Economic comparison between ceftiofur-treated and nontreated dairy cows with metritis

Randomized clinical trial of ketoprofen or ceftiofur for treatment of metritis in dairy cows

Our objectives were to compare the efficacy of ketoprofen or ceftiofur for treatment of metritis in dairy cows considering subsequent health, production, and reproduction. Cows from 2 commercial dairy farms in Ontario, Canada were examined with a Metricheck device 3 times per week from 2 to 14 d in milk (DIM). Cows with metritis (fetid vaginal discharge; n = 193) were blocked by parity and fever (rectal temperature ≥39.5°C or <39.5°C) and within each block per farm, randomly assigned to receive 3 mg/kg BW of ketoprofen (KET) or 2.2 mg/kg of ceftiofur hydrochloride (CEF), once a day for 3 d. Day of enrollment was considered study d 0. Rectal temperature and attitude were evaluated in cows with metritis on study d 0, 3, 4, 7, 10, and 13, and vaginal discharge was evaluated on study d 4, 7, 10, and 13. Body condition was scored at enrollment and 35 DIM, and serum concentration of haptoglobin was measured at d 0, 2, 4, and 7. Cows with rectal temperature ≥39.5°C or a depressed attitude on d 3 were classified as clinical failure and received treatment with ceftiofur for 3 d (KET), or 2 additional days (CEF), to a maximum of 5 d of treatment with ceftiofur. At 35 ± 3 DIM cows were examined for uterine involution by transrectal palpation, purulent vaginal discharge (PVD) by Metricheck, and endometritis by endometrial cytology. Time to onset of cyclicity was assessed by serum progesterone (P4) measurements at 28, 42, and 56 DIM. Contemporary cows from the same farms without metritis (NOMET; n = 1,043) were used for comparison. Data were analyzed with mixed linear or logistic regression or Cox's proportional hazard models, including herd as a random effect. The proportion of clinical resolution of metritis on d 3 (96% vs. 92%), of cows with fever (from d 3 to d 13 after enrollment) or fetid discharge (from d 4 to d 13 after enrollment), and the number of medical treatments (3.1 vs. 3.3) were not different between CEF and KET, respectively. Cows in KET received fewer antibiotic treatments than cows in CEF (0.3 vs. 3.1). Uterine involution, the prevalence of PVD (50% vs. 47%) and subclinical endometritis (6.6% vs. 4.3%), and the proportion of cyclic cows (82% vs. 86%) did not differ between CEF and KET. Cows in KET had greater serum haptoglobin concentration from d 2 to 7 after enrollment. The incidence of mastitis, lameness, or displaced abomasum to 60 DIM and subclinical ketosis to 21 DIM did not differ among CEF, KET, and NOMET. There were no differences in median days to first AI (CEF = 68 d; 95% CI: 65-70; KET = 69 d; 95% CI: 68-72; NOMET = 69 d; 95% CI: 68-70), and median days to pregnancy (CEF = 118 d; 95% CI: 92-145; KET = 113 d; 95% CI: 90-135; NOMET = 105 d; 95% CI: 101-109), pregnancy at first AI at 33 d after insemination (CEF = 42%; KET = 41%; NOMET = 41%), pregnancy loss after first AI (CEF = 8%; KET = 11%; NOMET = 8%), hazard of pregnancy or hazard of culling up to 300 DIM. Milk yield was not different between CEF and KET during the first 10 weeks, but lesser in KET at wk 2 and 4 and CEF at wk 2, 4, and 6 than in NOMET. In this pilot-scale study, given early detection, we did not detect differences in subsequent health, milk yield, or reproductive performance in cows with metritis initially treated for 3 d with CEF or KET. Additional, larger studies are warranted.

