Effects of kidney function, serum albumin and hemoglobin on dementia severity in the oldest old people with newly diagnosed Alzheimer's disease in a residential aged care facility: a cross-sectional study

An investigation into the potential association between nutrition and Alzheimer's disease

Background

Malnutrition is the most common nutritional issue in Alzheimer's disease (AD) patients, but there is still a lack of a comprehensive evaluation of the nutritional status in AD patients. This study aimed to determine the potential association of various nutritional indices with AD at different stages.

Methods

Subjects, including individuals with normal cognition (NC) and patients diagnosed with AD, were consecutively enrolled in this cross-sectional study. Demographics, body composition, dietary patterns, nutritional assessment scales and nutrition-related laboratory variables were collected. Binary logistics regression analyses and receiver operating characteristic (ROC) curves were used to indicate the association between nutrition-related variables and AD at different stages.

Results

Totals of 266 subjects, including 73 subjects with NC, 72 subjects with mild cognitive impairment due to AD (AD-MCI) and 121 subjects with dementia due to AD (AD-D) were included. There was no significant difference in dietary patterns, including Mediterranean diet and Mediterranean-DASH diet intervention for neurodegenerative delay (MIND) diet between the three groups. Lower BMI value, smaller hip and calf circumferences, lower Mini Nutritional Assessment (MNA) and Geriatric Nutritional Risk Index (GNRI) scores, and lower levels of total protein, albumin, globulin, and apolipoprotein A1 were associated with AD (all p < 0.05). Total protein and albumin levels had the greatest ability to distinguish AD from non-AD (AUC 0.80, 95% CI 0.74-0.84, p < 0.001), increased by combining calf circumference, MNA score and albumin level (AUC 0.83, 95% CI 0.77-0.88, p < 0.001). Albumin level had the greatest ability to distinguish NC from AD-MCI (AUC 0.75, 95% CI 0.67-0.82, p < 0.001), and MNA score greatest ability to distinguish AD-MCI from AD-D (AUC 0.72, 95% CI 0.65-0.78, p < 0.001).

Conclusion

Nutritional status of AD patients is significantly compromised compared with normal controls, and tends to be worsened with AD progresses. Early identification and intervention of individuals with nutritional risk or malnutrition may be significantly beneficial for reducing the risk, development, and progression of AD.

Predicting the Rapid Progression of Mild Cognitive Impairment by Intestinal Flora and Blood Indicators through Machine Learning Method

INTRODUCTION

The aim of the work was to establish a prediction model of mild cognitive impairment (MCI) progression based on intestinal flora by machine learning method.

METHOD

A total of 1,013 patients were recruited, in which 87 patients with MCI finished a two-year follow-up. To establish a prediction model, 61 patients were randomly divided into a training set and 26 patients were divided into a testing set. A total of 121 features including demographic characteristics, hematological indicators, and intestinal flora abundance were analyzed.

RESULTS

Of the 87 patients who finished a two-year follow-up, 44 presented rapid progression. Model 1 was established based on 121 features with the accuracy 85%, sensitivity 85%, and specificity 83%. Model 2 was based on the first fifteen features of model 1 (triglyceride, uric acid, alanine transaminase, F-Clostridiaceae, G-Megamonas, S-Megamonas, G-Shigella, G-Shigella, S-Shigella, average hemoglobin concentration, G-Alistipes, S-Collinsella, median cell count, average hemoglobin volume, low-density lipoprotein), with the accuracy 97%, sensitivity 92%, and specificity 100%. Model 3 was based on the first ten features of model 1, with the accuracy 97%, sensitivity 86%, and specificity 100%. Other models based on the demographic characteristics, hematological indicators, or intestinal flora abundance features presented lower sensitivity and specificity.

CONCLUSION

The 15 features (including intestinal flora abundance) could establish an effective model for predicting rapid MCI progression.

Mild cognitive impairment in type 2 diabetes is associated with fibrinogen-to-albumin ratios

Background

Cognitive impairment is the main manifestation of diabetes central neuropathy. Currently, there is no effective dementia treatment; early diagnosis and treatment are particularly crucial. Inflammation index fibrinogen-to-albumin ratio (FAR) has been shown to predict complications of type 2 diabetes (diabetic kidney disease and diabetes-related arteriosclerosis), but its relationship with mild cognitive impairment (MCI) in type 2 diabetes (T2D) is undetermined. In this study, we examined the association between the FAR and mild cognitive impairment in type 2 diabetes.

