Is coronavirus disease 2019 associated with indicators of long‐term bladder dysfunction?
Bibliographic record
Abstract
OBJECTIVE: Early reports have suggested that coronavirus disease 2019 (COVID-19) can present with significant urinary frequency and nocturia, and that these symptoms correlate with markers of inflammation in the urine. We evaluated surrogate markers of chronic urinary symptoms to determine if they were more frequent after COVID-19 infection. METHODS: Routinely collected data from the province of Ontario was used to conduct a matched, retrospective cohort study. We identified patients 66 years of age or older who had a positive COVID-19 test between February and May 2020 and survived at least 2 months after their diagnosis. We matched them to two similar patients who did not have a positive COVID-19 test during the same time period. We measured the frequency of urology consultation, cystoscopy, and new prescriptions for overactive bladder medications during a subsequent 3-month period. Proportional hazard models were adjusted for any baseline differences between the groups. RESULTS: We matched 5617 patients with COVID-19 to 11,225 people who did not have COVID-19. The groups were similar, aside from a higher proportion of patients having hypertension and diabetes in the CoVID-19 cohort. There was no significantly increased hazard of new receipt of overactive bladder medication (hazards ratio [HR]: 1.04, p = 0.88), urology consultation (HR: 1.40, p = 0.10), or cystoscopy (HR: 1.14, p = 0.50) among patients who had COVID-19, compared to the matched cohort. CONCLUSION: Surrogate markers of potential bladder dysfunction were not significantly increased in the 2-5 months after COVID-19 infection.
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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 | 0.005 |
| 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".