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Contrasting Treatment- and Farm-Level Metrics of Antimicrobial Use Based on Used Daily Dose vs. Defined Daily Dose for the German Antibiotics Minimization Concept

ABSTRACT: The German Antibiotics Minimization Concept defines a farm-level benchmarking process based on half-yearly treatment frequencies that applies to six animal populations for fattening: calves (≤ 8 months), cattle (> 8 months), piglets (≤ 30 kg), pigs (> 30 kg), broiler chickens, and turkeys. The treatment frequency defined in the Minimization Concept takes into account the number of animals treated, the treatment duration, and the number of active antimicrobial ingredients, for each individual treatment, and is equivalent to a treatment frequency based on the used daily dose (UDD) and the actual weight of the animals at the time of treatment. With data from the German benchmarking system for the seven half-year periods from the second semester 2014 to the end of 2017, we compared UDD-based metrics of antimicrobial use (AMU) at the treatment and the farm level with metrics based on defined daily doses for animals (DDDvet) and standardized animal weights assumed at the time most likely for treatment. We show the extent to which DDDvet-based metrics would introduce errors into the measurement of AMU at the treatment level and consequently at the farm level. To that end, we introduce the average animal daily dose ratio, an aggregate measure that quantifies how choice of antimicrobial substances, deviations of used doses from recommended doses, of recommended doses from DDDvet values, and of treatment weights from standardized weights, affect a farm's AMU metrics. Our results show that in all animal populations considered benchmarking processes would become less successful at targeting high users. This would be especially true for broiler chickens and turkeys where the relative weight gain during fattening is the largest and overdosing appears to be common practice. Therefore, in AMU monitoring systems with the purpose of benchmarking farms UDD-based metrics are preferable to DDDvet-based metrics.

SUBMITTER: Flor M

PROVIDER: S-EPMC9271936 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: The consumption of antibiotics is one of the metrics used to evaluate the impact of antimicrobial stewardship programs (ASP). The aim of this study was to determine the prevalence of antibiotic consumption in Brazilian intensive care units (ICUs) and estimate the deviation of the prescribed daily dose (PDD) from the defined daily dose (DDD). Methods: This is a multicenter, observational, point-prevalence study carried out in adult ICUs of 8 Brazilian hospitals from August 2019, to February 2020. We collected data on the patient's demographic and clinical characteristics, antibiotic therapy, classification and site of infections. The DU90 (antibiotic accounting for 90% of the volume utilized) was calculated, and the antibiotics were classified by the Anatomical Therapeutic Chemical (ATC) Index and the World Health Organization (WHO) Access, Watch, Reserve (AWaRe) groups. For the most prevalent antibiotics, the deviation of PDD from DDD was determined. Results: Three hundred thirty-two patients from 35 ICUs were analyzed. The prevalence of antibiotic use was 52.4%. The patients in use of antibiotics were predominantly over 60 years of age (81.6%) with pulmonary infections (45.8%). A predominance of empirical regimens was observed (62.6%) among antibiotic therapies. The highest frequencies of prescriptions observed were for piperacillin + tazobactam (16.1%), meropenem (13.3%), amoxicillin + clavulanate (7.2%), azithromycin (7.2%), and teicoplanin (6.1%). The watch (64.2%) and reserve (9.6%) categories of the AWaRe classification accounted for 73.8% of all antibiotics, and they were prescribed alone or in combinations. High variability of doses was observed for the most prescribed antibiotics, and large deviations of PDD from the DDD were observed for meropenem, teicoplanin, and tigecycline. Conclusions: The high prevalence of antibiotic prescription was related to a predominance of empirical regimens and antibiotics belonging to the WHO Watch classification. High variability of doses and large deviations of PDD from DDD for meropenem, teicoplanin, and tigecycline was observed, suggesting that DDD may be insufficient to monitor the consumption of these antibiotics in the ICU population. The variability of doses found for the most prescribed antibiotics suggests the need for monitoring and intervention targets for antibiotic stewardship teams.

Project description:Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the "average farm" level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales.

Project description:BackgroundSeasonal long-distance movements are a common feature in many taxa allowing animals to deal with seasonal habitats and life-history demands. Many species use different strategies to prioritize time- or energy-minimization, sometimes employing stop-over behaviours to offset the physiological burden of the directed movement associated with migratory behaviour. Migratory strategies are often limited by life-history and environmental constraints, but can also be modulated by the predictability of resources en route. While theory on population-wide strategies (e.g. energy-minimization) are well studied, there are increasing evidence for individual-level variation in movement patterns indicative of finer scale differences in migration strategies.MethodsWe aimed to explore sources of individual variation in migration strategies for long-distance migrators using satellite telemetry location data from 41 narwhal spanning a 21-year period. Specifically, we aimed to determine and define the long-distance movement strategies adopted and how environmental variables may modulate these movements. Fine-scale movement behaviours were characterized using move-persistence models, where changes in move-persistence, highlighting autocorrelation in a movement trajectory, were evaluated against potential modulating environmental covariates. Areas of low move-persistence, indicative of area-restricted search-type behaviours, were deemed to indicate evidence of stop-overs along the migratory route.ResultsHere, we demonstrate two divergent migratory tactics to maintain a similar overall energy-minimization strategy within a single population of narwhal. Narwhal migrating offshore exhibited more tortuous movement trajectories overall with no evidence of spatially-consistent stop-over locations across individuals. Nearshore migrating narwhal undertook more directed routes, contrasted by spatially-explicit stop-over behaviour in highly-productive fjord and canyon systems along the coast of Baffin Island for periods of several days to several weeks.ConclusionsWithin a single population, divergent migratory tactics can achieve a similar overall energy-minimizing strategy within a species as a response to differing trade-offs between predictable and unpredictable resources. Our methodological approach, which revealed the modulators of fine-scale migratory movements and predicted regional stop-over sites, is widely applicable to a variety of other aquatic and terrestrial species. Quantifying marine migration strategies will be key for adaptive conservation in the face of climate change and ever increasing human pressures.

