#5489 CROSS-TALK BETWEEN FRAILTY AND IMMUNOSENESCENCE IN PATIENTS WITH CHRONIC KIDNEY DISEASE
Notice bibliographique
Résumé
Abstract Background and Aims Chronic kidney disease (CKD) has been proposed as a model of premature ageing. The immune system is an important factor in the ageing process and can modulate the rate of ageing. The uremic environment highly affects this system, deteriorating its functionality and increasing susceptibility to infections, cancer, and pathologies like cardiovascular disease. Also, CKD patients are highly predisposed to frailty, which increases the organism's vulnerability to disease. This premature ageing, partially caused by the immune disorder and increased frailty, is responsible for these patients' high morbidity and mortality. Understanding these processes and how they are affected by different treatments will help generate better nutritional, pharmacological and lifestyle strategies. For this, the aim of this study was to determine the immune and frailty status of patients with CKD and their therapies. Method We performed a cross-sectional study involving 18 healthy subjects (HS) and 156 patients from the Nephrology Department of the Hospital Universitario “12 de Octubre” (Madrid, Spain). The distribution of patients was as follows: 40 with end-stage renal disease (ESRD), 40 on haemodialysis (HD), 36 on peritoneal dialysis (PD) and 40 patients who had received initial kidney transplantation (KT). The frailty status of the patients was assessed by the Edmonton Frail Scale test. Lymphocyte populations (T lymphocytes, T-helper lymphocytes, T-cytotoxic lymphocytes, and B lymphocytes) and monocytes (classical, intermediate, non-classical, and the expression of the adhesion molecule ICAM-1 and co-stimulatory B7.2) were determined in peripheral blood samples. Results The patients were similar in age and sex. The number of frail individuals was higher in patients (ESRD p<0.001, PD p<0.001, KT p = 0.004) than in HS, particularly in HD (p<0.001) (Figure 1). Regarding immune phenotype (Figure 2), HD patients showed a lower number of T-cells (p<0.001), particularly T-helper cells (p<0.001), than the other groups. Also, DP patients presented fewer T and T-cytotoxic cells than HS (p = 0.029, p = 0.05). Also, HD showed lower T-cytotoxic and helper/cytotoxic ratios than HS (p = 0.022; p = 0.011) and ESRD (p = 0.017; p = 0.008). The proportion of classical monocytes decreased, and the proportion of intermediate and non-classical monocytes increased in HD with respect to the other groups (p<0.001). The expression of the costimulatory molecule B7.2 was increased in the patients with respect to HS in all monocyte subsets (Classical: ESRD p = 0.002, HD p<0.001, PD p<0.001, KT p<0.001; Intermediate: ESRD p = 0.014, HD p<0.001, PD p<0.001, KT p = 0.002; Non-classical: ESRD p = 0.006, HD p<0.001, PD p<0.001, KT p = 0.013), while adhesion molecules were only elevated in HD with respect to HS in all subsets (classical p<0.001, intermediate p<0.001, non-classical p = 0.023). Conclusion The CKD patients, regardless of the treatment, showed, in general, an alteration in the lymphocyte subsets. These alterations were more significant in dialysis patients, particularly in HD patients. This group also presented the most significant alterations in monocyte subsets and higher frailty. This may explain why haemodialysis patients show major adverse outcomes compared to other treatments. Determining immune profiles can help us to relate these alterations to adverse events to carry out preventive and personalised medicine.
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 | 0,001 |
| 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 | 0,000 | 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) | 0,005 | 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 ».