Prognostic blood biomarkers have generated clinical interest, resulting in therapeutic and diagnostic improvements [1]. A more personalized and targeted medicine offers opportunities to enhance treatment safety, efficacy as well as cost effectiveness. In this context, mid-regional pro-adrenomedullin (ProADM) provides prognostic information in various clinical settings and across different patient populations, predominantly suffering from cardiovascular and infectious diseases [2‐8].

Adrenomedullin (ADM) is a 52-amino acid ringed peptide, belonging to the calcitonin peptide superfamily [9, 10]. It is produced ubiquitously by endothelial cells in cardiovascular, renal, pulmonary, cerebrovascular and endocrine tissues [11‐13]. Studies reported several effects of ADM including vasodilatory, natriuretic, diuretic, anti-oxidative, anti-inflammatory, antimicrobial and metabolic effects [14‐19]. Unfortunately, ADM measurement is challenging and not available outside the research setting. ProADM, the prohormone of ADM, however, is less biologically active, stable and commercially available [20].

Several studies found ProADM to be a strong and independent predictor of outcomes in patients with COPD [21], acute or chronic heart failure [22‐26], community-acquired pneumonia [27, 28] and sepsis [29‐32]. ProADM blood levels were also associated with morbidity after acute coronary syndrome [33‐36], and predicted adverse outcomes in patients presenting to the emergency department (ED) with dyspnea [23, 37] or even nonspecific complaints [38]. Also, studies found association of ProADM with metabolic syndrome and its components, i.e. type 2 diabetes [39, 40].

Stratification of patients with lower respiratory infection based on a clinical algorithm including ProADM stratification tended to shorten length of hospital stay without an increase in adverse clinical outcome [41, 42].

In the setting of primary care, in smaller studies ProADM was associated with mortality in patients with urinary tract infections [43], type 2 diabetes [43‐45] or heart failure [25, 46‐49]. It is not known whether this marker helps to predict long-term risk, which could be useful for directing preventive measures. The aim of the current analysis was to investigate the ability of ProADM to predict long-term all-cause mortality and adverse outcome in a primary care cohort, visiting their general practitioner for respiratory infections.

Within this prospective, observational 10-year follow-up study of a small cohort of community-dwelling ARTI patients, we found ProADM on admission and after 7 days to be an age-independent predictor for all-cause mortality. No significant associations of ProADM and secondary outcomes were found, namely adverse outcome, MACCE and new onset of diabetes.

Our results are in-line with previous research reporting associations of ProADM and short-term mortality in inpatients [2‐4, 21‐38] as well as in primary care populations [25, 43‐49]. Importantly, also in long-term follow-up over 10 years the prognostic accuracy remained stable over time. Thus, based on this study and previous research, ProADM is a short- and long-term valid prognostic marker for patients from the community who may benefit from preventive measures. Our study suggests that ProADM should be evaluated in future long-term studies in outpatients assessing the accuracy of clinical scores (e.g., Pneumonia Severity Index, CURB65 (confusion, uremia, respiratory rate, blood pressure, age at least 65 years) score or Framingham score) in combination with novel markers to predict long-term outcome in this setting and direct individual use of medication or even hospital admission.

Although there is no clear understanding why an increase in ProADM points to increased mortality risk, existing data suggests that elevated ProADM levels reflect disease severity and endothelial and cardiovascular dysfunction [11‐19]. Also, higher ADM levels increases cardiac output, induces hypotension and vasodilation, and increases glomerular filtration rate and fractional sodium excretion [10, 19, 54], thereby inducing a reduction in cardiac pre- and afterload [20]. Thus, the involvement of ADM in several pathological disease states and comorbidities might explain the associations found in this and previous studies.

Median ProADM blood levels in our outpatient cohort were 0.3 nmol/l on admission and 0.2 nmol/l on day 7 and thus significantly lower compared to other hospitalized patient cohorts. The AtheroGene study found median ProADM levels of around 0.5 and 0.6 nmol/L in patients with stable angina and acute coronary syndrome [35]. The LAMP study reported median concentration of 0.73 nmol/L in patients with myocardial infarction [36], while the GISSI study found a median ProADM concentration of 0.75 nmol/L in patients with chronic heart failure [26]. Analysis of a presumably healthy subset in a large outpatient cohort (n = 5258) lead to a reference interval of 0.23—0.64 nmol/L [18, 55]. These differences demonstrate that levels of ProADM need to be adapted to the specific clinical setting to be interpreted in a meaningful way.

Interestingly, although several previous studies have suggested that ProADM was also associated with other adverse outcomes in addition to all-cause mortality [26, 27, 33‐36, 44‐46], we did not find such statistically significant association with the incidence of our secondary combined endpoint including pulmonary embolism and MACCE. Also, in contrast to another study [39], our analysis did not find an association of ProADM with new onset diabetes mellitus. This may be due to the small number of events in our generally healthy population with a low burden of comorbidities and thus low power of our analysis. Further, the respiratory infection of patients during the initial trial may have had an influence on ProADM levels. Thus, similar to lipid levels, [56] this marker may be best analyzed during stable conditions for the purpose of long-term risk assessment.

The main strengths of this study include the 10 years of follow-up, the participation of multiple GP practices, and the community sample of patients with ARTI of different severity representative for patients mainly treated in primary care. Nonetheless, we are aware of several limitations. First, this is a secondary analysis of a previous trial and baseline risk assessment is incomplete as is the availability of ProADM levels in the cohort. For 291 (63.5%) patients no data concerning ProADM blood levels was available, because blood sampling was only done in a sub fraction of the overall cohort during a certain time period. Selection bias is thus possible. Second, due to the long follow-up period, a recall bias has to be considered. Further, no information was available on the cause of death, when patients were tracked through the register of deaths. Third, our sample was small and we observed only few events for the analysis of the relationship between ProADM levels and adverse outcomes.

This posthoc analysis found an association of elevated ProADM blood levels and 10-year all-cause mortality in a primary care cohort with respiratory tract infections. Due to the methodological limitations including incomplete data regarding follow-up information and biomarker measurement, this study warrants validation in future larger studies. If validated, ProADM may help to risk stratify patients and thereby allows to improve allocation of health care resources and preventive measures.