica Cricca","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Monica","middleName":"","lastName":"Cricca","suffix":""},{"id":624166691,"identity":"ba3f58ff-ab5f-41b9-ab39-08f406d4883a","order_by":22,"name":"Vittorio Sambri","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Vittorio","middleName":"","lastName":"Sambri","suffix":""}],"badges":[],"createdAt":"2026-03-28 09:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9251510/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9251510/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107254754,"identity":"7d0aec3d-6bc7-4a48-8069-fcc70439ff2e","added_by":"auto","created_at":"2026-04-19 12:05:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44135,"visible":true,"origin":"","legend":"\u003cp\u003eBlood culture results and MR-proADM levels.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9251510/v1/0691f05f227eb98bc90a0e54.png"},{"id":107483057,"identity":"4885a6c6-aac2-41cb-ba57-eb7f67d5f7f8","added_by":"auto","created_at":"2026-04-22 02:26:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48843,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Mean MR-proADM levels (nmol/L) in patients with Gram-negative (Gram -, n=16), Gram-positive (Gram +, n=20), or negative blood cultures (Negative, n=69) who had three consecutive measurements at t0, t24, and t48. (B) Mean MR-proADM levels (nmol(L) in Gram negative group (n=23) with two measurements (t0, t24h).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9251510/v1/0486a3682319d2be8f413dae.png"},{"id":107254756,"identity":"7b7e44e3-d0d3-442f-88c5-f65aeb18c8c6","added_by":"auto","created_at":"2026-04-19 12:05:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":116296,"visible":true,"origin":"","legend":"\u003cp\u003eThe terms Dead/Survived 7 days after enrollment and Dead/Survived 28 days after enrollment are observed, in Blood culture negative (a), in Grm negative group (b) and Gram positive group (c).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9251510/v1/39feb430c97d4043576a4ccf.png"},{"id":107254757,"identity":"05df7265-5b12-4aa6-8c55-462067724e18","added_by":"auto","created_at":"2026-04-19 12:05:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17046,"visible":true,"origin":"","legend":"\u003cp\u003eMR-proADM progression stratified by age group. Median MR-proADM concentrations (nmol/L) measured at baseline (t0), 24 hours (t24), and 48 hours (t48) are shown for patients aged \u0026gt;60 years (group 1) and \u0026lt;60 years (group 2). Bars represent median values and error bars indicate variability (interquartile range).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9251510/v1/2d6bfb004d19cab3b7bf09f9.png"},{"id":107254758,"identity":"61dc6eba-3b10-438f-8a33-75539235ddea","added_by":"auto","created_at":"2026-04-19 12:05:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":51675,"visible":true,"origin":"","legend":"\u003cp\u003eTime course of MR-proADM and C-reactive protein (CRP) in Gram-negative bacteremia. Median MR-proADM (bars, left axis) decreased over time, while CRP (line, right axis) peaked at 24 h and declined at 48 h (a). Time course of MR-proADM and C-reactive protein (CRP) in Gram-positive bacteremia. MR-proADM levels were lower and progressively decreased, whereas CRP increased at 24 h and markedly declined at 48 h (b).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9251510/v1/149a7fa79549f7b27222e3a7.png"},{"id":107485784,"identity":"1b6bf695-0c5d-4cfd-800f-c85e370f0b4d","added_by":"auto","created_at":"2026-04-22 02:36:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":616485,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9251510/v1/e8524f56-ec69-464f-b370-1315bcd50b57.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of the clinical contribution in sepsis risk assessment with MR-proADM as an early biomarker of endothelial dysfunction: preliminary data from a cohort of critically ill patients tested by the LIAISON® BRAHMS MR-proADM™ Assay","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSepsis is the systemic response to infection, generally due to common bacterial organisms such as \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, streptococci, \u003cem\u003eEnterobacteriaceae\u003c/em\u003e, and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSepsis and septic shock remain a global health challenge with high mortality rates and increasing antibiotic resistance, underscoring the need for effective strategies for early recognition, risk stratification, and prognosis assessment (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSepsis is a fairly common condition and is one of the most frequent causes of death in most ICU (intensive care units) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the ICU, there are two main challenges to consider: strategies to identify septic status early and moderate antibiotic use.\u003c/p\u003e \u003cp\u003eIn general, clinicians must empirically choose from a wide range of broad-spectrum agents, often without immediate microbiological guidance. In addition, despite timely empirical therapy, the patient's condition can still worsen. In addition, the use of non-targeted antibiotics leads to a progressive increase in the phenomenon of antibiotic resistance, reducing the ammunition that can be used for future infections (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Methods for rapid identification of sepsis make use of clinical scores, standardized tools used to quantify disease severity, estimate prognosis, and support clinical decision-making (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). They integrate clinical, physiological and laboratory parameters, allowing an objective and reproducible assessment of the patient, particularly in emergency, intensive care and sepsis settings.