FP732PROTEIN-ENERGY WASTING IN ELDERLY MAINTENANCE HEMODIALYSIS PATIENTS
Notice bibliographique
Résumé
INTRODUCTION: In Kazakhstan the number of geriatric patients on maintenance hemodialysis (MHD) has been increasing. Protein-energy wasting (PEW) is prevalent complication in these patients. The primary objectives of this study were to evaluate the prevalence of PEW in elderly patients on MHD by using different nutritional assessment tools and assess their association with clinical and laboratory measurements. A secondary objective was to investigate the relationship between nutritional status and frailty among these patients. METHODS: A multicenter cross-sectional study included 65 patients aged ≥ 65 years undergoing HD for at least 3 months in 7 outpatient HD facilities in Almaty, Kazakhstan. The study was performed from July to September 2018. Nutritional status of patients was evaluated by using Mini Nutritional assessment (MNA), Malnutrition-Inflammation Score (MIS), and anthropometric measurements (body mass index (BMI), triceps skinfold (TSF), mid-arm muscle circumference (MAMC)), biochemical data were collected from medical records. Frailty was defined in accordance with the Edmonton Frail scale (EFS). RESULTS: In the study, participants’ median age was 69 (range: 65–88) years old, and median dialysis vintage was 36 (IQR 15–60) months, 20% were aged 75 year old and older, 53.8% were female. The major causes of the ESRD were hypertension (38.5%) and diabetes (24.6%). Based on MIS the prevalence of PEW was 73.8%. According to MNA, the nutritional status was normal in 43.1% of patients, risk of malnutrition was detected in 47.7%, and malnutrition in 9.2% of patients on MHD. Mean body weight was 69,1±11.3kg, the mean BMI was slightly overweight 25.6±4.29kg/m2, while hand-grip strength was 21.33±3.36 in men and 15.5±5.51 in women, p=0.008, and it is lower than the normal population standard values. CRP was negative in 55.4% of cases. While MAMC was found to be significantly higher in male patients (24.87±1.93cm in men and 23.39±2.76cm in women, p=0.018), TSF was found to be significantly higher in female patients (9.56±3.74mm in men and 16.68±7.38cm in women, p<0.001). No significant difference was observed between genders in the frequency of malnutrition according to SGA, MNA, MIS, BMI, serum albumin, creatinine. The prevalence of frailty assessed by the EFS 43.1% were classified as non-frail patients, 33.8% as vulnerable, and 23.1% as frail. Among the frail patients, 86.7% were female (p=0.005) and 93.3% of frail patients had PEW (p=0.001) evaluated by MIS. CONCLUSIONS: Protein-energy wasting is common among elderly hemodialysis patients in Kazakhstan. Its prevalence varies between 56.9% and 73.8% depending on the measurement tool used to evaluate the nutritional status. In our country with limited resources, MIS and MNA nutritional scores could help to follow the nutritional status of our elderly hemodialysis patients. Also the study showed that the prevalence of frailty is high among female patients, and we detected that PEW increased in female frail patients.
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 | 0,000 | 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) | 0,002 | 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 ».