Creation and Validation of a Visual Macroscopic Hematuria Scale for Optimal Communication and an Objective Hematuria Index
Bibliographic record
Abstract
PURPOSE: Macroscopic hematuria is a common symptom and sign that is challenging to quantify and describe. The degree of hematuria communicated is variable due to health worker experience combined with lack of a reliable grading tool. We produced a reliable, standardized visual scale to describe hematuria severity. Our secondary aim was to validate a new laboratory test to quantify hemoglobin in hematuria specimens. MATERIALS AND METHODS: Nurses were surveyed to ascertain current hematuria descriptions. Blood and urine were titrated at varying concentrations and digitally photographed in catheter bag tubing. Photos were processed and printed on transparency paper to create a prototype swatch or card showing light, medium, heavy and old hematuria. Using the swatch 60 samples were rated by nurses and laymen. Interobserver variability was reported using the generalized kappa coefficient of agreement. Specimens were analyzed for hemolysis by measuring optical density at oxyhemoglobin absorption peaks. RESULTS: Interobserver agreement between nurses and laymen was good (kappa = 0.51, p <0.001). Subgroup analysis showed substantial agreement for light hematuria (kappa = 0.71). Overall agreement improved when the moderate (kappa = 0.28) and heavy (kappa = 0.53) hematuria categories were combined (kappa = 0.70). Compared to known blood concentrations the assay of optical density at oxyhemoglobin absorption peaks showed a linear trend. CONCLUSIONS: A simple visual scale to grade and communicate hematuria with adequate interobserver agreement is feasible. The test for optical density at oxyhemoglobin absorption peaks is a new method, validated in our study, to quantify hemoglobin in a hematuria specimen.
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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 | 0.021 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".