Standard of dental prescriptions for antibiotics dispensed in the systempublic oral health services in the state of Minas Gerais
Notice bibliographique
Résumé
Antibiotics, along with analgesics and anti-inflammatory drugs, are the most commonly used medications in dentistry. The prescription of antibiotics by dental surgeons happens all over the world, and the irrational use of these drugs can result in therapeutic failure, increased risk of adverse reactions and economic impact, besides being the main cause of antimicrobial resistance. The literature points out that pain of dental origin is rarely caused by a bacterial infection requiring antibiotic medication and is usually best managed with the use of analgesics and local dental procedures. The results of surveys conducted in England and Canada suggest that antibiotic prescriptions by dental surgeons are increasing alarmingly. It is also known that the pattern of antibiotic prescribing can be influenced by both clinical and non clinical factors. In this sense, generating information on antibiotic consumption is essential for countries to adopt measures to raise awareness among the population and health professionals about the appropriate use of these drugs, monitor the impact of interventions, and improve the process of acquiring, prescribing, and dispensing these drugs. The aim of this study was to analyze the possible association between dental antibiotic prescriptions in the public sector of a southeastern Brazilian state, health services characteristics, and municipal social characteristics. The study design was of the ecological type, the year analyzed was 2017, and the data were obtained from the database of the Integrated Pharmaceutical Assistance Management System. The outcome variable of the first article of this PhD Thesis was the number of Defined Daily Doses (DDD) per 1,000 inhabitants/year of the municipalities. The outcome variable of the second article was the municipalities' adherence to a dental prescription information system. The database was analyzed initially in Excel version 2016 program (Microsoft, Seattle, USA) and later in SPSS version 25.0 program (IBM SPSS Statistics for Windows, Armonk, NY, USA). The CART (Classification And Regression Tree) technique was used to determine the influence of the social characteristics of the municipalities (Human Development Index, Gini Index, proportion of rural population, proportion of beneficiary families of the Bolsa Família Program, rural/urban typology, whether or not the municipality is the headquarters of a Dental Specialties Center, seat of a Health Macro-region and Microregion) and the characteristics of oral health services (oral health coverage in the Family Health Strategy and Primary Health Care, population coverage of first dental consultation, number of dentists and oral health teams per 1000 inhabitants, and percentage of individual preventive and restorative dental procedures). Antibiotics were the most prescribed drugs by dental surgeons in the public sector surveyed, with penicillins being the most prescribed group. The overall average of DDD/1000hab/year, for the 421 municipalities surveyed, was 96.54. It was concluded that socioeconomic factors and organization of health services were associated with the use of antibiotics. There is a need for advances in the surveillance of antibiotic prescribing in public oral health services in the state of Minas Gerais
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 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 ».