A sensitive lateral flow immunoassay relying on time-resolved fluorescent microspheres immune probe for determination of ceftiofur and its metabolite

Ceftiofur (CEF) is an antimicrobial agent with high efficiency and low toxicity, desfuroylceftiofur is its main metabolite, but they are also have potential harm to human health. In this study, ceftiofur was combined with carrier proteins to get artificial antigens. A specific antibody (pAb) against CEF and desfuroylceftiofur was prepared. A sensitive and rapid paper-based sensor relying on time-resolved fluorescent microspheres (TRFMs) immune probes was developed, which were time-resolved fluorescent immunochromatographic strips (TRFMs-LFIA). The concentrations of T line and C line, activated pH, antibody volume and probe volume were optimized. Quantitative limits of detection (qLODs) of TRFMs-LFIA for CEF and desfuroylceftiofur were 0.97 ng/mL and 0.41 ng/mL, respectively. And 50 % inhibiting concentrations (IC50) were 12.92 ng/mL and 12.58 ng/mL, respectively. Pretreatment procedures of real samples were simple and rapid. Detection time of TRFMs-LFIA strip was 15 min. Qualitative analysis of CEF and desfuroylceftiofur was achieved under a UV light, quantitative analysis was implemented with a fluorescent immunoassay analyzer. The average recovery rates ranged from 91.4 % to 107.7 % and corresponding coefficients of variation (CV) was 1.5%-9.7 %. Concentration levels of artificially-spiked samples were measured by TRFMs-LFIA and compared with detection results of High performance liquid chromatography (HPLC), which showed a good accordance. These results indicated that the proposed assay can provide an effective strategy for on-site detection of CEF and desfuroylceftiofur simultaneously.

A randomized controlled trial evaluating the efficacy of systemic ceftiofur administration for metritis therapy in dairy cows and the effect of metritis cure on economically important outcomes

The main objective of this study was to evaluate the effect of ceftiofur on metritis cure, milk yield, reproductive performance, and culling up to 300 DIM. The secondary objective was to evaluate the effect of metritis cure at 5 (ECURE) and 14 (LCURE) d after diagnosis on milk production, reproduction, and culling. A total of 422 Holstein cows diagnosed with metritis from 4 herds located in TX, CA, and FL were enrolled in a randomized clinical trial. Cows diagnosed with metritis (fetid, watery, reddish/brownish uterine discharge) were blocked by herd and parity and were randomly allocated to receive systemic administration of ceftiofur (CEF) or to remain untreated (CON). In addition, 399 non-metritic cows (NMET) were included for comparison purposes. Metritis cure was evaluated at 5 and 14 d after diagnosis and was defined as the absence of metritis clinical signs. Logistic regression models were fitted to the data to assess the effect of treatment on metritis cure. Milk yield was analyzed using a mixed linear model, while logistic regression, Cox proportional hazard and Kaplan-Meier survival analysis models were fitted to culling and reproduction data. Cows treated with CEF had 1.86 (95% CI: 1.22 - 2.81) and 1.68 (95% CI: 1.02 - 2.75) greater odds of being cured than CON cows at 5 and 14 d after diagnosis, respectively. No effect of CEF was observed for milk yield; however, NMET cows had greater milk yield compared with metritic cows (CEF = 36.0, 95% CI = 33.8 - 38.1; CON = 36.1, 95% CI = 33.9 - 38.2; NMET = 36.9 kg/d, 95% CI = 34.8 - 39.4). Likewise, no effect of CEF was observed on reproductive performance and culling. Nonetheless, the likelihood of conceiving for NMET cows was 1.72 (95% CI = 1.41 - 2.12) and 1.64 (95% CI = 1.33 - 2.00) times greater than for CEF and CON cows, respectively. Ceftiofur-treated and CON cows had 2.93 (95% CI = 1.90 - 4.51) and 2.37 (95% CI = 1.51 - 3.71) greater hazard of culling compared with NMET, respectively. Regardless of treatment, no differences between ECURE and LCURE were observed on milk yield, reproduction, and culling throughout the entire lactation, but cows that cured at 5 or 14 d after diagnosis had greater milk production in the first 60 DIM compared with cows that did not cure (NCURE). Cows in ECURE and LCURE also had a 1.59 (95% CI = 1.16 - 2.16) and 1.49 (95% CI = 1.08 - 2.05) greater hazard of pregnancy and 0.43 (95% CI = 0.26-0.71) and 0.56 (95% CI = 0.34-0.92) hazard of culling compared with NCURE. Ceftiofur therapy increased metritis cure, but benefits to productivity and longevity were not observed. Also, cows that fail to cure have impaired lactation performance, but no differences regarding timing of cure were observed.

