Risk factors for hemorrhage requiring embolization after percutaneous nephrolithotomy: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: The aim of this meta-analysis was to systematically review and identify the risk factors for severe hemorrhage after percutaneous nephrolithotomy (PCNL). METHODS: We searched the PubMed and EMBASE database for literature related to the risk factors of severe hemorrhage after PCNL requiring angiography and embolization through to September 2019. The necessary data for each eligible study were extracted by 2 independent reviewers. The Newcastle-Ottawa Scale (NOS) was used for assessing the methodological quality of the included studies. Statistical analyses were conducted using Comprehensive Meta-Analysis version 2 to identify whether there was a statistical association between risk factors and severe hemorrhage post-PCNL. RESULTS: The results of this meta-analysis showed that urinary tract infection (UTI) (OR =1.98, 95% CI, 1.21-3.26, P=0.007), diabetes mellitus (OR =4.07, 95% CI, 1.83-9.06, P=0.001), staghorn stone (OR =3.49, 95% CI, 1.25-9.76, P=0.017), and multiple tracts (OR =2.09, 95% CI, 1.33-3.28, P=0.001) were independent risk factors for severe hemorrhage post-PCNL, while hypertension (OR =1.18, 95% CI, 0.58-2.42, P=0.65) showed no significant statistical difference. CONCLUSIONS: Urologists should focus on the above identified risk factors for severe hemorrhage post-PCNL, including UTI, diabetes mellitus, staghorn stone, and multiple tracts. More high-quality studies with larger sample sizes are needed to validate these conclusions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".