FC006: Sex Differences in the Recognition, Monitoring and Management of Chronic Kidney Disease in Health Care
Notice bibliographique
Résumé
Abstract BACKGROUND AND AIMS Sex-specific differences exist in the population prevalence of chronic kidney disease (CKD), progression rates and health outcomes. Recognition, diagnosis and monitoring are central processes in the management of patients with CKD, but it is unknown whether these processes differ between men and women. METHOD This is an observational cohort study of all adult individuals (n = 227 847) with at least one eGFR (from serum creatinine) <60 mL/min/1.73 m2 during outpatient routine care in Stockholm, Sweden, 2009–2017. Through logistic regression, we evaluated differences by sex in carrying an ICD-10 code for CKD and provision of recommended medications (renin–angiotensin system inhibitors [RASi] and statins) at inclusion. Through Cox regression, we evaluated potential sex differences in receiving a CKD diagnosis, referral to nephrology care and performance of laboratory monitoring (creatinine and albuminuria) in the next 18 months from inclusion. We also explored time-trends, comparing the above-mentioned nephrology care indicators among 70–80 000 unique eligible individuals per calendar year (in total 695 632 observations), thus allowing participants to contribute to different calendar year-cohorts. RESULTS We identified more women (55%) than men (45%) with probable CKD (eGFR < 60 mL/min/1.73 m2). Women were generally older than men (median 77 versus 74 years), but eGFR was similar between sexes (51 mL/min/1.73 m2). More men than women had diabetes or myocardial infarction, but there was similar prevalence of hypertension. At inclusion and compared with men, women had lower risk of carrying an ICD-10 code for CKD (odds ratio [OR]: 0.47, 95% CI: 0.45–0.49) and were less likely to receive RASi (OR: 0.55; 0.50–0.61, among patient with albuminuria A3) or statins (OR: 0.64; 0.63–0.66, among patients ≥ 50 years), despite the presence of clear indications. In subsequent time-to-event analyses, women were less likely to receive a CKD diagnosis (hazard ratio [HR]: 0.43; 0.42–0.45) and visit a nephrologist (HR: 0.46; 0.43–0.48) regardless of CKD severity, presence of albuminuria or criteria for referral. Women were also less likely to undergo monitoring of creatinine or albuminuria, even among participants with diabetes (HR: 0.75; 0.74–0.76) or hypertension (HR: 0.76; 0.75–0.78). Multivariable adjustment including comorbidities, eGFR and indication for referral showed some attenuation of the effect, but a sex difference remained. Although in absolute terms there has been a gradual improvement in all nephrology care indicators over time, the observed sex gap persisted throughout. CONCLUSION We found profound sex differences in the detection, recognition, monitoring and management (including referrals) of CKD in healthcare, also across high-risk groups and indications.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| 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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».