SynthesisAntimicrobial resistance and infection control2019
Using the best available data to estimate the cost of antimicrobial resistance: a systematic review.
Synthesis in Antimicrobial resistance and infection control, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.
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
34 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Antibacterial and Antioxidant Effects of Grape Seed Varieties in Iran: A Systematic Review.Veterinary medicine and science · 2026Pooled it
- Economic Evaluation of Interventions to Reduce Antimicrobial Resistance: A Systematic Literature Review of Methods.PharmacoEconomics · 2025Pooled it
- The impact of inpatient bloodstream infections caused by antibiotic-resistant bacteria in low- and middle-income countries: A systematic review and meta-analysis.PLoS medicine · 2023Pooled it
- Pooled it
- Understanding Recent Developments in Colistin Resistance: Mechanisms, Clinical Implications, and Future Perspectives.Antibiotics (Basel, Switzerland) · 2025Review
- Can We Lower the Burden of Antimicrobial Resistance (AMR) in Heavily Immunocompromised Patients? A Narrative Review and Call to Action.Infectious diseases and therapy · 2025Review
- Adaptive Resistance ofMicroorganisms · 2025Article
- Observational
- From wastewater to resistance: characterization of multidrug-resistant bacteria and assessment of natural antimicrobial compounds.Frontiers in microbiology · 2025Article
- An Evidence-Based Serious Game App for Public Education on Antibiotic Use and Resistance: Randomized Controlled Trial.JMIR serious games · 2024Article
- Burden of Antimicrobial Resistance in Japan: A Systematic Literature Review and Meta-Analysis.Infectious diseases and therapy · 2024Article
- Resistance to first-line antibiotic therapy among patients with uncomplicated acute cystitis in Melbourne, Australia: prevalence, predictors and clinical impact.JAC-antimicrobial resistance · 2024Article
- An Evidence-Based Serious Game App for Public Education on Antibiotic Use and Antimicrobial Resistance: Protocol of a Randomized Controlled Trial.JMIR research protocols · 2023Article
- Attributable Patient Cost of Antimicrobial Resistance: A Prospective Parallel Cohort Study in Two Public Teaching Hospitals in Ghana.PharmacoEconomics - open · 2023Article
- Bacterial resistance to antibacterial agents: Mechanisms, control strategies, and implications for global health.The Science of the total environment · 2023Review
- New MraYAntibiotics (Basel, Switzerland) · 2022Article
- Evaluation ofOman medical journal · 2022Article
- Modelling the Future Clinical and Economic Burden of Antimicrobial Resistance: The Feasibility and Value of Models to Inform Policy.Applied health economics and health policy · 2022Review
- Exploring the economic impact of inappropriate antibiotic use: the case of upper respiratory tract infections in Ghana.Antimicrobial resistance and infection control · 2022Article
- Mortality, Length of Stay, and Healthcare Costs Associated With Multidrug-Resistant Bacterial Infections Among Elderly Hospitalized Patients in the United States.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022Article
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: Valuation of the economic cost of antimicrobial resistance (AMR) is important for decision making and should be estimated accurately. Highly variable or erroneous estimates may alarm policy makers and hospital administrators to act, but they also create confusion as to what the most reliable estimates are and how these should be assessed. This study aimed to assess the quality of methods used in studies that quantify the costs of AMR and to determine the best available evidence of the incremental cost of these infections. Methods: In this systematic review, we searched PubMed, Embase, Cinahl, Cochrane databases and grey literature sources published between January 2012 and October 2016. Articles reporting the additional burden of Results: Of 1094 identified studies, we identified 12 peer-reviewed articles and two reports that quantified the economic burden of clinically important resistant infections. Two studies used multi-state modelling to account for the timing of infection minimising the risk of time dependent bias and these were considered to generate the best available cost estimates. Studies report an additional CHF 9473 per extended-spectrum beta-lactamases -resistant Conclusions: Implementation of AMR policy and decision-making should be guided only by reliable, unbiased estimates of effect size. Generating these estimates requires a thorough understanding of important biases and their impact on measured outcomes. This will ensure that researchers, clinicians, and other key decision makers concerned with increasing public health threat of AMR are accurately guided by the best available evidence.
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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.