Hematuria Is Not a Risk Factor for the Hypertension of Hemophilia
Notice bibliographique
Résumé
Abstract Introduction: Advances in hemophilia care have led to improved life expectancy and a cohort at risk for age-related comorbidities such as hypertension and cardiovascular diseases. Several studies have shown an increased prevalence of hypertension in patients with hemophilia compared to age-matched general population. However, causes of the increased prevalence of hypertension in patients with hemophilia are unclear. Hemophilia-specific risk factors such as renal bleeding or micro-bleeding may be implicated, but data are limited and conflicting regarding the association between hematuria, renal insufficiency and hypertension. In this two-centre prospective cohort study, we aim to assess the prevalence of gross or microscopic hematuria detected on routine surveillance urinalysis and microscopy, and determine the impact of hematuria on blood pressure and renal function. Methods: 135 adult males with mild-severe hemophilia A and B followed by the British Columbia Adult Bleeding Disorders Program (n=56) and the University of California, San Diego Hemophilia Treatment Center (n=79) were included. Screening urinalysis/microscopy were performed in all patients during routine clinic visits. Hematuria was defined as either a self-reported history of gross hematuria, or > 3 red blood cells per high-power field on urine microscopy in the absence of urinary tract infections. Hypertension was defined as systolic blood pressure (SBP) ≥140mmHg or diastolic blood pressure (DBP) ≥90mmHg on ≥2 occasions, or use of anti-hypertensive medications. Univariate and multivariate logistic regression analysis were used to examine the significance of hematuria and other potential hypertension risk factors. Results: The prevalence of hypertension was 44% in this population, 71% of whom were on anti-hypertensives, of whom 43% achieved blood pressure control (SBP <140 mmHg, and DBP <90mmHg) at last clinic visit. The median age was 42 years (IQR 30-57 years). On univariate analysis, patients with hypertension tended to be older (median age 56 years vs 35 years, P<0.001), had a higher prevalence of diabetes (17% vs 1%, P=0.001), dyslipidemia (35% vs 11%, P<0.001), and obesity (BMI >30; 32% vs 13%, P=0.012) compared to patients without hypertension. Despite the high prevalence of hematuria (34%), chronic kidney disease was rare (2%). On multivariate analysis, only age remains as a significant predictor of hypertension. Hematuria was associated with neither hypertension nor renal insufficiency and was not more prevalent in severe hemophilia. Conclusion: Hypertension was prevalent in our cohort of patients with hemophilia, but not optimally controlled. Hematuria was prevalent, not associated with a diagnosis of hypertension or renal dysfunction, and could not explain the hypertension while renal disease was rare. Larger prospective studies are needed to better elucidate the risk factors and mechanisms for increased prevalence of hypertension in the hemophilia population. Disclosures Sun: Baxter: Other: AHCDC/Baxter fellowship training award. Von Drygalski:Baxalta: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria, Speakers Bureau; Biogen: Consultancy, Honoraria, Speakers Bureau; CSL Behring: Consultancy, Honoraria, Speakers Bureau; Novo Nordisk: Consultancy, Honoraria, Speakers Bureau; Grifols: Consultancy, Honoraria, Speakers Bureau; Hematherix LLC: Membership on an entity's Board of Directors or advisory committees. Jackson:Biogen: Honoraria, Speakers Bureau; Baxalta: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bayer: Membership on an entity's Board of Directors or advisory committees; Novo Nordisk: Membership on an entity's Board of Directors or advisory committees.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».