Evaluating differences in milk production, reproductive performance, and survival associated with vaginal discharge characteristics and fever in postpartum dairy cows

The objective was to assess differences in productive and reproductive performance, and survival associated with vaginal discharge characteristics and fever in postpartum dairy cows located in Western and Southern states of the U.S.A. This retrospective cohort study included data from 3 experiments conducted in 9 dairies. Vaginal discharge was evaluated twice within 12 DIM and scored on a 5-point scale. The highest score observed for each cow was used for group assignment (VD group) as follows: VD 1 and 2 (VD 1/2; n = 1,174) = clear mucus/lochia with or without flecks of pus; VD 3 (n = 1,802) = mucopurulent with < 50% pus; VD 4 (n = 1,643) = mucopurulent with ≥50% of pus or non-fetid reddish/brownish mucous, n = 1,643; VD 5 = fetid, watery, and reddish/brownish, n = 1,800. All VD 5 cows received treatment according to each herd's protocol. Rectal temperature was assessed in a subset of VD 5 cows, and subsequently divided into Fever (rectal temperature ≥39.5°C; n = 334) and NoFever (n = 558) groups. A smaller proportion of cows with VD 5 (67.6%) resumed ovarian cyclicity compared with VD 1/2 (76.2%) and VD 4 (72.9%) cows; however, a similar proportion of VD5 and VD 3 (72.6%) cows resumed ovarian cyclicity. A smaller proportion of VD 5 (85.8%) cows received at least one artificial insemination (AI) compared with VD 1/2 (91.5%), VD 3 (91.0%), or VD 4 (91.6%) cows. Although we did not detect differences in pregnancy at first AI according to VD, fewer cows with VD 5 (64.4%) were pregnant at 300 DIM than cows with VD 1/2 (76.5%), VD 3 (76.2%), or VD 4 (74.7%). Hazard of pregnancy by 300 DIM was smaller for VD 5 compared with VD 1/2, VD 3, or VD 4 cows. A greater proportion of VD 5 cows were removed from the herd within 300 DIM compared with other VD groups. There was 760 kg lesser milk production within 300 DIM for VD 5 compared with VD 2, VD 3, and VD 4, whereas VD 2, VD 3, and VD 4 had similar milk production. We did not detect an association between fever at diagnosis of VD 5 and reproductive performance or milk production. A greater proportion of VD 5 cows without fever were removed from the herd by 300 DIM compared with VD 5 cows with fever. Differences in productive and reproductive performance, and removal of the herd were restricted to fetid, watery, and reddish/brownish vaginal discharge, which was independent of fever.

Predictive models for metritis cure using farm-collected data, metabolic and inflammation biomarkers, and hemogram variables measured at diagnosis

