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P303: Safety of intravenous samples and risk management of infectious waste: the case of Mali
Springer Science and Business Media LLC - Tập 2 - Trang 1-1 - 2013
AM Traoré, M Fomba, T Cissé, S Yehia, B Diarra, DS Ouloguem, H Cissé, DK Minta
Validation of national hospital antimicrobial consumption data in England
Springer Science and Business Media LLC - Tập 4 Số S1 - 2015
Berit Müller‐Pebody, David Ladenheim, Christopher Fuller, Diane Ashiru‐Oredope, Susan Hopkins
Eastern Mediterranean region tuberculosis economic burden in 2014
Springer Science and Business Media LLC - Tập 4 - Trang 1-1 - 2015
A Sargazi, Z Sepehri, A Sagazi, PK Nadakkavukaran Jim, Z Kiani
Determination of bacteria migration speed through urinary catheter systems in case of urostomy
Springer Science and Business Media LLC - Tập 4 - Trang 1-1 - 2015
FHH Brill, H Braunwarth, D Hegeholz, W Droste
Estimating the effect of practicing nursing professionals density on cumulative carbapenem-resistance prevalence in gram-negative invasive Isolates: a 30 European country observational modeling study
Springer Science and Business Media LLC - Tập 11 - Trang 1-13 - 2022
Hani E. J. Kaba, Simone Scheithauer
The burden of antimicrobial-resistance, specifically carbapenem-resistance in gram-negative bacteria (CRGN), presents a serious public health threat worldwide. In Europe, Southern and Eastern countries (SEC) display a higher CRGN-prevalence as compared to Northern and Western countries (NWC). Since SEC also display lower nurse-density on average, we hypothesized that the occurrence of CRGN might correlate with nurse understaffing and therefore aimed at quantifying a potential independent effect of nurse-density on total CRGN in Europe. A 30-country cross-sectional study was conducted. Cumulative six-year CRGN-prevalence (2011–2016) in four gram-negative bacterial species was determined based on > 700 k clinical invasive isolates (EARS-net). We performed multivariable log-linear regression to provide estimations of the effect of nurse-density while adjusting to various health-system variables. Multivariable analysis (adj.-R2 ~ 93%) suggested an average 0.4% [95%-CI 0.2–1.0%] CRGN-increase due to a decrement of one practicing nurse per week of hospital-stay of one population individual. Our modeling provided CRGN-estimations in two non-EARS-net countries (Switzerland and Turkey), which were almost equal to empirically estimated values (CAESAR-Network). Furthermore, a nurse-density-dependent moderation of the inter-species distribution balance was a likely pathway of the observed effect. These observations were specific for CRGN, in contrast to other resistance types in the same species. This is the first attempt of quantifying potential nurse-density effects on antimicrobial-resistance at national level. Our results suggest an increase in CRGN by decreasing nurse-density. Nurse-density is thus a novel factor that might improve our understanding of the unbalanced CRGN-distribution among sub-European regions. Consequently, integrating nurse-density in future AMR-policies could be beneficial.
Burden for the infection control programme of a European hospital of getting prepared and treat a patient (PT) with Ebola virus disease (EVD)
Springer Science and Business Media LLC - Tập 4 - Trang 1-1 - 2015
A Iten, MN Charaïti, C Ginet, P Brennenstuhl, D Pittet
Thực hiện và tác động của các chương trình quản lý kháng sinh ở trẻ em: một đánh giá toàn diện có hệ thống Dịch bởi AI
Springer Science and Business Media LLC - - 2020
Daniele Donà, Elisa Barbieri, Marco Daverio, Rebecca Lundin, Carlo Giaquinto, Theoklis E. Zaoutis, Mike Sharland
Tóm tắtĐặt vấn đề

Đại trà sử dụng kháng sinh rất phổ biến trong cộng đồng và trong bệnh viện, với tỷ lệ đáng kể việc sử dụng có thể không thích hợp. Việc lạm dụng kháng sinh làm gia tăng nguy cơ độc tính, tăng chi phí chăm sóc sức khỏe và sự chọn lọc tình trạng kháng thuốc. Mục tiêu chính của đánh giá hệ thống này là tóm tắt tình trạng hiện tại của bằng chứng về việc thực hiện và kết quả của các chương trình quản lý kháng sinh (ASP) cho trẻ em trên toàn cầu.

