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Untersuchungen zu einem entscheidungsbaumbasierten Verfahren des Selektiven Trockenstellens in Bayern und der Durchführung des Selektiven Trockenstellens von Tierärzten mit und ohne Integrierte Tierärztliche Bestandsbetreuung in Deutschland
Untersuchungen zu einem entscheidungsbaumbasierten Verfahren des Selektiven Trockenstellens in Bayern und der Durchführung des Selektiven Trockenstellens von Tierärzten mit und ohne Integrierte Tierärztliche Bestandsbetreuung in Deutschland
The German antibiotic resistance strategy (“DART”) has provided a legal basis for minimising the use of antibiotics and since 21th April 2021 Veterinary Herd Health Management (VHHM) has been established by law for the first time as well. Selective Dry Cow Treatment (SDCT) is one way to reduce the use of antibiotics in dairy farming and guidelines for VHHM provide for the controlled minimisation of antibiotic use on farms were VHHM is applied. In addition, there are various recommendations for the implementation of SDCT. These differ in the selection of decision criteria at herd and cow-level and/or in the different thresholds used. The aim of this dissertation project was to evaluate the implementation of SDCT and VHHM in German veterinary practices that have a focus on cattle on the one hand. For this research question a survey was used to compare and contrast veterinary practitioners that utilize VHHM in relation to SDCT with those that do not (Paper I). On the other hand, in a follow up study the 4 parameters of a decision tree based procedure for SDCT with no negative impact on udder health, were analyzed for their efficacy in detecting cows for dry cow treatment (DCT, use of intramammary antimicrobials). These were clinical mastitis history (during lactation), somatic cell count of the last 3 milk yield recordings prior dry off (SCC, ≥ 200,000 cells/ml), culturing of quarter milk samples 10-14 days prior dry off (“deviate from normal” when “Major Pathogens” were detected) and California-Mastitis-Test (CMT, “positive” with grade > 1/+) at dry off. Furthermore, this study set out to review if all 4 parameters are needed for accurate decision making and whether culturing can be replaced otherwise, e.g. with information from milk yield recordings (Paper II). For study I, a survey (n = 600) was distributed to veterinary livestock practitioners at 7 advanced training courses in Germany between July 2019 and January 2020. Participation was voluntary and anonymous. Data analysis was carried out by means of descriptive statistics as well as by linear and logistic regression.The response rate was 39.3 % (n = 236). 54.2 % (n = 128) of the veterinarians reported that they conduct VHHM. Procedures for SDCT were used on farms overseen by 75.0 % (n = 177) of the vets, of these 100 (56,5 %) vets conduct VHHM whereas 69 (39.0 %) did not. Different decision criteria applied at herd (81.6 %, n = 142) and at individual cow level (97.7 %, n = 172) respectively. Milk yield recordings’ SCC, clinical mastitis history, CMT and culturing were used by 96.0 %, 86.3 %, 70.9 % and 68.6 % of the veterinarians who have overseen farms that used procedures for SDCT. A performance review of SDCT was carried out more frequently on farms of veterinarians that practice VHHM (66.0 %, n = 66) than those that do not (41.0 %, n = 28). An increase in the number of farms conducting VHHM was associated with an increase in the proportion of farms using SDCT. An increase of the probability of good udder health was associated with SDCT-farms that also apply VHHM (OR:1.025;p< 0.05). The provision of consultation for problems arising during the dry period (OR:3.639; p< 0.05), the frequency of veterinarians addressing SDCT with farmers (OR:1,595; p< 0,05) and vice versa (OR:1,538; p< 0.05), as well as frequency of consultation for drying off management (OR:1,608; p< 0.05) had an positive impact on the likelihood of SDCT being implemented on a farm and whether this process was ultimately successful. Within (the follow up) study II records of 18 Bavarian dairy farms with a defined status of udder health from 06/2015 to 08/2017 were considered. Data analysis was carried out by means of descriptive statistics, as well as by binary cost sensitive classification tree and 2 logit-models. The outcomes of the full 4-parameter decision tree were taken as ground truth for the statistical analysis. 