Natriuretic Peptides to Predict Short-Term Mortality in Patients With Sepsis: A Systematic Review and Meta-analysis

Data are conflicting regarding the optimal cutoffs of B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) to predict short-term mortality in patients with sepsis. We conducted a comprehensive search of several databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus) for English-language reports of studies evaluating adult patients with sepsis, severe sepsis, and septic shock with BNP/NT-proBNP levels and short-term mortality (intensive care unit, in-hospital, 28-day, or 30-day) published from January 1, 2000, to September 5, 2017. The average values in survivors and nonsurvivors were used to estimate the receiver operating characteristic curve (ROC) using a parametric regression model. Thirty-five observational studies (3508 patients) were included (median age, 51-75 years; 12%-74% males; cumulative mortality, 34.2%). A BNP of 622 pg/mL had the greatest discrimination for mortality (sensitivity, 0.695 [95% CI, 0.659-0.729]; specificity, 0.907 [95% CI, 0.810-1.003]; area under the ROC, 0.766 [95% CI, 0.734-0.797]). An NT-proBNP of 4000 pg/mL had the greatest discrimination for mortality (sensitivity, 0.728 [95% CI, 0.703-0.753]; specificity, 0.789 [95% CI, 0.710-0.867]; area under the ROC, 0.787 [95% CI, 0.766-0.809]). In prespecified subgroup analyses, identified BNP/NT-proBNP cutoffs had higher discrimination if specimens were obtained 24 hours or less after admission, in patients with severe sepsis/septic shock, in patients enrolled after 2010, and in studies performed in the United States and Europe. There was inconsistent adjustment for renal function. In this hypothesis-generating analysis, BNP and NT-proBNP cutoffs of 622 pg/mL and 4000 pg/mL optimally predicted short-term mortality in patients with sepsis. The applicability of these results is limited by the heterogeneity of included patient populations.