Antibiotic prescribing practices for hospitalised children with suspected bacterial infections in a paediatric hospital in Nigeria
Notice bibliographique
Résumé
Background: The burden of infectious diseases among Nigerian children is high. These children are often prescribed antibiotics during periods of hospitalisation. Unfortunately antibiotic resistance (ABR) threatens the availability and efficacy of antibiotics for use by vulnerable children and the future generations. Monitoring prescribing trends in our hospital as a means of identifying targets for improving prescribing is inevitable.Objective: The aim of the study was to evaluate antibiotic prescribing practices for hospitalised children with suspected bacterial infections in a Paediatric hospital in Nigeria.Methods: A retrospective survey was carried out using case notes of previously hospitalised patients admitted between January and June 2016. Data from 150 case notes of patients admitted for suspected bacterial infections were collected using a predesigned data collection form. Patients’ demographics, infection type, details of prescribed antibiotics, length of hospital stay and microbiological assessments were noted. Data were analysed using statistical package for social sciences (SPSS) version 22. Frequencies and percentages were calculated for categorical variables. Means and standard deviations were calculated for continuous (numerical) variables. Correlation was also employed in the analysis.Results: Of the 150 patients, 53.3% were males and 86% were children under 5 years of age. The mean duration of hospital stay was 7.59 (± 5.4) days. The most common infections were respiratory tract infection (32%) and sepsis (31.3%). The most common empirically prescribed antibiotics at the onset of admission were Gentamicin and a fixed dose combination of Ampicillin/Cloxacillin which were prescribed for 64.7% and 52.7% of the patients respectively. Cultures were ordered for only 7 (4.7%) of patients at the onset of hospitalisation. All antibiotics administered on admission were parenteral formulations and only 4% of the patients had their antibiotic switched to oral route on or before the third day of patients’ admission. Another 71.3% were converted to oral formulations on the day of discharge from the hospital. A total of 87.3% were discharged on antibiotics and the most commonly prescribed antibiotic at discharge was Cefixime (37.2% of antibiotics prescribed as take home medication).Conclusions: Antibiotics were started empirically in all cases and cultures were ordered for few patients at the start of antibiotic therapy. Cultures should be more frequently ordered in the hospital to guide antibiotic prescribing for patients admitted for suspected bacterial infections. In addition, timely intravenous (IV) to oral (PO) antibiotic switch should be practised whenever appropriate. Educating physicians on the benefits of early switch from IV to PO formulations when appropriate is also recommended. Initiatives such as the “Antibiotic Time out” or Start Smart-then Focus approach will be appropriate in the hospital. Introduction of an empiric antibiotic policy in the hospital is highly recommended.
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 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».