Phương pháp

Các cơ sở dữ liệu MEDLINE, Embase và Thư viện Cochrane đã được tìm kiếm một cách có hệ thống để xác định các nghiên cứu báo cáo về ASP ở trẻ em từ 0-18 tuổi và được thực hiện trong các thiết lập ngoại trú hoặc nội trú. Ba nhà nghiên cứu đã độc lập xem xét các bài báo đã xác định để đưa vào và rút trích dữ liệu liên quan.

Kết quả

Từ 41,916 nghiên cứu được sàng lọc, 113 nghiên cứu đủ điều kiện đưa vào nghiên cứu này. Phần lớn các nghiên cứu có nguồn gốc từ Hoa Kỳ (52.2%), trong khi một số ít được thực hiện ở châu Âu (24.7%) hoặc châu Á (17.7%). Bảy mươi bốn (65.5%) nghiên cứu sử dụng thiết kế trước và sau, và mười sáu (14.1%) là thử nghiệm ngẫu nhiên. Phần lớn (81.4%) mô tả các ASP trong bệnh viện với một nửa các can thiệp ở các khoa nhi hỗn hợp và mười (8.8%) ở phòng cấp cứu. Chỉ có mười sáu (14.1%) nghiên cứu tập trung vào chi phí của các ASP. Gần như tất cả các nghiên cứu (79.6%) cho thấy sự giảm đáng kể trong các đơn thuốc không phù hợp. Độ tuân thủ sau khi thực hiện ASP đã gia tăng. Mười sáu trong số các nghiên cứu được đưa vào đã định lượng lượng tiết kiệm chi phí liên quan đến can thiệp với hầu hết các mức giảm là do tần suất sử dụng thuốc thấp hơn. Bảy nghiên cứu cho thấy độ nhạy cảm gia tăng của vi khuẩn được phân tích với sự giảm trong các nhà sản xuất beta-lactamase phổ rộng E. coliK. pneumoniae;giảm trong tỷ lệ kháng carbapenem của P. aeruginosađược quan sát sau khi tỷ lệ ngày dùng kháng sinh giảm; và, trong hai nghiên cứu ở thiết lập ngoại trú, sự gia tăng của S. pyogenesnhạy cảm với erythromycin theo sau sự giảm trong việc sử dụng macrolides.

Kết luận

Các ASP cho trẻ em có tác động đáng kể đến việc giảm sử dụng kháng sinh mục tiêu và thực nghiệm, chi phí chăm sóc sức khỏe, và tình trạng kháng kháng sinh trong cả môi trường nội trú và ngoại trú. Các ASP cho trẻ em hiện đã được triển khai rộng rãi tại Hoa Kỳ, nhưng cần rất nhiều sự điều chỉnh hơn nữa để tạo điều kiện cho việc áp dụng của chúng ở châu Âu, châu Á, châu Mỹ La-tinh và châu Phi.

#kháng sinh #quản lý kháng sinh #trẻ em #chi phí chăm sóc sức khỏe #kháng thuốc
Development of machine learning models for the detection of surgical site infections following total hip and knee arthroplasty: a multicenter cohort study
Springer Science and Business Media LLC - Tập 12 - Trang 1-10 - 2023
Guosong Wu, Cheligeer Cheligeer, Danielle A. Southern, Elliot A. Martin, Yuan Xu, Jenine Leal, Jennifer Ellison, Kathryn Bush, Tyler Williamson, Hude Quan, Cathy A. Eastwood
Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection. This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020. True SSI conditions were judged by the Alberta Health Services Infection Prevention and Control (IPC) program staff. Using the IPC cases as labels, we developed and validated nine XGBoost models to identify deep incisional SSIs, organ space SSIs and complex SSIs using administrative data, electronic medical records (EMR) free text data, and both. The performance of machine learning models was assessed by sensitivity, specificity, positive predictive value, negative predictive value, F1 score, the area under the receiver operating characteristic curve (ROC AUC) and the area under the precision–recall curve (PR AUC). In addition, a bootstrap 95% confidence interval (95% CI) was calculated. There were 22,059 unique patients with 27,360 hospital admissions resulting in 88,351 days of hospital stay. This included 16,561 (60.5%) TKA and 10,799 (39.5%) THA procedures. There were 235 ascertained SSIs. Of them, 77 (32.8%) were superficial incisional SSIs, 57 (24.3%) were deep incisional SSIs, and 101 (42.9%) were organ space SSIs. The incidence rates were 0.37 for superficial incisional SSIs, 0.21 for deep incisional SSIs, 0.37 for organ space and 0.58 for complex SSIs per 100 surgical procedures, respectively. The optimal XGBoost models using administrative data and text data combined achieved a ROC AUC of 0.906 (95% CI 0.835–0.978), PR AUC of 0.637 (95% CI 0.528–0.746), and F1 score of 0.79 (0.67–0.90). Our findings suggest machine learning models derived from administrative data and EMR text data achieved high performance and can be used to automate the detection of complex SSIs.
