Literature DB >> 24746098

Diagnosis of acute puerperal metritis by electronic nose device analysis of vaginal discharge in dairy cows.

O Burfeind1, M Bruins2, A Bos2, I Sannmann1, R Voigtsberger1, W Heuwieser3.   

Abstract

The objective of this study was to estimate the diagnostic accuracy of an electronic nose device using vaginal discharge samples to diagnose acute puerperal metritis (APM) in dairy cows. Uterine fluid was sampled manually with a gloved hand and under sterile conditions for electronic nose device analysis (day in milk (DIM) 2, 5, and 10) and bacteriologic examination (DIM 5), respectively, and on additional days, if APM was diagnosed during the daily clinical examinations. A dataset containing samples from 70 cows was used to create a model and to validate the APM status predicted by this model, respectively. Half of the dataset (n = 35; 14 healthy and 21 metritic cows) was provided with information regarding the APM diagnosis and contained all three measurements (DIM 2, 5, and 10) for each cow and was used as a training set whereas the second half was blinded (n = 35; 14 healthy and 21 metritic cows) and contained only the samples collected on DIM 5 of each cow and was used to validate the created prediction model. A receiver operating characteristic curve was calculated using the prediction results of the validation test. The best observed sensitivity was 100% with specificity of 91.6% when using a threshold value of 0.3. The calculated P-value for the receiver operating characteristic curve was less than 0.01. Overall, Escherichia coli was isolated in eight of 28 (28.6%) and 22 of 42 (52.4%) samples collected from healthy and metritic cows, respectively. Trueperella pyogenes and Fusobacterium necrophorum were isolated in 14 and six of 28 (50.0% and 21.4%) and 17 and 16 of 42 (40.5% and 38.1%) samples collected from healthy and metritic cows, respectively. The prevalence of Escherichia coli and Trueperella pyogenes was similar in the samples obtained from metritic cows used for the training set and the validation test. The results are promising especially because of the objective nature of the measurements obtained by the electronic nose device.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Electronic nose device; Odor; Sensitivity; Specificity; Vaginal discharge

Mesh:

Year:  2014        PMID: 24746098     DOI: 10.1016/j.theriogenology.2014.03.001

Source DB:  PubMed          Journal:  Theriogenology        ISSN: 0093-691X            Impact factor:   2.740


  2 in total

1.  A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance.

Authors:  Xiuzhen Guo; Chao Peng; Songlin Zhang; Jia Yan; Shukai Duan; Lidan Wang; Pengfei Jia; Fengchun Tian
Journal:  Sensors (Basel)       Date:  2015-06-29       Impact factor: 3.576

Review 2.  Electronic Nose Feature Extraction Methods: A Review.

Authors:  Jia Yan; Xiuzhen Guo; Shukai Duan; Pengfei Jia; Lidan Wang; Chao Peng; Songlin Zhang
Journal:  Sensors (Basel)       Date:  2015-11-02       Impact factor: 3.576

  2 in total

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