\u003c/p\u003e \u003cp\u003eHowever, the use of clinical scores alone could delay antibiotic treatment and worsen the patient's prognosis (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In the \u003cem\u003e2019 Gonzalez del Castillo study\u003c/em\u003e, it is well highlighted that the use of clinical scores to manage a septic system patient is often a reductive and dangerous measure for the patient. In fact, the use of endothelial dysfunction biomarker MR-proADM and clinical scores such as NEWS (National Early Warning Score) in relation to antibiotic use was investigated. ICU admission was delayed by 1.5 days in patients with elevated MR-proADM values and low NEWS values compared to matched patients with high NEWS values, despite similar mortality rates at 28 days (13.5% vs. 16.5%). Antibiotics were discontinued in 17.4% of patients with elevated MR-proADM and low NEWS values, with higher rates of ICU admission (27.3% vs. 4.8%) and infection-related hospital admission (54.5% vs. 14.3%) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlongside the early management of sepsis through the use of clinical scores, biomarkers are also used, molecules secreted early or during the septic event, the most used are C-Reactive Protein (CRP) and Procalcitonin (Pct) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Often, however, these methods do not disregard therapeutic failure, and it becomes necessary to understand what leads to therapeutic failure with the eventual exitus of the patient. It should be considered that treatment failure underlies a complex pathophysiological process of sepsis in which the host response is dysregulated and causes cellular, tissue and organ damage. Rapid diagnosis of bacterial infection and early assessment of a poor prognosis are essential for septic septic patients and for all levels of clinical patient management, which is why biochemical values that can help the clinician in the therapeutic decision of a critically ill patient are always sought. The favorable effects that follow the choice of the appropriate time to start and stop antibiotic therapy could also concern the reduction of health costs, both by avoiding the administration of inadequate antibiotic therapies and by reducing the duration of hospitalization.\u003c/p\u003e \u003cp\u003eNumerous literature reviews have emphasized the importance of biomarker assessment in the management of sepsis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCirculating biomarkers that reflect endothelial stress may increase early risk stratification (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). MR-proADM is a stable surrogate for adrenomedullin, implicated in the regulation of vascular tone and barrier integrity (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). ADM is a 52-amino acid peptide hormone isolated in 1993 from extracts of human pheochromocytoma (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). ADM belongs to the calcitonin gene peptide superfamily: calcitonin, PCT, calcitonin-related peptide (CGRP), Amylin, and ADM. The ADM molecule has a 27% similarity to CGRP (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The gene for human ADM is located on a single locus on chromosome 11. The mRNA encodes information for the synthesis of a prehormone known as preproadrenomedullin, which is composed of 185 amino acids, which is subsequently degraded into the 164-amino acid peptide called proadrenomedullin via pooping of the signal peptide. Proadrenomedullin has three vasoactive peptides: ADM, aminoterminal peptide proadrenomedullin (PAMP), and adrenotensin (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Studies show that the ADM protein possesses antimicrobial and anti-inflammatory properties, participating in the body's defense mechanism against bacterial invasion (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This makes it a candidate as an early indicator of organ dysfunction which is the exacerbation of an ongoing deep or systemic infection. ADM has homeostatic and regulatory roles, influencing the physiological functions of the cardiovascular system and kidneys. However, circulating ADM is extremely difficult to detect in blood samples because it degrades rapidly from the circulation in about 22 minutes thanks to plasma proteases (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). For this reason, it is decided to dose MR-proADM, which derives from the proteolytic cleavage of the polypeptide that leads to the formation of ADM in a 1:1 ratio. Numerous studies have investigated the possible role of ADM in septic processes, but none have yet correlated the value of the biomarker and its temporal trend with respect to the microorganism causing the septic event.\u003c/p\u003e \u003cp\u003eIn this work, we have chosen to investigate the properties of the biochemical marker MR-proADM as a support for ICU clinicians, providing them with a valid parameter together with the etiological diagnosis of sepsis through the Blood Culture reference model.