Materiały źródłowe

• #1 Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation

  https://pmc.ncbi.nlm.nih.gov/articles/PMC10141895/

  Severe clinical mastitis is a frequent disease of dairy cattle. An effective mean of predicting survival despite treatment would be helpful for making euthanasia decisions in poor prognosis cases. […] A reliable prognosis is important to make euthanasia decisions in poor prognosis cases. […] The objective of this study was to develop a predictive model for death or culling caused by an episode of severe clinical mastitis in dairy cattle after a first veterinary clinical examination of the animal at the farm, and with that model to develop a nomogram to predict the death or culling of an animal in the next 60 days. […] The nomogram included: lactation number, recumbency, depression intensity, capillary refilling time, ruminal motility rate, dehydration level, lactates concentration, hematocrit, band neutrophils count, monocyte count, and milk bacteriology.

• #2 Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning | Scientific Reports

  https://www.nature.com/articles/s41598-021-87300-0

  Mastitis is the most prevalent endemic disease in the dairy industry impacting productivity, profitability and cow welfare. […] Moreover, very little is known about the factors affecting the likely outcome of treatment for clinical mastitis cases. […] Although differences in cure rates depend on the different drugs used, the key factors found to be relevant in determining the outcome of treatment of clinical cases are the time when treatment is initiated and the duration of treatment, with more rapid initiation of treatment and longer treatment duration, both being associated with improved cure rates. […] For the first time, we demonstrated that external features, such as parity, SCC of previous lactation and number of clinical mastitis cases can increase the overall performance of the classifiers if used together with the spectral features obtained by the MALDI-TOF.

• #2 Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation

  https://pmc.ncbi.nlm.nih.gov/articles/PMC10141895/

  Severe clinical mastitis is a frequent disease of dairy cattle. An effective mean of predicting survival despite treatment would be helpful for making euthanasia decisions in poor prognosis cases. […] A reliable prognosis is important to make euthanasia decisions in poor prognosis cases. […] The objective of this study was to develop a predictive model for death or culling caused by an episode of severe clinical mastitis in dairy cattle after a first veterinary clinical examination of the animal at the farm, and with that model to develop a nomogram to predict the death or culling of an animal in the next 60 days. […] The nomogram included: lactation number, recumbency, depression intensity, capillary refilling time, ruminal motility rate, dehydration level, lactates concentration, hematocrit, band neutrophils count, monocyte count, and milk bacteriology.

• #3 Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation

  https://www.mdpi.com/2306-7381/10/4/268

  Severe clinical mastitis is a frequent disease of dairy cattle. An effective mean of predicting survival despite treatment would be helpful for making euthanasia decisions in poor prognosis cases. […] The objective was to develop a nomogram for prediction of death or culling in the 60 days following a severe mastitis episode in dairy cows at first veterinary visit in farm settings. […] The nomogram included: lactation number, recumbency, depression intensity, capillary refilling time, ruminal motility rate, dehydration level, lactates concentration, hematocrit, band neutrophils count, monocyte count, and milk bacteriology. […] The AUC and C-index showed a good calibration and ability to discriminate. […] Euthanizing animals having less than 25% probability of survival is economically optimal.

• #4 Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation

  https://www.mdpi.com/2306-7381/10/4/268

  The objective of this study was to develop a predictive model for death or culling caused by an episode of severe clinical mastitis in dairy cattle after a first veterinary clinical examination of the animal at the farm, and with that model to develop a nomogram to predict the death or culling of an animal in the next 60 days. […] The nomogram with all the predictors is presented in Figure 1. It predicts the overall survival (no death or culling) in the 60 days following a first veterinary visit for a severe clinical mastitis case in dairy cows. […] The C-index of the nomogram was 0.71 ± 0.01, and the tAUC is presented in Figure 2. […] Overall, the discriminatory abilities of the nomogram were fair to good (C-index and tAUC). […] The calibration curve of the nomogram at day 60 is presented in Figure 2. The calibration of the model was good: the calibration curve of the model is close to the straight line which represents a perfect calibration curve.