Methods

This is a retrospective and cross-sectional study. From January 2022 to December 2022, we have retrieved 328 inpatient medical records for T2D patients hospitalized at the First Hospital of Harbin Medical University from the hospital's electronic system. Subjects' cognitive function was assessed and grouped by the MoCA scales. Subjects' demographic and various laboratory indicators were collected. Using Spearman's bivariate correlation analysis, the FAR and other clinical variables were analyzed for association strength. A multiple linear regression analysis was conducted to determine the independent relationship between FAR and MoCA scores. Multivariate logistic regression was used to analyze the independent relationship between FAR and MCI. The capacity of the FAR to detect MCI was carried using receiver operating characteristic (ROC) analysis.

Results

The included participants' (n = 328; 61.9% male) mean age was 52.62 ± 10.92 years. MoCA scores and MCI prevalence significantly differed (p < 0.05) between the four subgroups of FAR quartiles. The FAR and the MoCA score were significantly negatively correlated in the entire population (p < 0.05). Based on the multiple linear regression analysis, lnFAR and lnMoCA are significantly correlated (β = -0.449, t = -8.21, p < 0.05, R2 = 0.469). In multivariate logistic regression analysis, FAR and MCI were independently correlated after adjusting for covariates (OR 95% CI 34.70 [13.90-86.66]). Finally, the analysis of receptor working characteristics shows that the optimal FAR cut-off value was 0.08 (sensitivity: 95.81%, specificity: 84.47%) for detecting MCI in type 2 diabetes.

Conclusion

In type 2 diabetes, the FAR was positive associations with MCI and negative associations with MoCA score. The high FAR was associated with an increased risk of MCI. FAR maybe a appropriate indicator of MCI risk for type 2 diabetes.

Classification and deep-learning-based prediction of Alzheimer disease subtypes by using genomic data

Late-onset Alzheimer's disease (LOAD) is the most common multifactorial neurodegenerative disease among elderly people. LOAD is heterogeneous, and the symptoms vary among patients. Genome-wide association studies (GWAS) have identified genetic risk factors for LOAD but not for LOAD subtypes. Here, we examined the genetic architecture of LOAD based on Japanese GWAS data from 1947 patients and 2192 cognitively normal controls in a discovery cohort and 847 patients and 2298 controls in an independent validation cohort. Two distinct groups of LOAD patients were identified. One was characterized by major risk genes for developing LOAD (APOC1 and APOC1P1) and immune-related genes (RELB and CBLC). The other was characterized by genes associated with kidney disorders (AXDND1, FBP1, and MIR2278). Subsequent analysis of albumin and hemoglobin values from routine blood test results suggested that impaired kidney function could lead to LOAD pathogenesis. We developed a prediction model for LOAD subtypes using a deep neural network, which achieved an accuracy of 0.694 (2870/4137) in the discovery cohort and 0.687 (2162/3145) in the validation cohort. These findings provide new insights into the pathogenic mechanisms of LOAD.

Cognitive Function Deterioration After Cardiopulmonary Bypass: Can Intraoperative Optimal Cerebral Regional Tissue Oxygen Saturation Predict Postoperative Cognitive Function?

OBJECTIVE

Cognitive impairment is a common neurologic complication after cardiac surgery with cardiopulmonary bypass (CPB). This study evaluated postoperative cognitive function to determine predictors of cognitive dysfunction, including intraoperative cerebral regional tissue oxygen saturation (rSO₂).

DESIGN

A prospective observational cohort study.

SETTING

At a single academic tertiary-care center.

PARTICIPANTS

A total of 60 adults undergoing cardiac surgery with CPB from January to August 2021.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

All patients underwent Mini-Mental State Examination (MMSE) and quantified electroencephalography (qEEG) 1 day before cardiac surgery, 7 days postoperatively (POD7), and POD60. Intraoperative cerebral rSO₂ was monitored continuously. For MMSE, no significant decrease in MMSE score was found on POD7 versus preoperatively (p = 0.09), but POD60 scores showed significant improvement compared with both preoperative (p = 0.02) and POD7 scores (p < 0.001). On qEEG, relative theta power on POD7 was increased versus preoperatively (p < 0.001), but it was decreased on POD60 (POD7 versus POD60, p < 0.001), and was close to preoperative data (p > 0.99). Baseline rSO₂ was an independent factor for postoperative MMSE. Both baseline and mean rSO₂ showed a significant influence in postoperative relative theta activity, whereas mean rSO₂ was the only predictor for the theta-gamma ratio (p = 0.04).

