Antibiotic Susceptibility Patterns of Bacterial Isolates from Routine Clinical Specimens from Referral Hospitals in Tanzania: A Prospective Hospital-Based Observational Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Antimicrobial resistance is one of the biggest threats of modern public health. Although sub-Saharan Africa is highly burdened with infectious diseases, current data on antimicrobial resistance are sparse. Methods: A prospective study was conducted between October 2018 and September 2019 to assess the antibiotic susceptibility patterns of clinical bacterial isolates obtained from four referral hospitals in Tanzania. We used standard media and Kirby-Bauer disc diffusion methods as per Clinical and Laboratory Standards Institute (CLSI) standards. Results: We processed a total of 2620 specimens of which 388 (14.8%) were culture-positive from patients with a median (IQR) age of 28 (12– 44) years. Of the positive cultures, 52.3% (203) were from females. Most collected specimens were ear pus 28.6% (111), urine 24.0% (93), wound pus 20.6% (80), stool 14.9% (58), and blood 8.3% (32). Predominant isolates were S. aureus 28.4% (110), E. coli 15.2% (59), P. aeruginosa 10.6% (41), P. mirabilis 7.0% (27), V. cholerae 01 Ogawa 6.2% (24), Klebsiella spp. 5.2% (20) and Streptococcus spp. 4.6% (18). Generally, the isolates exhibited a high level of resistance to commonly used antibiotics such as Ampicillin, Amoxicillin-Clavulanic acid, Erythromycin, Gentamicin, Tetracycline, Trimethoprim, third-generation Cephalosporins (Ceftriaxone and Ceftazidime), and reserved drugs (Clindamycin and Meropenem). S. aureus isolates were resistant to most of the antibiotics tested; 66.7% were classified as MRSA infections. Conclusion: Antibiotic resistance to commonly prescribed antibiotics was alarmingly high. Our findings emphasize the need for comprehensive national control programs to combat antibiotic resistance. Keywords: antibiotics, antimicrobial resistance, AMR, antibiotic susceptibility testing, methicillin-resistant Staphylococcus aureus , MRSA, bacterial isolates
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it