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Statistical methods Different cut-off values were evaluated in a simulation to determine their effects on the sensitivity (Se r ) and specificities (Sp r & Sp) of the test, The R statistical software (R version, 2000. ,
was plotted from these PPD Se r and Sp values (Figure 1a) The optimal PPD Se r (93% [84-98]) and PPD Sp (98.0% [96.3-99.0]) were obtained when the cut-off is about 0, p.2 ,
was plotted from these R Se r and Sp values (Figure 1b) The optimal R Se r (97% [89-100]) and R Sp (95.9% [93.8-97.5]) were obtained when the cut-off is about 0, p.1 ,
)] obtained were estimated at 100% [99.2-100] and 93, pp.9-91 ,
was plotted from these PPD Se r and Sp r values (Figure 1c) The optimal PPD Se r (83% [72-92]) and PPD Sp r (75.5% [71.7-79.0]) were obtained when the cut-off is about 0, p.5 ,
for different cut-off values obtained from the Se r study, are given in Table 1b. The R Sp r figures, for different cut-off values obtained from the Sp r study, are also given in Table 1b. The results, presented in Table 1b, show that R is more specific than sensitive (cut-off at 0.04, 80% [68-89] for R Se r and 93 ,
was plotted from these R Se r and Sp r values (Figure 1d) The optimal R Se r (87% [75-94]) and R Sp r (90, p.7 ,
s OD PC values are generally too high (average value about 2.5) and thus no longer corresponding to the dose-response zone. It is thus recommended for subsequent studies to dilute the kit's positive control so as to obtain OD PC values in the linear zone which are constant for each batch ,
a herd considered free of bTB for several years and presenting no other epidemiological link with other infected herds, or a herd from a bTB-free zone, specificity should be favored rather than sensitivity. The PPD?R interpretation would thus be more suitable ,
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