Subjective global assessment of malnutrition and dysphagia effect on the clinical and Para-clinical outcomes in elderly ischemic stroke patients: a community-based study

Development and Validation of a Nomogram for Predicting Nutritional Risk Based on Frailty Scores in Older Stroke Patients

BACKGROUND

In older stroke patients with frailty, nutritional deficiencies can amplify their susceptibility, delay recovery, and deteriorate prognosis. A precise predictive model is crucial to assess their nutritional risk, enabling targeted interventions for improved clinical outcomes.

OBJECTIVE

To develop and externally validate a nutritional risk prediction model integrating general demographics, physical parameters, psychological indicators, and biochemical markers. The aim is to facilitate the early identification of older stroke patients requiring nutritional intervention.

METHODS

This was a multicenter cross-sectional study. A total of 570 stroke patients were included, 434 as the modeling set and 136 as the external validation set. The least absolute shrinkage selection operator (LASSO) regression analysis was used to select the predictor variables. Internal validation was performed using Bootstrap resampling (1000 iterations). The nomogram was constructed based on the results of logistic regression. The performance assessment relied on the receiver operating characteristic curve (ROC), Hosmer--Lemeshow test, calibration curves, Brier score, and decision curve analysis (DCA).

RESULTS

The predictive nomogram encompassed seven pivotal variables: Activities of Daily Living (ADL), NIHSS score, diabetes, Body Mass Index (BMI), grip strength, serum albumin levels, and depression. Together, these variables comprehensively evaluate the overall health and nutritional status of elderly stroke patients, facilitating accurate assessment of their nutritional risk. The model exhibited excellent accuracy in both the development and external validation sets, evidenced by AUC values of 0.934 and 0.887, respectively. Such performance highlights its efficacy in pinpointing elderly stroke patients who require nutritional intervention. Moreover, the model showed robust goodness of fit and practical applicability, providing essential clinical insights to improve recovery and prognosis for patients prone to malnutrition.

CONCLUSIONS

Elderly individuals recovering from stroke often experience significant nutritional deficiencies. The nomogram we devised accurately assesses this risk by combining physiological, psychological, and biochemical metrics. It equips healthcare providers with the means to actively screen for and manage the nutritional care of these patients. This tool is instrumental in swiftly identifying those in urgent need of targeted nutritional support, which is essential for optimizing their recovery and managing their nutrition more effectively.

The Link between Stroke Risk and Orodental Status-A Comprehensive Review

One of the primary causes of disability and mortality in the adult population worldwide is stroke. A person's general health is significantly impacted by their oral and dental health. People who have poor oral health are more susceptible to conditions such as stroke. Stroke risk has long been linked to oral and dental conditions. The risk of stroke and its cost impact on the healthcare systems appear to be significantly reduced as a result of the decline in the incidence and prevalence of oral and dental illnesses. Hypothetically, better management of oral hygiene and dental health lead to reduced stroke risk. To the authors' best knowledge, for the first time, the potential link between dental health and stroke were cross-examined. The most typical stroke symptoms, oral and dental illnesses linked to stroke, and the role of oral healthcare professionals in stroke prevention are revealed. The potential mediating processes and subsequent long-term cognitive and functional neurological outcomes are based on the available literature. It must be noted that periodontal diseases and tooth loss are two common oral health measures. Lack of knowledge on the effects of poor oral health on systemic health together with limited access to primary medical or dental care are considered to be partially responsible for the elevated risk of stroke. Concrete evidence confirming the associations between oral inflammatory conditions and stroke in large cohort prospective studies, stratifying association between oral disease severity and stroke risk and disease effects on stroke survival will be desirable. In terms of clinical pathology, a predictive model of stroke as a function of oral health status, and biomarkers of systemic inflammation could be useful for both cardiologists and dentists.

Evaluation of nutritional status in patients with liver cirrhosis. Validity and prognostic value of the Patient-Generated Subjective Global Assessment

Introduction

Malnutrition is a common condition in liver cirrhosis (LC), which is associated with poor survival. Despite the wide range of tools, there is no agreement on a standard nutritional assessment method applicable to LC.

Aim

To determine the validity and prognostic value of the Patient-Generated Subjective Global Assessment (PG-SGA) as a nutritional assessment tool in LC patients.

Material and methods

In 2019-2021, 161 patients with LC (aged 55.2 ±11.6 years) were involved, of whom 23, 57, and 81 patients were classified as Class A, B, and C Child-Turcotte-Pugh (CTP), accordingly. Fifty patients died during follow-up (489 (293-639) days). The PG-SGA, Controlling Nutritional Status (CONUT), handgrip strength, and skeletal muscle index (SMI) were used to assess nutritional status.

Results

According to the PG-SGA 29.8% of patients were moderately malnourished and 29.8% were severely malnourished. 50.6% of CTP C patients were severely malnourished. Numerical PG-SGA correlated with CTP, Model for End-Stage Liver Disease, CONUT, SMI, and handgrip strength. Low SMI and handgrip strength were present in 87.5% and 66.7% of severely malnourished patients, respectively. PG-SGA predicted mortality (AUC = 0.775, p < 0.001). Severely malnourished patients had significantly lower survival than moderately malnourished and well-nourished patients in the Kaplan-Meier analysis. Hepatic encephalopathy (HR = 2.29, p = 0.046), hypoalbuminemia (HR = 2.27, p = 0.022), and severe malnutrition according to PG-SGA (HR = 2.39, p = 0.016) were independent predictors of mortality in Cox proportional hazards regression analysis.

Conclusions

The PG-SGA is a reliable nutritional assessment tool and can predict mortality in LC patients.