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马来西亚半岛东海岸家禽养殖场耐药菌株相关危险因素的识别:一项横断面研究。

Identification of Risk Factors Associated with Resistant Isolates from Poultry Farms in the East Coast of Peninsular Malaysia: A Cross Sectional Study.

作者信息

Elmi Sharifo Ali, Simons David, Elton Linzy, Haider Najmul, Abdel Hamid Muzamil Mahdi, Shuaib Yassir Adam, Khan Mohd Azam, Othman Iekhsan, Kock Richard, Osman Abdinasir Yusuf

机构信息

Faculty of Veterinary Medicine, Universiti Malaysia Kelantan, Pengkalan Chepa, Kota Bharu 16100, Kelantan, Malaysia.

The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield AL9 7TA, Hertfordshire, UK.

出版信息

Antibiotics (Basel). 2021 Jan 26;10(2):117. doi: 10.3390/antibiotics10020117.

Abstract

Antimicrobial resistance is of concern to global health security worldwide. We aimed to identify the prevalence, resistance patterns, and risk factors associated with () resistance from poultry farms in Kelantan, Terengganu, and Pahang states of east coast peninsular Malaysia. Between 8 February 2019 and 23 February 2020, a total of 371 samples (cloacal swabs = 259; faecal = 84; Sewage = 14, Tap water = 14) were collected. Characteristics of the sampled farms including management type, biosecurity, and history of disease were obtained using semi-structured questionnaire. Presumptive isolates were identified based on colony morphology with subsequent biochemical and PCR confirmation. Susceptibility of isolates was tested against a panel of 12 antimicrobials and interpreted alongside risk factor data obtained from the surveys. We isolated 717 samples from poultry and environmental samples. Our findings revealed that cloacal (17.8%, 46/259), faecal (22.6%, 19/84), sewage (14.3%, 2/14) and tap water (7.1%, 1/14) were significantly ( < 0.003) resistant to at least three classes of antimicrobials. Resistance to tetracycline class were predominantly observed in faecal samples (69%, 58/84), followed by cloacal (64.1%, 166/259), sewage (35.7%, 5/14), and tap water (7.1%, 1/84), respectively. Sewage water (OR = 7.22, 95% CI = 0.95-151.21) had significant association with antimicrobial resistance (AMR) acquisition. Multivariate regression analysis identified that the risk factors including sewage samples (OR = 7.43, 95% CI = 0.96-156.87) and farm size are leading drivers of antimicrobial resistance in the participating states of east coast peninsular Malaysia. We observed that the resistance patterns of isolates against 12 panel antimicrobials are generally similar in all selected states of east coast peninsular Malaysia. The highest prevalence of resistance was recorded in tetracycline (91.2%), oxytetracycline (89.1%), sulfamethoxazole/trimethoprim (73.1%), doxycycline (63%), and sulfamethoxazole (63%). A close association between different risk factors and the high prevalence of antimicrobial-resistant strains reflects increased exposure to resistant bacteria and suggests a concern over rising misuse of veterinary antimicrobials that may contribute to the future threat of emergence of multidrug-resistant pathogen isolates. Public health interventions to limit antimicrobial resistance need to be tailored to local poultry farm practices that affect bacterial transmission.

摘要

抗菌药物耐药性是全球卫生安全关注的问题。我们旨在确定马来西亚半岛东海岸吉兰丹州、登嘉楼州和彭亨州家禽养殖场中()耐药性的流行情况、耐药模式及相关风险因素。在2019年2月8日至2020年2月23日期间,共采集了371份样本(泄殖腔拭子 = 259份;粪便 = 84份;污水 = 14份;自来水 = 14份)。通过半结构化问卷获取了抽样养殖场的特征,包括管理类型、生物安全措施和疾病史。基于菌落形态初步鉴定分离株,随后进行生化和PCR确认。对分离株进行了针对一组12种抗菌药物的药敏试验,并结合从调查中获得的风险因素数据进行解读。我们从家禽和环境样本中分离出717份样本。我们的研究结果显示,泄殖腔样本(17.8%,46/259)、粪便样本(22.6%,19/84)、污水样本(14.3%,2/14)和自来水样本(7.1%,1/14)对至少三类抗菌药物有显著(<0.003)耐药性。粪便样本中主要观察到对四环素类的耐药性(69%,58/84),其次分别是泄殖腔样本(64.1%,166/259)、污水样本(35.7%,5/14)和自来水样本(7.1%,1/84)。污水(比值比 = 7.22,95%置信区间 = 0.95 - 151.21)与获得抗菌药物耐药性(AMR)有显著关联。多变量回归分析确定,包括污水样本(比值比 = 7.43,95%置信区间 = 0.96 - 156.87)和养殖场规模等风险因素是马来西亚半岛东海岸参与研究各州抗菌药物耐药性的主要驱动因素。我们观察到,在马来西亚半岛东海岸所有选定州中,分离株对12种抗菌药物的耐药模式总体相似。耐药性最高的是四环素(91.2%)、土霉素(89.1%)、磺胺甲恶唑/甲氧苄啶(73.1%)、强力霉素(63%)和磺胺甲恶唑(63%)。不同风险因素与高比例的抗菌药物耐药菌株之间的密切关联反映出接触耐药菌的增加,这表明人们对兽医抗菌药物滥用情况不断增加感到担忧,因为这可能会导致未来出现多重耐药病原体分离株的威胁。限制抗菌药物耐药性的公共卫生干预措施需要根据影响细菌传播的当地家禽养殖做法进行调整。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73be/7912622/ede0f05a1e06/antibiotics-10-00117-g001.jpg

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