Emphysematous pyelonephritis: Our experience in managing these cases
Bibliographic record
Abstract
INTRODUCTION: Emphysematous pyelonephritis (EPN) is a rare acute necrotising infection of renal parenchyma. We discuss clinical details and treatment strategies of 8 patients with EPN followed at our clinic. METHODS: We retrospectively reviewed the clinical, laboratory, radiological findings and treatment modalities of 8 patients with EPN followed at our urology clinic between 2012 and 2015. RESULTS: The mean patient age (female: 5; male: 3) was 62 (range: 51-82) years. Based on computed tomographic findings, EPN was classified as class 1 (n = 3), class 2 (n = 3) and class 3a (n = 2). All patients had fever, flank pain, nausea, and vomiting. Five patients had type 2 diabetes mellitus and 3 diabetic patients also had renal stones. Escherichia coli (n = 6), Klebsiella species (n = 1), and Proteus species (n = 1) were grown in urine cultures. All patients had unilateral involvement. Increased white blood cell counts, sedimentation rate, and C-reactive protein levels were detected in all cases. In addition to medical treatment, 2 patients underwent a nephrostomy catheter placement and another 2 patients underwent nephrectomy upon deterioration of her general health state. After achieving clinical stabilization with medical treatment, 1 patient underwent endoscopic ureteral stone treatment. The remaining 3 cases were treated only with antibiotherapy. All patients were discharged with clinical cure. CONCLUSION: Mortality rates of EPN are gradually decreasing. Preservation of renal reserve is possible due to early diagnosis, appropriate antibiotherapy, and drainage.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".