\u003c/p\u003e \u003cp\u003eThe automated LIAISON\u0026reg; BRAHMS MR-proADM\u0026trade; chemiluminescent immunoassay system offers standardized quantification of MR-proADM in plasma. This study investigates MR-proADM trends related to microbial etiology and clinical outcomes and compares its prognostic utility to CRP. The study was approved by the Ethics Committee of Romagna with Resolution no. 198 of 22/01/2025. \u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eStudy design and context\u003c/b\u003e: This prospective observational study enrolled 150 adult ICU patients from the AUSL Romagna network, Emilia Romagna, Italy, between April and October 2025. Informed consent to participate in the study was obtained from all patients as required by the Declaration of Helsinki. Patient inclusion criteria included: adulthood, intensive cure admission after surgery or trauma, and clinical picture of sepsis clinically assessed via clinical scores and haematological parameters according to Sepsis-3 guidelines. Blood samples for MR-proADM were collected in plasma tube with separator gel and K2_EDTA at three time points: admission (t0), 24 hours (t24), and 48 hours (t48). The blood culture was performed at the same time as the t0 of MR-proADM, in time of clinical suspicion of sepsis, in special bottles containing the culture medium and incubated at 37\u0026deg;C for up to 5 days. The results of the blood culture were used to classify patients into three groups:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBlood culture negative\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGram-negative bacteremia\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGram-positive bacteremia\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eClinical data included age, sex, and 7- and 28-days mortality.\u003c/p\u003e\n\u003ch3\u003eBiomarker measurement:\u003c/h3\u003e\n\u003cp\u003eMR-proADM was quantified from gel-separated EDTA plasma samples that were centrifuged and frozen at -20\u0026deg;C until assay. Subsequently, the biomarker test was performed using the LIAISON\u0026reg; BRAHMS MR-proADM\u0026trade; test (DiaSorin S.p.A., Saluggia (VC) - Italy). It is a sandwich chemiluminescent assay with anti-MR-proADM capture and isoaluminum-labeled detection antibodies on an automated platform. The assay range is 0.21\u0026ndash;10 nmol/L. Unbound materials were removed by automatic washing; chemiluminescent signal correlated with the concentration of MR-proADM by light emission detection. The reference values indicated by the test provide a cut-off of 0.87 nmol/L for the assessment of the risk of progression to a severe pathological condition. If the value is \u0026gt;\u0026thinsp;1.50 nmol/L the risk of progression to a more severe disease condition increases, and if\u0026thinsp;\u0026lt;\u0026thinsp;2.25 nmol/L a clinically stable patient can be safely discharged from the intensive care unit at a lower level of care.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOther laboratory markers\u003c/h2\u003e \u003cp\u003eC-reactive protein (CRP) was routinely measured by Roche Diagnostics S.p.A. (Monza (MB), Italy). Results are expressed in mg/L. Procalcitonin has been excluded from statistical considerations because it is used clinically downstream in the management of sepsis, to monitor the effectiveness of antibiotic treatment rather than roll in in therapy as is the case for CRP and MR-proADM.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIdentification of isolates:\u003c/h3\u003e\n\u003cp\u003eThe causative agent of sepsis was detected by blood culture examination in dedicated Culture Media bottles with positivity detected by the BacT/Alert Virtuo system (bioM\u0026eacute;rieux, Marcy l'Etoile, France). Subsequently, in positive aerobic/anaerobic bottles, the culture was examined by microscopic examination with Gram staining and species identification by mass spectrometry (MALDI-ToF).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eGiven the preliminary sample size, analyses focused on descriptive statistics and exploratory comparisons without inferential testing. Descriptive statistics summarized biomarker levels across groups and outcomes. Statistical analysis was carried out using Microsoft Excel statistical programs and one-way ANOVA tests and ANOVA tests for independent measures (Social Science Statistics).\u003c/p\u003e \u003cp\u003eIt was also used Wilcoxon signed-rank test is a non-parametric statistical test for to compare two related samples (paired data) or repeated measurements.\u003c/p\u003e \u003cp\u003eA statistical analysis was performed considering the time course of MR-proADM concentrations according to microbiological category, survival status and age. Median MR-proADM levels were assessed at baseline (t0), 24 hours (t24), and 48 hours (t48).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCohort characteristics:\u003c/h2\u003e \u003cp\u003eOf the 150 patients enrolled in the study, 96 had a negative microbiological result, 29 positive for Gram-negative microorganisms, and 25 positive for Gram-positive microorganisms (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). 64 female and 86 male subjects were enrolled, with an average age of 71 and 68 years, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of blood culture results and microorganisms isolated\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood culture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram -\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram +\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMicroorganism isolated in culture G+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCount\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacillus sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE. faecium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. agalactiae gr. B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. aureus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. capitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. epidermidis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. epidermidis/hominis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. hominis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. mitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMicroorganism isolated in culture