BackgroundThe early identification of patients at risk of dying from community-acquired pneumonia (CAP) is critical for their treatment and for defining hospital resource consumption. Mid-regional pro-adrenomedullin (MR-proADM) has been extensively investigated for its prognostic value in CAP. However, the results are conflicting. The purpose of the present meta-analysis was to explore the diagnostic accuracy of MR-proADM for predicting mortality in patients suffering from CAP, particularly emergency department (ED) patients.MethodWe systematically searched the PubMed, Embase, Web of Knowledge and Cochrane databases. Studies were included if a 2 × 2 contingency table could be constructed based on both the MR-proADM level and the complications or mortality of patients diagnosed with CAP. The prognostic accuracy of MR-proADM in CAP was assessed using the bivariate meta-analysis model. We used the Q-test and I2 index to evaluate heterogeneity.ResultsMR-proADM displayed moderate diagnostic accuracy for predicting complications in CAP, with an overall area under the SROC curve (AUC) of 0.74 (95 % CI: 0.70–0.78). Eight studies with a total of 4119 patients in the emergency department (ED) were included. An elevated MR-proADM level was associated with increased risk of death from CAP (RR 6.16, 95 % CI 4.71–8.06); the I2 value was 0.0 %, and a fixed-effects model was used to pool RR. The pooled sensitivity and specificity were 0.74 (95 % CI: 0.67–0.79) and 0.73 (95 % CI: 0.70–0.77), respectively. The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 2.8 (95 % CI, 2.3–3.3) and 0.36 (95 % CI, 0.29–0.45), respectively. In addition, the diagnostic odds ratio (DOR) was 8 (95 % CI, 5–11), and the overall area under the SROC curve was 0.76 (95 % CI, 0.72–0.80).ConclusionsOur study has demonstrated that MR-proADM is predictive of increased complications and higher mortality rates in patients suffering from CAP. Future studies are warranted to determine the prognostic accuracy of MR-proADM in conjunction with severity scores or other biomarkers and to determine an optimal cut-off level.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1566-3) contains supplementary material, which is available to authorized users.