The use of mid-regional proadrenomedullin to identify disease severity and treatment response to sepsis - a secondary analysis of a large randomised controlled trial

Background This study assessed the ability of mid-regional proadrenomedullin (MR-proADM) in comparison to conventional biomarkers (procalcitonin (PCT), lactate, C-reactive protein) and clinical scores to identify disease severity in patients with sepsis. Methods This is a secondary analysis of a randomised controlled trial in patients with severe sepsis or septic shock across 33 German intensive care units. The association between biomarkers and clinical scores with mortality was assessed by Cox regression analysis, area under the receiver operating characteristic and Kaplan-Meier curves. Patients were stratified into three severity groups (low, intermediate, high) for all biomarkers and scores based on cutoffs with either a 90% sensitivity or specificity. Results 1089 patients with a 28-day mortality rate of 26.9% were analysed. According to the Sepsis-3 definition, 41.2% and 58.8% fulfilled the criteria for sepsis and septic shock, with respective mortality rates of 20.0% and 32.1%. MR-proADM had the strongest association with mortality across all Sepsis-1 and Sepsis-3 subgroups and could facilitate a more accurate classification of low (e.g. MR-proADM vs. SOFA: N = 265 vs. 232; 9.8% vs. 13.8% mortality) and high (e.g. MR-proADM vs. SOFA: N = 161 vs. 155; 55.9% vs. 41.3% mortality) disease severity. Patients with decreasing PCT concentrations of either ≥ 20% (baseline to day 1) or ≥ 50% (baseline to day 4) but continuously high MR-proADM concentrations had a significantly increased mortality risk (HR (95% CI): 19.1 (8.0–45.9) and 43.1 (10.1–184.0)). Conclusions MR-proADM identifies disease severity and treatment response more accurately than established biomarkers and scores, adding additional information to facilitate rapid clinical decision-making and improve personalised sepsis treatment. Electronic supplementary material The online version of this article (10.1186/s13054-018-2001-5) contains supplementary material, which is available to authorized users.

Table S1 Survival analysis for the addition of MR-proADM to baseline biomarkers or scores Table S2 AUROC analysis for the addition of MR-proADM to baseline biomarkers or scores Table S3 Net reclassification improvement analysis for baseline MR-proADM and biomarker/score combinations Table S4 Survival analysis for MR-proADM within different organ dysfunction severity groups when combined with baseline biomarkers or scores Table S5 Characterisitics of MR-proADM cut-offs at baseline Table S6 SOFA and MR-proADM disease severity groups for 28 day mortality Table S7 SAPS II and MR-proADM disease severity groups for 28 day mortality Table S8 APACHE II and MR-proADM disease severity groups for 28 day mortality Table S9 Lactate and MR-proADM disease severity groups for 28 day mortality Table S10 Biomarker and SOFA association with 28 day mortality at days 1, 4, 7 and 10 Table S11 Disease severity groups and corresponding mortality rates throughout ICU treatment Table S12 Characterisitics of low severity MR-proADM cut-offs at days 1, 4, 7 and 10 Table S13 28 day mortality relative risk ratios for continuously maintained biomarker and score values Table S14 7 day, ICU and Hospital mortality rates following PCT and MR-proADM kinetics between baseline and day 1 Table S15 ICU and Hospital mortality rates following PCT and MR-proADM kinetics between baseline and day 4 Table S16 Baseline biomarker and clinical score correlation with SOFA at baseline and SOFA at day 1 Table S17 Baseline MR-proADM correlations with SOFA subscores at baseline and on day 1 Table S18 Biomarker correlations with SOFA scores throughout ICU treatment Table S19 Time Influence of infectious origin on 28 day mortality prediction Figure S3 Influence of microbial species on 28 day mortality prediction Figure S4 Influence of mode of ICU entry on 28 day mortality prediction
When patients were grouped according to operative emergency, non-operative emergency and elective surgery history resulting in admission to the ICU, MR-proADM provided the strongest and most balanced association with 28 day mortality across all groups ( Figure S4).

Correlation of biomarkers and clinical scores with SOFA at baseline and day 1
MR-proADM had the highest correlation of all biomarkers with the SOFA score at baseline. This correlation was significantly increased when baseline MR-proADM values were correlated with day 1 SOFA scores. The greatest correlation could be found between MR-proADM and SOFA on day 10, with differences between individual SOFA subscores found throughout (Table S16-18).

Additional prognostic value of MR-proADM measurements to baseline concentrations
Time-dependent Cox regression analysis indicated that the earliest significant additional increase in prognostic information to MR-proADM baseline values could be observed on day 1, with subsequent or cumulative measurements resulting in significantly stronger associations with 28 day mortality (Table S19).           Table S13.

day mortality relative risk ratios for continuously maintained biomarker and score values
Ascending biomarker and SOFA values were grouped into ventiles (increments of 5%) for all patients, based on respective concentrations or values at baseline. Corresponding cut-offs for each ventile were subsequently identified. 28 day mortality prediction was assessed depending on whether the concentration of each biomarker or score was continuously maintained above respective ventiles from baseline to day 10. Relative risk ratios were calculated for each ventile in order to identify the ratio of the risk in the exposed population (i.e. where biomarkers or scores were continuously maintained above the corresponding ventile) compared to that of the non-exposed population (i.e. where biomarkers or scores were below the respective ventile at one time point or more). The χ 2 test was subsequently performed to determine the significance of any difference between the the two populations.