92 Reshaping the Diagnostic Pathways for Investigation of Haematuria During and After The COVID-19 Pandemic: Diagnostic Accuracy of Strategies for Detection of Bladder Cancer from The IDENTIFY Cohort Study
Bibliographic record
Abstract
Abstract Introduction Diagnostic haematuria services have been reduced due to the COVID-19 pandemic, compromising patient care, and necessitating a more pragmatic pathway. Method The IDENTIFY study was an international, prospective, multicentre cohort study of over 11,000 patients referred to secondary care for investigation of haematuria. Using this data, we developed strategies using combinations of imaging and cytology as triage tests to maximise cancer detection within a pragmatic pathway. Results 8112 patients (74·4%) received an ultrasound or a CT urogram, with or without cytology. 5737 (70·7%) patients had visible haematuria (VH) and 2375 (29·3%) had non-visible haematuria (NVH). Diagnostic test performance was used to determine optimal age cut-offs for four proposed strategies. We recommended proceeding directly to transurethral resection of bladder tumour for patients of any age with positive triage tests for cancer. Patients with negative triage tests under 35-years-old with VH, or under 50-years-old with NVH can safely be discharged without undergoing flexible cystoscopy. The remaining patients may undergo flexible cystoscopy, with a greater priority for older patients to capture high risk bladder cancer. Conclusions We suggest diagnostic strategies in patients with haematuria, which focus on detection of bladder cancer, whilst reducing the burden to healthcare services in a resource-limited setting.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".