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Enregistrement W2577640125

Antimicrobial resistance in indicator Escherichia coli from medium-sized swine herds in North-eastern Thailand

2016· article· en· W2577640125 sur OpenAlexaboutno aff
Matilda Halje

Notice bibliographique

RevueEpsilon Archive for Student Projects (University of Southampton) · 2016
Typearticle
Langueen
DomaineEnvironmental Science
ThématiquePharmaceutical and Antibiotic Environmental Impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBiosecurityAntibiotic resistanceLivestockAntibioticsAntimicrobialBiotechnologyMedicineIntensive care medicineEnvironmental healthVeterinary medicineBiologyMicrobiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Antimicrobial resistance (AMR) is a fast growing global threat in several perspectives. In medicine the antimicrobials are crucial in the treatment of some diseases and without the antimicrobials those diseases might be fatal. In veterinary medicine antimicrobials are used as treatment, prevention and growth promoters and without them it would be difficult to handle some diseases which could result in extensive economic losses for the animal owner as well as for the society as a whole, especially in developing countries. \nExcessive and imprudent use of antibiotics may contribute to the development and dissemination of resistant bacteria and genes. Several studies have shown a risk for dissemination of resistant bacteria from food animals to humans and therefore measures have been taken on national as well as on international levels to curb this progression. One example of such measures is surveillance systems to monitor the resistance pattern of selected microbes regularly. A gained knowledge about the resistance patterns, along with knowledge about resistance mechanisms, makes it possible to adjust regulations and recommendations for antibiotic usage so that less broad-spectrum antibiotics are used in favor for the narrow-spectrum antibiotics or, for that matter, no antibiotics at all. \nImprovements in preventive management such as good hygiene and biosecurity would also decrease the need for antimicrobials in animals and livestock which would be beneficial in hindering the progression of AMR. \nThis study aims to contribute to the important monitoring and mapping of AMR in livestock. The pig production in Thailand is expanding and an increasing number of large-scaled farms are appearing at the same time as the number of smaller farms decreases. Therefore Thailand was chosen for this study. \nIn this study indicator Escherichia coli was cultured from rectal swabs from healthy sows on 27 medium-sized (100-500 sows) farms in the northeast of Thailand. Samples were collected from three sows at each farm, resulting in 81 samples in total. To test them for antibiotic susceptibility a VetMIC GN-mo panel was used – a MIC-based (minimum inhibitory concentration) broth-microdilution method. Antibiotic substances included in the study were: amoxicillin, ciprofloxacin, nalidixic acid, gentamicin, streptomycin, tetracycline, florfenicol, colistin, sulfamethoxazole, trimethoprim, chloramphenicol, meropenem, cefotaxime and ceftazidime. \nAt each farm a questionnaire was also filled in to enable identification of possible risk factors for antibiotic resistance. The questions were chosen and formulated in a manner that would give us insight in the routines regarding antibiotic usage, husbandry and health status of the pigs. \nFrom 81 samples, 81 Escherichia coli isolates were obtained. The percentage of resistant isolates among the tested isolates for each of the included antibiotics was as follows: ampicillin (85.2%), ciprofloxacin (48.1%), nalidixic acid (30.8%), gentamicin (7.4%), streptomycin (76.5%), tetracycline (86.3%), florfenicol (2.4%), colistin (0.0%), sulfamethoxazole (84.0%), trimethoprim (70.4%), chloramphenicol (58.0%), cefotaxime (1.2%) and ceftazidime (3.7%). Multidrug resistance (MDR) was found in 95.1% of the isolates. The variations in management and antibiotic usage among the farms were very small and therefore statistical relationships could not be obtained in regards to management, antibiotic usage and antibiotic resistance. \nSome of the results for meropenem were found to be unreliable. One of the strains (M13) had nevertheless a high minimum inhibitory concentration (MIC) for meropenem as well as for other betalactams and is therefore possibly ESBLCARBA-producing (extended spectrum betalactamase- and carbapenemase-producing). Such finding would be perturbing since an ESBLCARBA-producing strain are resistant to several highly important antimicrobials. This result needs however to be further investigated with PCR (polymerase chain reaction). \nAlthough there are undertakings regarding AMR in Thailand, the usage of antimicrobials in animals remains less defined and the presence of AMR seems to be high compared to Sweden and Europe as well as Canada. An AMR surveillance program is necessary in Thailand as well as other Southeast Asian countries to be able to draw plausible conclusions regarding the AMR and the effect of antibiotic usage in this region. \nThis study shows a wide use of antibiotics in the farms included. All of the farms administered antibiotics to the sows as injection as a routine after farrowing. The results from the antibiotic susceptibility tests display a generally high resistance frequency for a majority of the included antibiotics. This indicates that a wide use of antibiotics results in resistant bacteria, which makes a prudent antibiotic use, as well as surveillance systems, crucial to curb the development of more resistant bacteria.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,018
Score d'incertitude au seuil0,035

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,243
Écart entre enseignants0,226 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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