ArticleThe Journal of antimicrobial chemotherapy2024
Linking epidemiological and genomic data in cases of enteric fever in England to inform clinical management and public health action.
Article in The Journal of antimicrobial chemotherapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Research progress on immunoprotective mechanisms of enteric fever and vaccine development.Journal of advanced research · 2026Review
- Enhancing antimicrobial resistance surveillance and research: a systematic scoping review on the possibilities, yield and methods of data linkage studies.Antimicrobial resistance and infection control · 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
7 authors.
Funding
Abstract
objectivesTo explore the feasibility of linking data from enhanced surveillance patient questionnaires from each enteric fever case in England with genome sequencing data, including antimicrobial resistance (AMR) profiles, from the corresponding isolate of typhoidal salmonellae.
methodsAfter linking data we interrogated the merged dataset and assessed the utility of passive surveillance data to match and monitor antimicrobial treatment regimens in enteric fever patients with the AMR profiles of the infectious agent.
resultsA high proportion of cases were given antibiotics (n = 1230/1415; 86.9%); half of the cases stated the class of antibiotic they were given (n = 630/1239) and half were prescribed cephalosporins (n = 316/630). Reported treatment with a combination of antibiotics increased with symptom severity. Nearly half of isolates (n = 644/1415; 45.5%) had mutations conferring resistance to ciprofloxacin. Based on genome-derived AMR profiles, typhoidal salmonellae isolates inferred to be susceptible to the recommended first-line antimicrobials were twice as likely to be isolated from individuals residing in the least deprived areas compared with the most deprived (n = 26/169; 15.4% versus n = 32/442; 7.2%).
conclusionsDue to the high proportion of missing data obtained from patient interviews, we recommend a more transparent and systematic approach to recording the antibiotic prescription details by healthcare professionals in primary and secondary care. A more robust approach to data capture at this point in the care pathway would enable us to audit inconsistencies in the prescribing algorithms across England and ensure equitable treatment across all sections of society. Integrating prescribing data with the genome-derived AMR profiles of the causative agent at the individual patient level provides an opportunity to monitor the impact of treatment on clinical outcomes, and to promote best practice in real time.
Indexed as
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.