Improved Diagnostics Help to Identify Clinical Features and Biomarkers That Predict Mycoplasma pneumoniae Community-acquired Pneumonia in Children

Meyer Sauteur, Patrick M; Krautter, Selina; Ambroggio, Lilliam; Seiler, Michelle; Paioni, Paolo; Relly, Christa; Capaul, Riccarda; Kellenberger, Christian; Haas, Thorsten; Gysin, Claudine; Bachmann, Lucas M; van Rossum, Annemarie M C; Berger, Christoph

Several scores, ratios, algorithms, and prediction rules have been reported to diagnose Mp infection on the basis of clinical features [5, 7, 23, 24] . However, previous studies found no reliable signs or symptoms to differentiate Mp infection in CAP from other etiology [5, 6] , potentially because Mp infection was misclassified as infection when it was carriage. We recently demonstrated that the Mp IgM ASC ELISpot assay differentiates Mp infection from carriage [9] : While Mp DNA and/or IgM were also detected in 48% and 29% healthy control children (n = 21), all were tested negative by the Mp IgM ASC ELISpot assay [9] . Notably, the high Mp detection rate in CAP patients (46%) in this study may be related to the inclusion age of 3-18 years, in which Mp is most frequently detected [1, 2] , and the coinciding Mp epidemic in Europe during the study period [25] [26] [27] [28] . Prevalence estimates are important for translation of diagnostic study findings into clinical practice. When taking the Bayes theorem into account, the posttest probability of disease presence will be higher given a higher pretest probability or prevalence [29] [30] [31] . For proper implementation of a new diagnostic test into clinical practice, it is therefore necessary that the test will be assessed in the context of all the other diagnostic information that is available at the time point of testing.