Project description:Twice daily TAC (BID TAC) and prolonged released once daily dose tacrolimus (OD TAC) have different pharmacokinetic (PK) profiles in kidney transplant (KT) recipients. Precise dose adjustment recommendations when converting from BID TAC to OD TAC remain inconclusive. A single center, PK study was conducted in stable KT recipients taking constant doses of TAC, mycophenolic acid, and prednisolone. The area under the concentration-time curve (AUC) 0-24 and Ctrough were measured before and 4 weeks after 1:1 conversion from BID TAC to OD TAC without subsequent dose adjustment. A 90% confidence interval (CI) of geometric mean ratio (GMR) of OD TAC/BID TAC within the range of 0.9-1.11 was utilized to indicate equivalence of the narrow therapeutic index drugs. The roles of CYP3A5 genotypic polymorphism on PK parameters were also assessed. There were 20 patients with median time since transplantation of 18 months. The mean of CKD-EPI eGFR was 60.7 ± 16.43 mL/min/1.73 m2. The median total daily TAC dose of 0.058 mg/kg/day. The geometric means (%CV) of AUC0-24 of OD and BID TAC were 205.16 (36.4%) and 210.3 (32.5%) ng/mL × h, respectively, with a GMR of 0.98 (90%CI 0.91-1.04). The geometric means (%CV) of Ctrough of OD TAC and BID TAC were 5.43 (33.1%) and 6.09 (34.6%) ng/mL, respectively. The GMR of Ctrough was 0.89 (90%CI 0.82-0.98), which was below 0.9. The newly calculated target Ctrough level of OD TAC was 4.8-6.2 ng/mL. The best abbreviated AUC0-24 was AUC = 0.97(C0) + 5.79(C6) + 18.97(C12) - 4.26. The GMR AUC0-24 was within the range of 0.9-1.11 irrespective of CYP3A5 genotypic polymorphism while the GMR of Ctrough was below 0.9 only in the CYP3A5 expressor patients. The 1:1 conversion from BID TAC to OD TAC without subsequent dose adjustment provided similar AUC0-24 regardless of CYP3A5 genotypic polymorphism. However, the Ctrough was lower in the CYP3A5 expressor group. Therefore, it is not necessary to routinely increase the OD TAC dose after conversion.Trial registration: Thai Clinical Trials Registry (TCTR20210715002).

Project description:INTRODUCTION:The way physical activity (PA) and sedentary behavior (SB) are accumulated throughout the day (i.e., patterns) may be important for health, but identifying measurable and meaningful metrics of behavioral patterns is challenging. This study evaluated accelerometer-derived metrics to determine whether they predicted PA and SB patterns and were reliably measured. METHODS:We defined and measured 55 metrics that describe daily PA and SB using data collected by using the activPAL monitor in four studies. The first two studies were randomized crossover designs that included recreationally active participants. Study 1 experimentally manipulated time spent in moderate-to-vigorous-intensity PA and sedentary time, and study 2 held time in exercise constant and manipulated SB. Study 3 included inactive participants who increased exercise, decreased sedentary time, or both. The study conditions induced distinct behavioral patterns; thus, we tested whether the new metrics could improve the prediction of an individual's study condition after adjusting for the overall volume of PA or SB using conditional logistic regression. In study 4, we measured the 3-month reliability for the pattern metrics by calculating intraclass correlation coefficients in a community-dwelling sample who wore the activPAL monitor twice for 7 d. RESULTS:In each of the experimental studies, we identified new metrics that could improve the accuracy for predicting condition beyond SB and moderate-to-vigorous-intensity PA volume. In study 1, 23 metrics were predictive of a highly active condition, and in study 2, 24 metrics were predictive of a highly sedentary condition. In study 4, the median intraclass correlation coefficients (25-75th percentiles) of the metrics were 0.59 (0.46-0.65). CONCLUSIONS:Several new metrics were predictive of patterns of SB, exercise, and nonexercise behavior and are moderately reliable for a 3-month period. Applying these metrics to determine whether daily behavioral patterns are associated with health-outcomes is an important area of future research.

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Contrasting Treatment- and Farm-Level Metrics of Antimicrobial Use Based on Used Daily Dose vs. Defined Daily Dose for the German Antibiotics Minimization Concept

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