G-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCount\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA. baumannii\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCitrobacter koseri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE. coli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE.coli/K.pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterobacter aerogenes; E. faecalis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterococcus faecium; Klebsiella oxytoca; Enterococcus avium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH. influenzae/K. Pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK. Oxytoca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK. Pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorganella morganii\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeisseria subflava\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP. aeruginosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. marcescens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMR-proADM kinetics:\u003c/h2\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e it is possible to observe the average trend of MR-proADM in the three categories considering the values ​​obtained from 150 enrolled patients. Gram-negative bacteremia was associated with the highest MR-proADM values at all time points, while culture-negative patients showed intermediate levels and Gram-positive bacteremia the lowest (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.A). At baseline, MR-proADM concentrations differed significantly between Gram-negative bacteremia and other microbiological categories, with no significant difference between Gram-positive and culture-negative patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo assess temporal changes in MR-proADM levels, the primary analysis included only patients with comprehensive biomarker measurements at all three predefined time points, resulting in a cohort of 105 patients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.A). A one-way repeated measures ANOVA was then performed to assess changes within the group over time in association with a non-parametric statistical test Wilcoxon signed-rank.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePro-adrenomedullin (pro-ADM) levels according to blood culture result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood culture result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003et0 mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et24 mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et48 mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00 (3.05\u0026ndash;4.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.80\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50 (3.05\u0026ndash;4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90 (2.84\u0026ndash;4.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram-positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00 (2.10\u0026ndash;4.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50 (1.65\u0026ndash;3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20 (1.55\u0026ndash;3.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram-negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.97\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50 (3.10\u0026ndash;8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50 (2.35\u0026ndash;6.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00 (2.25\u0026ndash;6.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50 (3.10\u0026ndash;4.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;3.90 (2.85\u0026ndash;4.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50 (2.60\u0026ndash;4.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong the 105 patients included in the analysis, MR-proADM levels were measured at baseline (t0), 24 hours (t24), and 48 hours (t48) and stratified according to blood culture results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, mean MR-proADM values showed a progressive decrease over time, from 3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50 nmol/L at t0 to 3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50 nmol/L at t48.\u003c/p\u003e \u003cp\u003ePatients with Gram-negative bacteremia (n\u0026thinsp;=\u0026thinsp;16) exhibited the highest MR-proADM concentrations at all time points, with mean values decreasing from 5.97\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50 nmol/L at t0 to 4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00 nmol/L at t48. In the Gram-positive group (n\u0026thinsp;=\u0026thinsp;20), MR-proADM levels were lower and showed a reduction from 3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00 nmol/L at baseline to 2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20 nmol/L at 48 hours. In contrast, patients with negative blood cultures (n\u0026thinsp;=\u0026thinsp;69) displayed relatively stable MR-proADM concentrations over time, with no clear downward trend.\u003c/p\u003e \u003cp\u003eWilcoxon signed-rank tests demonstrated statistically significant reductions in MR-proADM levels between t0 and t48 in both Gram-negative (p\u0026thinsp;=\u0026thinsp;0.012) and Gram-positive (p\u0026thinsp;=\u0026thinsp;0.045) groups, whereas no significant change was observed in the blood culture\u0026ndash;negative group (p\u0026thinsp;=\u0026thinsp;0.32) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.A).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBecause only a limited number of Gram-negative patients had complete measurements at all three time points, a secondary analysis was conducted including patients with at least two-time measurements available. This approach increased the Gram-negative sample size to 23 patients obtaining the mean reduction of 33.1% in Gram values was observed from baseline (t0: 7.37) to 24 hours (t24: 4.93) in the study population (n\u0026thinsp;=\u0026thinsp;23). (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.B).