Abstracts from the 8th International Congress of the Asia Pacific Society of Infection Control (APSIC)
Springer Science and Business Media LLC - Tập 6 - Trang 1-49 - 2017
Nantanit Sutthiruk, Mari Botti, Julie Considine, Andrea Driscoll, Ana Hutchinson, Kumthorn Malathum, Cucunawangsih Cucunawangsih, Veronica Wiwing, Vivien Puspitasari, Rathina Kumar Shanmugakani, Yukihiro Akeda, Takuya Kodera, Pitak Santanirand, Kazunori Tomono, Takayuki Yamanaka, Hiroyuki Moriuchi, Hiroyuki Kitajima, Yuho Horikoshi, Alyona Lavrinenko, Ilya Azizov, Nurlan Tabriz, Margulan Kozhamuratov, Yekatherine Serbo, Dahae Yang, Woonhyoung Lee, Il Kwon Bae, Jae Hyun Lee, Hyukmin Lee, Jung Ok Kim, Seok Hoon Jeong, Kyungwon Lee, Thiba Peremalo, Priya Madhavan, Sharina Hamzah, Leslie Than, Eng Hwa Wong, Mohd Nasir Mohd Desa, Kee Peng Ng, Marionne Geronimo, Maria Fe Tayzon, Maria Jesusa Maño, Angela Chow, Pei-Yun Hon, Mar-Kyaw Win, Brenda Ang, Yee-Sin Leo, Tina See, Rocio Alvarez Marin, Marta Aires de Sousa, Nicolas Kieffer, Patrice Nordmann, Laurent Poirel, Wison Laochareonsuk, Sireekul Petyu, Pawin Wanasitchaiwat, Sutasinee Thana, Chollathip Bunyaphongphan, Woranan Boonsomsuk, Pakpoom Maneepongpermpoon, Silom Jamulitrat, Dorairajan Sureshkumar, Kalyanaraman Supraja, Soundararajan Sharmila, Benny Setiawan, Nicolaski Lumbuun, Haruo Nakayama, Toshiko Ota, Naoko Shirane, Chikako Matuoka, Kentaro Kodama, Masanobu Ohtsuka, Silverose Ann Andales Bacolcol, Melecia Velmonte, Allan Alde, Keithleen Chavez, Arlene Joy Esteban, Aisa Jensen Lee, Tai-Chin Hsieh, Shio-ShinJean, Huey-Jen Huang, Shu-Ju Huang, Yu-Huan Huang, Pei-Chen Cheng, Su-Fang Yu, Shih-Ming Tsao, Yuan-Ti Lee, Chien-Feng Li, Min-Chi Lu, Nattapol Pruetpongpun, Thana Khawcharoenporn, Pansachee Damronglerd, Nuntra Suwantarat, Anucha Apisarnthanarak, Sasinuch Rutjanawech, Lisa Cushinotto, Patty McBride, Harding Williams, Hans Liu, Phan Thi Hang, Dinh Pham Phuong Anh, Ngai Le, Dung Khu, Lam Nguyen, Roel Beltran Castillo, Ram Gopalakrishnan, Venkatasubramanian Ramasubramanian, Subramanian Sreevidya, Ranganathan Jayapradha, Atsushi Umetsu, Tetsuhiro Noda, Kenyuu Hashimoto, Akihiro Hayashi, Mikie Kabashima, Ursula Jadczak, Knut Elvelund, Marit Johnsen, Bente Borgen, Egil Lingaas, Chia-Hua Mao, Fu-Chieh Chang, Chang-Pan Liu, Ru-Hui Chao, Fu-chieh Chang, Chang-pan Liu, Junpen Pawapotako, Chadanan Prasertpan, Wantanee Malaihuan, Phisit Uirungroj, Chalermpong Saenjum, Teerapat Ouirungrog, Sue Borrell, Pauline Bass, Leon Worth, Zhao Xian-li, Li Xiao-long, Yao Xue-hua, Ren Wei, Zhang Xia Zeng, Man Ying Kong, Christopher Koon Chi Lai, Suet Yi Lee, Ngai Chong Tsang, M. M. O’Donoghue, M. V. Boost, L. K. P. Suen, G. K. Siu, K. W. Mui, C. K. C. Lai, D. N. C. Tsang, Yuka Sato, Mariko Tateishi, Mutsuko Mihashi, Jose Paulo Flor, Marko Bautista, V. Jay De Roxas, Justine Vergara, Nicolo Andrei Añonuevo, Marion Kwek, Jose Acuin, Anna