PREVALENCE, RISK FACTORS, AND OUTCOMES OF CHRONIC KIDNEY DISEASE IN SLE PATIENTS WITH AND WITHOUT LUPUS NEPHRITIS
Notice bibliographique
Résumé
PV055 / #458 Poster Topic: AS06 - Comorbidities Background/Purpose Chronic kidney disease (CKD) is defined as abnormalities of kidney structure or function persisting for >3 months, detected by decreased estimated glomerular filtration rate (eGFR) or albuminuria. While lupus nephritis (LN) is a well-known cause of CKD in patients with systemic lupus erythematosus (SLE), other risk factors also contribute to the development of CKD in these individuals. Currently, guidelines recommend monitoring urinary protein rather than albumin, which may lead to delayed diagnosis of CKD in SLE patients despite potential benefits of earlier detection. Aims: To assess the prevalence, associated factors, and long-term clinical outcomes of CKD among SLE patients, both with and without a history of LN. Methods A retrospective single-center study, conducted between 2014–2023 and included adult patients diagnosed with SLE for at least 12 months. Patients were categorized into CKD or non-CKD groups. CKD was defined as having a decreased eGFR <60 ml/min/1.73m2 and/or albuminuria ≥30 mg/24h both in 2 or more consecutive tests spaced at least 3 months apart. eGFR was calculated using MDRD formula. Patients who developed end-stage kidney disease (ESKD) during follow-up were excluded. Study flowchart is shown in Figure 1. Data on sociodemographic and clinical characteristics were collected. Figure 1. Results A total of 162 SLE patients were included, of them 77 (47.5%) were diagnosed as having CKD. Among these, 57 (35.2%) had albuminuria, 43 (26.5%) had decreased eGFR, and 22 (13.6%) patients had both albuminuria and decreased eGFR. Notably, 47 (61.1%) of the CKD patients, had never been diagnosed with LN. The odds ratio (OR) for having CKD was 2.55 (95% CI 1.3-5.2, p=0.008) in patients with LN as compared to patients without LN. Strikingly, all male patients were categorized as CKD. CKD was associated with higher rates of antiphospholipid syndrome, diabetes, hypertension, and heart disease (Table 1). Additionally, CKD patients experienced higher rates of severe SLE exacerbations and severe infections requiring hospitalizations and more damage accumulation (Table 1). Despite comparable follow-up time, CKD patients had significantly higher mortality rates compared to non-CKD on univariate analysis (23.4% vs 0, p<0.001). Multivariate COX, age- and sex-adjusted model is shown in Figure 2, p<0.01). Table 1. Figure 2. Conclusions CKD is prevalent among patients with SLE, including those without a diagnosis of LN. CKD in SLE patients is associated with higher rates of comorbidities, severe disease exacerbations, and markedly increased mortality. Given the chronic and progressive nature of CKD, these findings suggest that proactive monitoring in SLE patients should include the measurement of albuminuria in addition to proteinuria. This approach could facilitate the introduction of new treatment options, thereby reducing the substantial morbidity and mortality associated with CKD in SLE.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».