Resistance Profile of Klebsiella pneumoniae Strains Isolated at the Yaounde General Hospital and the Yaounde Gyneco-Obstetric and Pediatric Hospital
Bibliographic record
Abstract
Introduction: Dissemination of resistant bacteria is responsible for a considerable increase in mortality, morbidity and cost of treatment. Our study aimed to determine the frequency of Klebsiella pneumoniae infections in two referral hospitals in Yaounde Cameroon, and to examine the antibiotic resistance profile. Methods: A cross-sectional descriptive study was carried out for a five-month period. Samples were collected from in and out- patients at the Yaounde General Hospital and at the Yaounde Gyneco-Obstetric and Pediatric Hospital. The bacteria isolation was done using standard bacteriological procedures and the identification of Klebsiella pneumoniae species was done using API 20E sytem (Biomerieux). Antibiotic susceptibility testing was determined using the disc diffusion method on Mueller Hinton media and the interpretation of the antibiogram was performed as recommended by the Comité de l’Antibiogramme de la Société Française de Microbiologie (2019). The data collected were analyzed with Epi Info 7.0 software and Excel 2013. Results: The frequency of Klebsiella pneumoniae infections was 2.48% (52/2096). The majority of Klebsiella pneumoniae strains were isolated from urinary tract infections 55.77% (29/52). Most isolates were recovered from in-patients 63.46% (33/52) received at the pediatrics unit 25.0% (13/52). Few isolates were resistant to imipenem and meropenem with a resistance rate of 3.85% (2/52) each, while a considerable number of isolates were highly resistant to antibiotics such as ticarcillin 96.15% (50/52), amoxicillin + clavulanic acid 94.23% (49/52) and piperacillin 86.54% (45/52). The majority of isolates 73.08% (38/52) were multidrug-resistant and one isolate was resistant to all tested antibiotics (superbug). Conclusion: More than half of the isolates were multidrug-resistant and one isolate from an in-patient was found to be resistant to all tested antibiotics. These findings demonstrate the importance of establishing an effective surveillance system for antimicrobial resistance in Cameroon.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".