Josea Sanchez, Avel Bathan, Jamilah Binte Jantan, Chua Chor Guek, Eu Chiow Kian, Pampe Anak Pirido, Nur Fadilah Binte Mohd Aron, Leah May Estacio, Francis Alvarez Palana, Michelle Gracia, Nur Syafiqah Binte Shamsuddin, Kersten Timbad Castro, Madonna Baloria, Faezah Binte Adam, Zhang Wei, Poh Bee Fong, Marimuthu Kalisvar, I-Ju Chuang, Yi-ChunCho, Yu-Fen Chiu, Lung-Chih Chen, Yi-Chun Lin, Shao-Xing Dong, Yi-Chieh Lee, Hui-Chen Kuan, Hsin-Hua Lin, Chia-Chun Chi, Chin-Te Lu, Tang Ya-Fen, Su Li-Hsiang, Liu Jien-Wei, Hsuehlan Chao, PinRu ChangChien, WeiFang Chen, ChungHsu Lai, Lutfe Ara, Syed Mohammad Niaz Mowla, Shaikh Mahmud Kamal Vashkar, Wai Fong Chan, Mabel Yin ChunYau, Karen Kam LingChong, Tze OnLi, Rajwinder Kaur, Ng Po Yan, Gloria Chor Shan Chiu, Christina W. Y. Cheung, Patricia T. Y. Ching, Radley H. C. Ching, Conita H. S. Lam, C. H. Kan, Shirley S. Y. Lee, C. P. Chen, Regina F. Y. Chan, Annie F. Y. Leung, Isadora L. C. Wong, S. S. Lam, Queenie W. L. Chan, Cecilia Chan, Seyed Sadeq Seyed Nematian, Charles John Palenik, Mehrdad Askarian, Nahid Hatam, Itaru Nakamura, Hiroaki Fujita, Ayaka Tsukimori, Takehito Kobayashi, Akihiro Sato, Shinji Fukushima, Tetsuya Matsumoto, V. James De Roxas, V James De Roxas, Nicolo AndreiAñonuevo, Yeng May Ho, Jia Qi Kum, Bee Fong Poh, Kalisvar Marimuthu, Tzu-Yin Liu, Sin-Man Chu, Hui-Zhu Chen, Tun-chieh Chen, Yichun Chen, Ya-Ching Tsao, Sumawadee Skuntaniyom, Pirawadee Tipluy, Sangwan Paengta, Ratchanee wongsaen, Sutthiphun thanomphan, Samettanet Tariyo, Buachan Thongchuea, Pattama Khamfu, Sutthiphan Thanomphan, Wipaporn Natalie Songtaweesin, Suvaporn Anugulruengkit, Rujipat Samransamruajkit, Darintr Sosothikul, Ornanong Tansrijitdee, Anry Nakphunsung, Patchareeyawan Srimuan, Jirachaya Sophonphan, ThanyaweePuthanakit, Kunyanut Payuk, Wilawan Picheansathian, Nongkran Viseskul, Elizabeth DeNardo, Rachel Leslie, Todd Cartner, Luciana Barbosa, Heinz-Peter Werner, Florian H. H. Brill, Julia Yaeko Kawagoe, Elizabeth De Nardo, Sarah Edmonds- Wilson, David Macinga, Patricia Mays-Suko, Collette Duley, Tran Thi Thuy Hang, Tran Thi My Hanh, Christopher Gordon, Roopa Durairaj, Anusha Rohit, Saujanya Saravanakumar, Jothymani Hemalatha, Ryuichi Hirano, Yuichi Sakamoto, Shoji Yamamoto, Naoki Tachibana, Miho Miura, Fumiyo Hieda, Yoshiro Sakai, Hiroshi Watanabe, Silverose Ann Bacolcol, Keitleen Chavez, Jia-Wei Lim, Aung-Aung Hein, Grace Tin, Vanessa Lim, Huwi-chun Chao, Chiu-Yin Yeh, Mei-feng Lo, Chonlada Piwpong, Songyos Rajborirug, Ploypailin Preechawetchakul, Yada Pruekrattananapa, Tharntip Sangsuwan, Ratchanee Wongsaen, Sungwan Paengta, Napatnun Nilchon, Sutthipun Thanompan, Samattanet Tariyo, Svetlana Kolesnichenko, Yerbol Tishkambayev, Asylkhan Alibecov, Yekaterina Serbo, Youngwon Nam, Jae Hyeon Park, Yun Ji Hong, Taek Soo Kim, Jeong Su Park, Kyoung Un Park, Eui-Chong Kim, Samuel Abumhere