Genomic and clinical characteristics of campylobacteriosis in Australia
Notice bibliographique
Résumé
Abstract Campylobacter spp. are a common cause of bacterial gastroenteritis in Australia, primarily acquired from contaminated meat. We investigated the relationship between genomic virulence characteristics and the severity of campylobacteriosis, hospitalisation, and other host factors. We recruited 571 campylobacteriosis cases from three Australian states and territories (2018–2019). We collected demographic, health status, risk factors, and self-reported disease data. We whole genome sequenced 422 C. jejuni and 84 C. coli case isolates along with 616 retail meat isolates. We classified case illness severity using a modified Vesikari scoring system, performed phylogenomic analysis, and explored risk factors for hospitalisation and illness severity. On average, cases experienced a 7.5-day diarrhoeal illness with additional symptoms including stomach cramps (87.1%), fever (75.6%), and nausea (72.0%). Cases aged ≥75 years had milder symptoms, lower Vesikari scores, and higher odds of hospitalisation compared to younger cases. Chronic gastrointestinal illnesses also increased odds of hospitalisation. We observed significant diversity among isolates, with 65 C. jejuni and 21 C. coli sequence types. Antimicrobial resistance genes were detected in 20.4% of isolates, but multidrug resistance was rare (0.04%). Key virulence genes such as cdtABC ( C. jejuni ) and cadF were prevalent (>90% presence) but did not correlate with disease severity or hospitalisation. However, certain genes appeared to distinguish human C. jejuni cases from food source isolates. Campylobacteriosis generally presents similarly across cases, though some are more severe. Genotypic virulence factors identified in the literature to-date do not predict disease severity but may differentiate human C. jejuni cases from food source isolates. Host factors like age and comorbidities have a greater influence on health outcomes than virulence factors. Author summary This study focused on Campylobacter, a common cause of gastroenteritis in Australia. We explored the relationship between Campylobacter’s genomic characteristics and disease severity, hospitalisation, and host-related factors. In 2018 – 2019, we collected data from 571 campylobacteriosis cases from Eastern Australia, focusing on demographics, health status, risk factors, and self-reported symptoms. We sequenced 422 C. jejuni and 84 C. coli case isolates and 616 retail meat isolates. We used a modified Vesikari scoring system to assess illness severity, performed phylogenomic analysis, and explored hospitalisation and severity risk factors. Cases experienced an average 7.5-day period of diarrhoea with additional symptoms including stomach cramps, fever, and nausea. Older individuals (75+ years) had milder symptoms but a higher chance of hospitalisation. Those with chromic gastrointestinal conditions faced increased hospitalisation odds. Case isolates showed considerable diversity. Antimicrobial resistance genes were detected in some isolates, but multidrug resistance was rare. Virulence genes did not predict severity or hospitalisation, but some genes did differentiate between case and food source C. jejuni isolates. Host-related factors including age and comorbidities are more important in determining health outcomes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».