Prevalence of frailty and associated factors in coronary artery bypass graft surgery patients
Notice bibliographique
Résumé
Abstract Background Frail patients are at increased risk for postoperative delirium, complications, delayed recovery, prolonged hospital and intensive care unit stay, morbidity and mortality. The number of studies examining frailty in cardiovascular surgery patients is limited (1,2). In this context, it is important to determine the prevalence of frailty in cardiac surgery patients (3,4). Purpose This research was conducted to examine the prevalence of frailty in coronary artery bypass graft surgery patients and associated factors with frailty. Methods The research was descriptive cross-sectional type. It was conducted between 18.02.2021 and 18.02.2022 at the cardiovascular surgery department of a training and research hospital in Turkey. A total of 96 patients who had undergone coronary artery bypass graft (CABG) were included. The "Sociodemographic and Clinical Data Form" which was prepared in accordance with the literature, the "Modified Fried Frailty Index", the "Mini Nutritional Assessment Test-Short Form", the "Barthel Daily Living Activities Index", the "Charlson Comorbidity Index", and the "Montreal Cognitive Assessment Scale" were used to collect data. The data were analyzed using the SPSS 23.0 package program. Descriptive statistics, Kolmogorov-Smirnov test, Chi-square test, One Way ANOVA, Kruskal Wallis test and multinomial logistic regression analysis were used in the evaluation of the data. Results As a result of the study, the mean age of the patients was 65.65±8.72 years (min:40-max:85), 62.5% consisted of males. The majority of patients (94.8%) had comorbid diseases, most of whom had hypertension (66.7%) and diabetes mellitus (63.5%). The mean ejection fraction of the patients was normal (54.59±8.70) according to the European Society of Cardiology and the majority (80.2%) were in the preserved LVEF group. The mean EuroSCORE was intermediate (4.79±2.40) and 49% of the patients were at intermediate risk for mortality. The majority of the patients (94.8%) were in the ASA III class according to the American Society of Anaesthesiologists. Of the patients. 14.6% were determined as ‘non-frail’, 45.8% as ‘pre-frail’ and 39.6% as ‘frail’. Age, educational status, income level, beta-blocker use, nutritional status, daily living activities, cognitive status, number of comorbidities, and level of potassium, procalcitonin and creatinine were found to be associated with frailty (p<0.05). Malnutrition, decreased daily living activity, cognitive impairment and creatinine elevation were found to be predictors of frailty (p<0.05). Sociodemographic and Clinical Characteristics by Frailty Status was presented in Table 1. Conclusions More than a third of CABG patients were frail. Malnutrition, decreased daily living activity, impaired cognitive status and high creatinine levels increased the risk. It is important to assesment frail cardiac surgery patients and provide them with appropriate nursing management.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 ».