Aziegbemhin, Onaiwu Enabulele, Yao-Shen Tung, An-Chi Chen, Shen-Min Huang, Yui-Yein Yang, Li-Hung Wu, Chin-cheng Lin, Tzu Hao Lien, Jia Hao Chang, Yu Shan Huang, Yi Shun Chen, Sasithorn Sirilun, Phisit Ouirungroj, Suwanna Trakulsomboon, Patcharee Prasajak, Maryanne W. N. Kwok, Lady S. H. Ng, Lindy M. T. Wong, Lenina S. L. Poon, Mary K. L. Lai, Holly H. S. Cheng, S. K. Fong, Cindy F. Y. Leung, Jumpei Hasegawa, Hiroki Shirakawa, Sachiko Wakai, Makiko Mieno, Shuji Hatakeyama, Manu Deeudom, Prasit Tharavichitkul, Terrence Chinniah, Jackson Tan, Kavitha Prabu, Sartaj Alam, Aung Kyaw Wynn, Rashidah Ahmad, Amalina Sidek, Dg Azizah Samsuddin, Noraini Ajis, Aliyah Ahmad, Susylawathi Magon, Boon Chu, Jiqiu Kuang, Yan Gao, Shoujun Wang, Yunxiao Hao, Rong Liu, Dongmei Li, Hui Wang, Hisanori Nishio, Hitomi Mori, Yoshiko Morokuma, Takaaki Yamada, Makiko Kiyosuke, Sachie Yasunaga, Kazuhiro Toyoda, Nobuyuki Shimono, Dmitriy Babenko, Anar Turmuhambetova, Antonella Cheşcă, Mark A. Toleman, Lyudmila L. Akhmaltdinova, Mark Albert Magsakay, Angelo Macatibag, Jeannica Kriselle Lerios, Alyona Lavrineko, Dmitry Babenko, Eugene Sheck, Mikhail Edelstein, Lih-Yue Li, Chiung-Wen Chan, Hui-Chuan Pan, Wipa Vanishakije, Warisra Jaikampun, Su-Yin Li, Jian-Feng Li, Yu-Ping Wu, Chiao-Hui Lin, Ping-Chin Chang, Samatanet Tariyo, Suttsiphan Thanompan, Suchada Sukkra, Khalequ Zaman, Sheikh Farzana Zaman, Farzana Zaman, Asma Aziz, Sayeed-Bin Faisal, Magali Traskine, Javier Ruiz-Guiñazú, Dorota Borys, Wendy Wai Yee Lam, May Chow, Lucy Choy, Joseph Kam, Sharifah Azura Salleh, Razila Yacob, Siti Rokiah Yusof, Nordiah Awang Jalil, Maria Lourdes Millan, Jose Lito Acuin, Melecia A. Velmonte, Silverose Ann A. Bacolcol, Ching-I Ting, Sunisa Dissayasriroj, Terrence Rohan Chinniah, Jauharatud DiniSuhaimi, Aizzuddin Mirasin, Nurul Morni, Azizah Samsuddin, Amalina AbuBakar, Amanie Shafiee, Julaini Safar, Leung Annie, Fung Yuk Ling, Lau Edna, Luk Kristine, Satoshi Shinomiya, Kumiko Yamamoto, Kayoko Kjiwara, Mitsuhiro Yamaguchi, Wei Zhang, Bee-Fong Poh, Ming-Chin Chan, Chih-Chien Wang, Huan-Yu Huang, Chiung-Ling Lai, Sajeerat Kosol, Wantana Sakolwirat, Patchanee Paepong, Sawalee Jansanga, Pattarin Jaisamoot, Nuttha Thongnuanual, Chittima Srithong, Somporn Somsakul, Sutima Plongpunth, Mukkapon Punpop, Porntip Malathum, Kulada Peautiwat, Nattawipa boon kirdram, Pimpaporn Klunklin, Geetha Samethadka, Naoko Suzuki, Hitomi Asada, Masao Katayama, Atsushi Komano, Hidehiro Watanabe, Hye Kyung Seo, Joo-Hee Hwang, Myoung Jin Shin, Su Young Kim, Eu Suk Kim, Kyoung-Ho Song, Hong Bin Kim, Lai-Si Un, Choi-Ian Vong, Jocelyn Koh, Sherly Agustinus, Rozita Bte Abu Hassan, Yin Phyu Thinn, Benjamin Ng, Soe Pyae Tun, Su Mon Thi Ha, Xue Xiaoting, Lin Li, Leyland Chuang, Attanayaka Mudiyanselage Chulani Niroshika, Kaluarachchige Anoma Kaluarachchi Perera, Dimingo Kankanamalage Diana Grace Fernando, Bodhipakshage