Antibiotic Antibiogram in Patients With Complicated Urinary Tract Infections in Nephrology Unit of South Waziristan
Bibliographic record
Abstract
Objectives To evaluate the antibiotic antibiogram in patients with complicated urinary tract infections (cUTIs) presenting to a Nephrology unit of South Waziristan. Methods A cross-sectional study was conducted at the Department of Nephrology, Sholam, South Waziristan. The study included all patients who presented with cUTIs and the symptoms included urinary urgency, hematuria, dysuria, suprapubic discomfort, and increased frequency. Those patients with clinical manifestations but are on antibiotics within the past five days were excluded. Results A total of 158 patients were included in the study with 113 (71.5%) females and 45 (28.5%) males. A total of 95 (60%) cases had gram-negative microbes, 47 (30%) had gram-positive cocci, and 16 (10%) had candida infection. In our study, the highly prevalent uropathogenic gram-positive bacteria showed the highest sensitivity to Linezolid, Rifampicin, and Vancomycin. Methicillin-resistant staph aureus was detected in 25% of isolates. All isolates of candida were sensitive to fluconazole. Gram-negative bacteria were highly resistant to ceftazidime, cefepime, ceftriaxone, and ciprofloxacin. Conclusion The development of bacterial resistance against multiple antibiotics is a global crisis that restricts the drug of choice for the treatment of cUTIs. In our study, we showed that overall, E.coli (gram negative) and S. Aureus (gram-positive) showed variable resistance to many antibiotics including ceftazidime, cefepime, piperacillin-tazobactam, ceftriaxone, and clindamycin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".