Short communication: Model for metritis severity predicts that disease misclassification underestimates projected milk production losses

Abstract

The objective of this research was to determine the effect of disease misclassification on the estimated effect of metritis on milk production. Misclassification introduces bias that usually results in an underestimation of the association between exposure (disease) and the outcome of interest (milk production). This distorted measure of association results from the comparison of an affected population (some of which may not truly be affected) to a nonaffected population (which often includes affected subjects that are unidentified). A convenience sample of DairyComp305 (Valley Agricultural Software, Tulare, CA) data representing 1 yr of calvings (n = 3,277) from 1 Midwestern Holstein herd was used. This herd was chosen because of its ongoing efforts to consistently and completely record all clinical diseases, including the incidence of both mild and severe metritis cases. Metritis was defined as the presence of a flaccid uterus containing fetid fluids or a foul watery discharge within 14 d of calving. Cows that appeared clinically normal other than the discharge were considered mild and those with systemic signs of disease were classified as severe. The original data set included metritis recorded as mild, severe, or not recorded (NR), where no metritis was observed, and was considered to contain the metritis true severity (TrS). First, to evaluate the effect of misclassification bias, we retrospectively randomized 45% of mild metritis to be classified as NR to simulate inconsistent disease recording (IR); then, in a separate model, all mild metritis cases were changed to NR to simulate a situation of very poor disease recording (PR), where only the most severe cases are recorded. The TrS, IR, and PR data sets were analyzed separately in JMP (SAS Institute Inc., Cary, NC). An ANOVA was conducted for second test 305-d mature-equivalent milk projection (2nd305ME), and nonsignificant variables were removed, but the variable metritis was forced into all models. Based upon the TrS model, adjusting for effects of lactation group, month of calving, dystocia, twins, retained placenta, early-lactation mastitis, displaced abomasum, and significant interactions, a case of mild metritis was associated with 384 kg less 2nd305ME and a case of severe metritis was associated with 847 kg less 2nd305ME compared with no metritis. For the IR model, a case of mild metritis was associated with 315 kg less 2nd305ME and a case of severe metritis was associated with 758 kg less 2nd305ME compared with no metritis. For the PR model, severe metritis was associated with 680 kg less 2nd305ME compared with NR. The IR and PR models underestimated 2nd305ME loss for severe metritis cases by 89 and 166 kg/cow, and resulted in 180,441 and 330,256 kg of total milk loss unaccounted for at the herd level, respectively, compared with TrS. Overall, misclassification of metritis cases results in greater bias and largely underestimates the true association between metritis and the consequence costs of the disease.