Our objective was to evaluate the accuracy of predictive models for metritis spontaneous cure (SC) and cure among ceftiofur-treated cows using farm collected data only, and with the addition of hemogram variables and circulating concentration of metabolites, minerals, and biomarkers of inflammation measured at time of diagnosis. Data related to parity, calving related issues, body condition score (BCS), rectal temperature (RT), and days in milk (DIM) at metritis diagnosis were collected from a randomized clinical trial that included 412 metritic cows from 4 herds in TX, CA, and FL. Metritis was defined as the presence of red-brownish, watery, and fetid vaginal discharge, while cure was defined as the absence of metritis 14 d after initial diagnosis. Cows were randomly allocated to receive systemic ceftiofur therapy (2 subcutaneous doses of 6.6 mg/kg of ceftiofur crystalline-free acid on the day of diagnosis and 3 d later; CEF) or to remain untreated (CON). At enrollment (day of metritis diagnosis), blood samples were collected and submitted to cell blood count (CBC) and processed for the measurement of 13 minerals and biomarkers of metabolism and inflammation (BM). Univariable analysis to evaluate the association of farm collected data and blood assessed variables with metritis cure were performed, and variables with P ≤ 0.20 were offered to multivariable logistic regression models and retained if P ≤ 0.15. The area under the curve (AUC) for models predicting SC using farm data only and farm + BM, was 0.70 and 0.76 respectively. Cell blood count variables were not retained in the models for SC. For models predicting cure among CEF cows, the AUC was 0.75, 0.77, 0.80, and 0.80 for models using farm data only, farm + CBC, farm + BM, and farm + CBC + BM, respectively. Predictive models of metritis cure had fair accuracy, with SC models being less accurate than models predictive of cure among CEF cows. Additionally, adding BM variables marginally improved the accuracy of models using farm collected data, while CBC data did not improve the accuracy of predictive models.

Application of behavior data to predictive exploratory models of metritis self-cure and treatment failure in dairy cows

The objective was to evaluate the performance of exploratory models containing routinely available on-farm data, behavior data, and the combination of both to predict metritis self-cure (SC) and treatment failure (TF). Holstein cows (n = 1,061) were fitted with a collar-mounted automated- health monitoring device (AHMD) from -21 ± 3 to 60 ± 3 d relative to calving to monitor rumination and activity. Cows were examined for diagnosis of metritis at 4 ± 1, 7 ± 1, and 9 ± 1 DIM. Cows diagnosed with metritis (n = 132), characterized by watery, fetid, reddish/brownish vaginal discharge (VD) were randomly allocated to one of 2 treatments: Control (CON; n = 62) - no treatment at the time of metritis diagnosis (d 0); Ceftiofur (CEF; n = 70) - subcutaneous injection of 6.6 mg/kg of ceftiofur crystalline-free acid on d 0 and 3 relative to diagnosis. Cure was determined 12 d after diagnosis and was considered when VD became mucoid and not fetid. Cows in CON were used to determine SC and cows in CEF were used to determine TF. Univariable analyses were performed using farm-collected data (parity, calving season, calving-related disorders, body condition score, rectal temperature, and days in milk at metritis diagnosis) and behavior data (i.e., daily averages of rumination, activity generated by AHMD, and derived variables) to assess their association with metritis SC or TF. Variables with a P ≤ 0.20 were included in the multivariable logistic regression exploratory models. To predict SC, the area under the curve (AUC) for the exploratory model containing only data routinely available on-farm was 0.75. The final exploratory model to predict SC combining routinely available on-farm data and behavior data increased the AUC to 0.87, sensitivity (Se) 87% and specificity (Sp) 71%. To predict TF, the AUC for the exploratory model containing only data routinely available on-farm was 0.90. The final exploratory model combining routinely available on-farm data and behavior data increased the AUC to 0.93, Se of 93% and Sp of 82%. Cross-validation analysis revealed that generalizability of the exploratory models was poor, which indicates that the findings are applicable to the conditions of the present exploratory study. In summary, the addition of behavior data contributed to increasing the prediction of SC and TF. Developing and validating accurate prediction models for SC could lead to a reduction in antimicrobial use, whereas accurate prediction of cows that would have TF may allow for better management decisions.

Uterine Disease in Dairy Cows: A Comprehensive Review Highlighting New Research Areas

Uterine disease is an intensely studied part of dairy cattle health management as it heavily affects many commercial dairy farms and has serious economic consequences. Forms of the disease, pathophysiology, pathogens involved and the effects of uterine disease on the health and performance of cows have already been well described by various authors. Lately, researchers' attention has shifted towards the healthy microbiome of the uterus and the vagina to put emphasis on prevention rather than treatment. This aligns with the growing demand to reduce the use of antibiotics or-whenever possible-replace them with alternative treatment options in farm animal medicine. This review provides a comprehensive summary of the last 20 years of uterine disease research and highlights promising new areas for future studies.

