Antibiotic prescribing practices for hospitalised children with suspected bacterial infections in a paediatric hospital in Nigeria
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".