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMR-proADM in survivor and dead categories\u003c/h3\u003e\n\u003cp\u003eWhen stratified by blood culture results and short- and mid-term mortality, MR-proADM levels showed marked differences between non-survivors and survivors across all time points (t0, t24, t48) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eBlood culture–negative patients\u003c/h3\u003e\n\u003cp\u003eAt 7 days, patients who died exhibited substantially higher MR-proADM values than survivors at all time points, with a\u0026thinsp;+\u0026thinsp;189% difference at t0 (10.0 vs 3.46), +\u0026thinsp;185% at t24 (5.4 vs 3.51), and +\u0026thinsp;84% at t48 (5.9 vs 3.2).\u003c/p\u003e \u003cp\u003eA similar pattern was observed for 28-day mortality, where non-survivors had MR-proADM levels 153% higher at t0 (8.33 vs 3.29), 148% higher at t24 (7.28 vs 2.93), and 174% higher at t48 (7.1 vs 2.59) compared with survivors.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGram-negative bacteremia\u003c/h2\u003e \u003cp\u003eGram-negative non-survivors displayed the highest absolute MR-proADM concentrations. At 7 days, MR-proADM levels were +\u0026thinsp;146% higher at t0 (17.3 vs 7.02), +\u0026thinsp;249% at t24 (10.2 vs 2.92), and +\u0026thinsp;618% at t48 (13.0 vs 1.81) compared with survivors.\u003c/p\u003e \u003cp\u003eComparable differences were observed for 28-day mortality, with increases of +\u0026thinsp;108% at t0 (14.6 vs 7.02), +\u0026thinsp;184% at t24 (8.3 vs 2.92), and +\u0026thinsp;430% at t48 (9.6 vs 1.81) in non-survivors versus survivors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGram-positive bacteremia\u003c/h2\u003e \u003cp\u003eIn Gram-positive infections, MR-proADM levels were overall lower and showed a less consistent association with early mortality. At 7 days, non-survivors had 61% lower MR-proADM at t0 compared with survivors (1.53 vs 3.90), while differences at t24 and t48 were modest (+\u0026thinsp;5% and \u0026minus;\u0026thinsp;46%, respectively).\u003c/p\u003e \u003cp\u003eConversely, at 28 days, non-survivors exhibited higher MR-proADM levels than survivors, with increases of +\u0026thinsp;73% at t0 (4.75 vs 2.75), +\u0026thinsp;80% at t24 (3.75 vs 2.08), and +\u0026thinsp;69% at t48 (3.47 vs 2.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAge-stratified analysis and the comparison with CRP:\u003c/h2\u003e \u003cp\u003eAge-stratified analysis showed lower and stable levels of MR-proADM in younger patients, while older patients had higher baseline values at all observation points (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCRP showed a nonspecific increase between the two groups, Gram-negative and Gram-positive, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea and b, respectively. Furthermore, it should be noted that for MR-proADM, a trend can be observed that provides early indications, unlike CRP, which peaks 24 hours after suspected sepsis and then declines, assuming values ​​that are not indicative of the patient's infectious status.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this prospective observational study, we evaluated the temporal kinetics and prognostic value of MR-proADM measured using a fully automated chemiluminescent assay in critically ill patients with suspected sepsis, stratified by microbiological etiology and clinical outcome.\u003c/p\u003e \u003cp\u003eOne of the most relevant results of this study is the consistent observation of higher concentrations of MR-proADM in patients with Gram-negative bacteremia at all measured time points compared to Gram-positive and culture-negative patients. This pattern likely reflects the profound endothelial activation and vascular dysfunction induced by Gram-negative pathogens, whose lipopolysaccharide (LPS) triggers a potent innate immune response via Toll-like receptor 4 signaling, leading to widespread cytokine release, nitric oxide production, and capillary leakage (\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Adrenomedullin plays a central role in maintaining the integrity of the endothelial barrier and regulating vascular tone during inflammatory stress (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Elevated MR-proADM concentrations in Gram-negative sepsis may therefore represent a compensatory response to severe endothelial injury, rather than a simple indicator of infection burden. This interpretation is consistent with previous studies that have demonstrated higher levels of MR-proADM in patients with septic shock and severe organ dysfunction, particularly in settings characterized by distributional shock and vasoplegia (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Intriguingly, culture-negative patients showed intermediate MR-proADM values, suggesting that even in the absence of microbiological confirmation, a subset of these patients may experience significant endothelial stress. This observation is consistent with previous evidence indicating that blood culture can remain negative in up to 40\u0026ndash;50% of septic patients despite a true infection, often due to previous antibiotic exposure or low bacterial load (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). MR-proADM can therefore provide pathophysiological information complementary to microbiological diagnostics.