Effects of targeted clinical examination based on alerts from automated health monitoring systems on herd health and performance of lactating dairy cows

Our objectives were to compare the proportion of lactating dairy cows diagnosed with health disorders (HD) and herd performance when using a health monitoring program designed to rely primarily but not exclusively on alerts from automated health monitoring (AHM) systems or a health monitoring program based primarily on systematic clinical examinations, milk yield monitoring, and visual observation of cows. In a clinical trial, at ∼30 d before expected parturition, nulliparous and parous Holstein cows, stratified by parity and days in gestation, were randomly assigned to the high-intensity clinical monitoring (HIC-M; n = 625) or automated monitoring (AUT-M; n = 624) treatment. Cows were fitted with a neck-attached rumination and physical activity monitoring tag, and individual daily milk yield data were collected from parlor milk meters. For cows in HIC-M, clinical examination was conducted daily until 10 d in milk (DIM) and then in response to milk yield reduction alerts or visual observation of clinical signs of HD over the course of 21 DIM. For cows in AUT-M, clinical examination until 21 DIM was because of health index (HI) score alerts and reduced milk yield alerts. The HI score alerts used were generated based on the manufacturer's settings for the system for the last 2-h period before cows were selected for examination. Visual observation of clinical signs of HD was used for identifying cows potentially missed by automated alerts. Binomial and quantitative data were analyzed by logistic regression and ANOVA with repeated measures, respectively. The percentage of cows diagnosed with at least 1 HD during the experimental treatments risk period tended to be greater and the incidence rate ratio of HD diagnosed was greater in the HIC-M than in the AUT-M treatment. We found no difference between treatments for cows that exited the herd up to 60 or 150 DIM, but more cows tended to exit the herd from 61 to 150 DIM in the HIC-M than in the AUT-M treatment. No differences were detectable between treatments in daily or total milk yield to 21 DIM or in weekly mean milk yield and total milk yield to 150 DIM. More cows were inseminated in estrus for first service if in the HIC-M treatment and had no HD diagnosed than if in the HIC-M treatment but with HD diagnosed, or in the AUT-M treatment and had no HD diagnosed. Cows in the AUT-M treatment with HD diagnosed did not differ from other groups. No differences between treatments were observed in pregnancies per artificial insemination or pregnancy loss for first service. Despite a reduction in the risk of diagnosis of HD, no evidence indicated that a health monitoring program that relied on AHM system alerts to select cows for clinical examination reduced herd performance compared with a more intensive program that included systematic clinical examinations of all cows for the first 10 DIM, reduced milk yield alerts, and visual observation. However, to obtain the same herd performance as with the HIC-M treatment, the AUT-M treatment required use of visual observation. In conclusion, a health monitoring program designed to rely primarily on targeted clinical examination based on alerts from automated health monitoring systems might be a feasible alternative to programs that rely more on clinical examination, provided that visual observation is used to identify cows not detected by automated alerts.

Review: Postpartum reproductive disease and fertility in dairy cows

This paper reviews recent data and concepts on metritis, purulent vaginal discharge (PVD), and endometritis in dairy cows and the ways in which these diseases affect reproductive performance. Metritis is characterized by fetid discharge from the uterus, with or without fever. Purulent vaginal discharge describes exudate that is >50% pus that may be attributable to uterine infection or cervicitis. Endometritis is inflammation of the uterus diagnosed by endometrial cytology with a proportion of neutrophils (typically ≥5%) that is associated with impaired fertility. Metritis and PVD are associated with uterine bacterial dysbiosis: changes in the microbiota to lesser diversity and greater abundance of pathogens, especially Gram-negative anaerobic bacteria, and Trueperella pyogenes in the case of PVD. Metritis is justifiably treated with approved antibiotics but criteria for more selective treatment without loss of performance are emerging. Purulent vaginal discharge is not synonymous with clinical endometritis, and greater precision in terminology is warranted. PVD is likely under-diagnosed and represents an opportunity for improved management in many herds. Endometritis seems in many cases to reflect persistent, dysregulated inflammation, for which the inciting cause is unclear. Postpartum uterine infection and inflammation have harmful effects on oocytes, embryo development, and the endometrium for at least three months, even if the disease is apparently resolved. Emerging concepts of the resolution and regulation of inflammation are promising for the improvement of prevention and therapy of endometritis.

