Prevalence and associated factors for dipstick microscopic hematuria in men
Bibliographic record
Abstract
BACKGROUND: Microscopic hematuria is a common incidental finding on routine urinalysis. Although there are no clear recommendations to perform routine urinalysis, some studies have shown that up to 50% of general practitioners continue to perform annual routine urinalysis regardless of age or risk factors. The aim of this study was to identify associated factors and prevalence of dipstick microscopic hematuria in the general male population presenting to an annual public men's health fair. METHOD: We conducted a retrospective analysis of prospectively collected data at an annual Men's Health fair from 2008 to 2013. Patient reported health questionnaires, basic physical exam including digital rectal exam, basic bloodwork and dipstick urinalysis data was examined. RESULTS: A total of 979 patients were reviewed. Of these, 850 provided a urine sample and were included in the final analysis. Seventy-three (8.6%) patients had positive hematuria on urinalysis. Average age in both groups was 55 years. Presence of microscopic hematuria was correlated with presence of diabetes and proteinuria with odds-ratio of 2.8 (1.3-5.8) and 2.9 (1.7-5.0) respectively on multivariate analysis. There was no significant correlation identified with age, hypertension, coronary artery disease, body-mass index, smoking, prostate specific antigen (PSA) or International Prostate Symptom Score (IPSS). Limitation of this study is the lack of follow-up and knowledge of subsequent investigations of patients. CONCLUSION: Microscopic hematuria is a prevalent condition in the male population presenting to a health fair. The only factors associated with microscopic hematuria were diabetes and proteinuria. No association was found between hematuria and smoking, age, or lower urinary tract symptoms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".