\u003c/p\u003e \u003cp\u003eLongitudinal evaluation of MR-proADM revealed distinct kinetic patterns among microbiological categories. A statistically significant decline over 48 hours was observed exclusively in Gram-positive bacteremia when complete serial measurements were available, while values remained stable in culture-negative patients and declined more slowly in Gram-negative infections. These findings suggest that the kinetics of MR-proADM may reflect differences in the reversibility of endothelial dysfunction depending on the pathogen type. Gram-positive infections, often characterized by localized infectious sources and a lower endotoxin burden, may allow for faster restoration of endothelial homeostasis once appropriate antimicrobial therapy has been initiated (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Conversely, Gram-negative sepsis may be associated with sustained endothelial activation and explain the slower or incomplete decline in MR-proADM observed in this group. The persistence of elevated MR-proADM values has been previously linked to ongoing microcirculatory dysfunction and poor outcome, even in patients showing apparent clinical stabilization (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Our results reinforce the concept that MR-proADM kinetics, rather than isolated measurements, provide clinically meaningful information regarding the disease pathway.\u003c/p\u003e \u003cp\u003eNon-survivors consistently showed higher, non-decreasing levels of MR-proADM over time than survivors, who showed a progressive reduction. This result is in line with numerous studies identifying MR-proADM as a strong independent predictor of short- and medium-term mortality in sepsis and septic shock (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). From a mechanistic perspective, elevated persistent MR-proADM likely reflects irreversible endothelial injury, loss of vascular barrier function, and progression to multiorgan failure. The association between declining MR-proADM levels and survival supports its role as a dynamic indicator of recovery rather than a static indicator of disease severity.\u003c/p\u003e \u003cp\u003eAge-stratified analysis revealed higher baseline concentrations of MR-proADM in elderly patients, consistent with previous reports showing that MR-proADM increased with age, even in non-septic populations (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This phenomenon may reflect age-related endothelial dysfunction, increased vascular rigidity, and reduced compensatory capacity during systemic inflammation. These results highlight the importance of interpreting MR-proADM values in the clinical and demographic context and oppose rigid threshold values without age adjustment. CRP showed slower kinetics and failed to discriminate between microbiological categories or survival outcomes. Although CRP remains a widely used inflammatory marker, its hepatic origin and delayed response limit its usefulness in early risk stratification and prognostic assessment (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In contrast, MR-proADM directly reflects endothelial stress, capturing a critical pathophysiological component of sepsis that precedes organ visual failure. The early divergence of MR-proADM trajectories observed in our cohort underscores their potential superiority over traditional inflammatory markers for early prognostic assessment.\u003c/p\u003e \u003cp\u003eThe LIAISON\u0026reg; BRAHMS MR-proADM\u0026trade; automated assay enables standardized and reproducible measurement of MR-proADM, making it easy to integrate into routine laboratory workflows. Early identification of patients with persistently elevated or increasing MR-proADM levels could support clinical decision-making, including escalation of monitoring, optimization of hemodynamic support, and re-evaluation of therapeutic strategies.\u003c/p\u003e \u003cp\u003eMoreover, MR-proADM may complement clinical scores, which alone can underestimate the risk in certain subgroups of patients, as previously demonstrated in studies combining MR-proADM with early warning scores (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). However, our findings caution against using MR-proADM as a standalone tool, emphasizing the need for integrated clinical interpretation.\u003c/p\u003e \u003cp\u003eOur results support MR-proADM as an early marker of endothelial dysfunction and adverse prognosis, overcoming CRP in discriminating between disease severity and outcome, and provide new insights into its behaviour according to the pathogen category.\u003c/p\u003e \u003cp\u003eThis study has several limitations, including the single-network design, the limited sample size in subgroup analyses, and the exploratory nature of the statistical approach. The absence of systematic measurements of procalcitonin prevented direct comparison with other biomarkers for sepsis.\u003c/p\u003e \u003cp\u003eFuture multicenter studies with larger cohorts are needed to validate these findings, establish clinically actionable threshold values, and evaluate the role of MR-proADM-guided therapeutic algorithms, including antimicrobial stewardship strategies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eMR-proADM measured on the LIAISON\u0026reg; platform is a promising early biomarker of endothelial dysfunction and adverse outcome in sepsis. It shows a stronger early prognostic value than CRP. Larger studies are needed to validate clinical cut-offs and integrate MR-proADM into therapeutic algorithms.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eCGRP (calcitonin-related peptide);\u003c/p\u003e \u003cp\u003eCRP (C Reactive Protein);\u003c/p\u003e \u003cp\u003eICU (Intensive Care Unit\u003cem\u003e);\u003c/em\u003e\u003c/p\u003e \u003cp\u003eMR-proADM (mid-region pro-adrenomedullin);\u003c/p\u003e \u003cp\u003eNEWS (National Early Warning Score).