ReviewJAC-antimicrobial resistance2024
Antibiotic prescribing and bacterial infection in COVID-19 inpatients in Southeast Asia: a systematic review and meta-analysis.
Review in JAC-antimicrobial resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Changes in the Epidemiology of Multidrug-Resistant Organisms During the COVID-19 Pandemic: A Six-Year Retrospective Study at a Tertiary Care Hospital in Northeastern Thailand.Medical sciences (Basel, Switzerland) · 2026Observational
- Antibiotic use in patients with severe acute respiratory syndrome due to SARS-CoV-2 in a Brazilian University Hospital (2020-2021).Antimicrobial stewardship & healthcare epidemiology : ASHE · 2026Article
- The overuse of antimicrobials during the COVID-19 pandemic: data from 25 general hospitals in Shanxi, China.BMC infectious diseases · 2025Article
- Increase in Antibiotic Utilisation in Primary Care Post COVID-19 Pandemic.Antibiotics (Basel, Switzerland) · 2025Article
- Host gene expression in the Nasopharynx can discriminate microbiologically confirmed viral and bacterial lower respiratory tract infection.Journal of clinical and translational science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The prescribing of antibiotics to treat COVID-19 patients has been observed to occur frequently, often without clear justification. This trend raises concerns that it may have exacerbated antimicrobial resistance (AMR). Despite longstanding concerns over AMR in Southeast Asian countries, data on this issue are notably lacking. Objectives: To explore the impact of COVID-19 on antibiotic prescribing, bacterial infection prevalence and common resistant pathogens in COVID-19 inpatients. Methods: We searched PubMed, EMBASE, Web of Science and ThaiJO (a Thai academic database) to identify studies conducted in ASEAN member countries and published between December 2019 and March 2023. Screening and data extraction were done by two independent reviewers, with results synthesized using random-effects meta-analyses and descriptive statistical analyses. This review was registered with PROSPERO (CRD42023454337). Results: Of the 29 studies (19 750 confirmed COVID-19 cases) included for final analysis, the antibiotic prescribing rate was 62.0% (95%CI: 46.0%-76.0%) with a prescribing rate of 58.0% (21.0%-91.0%) in mild/moderate cases versus 91.0% (82.0%-98.0%) in severe/critical cases. Notably, 80.5% of antibiotics prescribed fall under the WHO AWaRe 'Watch' list, followed by 'Access' at 18.4% and 'Reserve' at 1.0%. The reported bacterial infection prevalence was 16.0% (7.0%-29.0%), with Conclusions: High antibiotic prescribing rates, disproportionate to bacterial infections and varying practices for COVID-19 inpatients across countries highlight the urgent need for this region to collaborate to tackle and mitigate AMR.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.