• #5 Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation

  https://pmc.ncbi.nlm.nih.gov/articles/PMC10141895/

  Euthanizing animals having less than 25% probability of survival is economically optimal. […] The C-index of the nomogram was 0.71 0.01, and the tAUC is presented in Figure 2. […] The calibration of the model was good: the calibration curve of the model is close to the straight line which represents a perfect calibration curve. […] The misclassification cost term of the nomogram at day 60 is presented in Figure 4. […] The DCA is a recent tool, but more and more journal editors endorse this tool. […] The best-guess prognosis of veterinarians was statistically able to properly discriminate the animals by risk categories (significant LogRank test) but provided a low benefit in the investigated range. […] These two nomograms were shown to be clinically and economically relevant.

• #6 Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation

  https://www.mdpi.com/2306-7381/10/4/268

  The misclassification cost term of the nomogram at day 60 is presented in Figure 4. […] The second nomogram has slightly worse discriminative abilities compared to the first nomogram: tAUC of less than 0.8 at all times. […] The DCA and MCT at day 60 of the second nomogram are available in Figure 7. […] The DCA is a recent tool, but more and more journal editors endorse this tool. […] The misclassification cost term is a tool to find an economically optimal cut-off point. […] The „best-guess” prognosis of veterinarians was statistically able to properly discriminate the animals by risk categories (significant LogRank test) but provided a low benefit in the investigated range. […] An innovative method was used to develop and internally validate nomograms to predict non-survival of dairy cows suffering from severe clinical mastitis in the 60-day period following a first veterinary exam in farm settings.

• #7 Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning | Scientific Reports

  https://www.nature.com/articles/s41598-021-87300-0

  Mastitis is the most prevalent endemic disease in the dairy industry impacting productivity, profitability and cow welfare. […] Moreover, very little is known about the factors affecting the likely outcome of treatment for clinical mastitis cases. […] Although differences in cure rates depend on the different drugs used, the key factors found to be relevant in determining the outcome of treatment of clinical cases are the time when treatment is initiated and the duration of treatment, with more rapid initiation of treatment and longer treatment duration, both being associated with improved cure rates. […] For the first time, we demonstrated that external features, such as parity, SCC of previous lactation and number of clinical mastitis cases can increase the overall performance of the classifiers if used together with the spectral features obtained by the MALDI-TOF.

• #8 Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning | Scientific Reports

  https://www.nature.com/articles/s41598-021-87300-0

  The increased performance is possibly explained by recent findings, showing that milk SCC can be influenced by parity, lactation stage, health and other factors, regardless of whether the cow is infected or not. […] This demonstrates the platform’s ability to generate hypotheses that may not only support better decision making and treatment selection but also may expand our knowledge of the molecular basis of progression to a persistent infection. […] The proteins found to be discriminant between responsive and unresponsive S. uberis isolates (i.e. SUB1659A (rpmH), SUB0090 (infA), SUB0086 (rpmD) and SUB0956 (rpsT)) and the resistome interactions (SUB1631 (ksgA) and SUB1644 (fusA)) revealed are new but in many cases involve known genes characterised for their AMR function in other species.

• #9 Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning | Scientific Reports

  https://www.nature.com/articles/s41598-021-87300-0

  However, this is the first time these molecular determinants have been identified as possibly being involved in the progression to a persistent S. uberis infection. […] Overall, the results of this study meet the critical need to integrate various kinds of omics data with associated metadata to provide a robust, effective and rapid means to discriminate responsive and unresponsive strains of S. uberis.