\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e● \u0026nbsp; \u0026nbsp; \u0026nbsp; Ethics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Romagna with Resolution no. 198 of 22/01/2025.\u003c/p\u003e\n\u003cp\u003eInformed consent to participate in the study was obtained from all patients as required by the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp; \u0026nbsp; \u0026nbsp; Consent for publication\u003c/p\u003e\n\u003cp\u003eInformed consent for data publication in the study was obtained from all patients.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp; \u0026nbsp; \u0026nbsp; Availability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available because they are owned by AUSL Romagna and subject to confidentiality agreements, but are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp; \u0026nbsp; \u0026nbsp; Competing Interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp; \u0026nbsp; \u0026nbsp; Funding\u003c/p\u003e\n\u003cp\u003eThis study was supported by research funding from Local Health Authority of Romagna.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp; \u0026nbsp; \u0026nbsp; Authors' contributions\u003c/p\u003e\n\u003cp\u003eConceptualization: LG, VS; Data Curation: LG, SS; Formal Analysis: ABS, LG, FB, MEP; Investigation: LG; Funding acquisition: VS; Methodology: LG, VS, MT, EG; Project administration: LG; Resources: LG; Software: LG, ABS; Supervision: VS, MC, AMDP; Validation: LG; Visualization: LG, MB; Writing — original draft: LG; Writing — revision and editing: LG, SS, EG, MT, CG, FB, GG, PF, MEP, ABS, MB, MG, GG, CC, LI, LD, GD, SZ, MSM, AM, AMDP, MC, VS.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp;Clinical trial number\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e● \u0026nbsp;Acknowledgments\u003c/p\u003e\n\u003cp\u003eWe thank the laboratory staff for their practical support, clinical analyses, and sample management. Special thanks to the technicians of the Unit of Microbiology the Greater Romagna Area Hub Laboratory: Rosario Romano, Lorena Esposito, Sara Cappucci, Vilma Sternini, Barabara Ceccarelli, Barbara Marchini, Lorella Mazzotti, Alfonso Sacconi.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBauer M, Gerlach H, Vogelmann T, Preissing F, Stiefel J, Adam D. Mortality in sepsis and septic shock in Europe, North America and Australia between 2009 and 2019\u0026mdash; results from a systematic review and meta-analysis. Crit Care. 2020;24(1):239.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348(16):1546\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarnacho-Montero J, Ortiz-Leyba C, Herrera-Melero I, Aldabo-Pallas T, Cayuela-Dominguez A, Marquez-Vacaro JA, et al. Mortality and morbidity attributable to inadequate empirical antimicrobial therapy in patients admitted to the ICU with sepsis: a matched cohort study. J Antimicrob Chemother. 2007;61(2):436\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent JL, Moreno R. Clinical review: Scoring systems in the critically ill. Crit Care. 2010;14(2):207.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003edel Gonzalez J, Wilson DC, Clemente-Callejo C, Rom\u0026aacute;n F, Bard\u0026eacute;s-Robles I, Jim\u0026eacute;nez I, et al. Biomarkers and clinical scores to identify patient populations at risk of delayed antibiotic administration or intensive care admission. Crit Care. 2019;23(1):335.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChuang CL, Yeh HT, Niu KY, Chen CB, Seak CJ, Yen CC. Diagnostic performances of procalcitonin and C-reactive protein for sepsis: a systematic review and meta-analysis. Eur J Emerg Med. 2025;32(4):248\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhuja N, Mishra A, Gupta R, Ray S. Biomarkers in sepsis-looking for the Holy Grail or chasing a mirage! World J Crit Care Med. 2023;12(4):188\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChrist-Crain M, Morgenthaler NG, Struck J, Harbarth S, Bergmann A, M\u0026uuml;ller B. Mid-regional pro-adrenomedullin as a prognostic marker in sepsis: an observational study. Crit Care. 2005;9(6):R816.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIshimitsu T, Kojima M, Kangawa K, Hino J, Matsuoka H, Kitamura K, et al. Genomic Structure of Human Adrenomedullin Gene. Biochem Biophys Res Commun. 1994;203(1):631\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitamura K, Kangawa K, Kawamoto M, Ichiki Y, Nakamura S, Matsuo H, et al. Adrenomedullin: A Novel Hypotensive Peptide Isolated from Human Pheochromocytoma. Biochem Biophys Res Commun. 1993;192(2):553\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePierrakos C, Vincent JL. Sepsis biomarkers: a review. Crit Care. 2010;14(1):R15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeeran K, O\u0026rsquo;Shea D, Upton PD, Small CJ, Ghatei MA, Byfield PH, et al. Circulating Adrenomedullin Does Not Regulate Systemic Blood Pressure but Increases Plasma Prolactin after Intravenous Infusion in Humans: A Pharmacokinetic Study 1. J Clin Endocrinol Metab. 1997;82(1):95\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAngus DC, van der Poll T. Severe Sepsis and Septic Shock. N Engl J Med. 2013;369(9):840\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSinger M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpal SM, van der Poll T. Endothelial barrier dysfunction in septic shock. J Intern Med. 2015;277(3):277\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang P. ADRENOMEDULLIN IN SEPSIS AND SEPTIC SHOCK. Shock. 1998;10(5):383\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuberviola B, Castellanos-Ortega A, Llorca J, Ortiz F, Iglesias D, Prieto B. Prognostic value of proadrenomedullin in severe sepsis and septic shock patients with community-acquired pneumonia. Swiss Med Wkly. 