The studies are ordered by ascending cutoff (in g/dL), sensitivity, and study name. To determine the accuracy of REF and BRIX for assessment of inadequate Carbendazim transfer of passive immunity (ITPI) in calves. Design Systematic review and meta\analysis of diagnostic accuracy studies. Methods Databases (PubMed and CAB Abstract, Searchable Proceedings of Animal Science) and Google Scholar were searched for relevant studies. Studies were eligible if the accuracy (sensitivity and specificity) of REF or BRIX was decided using direct measurement of IgG by RID or turbidimetry as the reference standard. The study populace included calves 14 days old that were fed with natural colostrum (colostrum replacement products were excluded). Quality assessment was performed by the QUADAS\2 tool. Hierarchical models were used for meta\analysis. Results From 1,291 recommendations identified, 13 studies of 3,788 calves were included. Of these, 11 studies evaluated REF and 5 studies evaluated BRIX. The median (range) prevalence of ITPI (defined as calves with IgG 10 g/L by RID or TIA) was 21% (1.3C56%). Risk of bias and applicability concerns were generally low or unclear. For REF, summary estimates were obtained for 2 different cutoffs: 5.2 g/dL (6 studies) and 5.5 g/dL (5 studies). For the 5.2 g/dL cutoff, the summary sensitivity (95% CI) and specificity (95% CI) were 76.1% (63.8C85.2%) and 89.3% (82.3C93.7%), and 88.2% (80.2C93.3%) and 77.9% (74.5C81.0%) for the 5.5 g/dL cutoff. Due to the low number of studies using the same cutoffs, summary estimates could not be obtained for BRIX. Conclusions and Clinical Importance Despite their widespread use on dairy farms, evidence about the optimal strategy for using refractometry, including the optimal cutoff, are sparse (especially for BRIX). When using REF to rule out ITPI in herds, the 5.5 g/dL cutoff may be used whereas for ruling in ITPI, the 5.2 g/dL cutoff may be used. +?is the proportion of test positives, and is the number in group in the = 0 and is coded as ?0.5. For the ITPI group, = 1 and is coded as 0.5. The implicit threshold models the trade\off between true and false\positive fractions, while (accuracy parameter) steps the difference between the true and false\positive fractions. Both and are modeled as random effects with impartial normal distributions. The shape parameter, , allows for asymmetry in the shape of the summary receiver Carbendazim operating characteristic (SROC) curve. We chose the HSROC model so that we could estimate SROC curves because we expected studies to use different cutoffs. For this analysis, if a study reported more than 1 cutoff, we randomly selected 1 cutoff so that only a pair of sensitivity and specificity was included from each study. Only studies that defined ITPI using a cutoff of 10 g/L for Ctsd the reference standard were included in all meta\analyses. The HSROC model was fitted using the NLMIXED procedure in the SASb software package.24 As several cutoffs have been recommended depending on the objective of maximizing sensitivity or specificity,1, 10 we also estimated summary estimates of sensitivity and specificity at these cutoffs (using 5.0C5.2 g/dL and 5.5 g/dL for REF, and 8.4% for BRIX). When analyses using the HSROC model failed to converge due to the small number of studies, because summary estimates were the focus of these analyses, we used univariate random effects logistic regression models (UREM) which are recommended when data are sparse.25 This model is a simplification of the bivariate model by assuming the covariance is zero as follows: and variance for the logit sensitivities, and mean and Carbendazim variance for the logit specificities. A binomial likelihood is used for modeling within\study variability. Heterogeneity was investigated by visual examination of forest plots and SROC plots. We planned to formally investigate heterogeneity by adding a covariate to the HSROC model.