848 drying off processes (CDO) of 739 dairy cows were included and have been treated as cross-sectional data. SCC and CMT selected 88.1 %, in combination with clinical mastitis history 95.6 % of the CDO that received DCT (n = 494). Culturing selected 4.4 % (n = 22, infected with Major Pathogens thereof 8x S.aureus) of the CDO that received DCT. The average of geometric mean SCC (within 100 d prior DO) for CDO with negative results in culturing was < 100,000 SC/ml, 100-150,000 SC/ml for CDO infected with minor pathogens, and ≥ 150,000 SC/ml for CDO infected with major pathogens (without S.aureus). Using SCC during lactation (> 200,000 SC/ml) and positive CMT at dry off to select CDO for DCT, as opposed to the decision tree, 37 CDO (4.4 %) would have been treated “incorrectly without” and 43 CDO (5.1 %) “unnecessarily with“ DCT. Modifications were identified by binary cost sensitive classification tree that would select 207/436 CDO with no growth or minor pathogens in culturing correctly (no clinical mastitis history and SCC < 200.000 SC/ml .during 3 months prior dry off). Among others these were SCC < 131.000 SC/ml within 100 d prior to dry. The best model (binary logistic regression, target value: “antibiotic dry cow treatment”, characteristics: yes/no) for grading CDO for or against DCT (CDO without clinical mastitis history and SCC <200,000 SC/ml [last 3 months prior dry off]) had metrics of AUC=0.74, Accuracy=0.78, balanced Accuracy=0.63, Sensitivity= 0.92, Specificity=0.33. Multinomial regression calculations showed that an increase in log lactation number led to a decrease in the chance of detecting minor pathogens (factor 0,327 [Minor Pathogen, CMT negative], factor 0,446 [Minor Pathogen, CMT positive]). According to available data, both VHHM and SDCT are established parts of veterinary practice in bovine care (Paper I). In practice, SDCT is partially conducted within the framework of a controlled procedure including a performance review. The implementation of VHHM has an effect on the number of farms performing SDCT as well as on udder health where VHHM and SDCT are combined on a farm. The range and frequency of consultation by veterinarians have a significant influence on a reduction of use of antibiotics by implementation of SDCT. In herds with a defined udder health status the parameters SCC, CMT and clinical mastitis history in combination are suitable selection criteria for SDCT (Paper II). When omitting culturing, lower thresholds for SCC should be considered for each farm individually to select CDO for DCT. Nonetheless, the proposed modifications using information from milk yield recording are promising and should be validated with a bigger sample size. The most accurate simplified model could not replace the full decision tree.
udder health, antibiotic reduction, dairy cows
Sonnewald-Daum, Tanja
2024
Deutsch
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Sonnewald-Daum, Tanja (2024): Untersuchungen zu einem entscheidungsbaumbasierten Verfahren des Selektiven Trockenstellens in Bayern und der Durchführung des Selektiven Trockenstellens von Tierärzten mit und ohne Integrierte Tierärztliche Bestandsbetreuung in Deutschland. Dissertation, LMU München: Tierärztliche Fakultät
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Abstract

The German antibiotic resistance strategy (“DART”) has provided a legal basis for minimising the use of antibiotics and since 21th April 2021 Veterinary Herd Health Management (VHHM) has been established by law for the first time as well. Selective Dry Cow Treatment (SDCT) is one way to reduce the use of antibiotics in dairy farming and guidelines for VHHM provide for the controlled minimisation of antibiotic use on farms were VHHM is applied. In addition, there are various recommendations for the implementation of SDCT. These differ in the selection of decision criteria at herd and cow-level and/or in the different thresholds used. The aim of this dissertation project was to evaluate the implementation of SDCT and VHHM in German veterinary practices that have a focus on cattle on the one hand. For this research question a survey was used to compare and contrast veterinary practitioners that utilize VHHM in relation to SDCT with those that do not (Paper I). On the other hand, in a follow up study the 4 parameters of a decision tree based procedure for SDCT with no negative impact on udder health, were analyzed for their efficacy in detecting cows for dry cow treatment (DCT, use of intramammary antimicrobials). These were clinical mastitis history (during lactation), somatic cell count of the last 3 milk yield recordings prior dry off (SCC, ≥ 200,000 cells/ml), culturing of quarter milk samples 10-14 days prior dry off (“deviate from normal” when “Major Pathogens” were detected) and California-Mastitis-Test (CMT, “positive” with grade > 1/+) at dry off. Furthermore, this study set out to review if all 4 parameters are needed for accurate decision making and whether culturing can be replaced otherwise, e.g. with information from milk yield recordings (Paper II). For study I, a survey (n = 600) was distributed to veterinary livestock practitioners at 7 advanced training courses in Germany between July 2019 and January 2020. Participation was voluntary and anonymous. Data analysis was carried out by means of descriptive statistics as well as by linear and logistic regression.The response rate was 39.3 % (n = 236). 