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElke G, Bloos F, Wilson DC, Brunkhorst FM, Briegel J, Reinhart K, et al. The use of mid-regional proadrenomedullin to identify disease severity and treatment response to sepsis - a secondary analysis of a large randomised controlled trial. Crit Care. 2018;22(1):79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLamy B, Darg\u0026egrave;re S, Arendrup MC, Parienti JJ, Tattevin P. How to Optimize the Use of Blood Cultures for the Diagnosis of Bloodstream Infections? A State-of-the Art. Front Microbiol. 2016;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen J. The immunopathogenesis of sepsis. Nature. 2002;420(6917):885\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoffre J, Hellman J, Ince C, Ait-Oufella H. Endothelial Responses in Sepsis. Am J Respir Crit Care Med. 2020;202(3):361\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndaluz-Ojeda D, Nguyen HB, Meunier-Beillard N, Cicu\u0026eacute;ndez R, Quenot JP, Calvo D, et al. Superior accuracy of mid-regional proadrenomedullin for mortality prediction in sepsis with varying levels of illness severity. Ann Intensive Care. 2017;7(1):15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaeed K, Wilson DC, Bloos F, Schuetz P, van der Does Y, Melander O, et al. The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study. Crit Care. 2019;23(1):40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;nal U, Valenzuela-S\u0026aacute;nchez F, Vandana KE, Rello J. Mid-Regional Pro-Adrenomedullin (MR-proADM) as a Biomarker for Sepsis and Septic Shock: Narrative Review. Healthcare. 2018;6(3):110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePepys MB, Hirschfield GM. C-reactive protein: a critical update. J Clin Invest. 2003;111(12):1805\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValenzuela-S\u0026aacute;nchez F, Valenzuela-M\u0026eacute;ndez B, Rodr\u0026iacute;guez-Guti\u0026eacute;rrez JF, Estella-Garc\u0026iacute;a \u0026Aacute;, Gonz\u0026aacute;lez-Garc\u0026iacute;a M\u0026Aacute;. New role of biomarkers: mid-regional pro-adrenomedullin, the biomarker of organ failure. Ann Transl Med. 2016;4(17):329\u0026ndash;329.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller JM, Binnicker MJ, Campbell S, Carroll KC, Chapin KC, Gilligan PH, et al. A Guide to Utilization of the Microbiology Laboratory for Diagnosis of Infectious Diseases: 2018 Update by the Infectious Diseases Society of America and the American Society for Microbiologya. Clin Infect Dis. 2018;67(6):e1\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sepsis, MR-proADM, Automatic immunoanalysis, Prognostic biomarkers, ICU, Endothelial dysfunction","lastPublishedDoi":"10.21203/rs.3.rs-9251510/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9251510/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives: \u003c/strong\u003e\u003cbr\u003e\nSepsis is the leading cause of death in the ICU. Early recognition and immediate management of the causes of sepsis is the focus of this work, aimed at evaluating one of the early-onset biomarkers in the phases of organ dysfunction typical of sepsis.\u003c/p\u003e\n\u003cp\u003eTo evaluate the performance of mid-region pro-adrenomedullin (MR-proADM) as an early biomarker of endothelial dysfunction and prognosis in critically ill patients with suspected sepsis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e\u003cbr\u003e\nIn this prospective observational cohort, 150 adult patients admitted to the Intensive Care Units (ICU) of AUSL Romagna from April to October 2025 were enrolled. Plasmmatic MR-proADM was quantified at baseline (t0), 24 hours (t24), and 48 hours (t48) using the LIAISON® BRAHMS MR-PROADM™ chemiluminescent assay. Patients were stratified according to blood culture results: culture negative, Gram negative and Gram-positive bacteremia. The primary outcomes were MR-proADM kinetics and association with 7- and 28-day mortality. Secondary outcome included comparison with C-reactive protein (CRP) trends.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003cbr\u003e\nMR-proADM levels were significantly higher in Gram-negative bacteremia than in the Gram-positive and culture-negative groups at all time points. Non-survivors showed persistently elevated or increasing MR-proADMs, while survivors showed declining trends. CRP showed slower kinetics and poor discrimination between infection categories.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003e\u003cbr\u003e\nMR-proADM identifies early endothelial dysfunction and predicts outcomes in sepsis. Its early kinetic changes outperform CRP for prognosis but require validation in larger cohorts to establish clinical cut-offs and utility in antimicrobial decision support.\u003c/p\u003e","manuscriptTitle":"Evaluation of the clinical contribution in sepsis risk assessment with MR-proADM as an early biomarker of endothelial dysfunction: preliminary data from a cohort of critically ill patients tested by the LIAISON® BRAHMS MR-proADM™ Assay","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:05:23","doi":"10.21203/rs.3.rs-9251510/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-09T10:33:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-09T10:28:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-09T07:59:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-08T09:09:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2026-04-08T08:23:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f3b2d71a-2613-48fb-b709-7e7eaf2db2b7","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-19T12:05:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:05:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9251510","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9251510","identity":"rs-9251510","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}