Evaluating factors that dictate struvite stone composition: A multi-institutional clinical experience from the EDGE Research Consortium
Bibliographic record
Abstract
INTRODUCTION: Struvite stones account for 15% of urinary calculi and are typically associated with urease-producing urinary tract infections and carry significant morbidity. This study aims to characterize struvite stones based on purity of stone composition, bacterial speciation, risk factors, and clinical features. METHODS: Retrospective data was collected from patients diagnosed with infection stones between 2008 and 2012. Stone analysis, perioperative urine cultures, bacterial speciation, and clinical data were collected and analyzed. The purity of struvite stones was determined. Statistical comparisons were made among homogeneous and heterogeneous struvite stones. RESULTS: From the four participating centres, 121 struvite stones were identified. Only 13.2% (16/121) were homogenous struvite. Other components included calcium phosphate (42.1%), calcium oxalate (33.9%), calcium carbonate (27.3%), and uric acid (5.8%). Partial or full staghorn calculi occurred in 23.7% of cases. Urease-producing bacteria were only present in 30% of cases. Proteus, E. coli, and Enterococcus were the most common bacterial isolates from perioperative urine, and percutaneous nephrolithotomy was the most common modality of treatment. Only 40% of patients had a urinalysis that was nitrite-positive, indicating that urinalysis alone is not reliable for diagnosing infection stones. The study's limitation is its retrospective nature; as such, the optimal timing of cultures with respect to stone analysis or treatment was not always possible, urine cultures were often not congruent with stone cultures in the same patient, and our findings of E. coli commonly cultured does not suggest causation. CONCLUSIONS: Struvite stones are most often heterogeneous in composition. Proteus remains a common bacterial isolate; however, E. coli and Enterococcus were also frequently identified. This new data provides evidence that patients with struvite stones can have urinary tract pathogens other than urease-producing bacteria, thus challenging previous conventional dogma.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".