Differences in uterine and serum metabolome associated with metritis in dairy cows

Objectives were to evaluate differences in the uterine and serum metabolomes associated with metritis in dairy cows. Vaginal discharge was evaluated using a Metricheck device (Simcro) at 5, 7, and 11 d in milk (DIM; herd 1) or 4, 6, 8, 10, and 12 DIM (herd 2). Cows with reddish or brownish, watery, and fetid discharge were diagnosed with metritis (n = 24). Cows with metritis were paired with herdmates without metritis (i.e., clear mucous vaginal discharge or clear lochia with ≤50% of pus) based on DIM and parity (n = 24). Day of metritis diagnosis was considered study d 0. All cows diagnosed with metritis received antimicrobial therapy. The metabolome of uterine lavage collected on d 0 and 5, and serum samples collected on d 0 were evaluated using untargeted gas chromatography time-of-flight mass spectrometry. Normalized data were subjected to multivariate canonical analysis of population using the MultBiplotR and MixOmics packages in R Studio. Univariate analyses including t-test, principal component analyses, partial least squares discriminant analyses, and pathway analyses were conducted using Metaboanalyst. The uterine metabolome differed between cows with and without metritis on d 0. Differences in the uterine metabolome associated with metritis on d 0 were related to the metabolism of butanoate, amino acids (i.e., glycine, serine, threonine, alanine, aspartate, and glutamate), glycolysis and gluconeogenesis, and the tricarboxylic acid cycle. No differences in the serum metabolome were observed between cows diagnosed with metritis and counterparts without metritis on d 0. Similarly, no differences in uterine metabolome were observed between cows with metritis and counterparts not diagnosed with metritis on d 5. These results indicate that the establishment of metritis in dairy cows is associated with local disturbances in amino acid, lipid, and carbohydrate metabolism in the uterus. The lack of differences in the uterine metabolome on d 5 indicates that processes implicated with the disease are reestablished by d 5 after diagnosis and treatment.

Antimicrobial resistance in dairy slurry tanks: A critical point for measurement and control

Waste from dairy production is one of the largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs) in many parts of the world. However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with > 99 % reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for measurement and control of AMR, and that actions to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

Behavioral changes of metritic primiparous cows treated with chitosan microparticles or ceftiofur

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Chitosan microparticles negatively affected the rumination and activity of cows with metritis.

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The negative effect of CM on rumination and activity indicates a negative systemic effect that may be associated with increased inflammation in the uterus.

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Regardless of treatment, cows with metritis had decreased rumination and activity starting 5 days before diagnosis until at least 2 days after diagnosis.

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The automated health-monitoring device was a useful tool to evaluate rumination and activity patterns after metritis treatment.

