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Enregistrement W4408804265 · doi:10.5498/wjp.v15.i4.103092

Nutritional status of elderly hypertensive patients and its relation to the occurrence of cognitive impairment

2025· article· en· W4408804265 sur OpenAlexaboutno aff
Qiao Xu, Shourong Lu, Ying Yang, Jie Yu, Zhuo Wang, Bing-Shan Zhang, Kan Hong

Notice bibliographique

RevueWorld Journal of Psychiatry · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueNutrition and Health in Aging
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCognitive impairmentMedicineCognitionRelation (database)DementiaGerontologyInternal medicineEnvironmental healthPsychiatryDiseaseComputer scienceData mining

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Hypertension is a common chronic disease in the elderly population, and its association with cognitive impairment has been increasingly recognized. Cognitive impairment, including mild cognitive impairment and dementia, can significantly affect the quality of life and independence of elderly individuals. Therefore, identifying risk factors for cognitive impairment in elderly hypertensive patients is crucial for developing effective interventions and improving health outcomes. Nutritional status is one of the potential factors that may influence cognitive function in elderly hypertensive patients. Malnutrition or inadequate nutrition can lead to various health problems, including weakened immune system, increased susceptibility to infections, and impaired physical and mental function. Furthermore, poor nutritional status has been linked to increased risk of cognitive decline and dementia in various populations. In this observational study, we aimed to investigate the nutritional status of elderly hypertensive patients and its relationship to the occurrence of cognitive impairment. By collecting baseline data on general information, body composition, and clinical indicators, we hope to identify risk factors for cognitive impairment in this patient population. The results of this study are expected to provide more scientific basis for the health management of elderly patients with hypertension, particularly in terms of maintaining good nutritional status and reducing the risk of cognitive impairment. AIM: To explore the differences between clinical data and cognitive function of elderly hypertensive patients with different nutritional status, analyze the internal relationship between nutritional statuses and cognitive impairment, and build a nomogram model for predicting nutritional status in elderly hypertensive patients. METHODS: The present study retrospectively analyzed 200 elderly patients admitted to our hospital for a hypertension during the period July 1, 2024 to September 30, 2024 as study subjects, and the 200 patients were divided into a modeling cohort (140 patients) and a validation cohort (60 patients) according to the ratio of 7:3. The modeling cohort were divided into a malnutrition group (26 cases), a malnutrition risk group (42 cases), and a normal nutritional status group (72 cases) according to the patients' Mini-Nutritional Assessment Scale (MNA) scores, and the modeling cohort was divided into a hypertension combined with cognitive impairment group (34 cases) and a hypertension cognitively normal group (106 cases) according to the Montreal Cognitive Assessment Scale (MoCA) scores, and the validation cohort was divided into a hypertension combined with cognitive impairment group (14 cases) and hypertension cognitively normal group (46 cases). The study outcome was the occurrence of cognitive impairment in elderly hypertensive patients. Univariate and multivariate logistic regression was used to explore the relationship between the general information of the elderly hypertensive patients and the influence indicators and the occurrence of cognitive impairment, the roadmap prediction model was established and validated, the patient work receiver operating characteristic curve was used to evaluate the predictive efficacy of the model, the calibration curve was used to assess the consistency between the predicted events and the actual events, and the decision curve analysis was used to evaluate the validity of the model. Pearson correlation analysis was used to explore the relationship between nutrition-related indicators and MoCA scores. RESULTS: = 0.000) was an independent risk factor for patients with cognitive impairment. In this study, the prediction nomogram tailored for cognitive deterioration in elderly patients with hypertension demonstrated robust predictive power and a close correspondence between predicted and observed outcomes. This model offers significant potential as a means to forestall cognitive decline in hypertensive elderly patients. ALP was negatively correlated with MoCA score, while BMI, MNA score, Hb and ALB were positively correlated with MoCA score. CONCLUSION: BMI, MNA score, Hb and ALB were independent protective factors for cognitive impairment in elderly hypertensive patients and were positively correlated with MoCA score. ALP was an independent risk factor for cognitive impairment in elderly hypertensive patients and was negatively correlated with the MoCA score. The column line graph model established in the study has a good predictive value.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,033
Score d'incertitude au seuil0,180

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,324
Écart entre enseignants0,305 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations7
Publié2025
Routes d'admission1
Résumé présentoui

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