Antimicrobial consumption in hospitalised COVID-19 patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction Despite COVID-19 being a viral illness, antibiotic use has been more prevalent. In addition, co-infection (3.5%) and secondary infection (14.3%) were relatively low in hospitalised patients with COVID-19. A major concern is the increased risk of antimicrobial resistance (AMR) due to inappropriate antibiotic consumption (1). Aim This review aims to evaluate antimicrobial consumption (excluding repurposed drugs such as remdesivir) in hospitals and determine the prevalence of COVID-19 patients who received antibiotic therapy using meta-analysis. Methods The review was conducted according to PRISMA guidelines (2). The two investigators independently developed and applied eligibility criteria to examine original articles. Studies were eligible for inclusion if they met the following criteria: (i) original research studies with a minimum sample of 50 patients; (ii) focussed on antibiotic consumption (AMC); (iii) patients with COVID-19 or consumption amid COVID-19 pandemic; (iv) any age group or gender; and (v) reported in the English language. The included articles were retrieved from MEDLINE, CINAHL, WHO COVID-19 databases, including studies published in EMBASE, Scopus, WHO-COVID, and LILACS between December 2019 to July 2021. The modified version of Newcastle-Ottawa Scale (NOS) was used to measure biases in included studies after the consensus by both authors. The random-effects model was used to estimate the pooled prevalence or proportion of AMC among hospitalized COVID-19 patients. Results A total of 34 studies conducted among hospitalised COVID-19 patients were included. The extracted studies presented AMC in defined daily doses (DDD) or frequency and percentages. Azithromycin was the most frequently prescribed antibiotic in almost all studies. The meta-analysis that examined overall AMC using data from 25 studies (17 studies from high income countries and eight from low-middle income countires) revealed 69% (95% CI:63%-74%) of hospitalized COVID-19 received at least one course of antibiotics. The sub-group analysis of studies from high income countries (HICs) revealed 59% (95% CI: 51%-66%) consumed antibiotics compared with 89% (95% CI: 82% to 94%) among hospitalised COVID-19 patients in low-middle income countries (LMICs). Conclusion This review highlights the trend of antibiotic consumption in hospitalised COVID-19 patients. A significant rise in antibiotic consumption was observed in LMICs and increased antibiotic consumption in the first few months of the COVID-19 pandemic in HIC. The review outcomes emphasised the importance of rational and judicious use of antimicrobial therapy as well as to strenghting the antimicrobial stewardship policies and activities, particularly during a global pandemic. The limitation of the review undertaken was not identified incidence of co-infection and don’t include studies on reported AMC in immunocompromised patients. References (1) Rawson TM, Ming D, Ahmad R, Moore LSP, Holmes AH. Antimicrobial use, drug-resistant infections and COVID-19. Nature reviews Microbiology. 2020;18(8):409-10. (2) Beller EM, Glasziou PP, Altman DG, Hopewell S, Bastian H, Chalmers I, et al. PRISMA for Abstracts: Reporting Systematic Reviews in Journal and Conference Abstracts. PLOS Medicine. 2013;10(4):e1001419.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".