Investigating the Effect of Antibiotic Exposure on the Prevalence of Antibiotic-resistant H. pylori Infection and the Incidence of Anti-H. pylori Treatment Failure in Northern Canadian Communities
Notice bibliographique
Résumé
The frequent and improper use of antibiotics for the treatment of unrelated bacterial infections is believed to influence the development of antibiotic-resistant H. pylori infection. Antibiotic-resistant H. pylori infection is a major risk factor for the failure of anti-H. pylori treatment regimens to eliminate the infection. Considering the limited therapeutic options available to eliminate H. pylori infection, it is of public health interest to better understand factors that impact the occurrence of antibiotic resistance in H. pylori to inform strategies to prevent its occurrence and improve the effectiveness of anti-H. pylori treatment regimens. Northern Canadian Aboriginal communities are disproportionately affected by H. pylori infection relative to southern Canadian communities. In response to community concerns regarding H. pylori-associated health outcomes, the Canadian North Helicobacter pylori (CANHelp) Working Group conducts community-driven research to inform public health policy pertaining to control of H. pylori infection. One aim of the CANHelp Working Group is to improve the clinical management of H. pylori infection in northern Canadian communities by identifying factors that limit the effectiveness of anti-H. pylori treatment regimens. To better understand factors associated with antibiotic-resistant H. pylori infection and anti-H. pylori treatment effectiveness, this thesis aims to estimate among CANHelp project participants the effect of exposure to antibiotics on the prevalence of antibiotic-resistant H. pylori infection and incidence of anti-H. pylori treatment failure. I completed a systematic review of the literature published during 2010 to 2014 to synthesize current evidence of the prevalence of antibiotic-resistant H. pylori infection worldwide and antibiotic resistance mechanisms in H. pylori infection. To estimate the effect of antibiotic exposure on the prevalence of antibiotic-resistant H. pylori infection and the incidence of anti-H. pylori treatment failure, I developed a chart review tool to collect antibiotic exposure histories from participant medical charts for the 5-year period before enrollment in a CANHelp community project for H. pylori-positive participants who either had samples of H. pylori cultured from gastric biopsies or who had completed a post-treatment breath test to classify their post-treatment infection status. I used logistic regression to estimate odds ratios and 95% confidence intervals (CIs) for the effect of antibiotic exposure on the prevalence of antibiotic-resistant H. pylori infection among individuals who had H. pylori organisms cultured from gastric biopsy samples. I used robust Poisson regression and binomial regression to estimate risk ratios with 95% CIs and risk differences with 95% CIs, respectively, for the effect of antibiotic exposure on the average risk of treatment failure among individuals who completed a post-treatment breath test. I also completed a qualitative analysis of semi-structured interviews to describe participants’ perspectives on the value and potential harms of using antibiotics to treat infections and factors that influence their adherence to prescribed regimens. Results of my quantitative analysis provide evidence that suggest a higher frequency of antibiotic exposure was associated with the prevalence odds of antibiotic-resistant H. pylori infection as well as the risk of anti-H. pylori treatment failure in CANHelp communities. Additionally, the results suggest that previous exposure to anti-H. pylori treatment regimens is associated with both the prevalence odds of antibiotic-resistant H. pylori infection and the average risk of anti-H. pylori treatment failure in CANHelp communities. Results of my qualitative analysis provide evidence of widespread knowledge among participants of the importance of adherence to prescribed antibiotics regimens. Factors that influence adherence to prescribed antibiotics most frequently identified by participants included the occurrence of adverse events and forgetfulness. Given that poor adherence to prescribed antibiotic regimens is known to influence the occurrence of antibiotic-resistant bacterial infections, strategies that support individuals to manage adverse events and remember to take their medications may be useful to improve the effectiveness of anti-H. pylori treatment regimens, which would decrease the frequency of repeated exposure to such regimens and, in turn, decrease the occurrence of resistant H. pylori infection.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».