• #10 A new stage for predicting the prognosis of granulomatous lobular mastitis

  https://pmc.ncbi.nlm.nih.gov/articles/PMC11922289/

  The prognosis of granulomatous lobular mastitis (GLM) had been poor, primarily due to the lack of a unified disease assessment standard. […] The purpose of this cohort study was to establish a staging system for GLM to more accurately evaluate the prognosis of patients. […] Univariate and multivariate logistic regression analysis revealed that hyperlipidemia (HR: 2.031; 95% CI: 1.100-3.750) and microabscesses (HR: 2.087; 95% CI=1.138-3.827) were significant independent risk factors affecting the prognosis of GLM patients. […] This study constructed a rigorous and widely applicable GLM staging system (the 1st edition of GLM stage). The system demonstrated good predictive outcomes and provided strong support for clinical decision-making. […] The study revealed that hyperlipidemia and microabscesses were independent prognostic factors. Based on these findings, we constructed a rigorous and widely applicable GLM staging system. The system demonstrated good predictive outcomes and provided strong support for clinical decision-making.

• #11 A new stage for predicting the prognosis of granulomatous lobular mastitis | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0319956

  The prognosis of granulomatous lobular mastitis (GLM) had been poor, primarily due to the lack of a unified disease assessment standard. […] The purpose of this cohort study was to establish a staging system for GLM to more accurately evaluate the prognosis of patients. […] Univariate and multivariate logistic regression analysis revealed that hyperlipidemia (HR: 2.031; 95% CI: 1.100-3.750) and microabscesses (HR: 2.087; 95% CI=1.138-3.827) were significant independent risk factors affecting the prognosis of GLM patients. […] This study constructed a rigorous and widely applicable GLM staging system (the 1st edition of GLM stage). The system demonstrated good predictive outcomes and provided strong support for clinical decision-making.

• #12 Can imaging findings predict the outcome of idiopathic granulomatous mastitis? – Ozcan – Annals of Breast Surgery

  https://abs.amegroups.org/article/view/7744/html

  Imaging findings at baseline and follow-up do not correlate with final IGM outcome. […] Correlation of clinical follow-up findings is non-inferior to imaging; hence, clinical follow-up should be the mainstay of surveillance. […] In our study, IGM outcome could not be predicted on follow-up US imaging findings. Our findings indicate that follow-up US imaging in IGM was not helpful to predict the disease outcome, and US follow-up was not superior to clinical follow-up. […] Imaging findings at baseline and follow-up do not have a strong correlation with final IGM outcome. Correlation of clinical follow-up findings are non-inferior to imaging, hence clinical follow-up in surveillance is similar to imaging, therefore practitioners should utilize imaging judiciously in a cost-effective manner.

• #13 Correlation between Immune Factor Expression and Prognosis of Plasma Cell Mastitis Surgery and its Predictive Value for Prognosis

  https://www.imrpress.com/journal/CEOG/51/10/10.31083/j.ceog5110234/htm

  Correlation between Immune Factor Expression and Prognosis of Plasma Cell Mastitis Surgery and its Predictive Value for Prognosis. […] The expression of immune factors such as TNF-α, IL-6 and IL-10 is closely related to the prognosis of surgical treatment of PCM, which has high predictive value for its prognosis. […] Logistic regression analysis showed that the levels of TNF-α (odds ratio (OR) = 1.551, 95% confidence interval (95% CI): 1.276–1.886) and IL-6 (OR = 1.082, 95% CI: 1.046–1.119) were increased, which were risk factors for the prognosis of PCM (OR >1). […] Correlation analysis showed that TNF-α and IL-6 were negatively correlated with the prognosis of PCM, while IL-10 was positively correlated with the prognosis of PCM. […] ROC curve analysis showed that the areas under the curve for TNF-α, IL-6 and IL-10 to predict the prognosis of surgical treatment of PCM were 0.896, 0.931 and 0.709 respectively.

