?jirovecii or with polymerase chain reaction; alternatively, the detection of P.?jirovecii could have been achieved by histopathology in lung biopsy or autopsy specimens. Infants with primary P.?jirovecii lung infection were also included as cases. Cases diagnosed with probable PCP based on clinical and radiological findings alone were excluded. Controls needed to be patients with diagnoses other than PCP (such as patients with other respiratory infections/diseases Evodiamine and patients with conditions rendering them at risk for PCP or an invasive fungal infection). Patients with documented invasive fungal infections and healthy controls were excluded. If a study did not report specific data to
allow for the exclusion of the above two patient groups, it was included only if the patients Epigenetics Compound Library screening in these groups constituted <25% of the total control group. Studies that provided BDG diagnostic data that could not make mathematical sense according to known mathematical formulas were excluded. Articles written in languages other than English, Spanish, French, German or Italian were also excluded. From each of the included studies we extracted data on study design, the characteristics of the patient groups<br>
that were of interest to our meta-analysis, the criteria for the diagnosis of PCP, the strategy of BDG sampling, the criteria used for the definition of a positive test result, the methodology of BDG testing, and whether or not antimicrobial prophylaxis for PCP had been administered. We also extracted BDG diagnostic data, including the test cut-off level and the number of patients with true/false positive and true/false negative BDG results.
If the actual numbers for any of the above patient categories were not directly provided, we calculated BMS-777607 chemical structure these numbers from data on sensitivity/specificity or positive/negative predictive value using common mathematical formulas. If diagnostic data for more than one cut-off level were reported, we included data on the cut-off level that was closer to the one approved for each BDG assay. We carried out a meta-analysis of the diagnostic accuracy of BDG using a statistical model of bivariate meta-analysis of sensitivity and specificity [11,12]. We also calculated the positive/negative likelihood ratio (the ratio of the probabilities that the test will be positive/negative in cases with PCP vs. those without PCP) and the diagnostic odds ratio (which can be expressed as the positive likelihood ratio/negative likelihood ratio) [13]. We constructed a hierarchical summary receiver operating characteristics (HSROC) curve [11]. We assessed the presence of between-studies statistical heterogeneity using the chi-squared test [14]. A p value <0.1 for the chi-squared test indicated the presence of statistical heterogeneity. We also assessed the presence of between-studies heterogeneity by visual inspection of the ROC plane [15]. For all analyses performed, we used the midas module in Stata software v. 10 [16].</div>
allow for the exclusion of the above two patient groups, it was included only if the patients Epigenetics Compound Library screening in these groups constituted <25% of the total control group. Studies that provided BDG diagnostic data that could not make mathematical sense according to known mathematical formulas were excluded. Articles written in languages other than English, Spanish, French, German or Italian were also excluded. From each of the included studies we extracted data on study design, the characteristics of the patient groups<br>
that were of interest to our meta-analysis, the criteria for the diagnosis of PCP, the strategy of BDG sampling, the criteria used for the definition of a positive test result, the methodology of BDG testing, and whether or not antimicrobial prophylaxis for PCP had been administered. We also extracted BDG diagnostic data, including the test cut-off level and the number of patients with true/false positive and true/false negative BDG results.
If the actual numbers for any of the above patient categories were not directly provided, we calculated BMS-777607 chemical structure these numbers from data on sensitivity/specificity or positive/negative predictive value using common mathematical formulas. If diagnostic data for more than one cut-off level were reported, we included data on the cut-off level that was closer to the one approved for each BDG assay. We carried out a meta-analysis of the diagnostic accuracy of BDG using a statistical model of bivariate meta-analysis of sensitivity and specificity [11,12]. We also calculated the positive/negative likelihood ratio (the ratio of the probabilities that the test will be positive/negative in cases with PCP vs. those without PCP) and the diagnostic odds ratio (which can be expressed as the positive likelihood ratio/negative likelihood ratio) [13]. We constructed a hierarchical summary receiver operating characteristics (HSROC) curve [11]. We assessed the presence of between-studies statistical heterogeneity using the chi-squared test [14]. A p value <0.1 for the chi-squared test indicated the presence of statistical heterogeneity. We also assessed the presence of between-studies heterogeneity by visual inspection of the ROC plane [15]. For all analyses performed, we used the midas module in Stata software v. 10 [16].</div>