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Enregistrement W2738480806 · doi:10.5451/unibas-006715239

Secondary bacterial infection in Buruli ulcer

2016· dissertation· en· W2738480806 sur OpenAlexfundno aff
Grace Semabia Kpeli

Notice bibliographique

Revueedoc (University of Basel) · 2016
Typedissertation
Langueen
DomaineMedicine
ThématiqueMycobacterium research and diagnosis
Établissements canadiensnon disponible
Organismes subventionnairesInstitute of Infection and ImmunityNoguchi Memorial Institute for Medical Research, University of GhanaUBS Optimus FoundationVolkswagen Foundation
Mots-clésBuruli ulcerMycobacterium ulceransMedicineAntibioticsDiseaseAntibiotic therapyPathogenTransmission (telecommunications)Intensive care medicineTropical diseaseInternal medicineImmunologyBiologyMicrobiology

Résumé

récupéré en direct d'OpenAlex

Abstract
\nBuruli ulcer (BU) is a chronic debilitating disease of the skin and soft tissues caused by Mycobacterium ulcerans. It is one of the 17 neglected tropical diseases according to the World Health Organization and has been reported in over 30 countries with tropical and sub-tropical conditions globally. M. ulcerans is traditionally considered as an environmental pathogen and even though BU was discovered over half a century ago, the environmental reservoir and exact mode of transmission of this pathogen remain obscure. This makes it challenging to formulate strategies for its prevention. As such, control strategies geared towards the early detection and treatment of cases are vital to minimize morbidity, disability and the socio-economic burden associated with the disease. The introduction of antibiotic therapy for treatment in 2004 to replace surgery as first-line therapy has brought about an improvement in the management of the disease. However, despite reported successful outcomes with the antibiotic treatment, the healing process is still characterized by long hospitalizations as a result of delayed wound closure.
\nIn this thesis, we explored the factors which could contribute to the observed delayed wound healing in two BU treatment centers in Ghana; the Ga-West Municipal Hospital and the Obom Health Center. Through a combination of clinical, microbiological and histopathological analysis, we identified secondary infection of BU lesions by other bacteria as a major cause of delayed healing. Through quantitative microbiological studies, we analysed the evolution of the bacterial burden and identified increased loads of bacteria post treatment which could negatively impact on the healing potential of the wounds. Furthermore, we explored co-infection with Human immunodeficiency virus (HIV) in the Ga-West Municipal Hospital as a challenge to the management of BU and described challenges associated with the management of this co-infection. Studying the isolated bacterial species through phenotypic, molecular and whole genome approaches helped to identify health-care associated transmission through health workers and equipment as well as self transmission as potential sources of wound infection within the health centers. With these results, we made recommendations for the improvement of wound management in the health centers and made a case for the need for wound management guidelines which were absent in the health centers. We followed this up with the development of local guidelines for wound care and the implementation of several interventions in the health centers. We also identified antibiotic resistance as an increasing problem and described in detail through whole genome sequencing, a recently emerged and rapidly spreading clone of community acquired methicillin resistant Staphylococcus aureus with sequence type 88 in Ghana which has the potential to become a serious public health threat with implications for healthcare. This alarming result therefore calls for the urgent establishment of a surveillance system to monitor the use and distribution of antibiotics in Ghana and the emergence of antibiotic resistant pathogens.
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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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,559
Score d'incertitude au seuil0,987

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0140,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,245
Écart entre enseignants0,236 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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