54.2 % (n = 128) of the veterinarians reported that they conduct VHHM. Procedures for SDCT were used on farms overseen by 75.0 % (n = 177) of the vets, of these 100 (56,5 %) vets conduct VHHM whereas 69 (39.0 %) did not. Different decision criteria applied at herd (81.6 %, n = 142) and at individual cow level (97.7 %, n = 172) respectively. Milk yield recordings’ SCC, clinical mastitis history, CMT and culturing were used by 96.0 %, 86.3 %, 70.9 % and 68.6 % of the veterinarians who have overseen farms that used procedures for SDCT. A performance review of SDCT was carried out more frequently on farms of veterinarians that practice VHHM (66.0 %, n = 66) than those that do not (41.0 %, n = 28). An increase in the number of farms conducting VHHM was associated with an increase in the proportion of farms using SDCT. An increase of the probability of good udder health was associated with SDCT-farms that also apply VHHM (OR:1.025;p< 0.05). The provision of consultation for problems arising during the dry period (OR:3.639; p< 0.05), the frequency of veterinarians addressing SDCT with farmers (OR:1,595; p< 0,05) and vice versa (OR:1,538; p< 0.05), as well as frequency of consultation for drying off management (OR:1,608; p< 0.05) had an positive impact on the likelihood of SDCT being implemented on a farm and whether this process was ultimately successful. Within (the follow up) study II records of 18 Bavarian dairy farms with a defined status of udder health from 06/2015 to 08/2017 were considered. Data analysis was carried out by means of descriptive statistics, as well as by binary cost sensitive classification tree and 2 logit-models. The outcomes of the full 4-parameter decision tree were taken as ground truth for the statistical analysis. 848 drying off processes (CDO) of 739 dairy cows were included and have been treated as cross-sectional data. SCC and CMT selected 88.1 %, in combination with clinical mastitis history 95.6 % of the CDO that received DCT (n = 494). Culturing selected 4.4 % (n = 22, infected with Major Pathogens thereof 8x S.aureus) of the CDO that received DCT. The average of geometric mean SCC (within 100 d prior DO) for CDO with negative results in culturing was < 100,000 SC/ml, 100-150,000 SC/ml for CDO infected with minor pathogens, and ≥ 150,000 SC/ml for CDO infected with major pathogens (without S.aureus). Using SCC during lactation (> 200,000 SC/ml) and positive CMT at dry off to select CDO for DCT, as opposed to the decision tree, 37 CDO (4.4 %) would have been treated “incorrectly without” and 43 CDO (5.1 %) “unnecessarily with“ DCT. Modifications were identified by binary cost sensitive classification tree that would select 207/436 CDO with no growth or minor pathogens in culturing correctly (no clinical mastitis history and SCC < 200.000 SC/ml .during 3 months prior dry off). Among others these were SCC < 131.000 SC/ml within 100 d prior to dry. The best model (binary logistic regression, target value: “antibiotic dry cow treatment”, characteristics: yes/no) for grading CDO for or against DCT (CDO without clinical mastitis history and SCC <200,000 SC/ml [last 3 months prior dry off]) had metrics of AUC=0.74, Accuracy=0.78, balanced Accuracy=0.63, Sensitivity= 0.92, Specificity=0.33. Multinomial regression calculations showed that an increase in log lactation number led to a decrease in the chance of detecting minor pathogens (factor 0,327 [Minor Pathogen, CMT negative], factor 0,446 [Minor Pathogen, CMT positive]). According to available data, both VHHM and SDCT are established parts of veterinary practice in bovine care (Paper I). In practice, SDCT is partially conducted within the framework of a controlled procedure including a performance review. The implementation of VHHM has an effect on the number of farms performing SDCT as well as on udder health where VHHM and SDCT are combined on a farm. The range and frequency of consultation by veterinarians have a significant influence on a reduction of use of antibiotics by implementation of SDCT. In herds with a defined udder health status the parameters SCC, CMT and clinical mastitis history in combination are suitable selection criteria for SDCT (Paper II). When omitting culturing, lower thresholds for SCC should be considered for each farm individually to select CDO for DCT. Nonetheless, the proposed modifications using information from milk yield recording are promising and should be validated with a bigger sample size. The most accurate simplified model could not replace the full decision tree.