The main objective was to characterize behavioral changes in metritic primiparous cows treated with chitosan microparticles (CM) or ceftiofur (CEF). A secondary objective was to compare behavioral patterns of metritic cows with nonmetritic (NMET) cows. Nulliparous Holstein cows (n = 311) were fitted with a neck-mounted automated health-monitoring device (AHMD) from −21 to 60 d relative to calving. Cows diagnosed with metritis (d 0), characterized by watery, fetid, red-brownish uterine discharge within 21 d in milk were assigned randomly to CM (n = 45), intrauterine infusion of 24 g of CM dissolved in 40 mL of sterile distilled water on d 0, 2, and 4; CEF (n = 47), subcutaneous injection of 6.6 mg/kg ceftiofur crystalline-free acid on d 0 and 3; and control (CON; n = 39), no treatment. For comparison, NMET cows (n = 180) were matched with metritic cows according to age at calving and calving date. Postdiagnosis, there was an effect of treatment and an interaction between treatment and time on rumination and activity. The interaction showed that CM had lesser rumination than CEF from d 1 to 11, d 18, and d 20; CM had lesser rumination than CON from d 2 to 8; and CEF was not different from CON. The interaction showed that CM had lesser activity than CON on d 2, from d 6 to 11, and d 13 to 14; CM was not different from CEF; and CEF had lesser activity than CON on d 8, 9, 13, and 14. Prediagnosis, cows in CM, CEF, and CON had lesser rumination and activity than cows in NMET. Postdiagnosis, cows in CM, CEF, and CON had lesser rumination than NMET from d 0 to 2 and had lesser activity than NMET from d 0 to 5. In summary, CM decreased rumination and activity compared with CON, which indicates a negative systemic effect of CM. This may be associated with exacerbated inflammation in the uterus. Additionally, metritic cows had decreased rumination and activity prediagnosis, which may allow for the use of AHMD for metritis diagnosis.

Integration of statistical inferences and machine learning algorithms for prediction of metritis cure in dairy cows

The study's objectives were to identify cow-level and environmental factors associated with metritis cure to predict metritis cure using traditional statistics and machine learning algorithms. The data set used was from a previous study comparing the efficacy of different therapies and self-cure for metritis. Metritis was defined as fetid, watery, reddish-brownish discharge, with or without fever. Cure was defined as an absence of metritis signs 12 d after diagnosis. Cows were randomly allocated to receive a subcutaneous injection of 6.6 mg/kg of ceftiofur crystalline-free acid (Excede, Zoetis) at the day of diagnosis and 3 d later (n = 275); and no treatment at the time of metritis diagnosis (n = 275). The variables days in milk (DIM) at metritis diagnosis, treatment, season of the metritis diagnosis, month of metritis diagnostic, number of lactation, parity, calving score, dystocia, retained fetal membranes, body condition score at d 5 postpartum, vulvovaginal laceration score, the rectal temperature at the metritis diagnosis, fever at diagnosis, milk production from the day before to metritis diagnosis, and milk production slope up to 5, 7, and 9 DIM were offered to univariate logistic regression. Variables included in the multivariable logistic regression model were selected from the univariate analysis according to P-value. Variables were offered to the model to assess the association between these factors and metritis cure. Additionally, the univariate logistic regression variables were offered to a recursive feature elimination to find the optimal subset of features for a machine learning algorithms analysis. Cows without vulvovaginal laceration had 1.91 higher odds of curing of metritis than cows with vulvovaginal laceration. Cows that developed metritis at >7 DIM had 2.09 higher odds of being cured than cows that developed metritis at ≤7 DIM. For rectal temperature, each degree Celsius above 39.4°C led to lower odds to be cured than cows with rectal temperature ≤39.4°C. Furthermore, milk production slope and milk production difference from the day before to the metritis diagnosis were essential variables to predict metritis cure. Cows that had reduced milk production from the day before to the metritis diagnosis had lower odds to be cured than cows with moderate milk production increase. The results from the multivariable logistic regression and receiver operating characteristic analysis indicated that cows developing metritis at >7 DIM, with increase in milk production, and with a rectal temperature ≤39.40°C had increased likelihood of cure of metritis with an accuracy of 75%. The machine learning analysis showed that in addition to these variables, calving-related disorders, season, and month of metritis event were needed to predict whether the cow will cure or not from metritis with an accuracy ≥70% and F1 score (harmonic mean between precision and recall) ≥0.78. Although machine learning algorithms are acknowledged as powerful tools for predictive classification, the current study was unable to replicate its potential benefits. More research is needed to optimize predictive models of metritis cure.