Diagnostic utility of axial imaging in the evaluation of hematuria: A systematic review and critical appraisal of the literature
Bibliographic record
Abstract
INTRODUCTION: Increasing severity of hematuria is instinctively associated with higher likelihood of urological malignancy. However, the robustness of the evidentiary base for this assertion is unclear, particularly as it relates to the likelihood of upper urinary tract pathology. Thus, the value of axial imaging in the diagnostic workup of hematuria is unclear due to differences in the underlying patient populations, raising concern for sampling bias. We performed a systematic review to characterize the literature and association between severity of hematuria and likelihood of upper urinary tract cancer based on axial imaging. METHODS: MEDLINE, EMBASE, and Cochrane were systematically searched for all studies reporting on adult patients presenting with hematuria. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for reporting of this systematic review and meta-analysis and the Newcastle-Ottawa Scale for risk of bias assessment. Degree of hematuria was classified as "microscopic," "gross," or "unspecified." Three urological malignancies (bladder, upper tract urothelial, and renal cancer) were considered both individually and in aggregate. Random-effects model with pairwise comparisons was employed to arrive at the axial imaging diagnostic yields. RESULTS: Twenty-nine studies were included, of which six (20.7%) reported on patients with gross hematuria only, four (13.8%) reported on patients with microscopic hematuria only, seven (24.1%) included both, and 12 (41.4%) did not define or specify the severity of hematuria. Of 29 studies, two (6.9%) were at high-risk of bias, 21 (72.4%) at intermediate-risk, and six (20.7%) at low-risk of bias using the Newcastle-Ottawa criteria. Based on axial imaging, rates of diagnoses of renal, upper tract urothelial, and bladder cancers differed with differing severity of hematuria. Notably, rates of renal and upper tract urothelial carcinoma were higher in studies of patients with unspecified hematuria severity (3.6% and 10.4%, respectively) than among patients with gross hematuria (1.5% and 1.3%, respectively). When all urological malignancies were pooled, patients with unspecified hematuria were diagnosed more frequently (19.5%) compared to those with gross (15.3%) and microscopic hematuria (4.5%, difference=1.51%, 99% confidence interval 3.6-26.5%). CONCLUSIONS: Lack of granularity in the available literature, particularly with regards to patients with unspecified hematuria severity, limits the generalizability of these results and highlights the need for future studies that provide sufficient baseline information, allowing for firmer conclusions to be drawn.
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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 | 0.040 | 0.139 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.015 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".