Haematuria is not a risk factor of hypertension or renal impairment in patients with haemophilia
Bibliographic record
Abstract
INTRODUCTION: An increased prevalence of hypertension has been reported in patients with haemophilia compared to the age-matched general population, although the causes were unclear. To date, there has been limited data implicating haemophilia-specific risk factors such as renal bleeding. AIM: This two-centre prospective cohort study aimed to assess the prevalence of gross/microscopic haematuria, and the associations between haematuria, blood pressure and renal function. METHODS: Of 135 adult males, with mild to severe haemophilia followed by the British Columbia and University of California San Diego Hemophilia Treatment Centers were included. Screening urinalysis and microscopy were performed during all routine visits. Haematuria was defined as history of gross haematuria or >3 red blood cells per high-power field on microscopy in the absence of urinary tract infections. Logistic regressions were used to examine the significance of haematuria and other potential hypertension risk factors. RESULTS: The prevalence of hypertension was 44%, of whom 31% achieved adequate blood pressure control. Despite the high prevalence of haematuria (34%), renal dysfunction was rare. On univariate analysis, age, diabetes, dyslipidemia and obesity were associated with hypertension. On multivariate analysis, only age remains as a significant predictor of hypertension. Haematuria was not associated with hypertension, renal insufficiency or haemophilia severity. CONCLUSION: In this cohort, hypertension and haematuria were prevalent while renal disease was rare. Haematuria was not associated with a diagnosis of hypertension or renal dysfunction. Larger prospective studies are needed to elucidate the mechanisms for increased prevalence of hypertension in haemophilia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".