Rohini Hemamala, Chiu-yin Yeh, Hui-Chun Yang, Hsiang-Ju Chiu, Ya-Ling Shih, Yu-Shan Chien, Wan-Yi Lin, Chia-Yun Pan, Ying-Yun Chang, Chiu-Yuch Yea, Ming-Hsien Chu, Li-Chu Lee, Lin Yu-Hsiu, Guo Siao-Pei, Leung Pak-On, Sie Mei-Fe, Chen Jyh-Jou, Chang Yong-Yuan, Shu-Yuan Kuo, Yu-Hsiu Lin, Ji-Sheng Zhang, Pak-On Leung, Mei-Fe Sie, Jyh-Jou Chen, Yan-Ru Chen, Ying-Ling Chen, Chi-Fen Taou, Hsiao-Shan Chen, Hung-Jen Tang, Shin Yu Chen, Yin Yin Chen, Fu Der Wang, Tzu-Ping Shih, Chin-Yu Chen, Su-Jung Chen, Mei-chi Wu, Wan-ju Yang, Mei-ling Chou, Man-Ling Yu, Li-Chu Li, Cheng-Wei Chu, Wen-Hao Tsou, Wen-Chih Wu, Wen-Chi Cheng, Cho-Ching Sun, Shu-Hua Lu, Hsin-Ling Yang, Cheng-Yu Lu, Nitchawan Hirunprapakorn, Sirilux Apivanich, Ttipakorn Pornmee, Chonnikarnt Beowsomboon, Itthaporn Kumkoom, Nongyao Kasatpibal, Jittaporn Chitreecheur, JoAnne D. Whitney, Surasak Saokaew, Kirati Kengkla, Margaret M. Heitkemper, Thanomvong Muntajit, Siriluk Apivanich, Hang Thi Phan, Anh Pham Phuong Dinh, Tuyet Thi Kim Nguyen
Prevalence, identification of virulence factors, O-serogroups and antibiotic resistance properties of Shiga-toxin producing Escherichia coli strains isolated from raw milk and traditional dairy products
Springer Science and Business Media LLC - Tập 7 - Trang 1-11 - 2018
Reza Ranjbar, Farhad Safarpoor Dehkordi, Mohammad Hossein Sakhaei Shahreza, Ebrahim Rahimi
Shiga-toxigenic Escherichia coli strains are one of the most important foodborne bacteria with an emergence of antibiotic resistance. Foodborne STEC strains are mainly associated with presence of certain virulence factors and O-seogroups. The present investigation was done to study the distribution of virulence factors, O-serogroups and antibiotic resistance properties of Shiga-toxigenic Escherichia coli isolated from milk and dairy products. Six-hundred samples were randomly collected and immediately transferred to laboratory. All samples were cultured and E. coli strains were isolated. STEC strains were identified based on the presence of putative virulence factors and subtypes. STEC isolates were subjected to multiplex PCR and disk diffusion methods. One-hundred and eighty-one out of 600 samples (30.16%) harbored E. coli. Prevalence of STEC strains was 10.66%. O157 (43.75%) and O26 (37.50%) were the most frequently identified serogroups. Aac(3)-IV (100%), CITM (96.87%) and tetA (76.56%) were the most commonly detected antibiotic resistance genes. STEC strains had the highest prevalence of resistance against ampicillin (100%), gentamicin (100%) and tetracycline (96.87%). Kashk and dough were negative for presence of E. coli strains. High prevalence of resistant-O157 strains and simultaneous presence of multiple virulence factors pose an important public health problem regarding the consumption of raw milk and dairy products.
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