Farzana Refath, Harbarth Stephan Jürgen, Yu Ly-Mee, Carretto Edoardo, Moore Catrin E, Feasey Nicholas Alexander, Gales Ana C, Galal Ushma, Ergonul Onder, Yong Dongeun, Yusuf Md Abdullah, Veeraraghavan Balaji, Iregbu Kenneth Chukwuemeka, van Santen James Anton, Ribeiro Aghata Cardoso da Silva, Fankhauser Carolina Maria, Chilupsya Chisomo Judith, Dolecek Christiane, Ferreira Diogo Boldim, Pinarlik Fatihan, Jang Jaehyeok, Gücer Lal Sude, Cavazzuti Laura, Sultana Marufa, Haque M D Nazmul, Haddad Murielle Galas, Medugu Nubwa, Nwajiobi-Princewill Philip Ifeanyi, Marrollo Roberta, Zhao Rui, Baskaran Vivekanandan B, Peter J V, Chandy Sujith J, Bakthavatchalam Yamuna Devi, Walsh Timothy R
Department of Biology, Ineos Oxford Institute for Antimicrobial Research, University of Oxford, Oxford, UK.
Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland.
JAC Antimicrob Resist. 2025 Mar 26;7(2):dlaf037. doi: 10.1093/jacamr/dlaf037. eCollection 2025 Apr.
This study aimed to evaluate the trends in antimicrobial prescription during the first 1.5 years of COVID-19 pandemic.
This was an observational, retrospective cohort study using patient-level data from Bangladesh, Brazil, India, Italy, Malawi, Nigeria, South Korea, Switzerland and Turkey from patients with pneumonia and/or acute respiratory distress syndrome and/or sepsis, regardless of COVID-19 positivity, who were admitted to critical care units or COVID-19 specialized wards. The changes of antimicrobial prescription between pre-pandemic and pandemic were estimated using logistic or linear regression. Pandemic effects on month-wise antimicrobial usage were evaluated using interrupted time series analyses (ITSAs).
Antimicrobials for which prescriptions significantly increased during the pandemic were as follows: meropenem in Bangladesh (95% CI: 1.94-4.07) with increased prescribed daily dose (PDD) (95% CI: 1.17-1.58) and Turkey (95% CI: 1.09-1.58), moxifloxacin in Bangladesh (95% CI: 4.11-11.87) with increased days of therapy (DOT) (95% CI: 1.14-2.56), piperacillin/tazobactam in Italy (95% CI: 1.07-1.48) with increased DOT (95% CI: 1.01-1.25) and PDD (95% CI: 1.05-1.21) and azithromycin in Bangladesh (95% CI: 3.36-21.77) and Brazil (95% CI: 2.33-8.42). ITSA showed a significant drop in azithromycin usage in India (95% CI: -8.38 to -3.49 g/100 patients) and South Korea (95% CI: -2.83 to -1.89 g/100 patients) after WHO guidelines v1 release and increased meropenem usage (95% CI: 93.40-126.48 g/100 patients) and moxifloxacin (95% CI: 5.40-13.98 g/100 patients) in Bangladesh and sulfamethoxazole/trimethoprim in India (95% CI: 0.92-9.32 g/100 patients) following the Delta variant emergence.
This study reinforces the importance of developing antimicrobial stewardship in the clinical settings during inter-pandemic periods.
本研究旨在评估新冠疫情大流行的前1.5年期间抗菌药物处方的趋势。
这是一项观察性回顾性队列研究,使用了来自孟加拉国、巴西、印度、意大利、马拉维、尼日利亚、韩国、瑞士和土耳其的患者层面数据,这些数据来自入住重症监护病房或新冠专科病房的肺炎和/或急性呼吸窘迫综合征和/或败血症患者,无论其新冠病毒检测结果是否为阳性。使用逻辑回归或线性回归估计大流行前和大流行期间抗菌药物处方的变化。使用中断时间序列分析(ITSA)评估大流行对逐月抗菌药物使用的影响。
在大流行期间处方量显著增加的抗菌药物如下:孟加拉国的美罗培南(95%置信区间:1.94 - 4.07),规定日剂量(PDD)增加(95%置信区间:1.17 - 1.58)以及土耳其的美罗培南(95%置信区间:1.09 - 1.58);孟加拉国的莫西沙星(95%置信区间:4.11 - 11.87),治疗天数(DOT)增加(95%置信区间:1.14 - 2.56);意大利的哌拉西林/他唑巴坦(95%置信区间:1.07 - 1.48),DOT增加(95%置信区间:1.01 - 1.25)且PDD增加(95%置信区间:1.05 - 1.21);孟加拉国(95%置信区间:3.36 - 21.77)和巴西(95%置信区间:2.33 - 8.42)的阿奇霉素。ITSA显示,世界卫生组织v1版指南发布后,印度(95%置信区间:-8.38至-3.49克/100名患者)和韩国(95%置信区间:-2.83至-1.89克/100名患者)的阿奇霉素使用量显著下降,而在德尔塔变异株出现后,孟加拉国的美罗培南使用量增加(95%置信区间:93.40 - 126.48克/100名患者)和莫西沙星使用量增加(95%置信区间:5.40 - 13.98克/100名患者),印度的磺胺甲恶唑/甲氧苄啶使用量增加(95%置信区间:0.92 - 9.32克/100名患者)。
本研究强化了在疫情间歇期临床环境中开展抗菌药物管理的重要性。