• #14 Correlation between Immune Factor Expression and Prognosis of Plasma Cell Mastitis Surgery and its Predictive Value for Prognosis

  https://www.imrpress.com/journal/CEOG/51/10/10.31083/j.ceog5110234/htm

  The prognosis of surgical treatment of PCM was taken as a state variable (good prognosis = 1; poor prognosis = 0), using TNF-α, IL-6 and IL-10 as independent variables, and drawing ROC curve, as shown in Fig. 1. The results show that the area under the ROC curve (AUC) values of TNF-α, IL-6 and IL-10 are all above 0.600, which shows that the above indexes have good predictive value for the prognosis of surgical treatment of PCM.

• #15 Predicting an increased risk of severe clinical mastitis and economic loss using a threshold value of bovine leukemia virus proviral load in: American Journal of Veterinary Research Volume 85 Issue 3 (2024)

  https://avmajournals.avma.org/view/journals/ajvr/85/3/ajvr.23.09.0198.xml

  To establish a threshold value of bovine leukemia virus (BLV) proviral load (PVL) to identify increased risk of severe clinical mastitis, and to examine the prognosis and economic loss of clinical mastitis based on the newly established PVL cut-off value. […] PVL cut-off value was 17.8 copies/10 ng DNA for the dependent variable MILD vs SEVERE. […] There was no significant difference in prognosis after mastitis among the 3 groups. […] These results suggested that PVL cut-off value of 17.8 copies/10 ng DNA was a useful threshold for increased economic losses in BLV-infected cows; it may also serve as a new standard value for the detection and culling of BLV-infected cows in Japan. […] The severity of clinical mastitis in the present study was associated with BLV PVL in blood, with a cut-off value of 17.8 copies/10 ng DNA, and an area under the receiver-operating characteristic curve (AUC) of 0.717.

• #16 Predicting an increased risk of severe clinical mastitis and economic loss using a threshold value of bovine leukemia virus proviral load in: American Journal of Veterinary Research Volume 85 Issue 3 (2024)

  https://avmajournals.avma.org/view/journals/ajvr/85/3/ajvr.23.09.0198.xml

  The occurrence of severe clinical mastitis, the percentage of cows with systemic treatments, the number of treatments, and the technical fees for medical treatment were significantly higher in the above the cut-off value group than in the below the cut-off value group. […] These findings suggest that cows above the cut-off value are at high risk for severe clinical mastitis, the prognosis (in this study, somatic cell count and lifetime until slaughter) of mastitis could be ameliorated by appropriate, but costly treatment, which would result in significant economic loss due to the increased severity of clinical mastitis. […] In conclusion, the results of the present study suggested that the PVL cut-off value of 17.8 copies/10 ng DNA is a useful threshold for increased economic losses in terms of increased costs and number of treatments for clinical mastitis in BLV-infected cows, and it may also serve as a new standard value for the detection and culling of asymptomatic BLV-infected cows in Japan.

• #17 Automated prediction of mastitis infection patterns in dairy herds using machine learning | Scientific Reports

  https://www.nature.com/articles/s41598-020-61126-8

  Mastitis in dairy cattle is extremely costly both in economic and welfare terms and is one of the most significant drivers of antimicrobial usage in dairy cattle. […] An accurate, automated mastitis diagnosis tool has great potential to aid non-specialist veterinary clinicians to make a rapid herd level diagnosis and promptly implement appropriate control measures for an extremely damaging disease in terms of animal health, productivity, welfare and antimicrobial use. […] Using the random forest algorithm we were able to correctly replicate the herd level mastitis diagnosis with a high degree of accuracy when compared with a specialist veterinary clinician; using an external dataset, an accuracy of 98% was achieved for diagnosing CONT vs ENV and 78% for diagnosing EDP vs EL. […] There is great potential for automated diagnostic support tools to reduce the amount of training and time required to make such a diagnosis; where a clinician might require 30-60 minutes to evaluate all the information and make a herd mastitis diagnosis, a machine learning algorithm requires only seconds. […] The ML algorithm identified in this research has the potential to predict an accurate, probabilistic herd mastitis diagnosis which should aid veterinary practitioners in mastitis control.

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