CONCLUSIONS

The MMSE in patients undergoing CPB declined at POD7 and recovered by POD60. Lower baseline rSO₂ indicated a higher potential for MMSE decline at POD60. Inferior intraoperative mean rSO₂ was related to higher postoperative relative theta activity and theta-gamma ratio, implying subclinical or further cognitive impairment.

Renal function and neurodegenerative diseases : a two-sample Mendelian randomization study

BACKGROUND

Observational studies showed renal function had associations with Alzheimer's disease (AD), Parkinson's disease (PD), Lewy body dementia (LBD) and multiple sclerosis (MS). However, it is unknown whether these associations are causal.

METHODS

We use a two-sample Mendelian randomization (MR) analysis to investigate causal relationships between renal function and 6 neurodegenerative diseases (NDDs): AD (including familial AD), PD, LBD, frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS) and MS. Blood urea nitrogen (BUN), chronic kidney disease (CKD) and estimated glomerular filtration rate (eGFR) were used to measure renal function. The inverse-variance weighted (IVW) was the predominant estimation method. The results were further validated using sensitivity analysis (i.e. MR Egger regression, Cochran Q statistic of IVW, and leave-one-out method).

RESULTS

There was no indication of any causative relationship of BUN, CKD, or eGFR with AD, familial AD, PD, LBD, FTD and ALS (all P values >0.05). The IVW analysis demonstrated a causal relationship between eGFR and MS [odds ratio (OR), 4.89; 95% confidence interval (CI), 1.43 to 16.71; P = 0.01] that was not verified in the MR-Egger and weighted median (all P values >0.05). However, no causal association of MS with BUN (OR, 0.91; 95% CI, 0.40-2.07; P = 0.82) and CKD (OR,1.04; 95% CI, 0.88-1.23; P = 0.66) was found. There was no single SNP that affects the overall trend.

CONCLUSIONS

Our study showed that reduced eGFR was related to MS. The value of this study is that it provides a direction for further research on the relationship between reduced eGFR and MS.

A nomogram for predicting risk of death during hospitalization in elderly patients with Alzheimer's disease at the time of admission

Background and objectives

Elderly patients with Alzheimer's disease (AD) often have multiple underlying disorders that lead to frequent hospital admissions and are associated with adverse outcomes such as in-hospital mortality. The aim of our study was to develop a nomogram to be used at hospital admission for predicting the risk of death in patients with AD during hospitalization.

Methods

We established a prediction model based on a dataset of 328 patients hospitalized with AD -who were admitted and discharged from January 2015 to December 2020. A multivariate logistic regression analysis method combined with a minimum absolute contraction and selection operator regression model was used to establish the prediction model. The identification, calibration, and clinical usefulness of the predictive model were evaluated using the C-index, calibration diagram, and decision curve analysis. Internal validation was evaluated using bootstrapping.

Results

The independent risk factors included in our nomogram were diabetes, coronary heart disease (CHD), heart failure, hypotension, chronic obstructive pulmonary disease (COPD), cerebral infarction, chronic kidney disease (CKD), anemia, activities of daily living (ADL) and systolic blood pressure (SBP). The C-index and AUC of the model were both 0.954 (95% CI: 0.929-0.978), suggesting that the model had accurate discrimination ability and calibration. Internal validation achieved a good C-index of 0.940.

Conclusion

The nomogram including the comorbidities (i.e., diabetes, CHD, heart failure, hypotension, COPD, cerebral infarction, anemia and CKD), ADL and SBP can be conveniently used to facilitate individualized identification of risk of death during hospitalization in patients with AD.

iTRAQ-Based Proteomic Analysis of APP Transgenic Mouse Urine Exosomes

Alzheimer's disease (AD) is a common dementia disease in the elderly. To get a better understanding of the pathophysiology, we performed a proteomic analysis of the urine exosomes (U-exo) in AD model mice (J20). The polymer precipitation method was used to isolate U-exo from the urine of 3-month-old J20 and wild-type (WT) mice. Neuron-derived exosome (N-exo) was isolated from U-exo by immunoprecipitation. iTRAQ-based MALDI TOF MS/MS was used for proteomic analysis. The results showed that compared to WT, the levels of 61 and 92 proteins were increased in the J20 U-exo and N-exo, respectively. Gene ontology enrichment analysis demonstrated that the sphingolipid catabolic process, ceramide catabolic process, membrane lipid catabolic process, Aβ clearance, and Aβ metabolic process were highly enriched in U-exo and N-exo. Among these, Asah1 was shown to be the key protein in lipid metabolism, and clusterin, ApoE, neprilysin, and ACE were related to Aβ metabolism and clearance. Furthermore, protein-protein interaction analysis identified four protein complexes where clusterin and ApoE participated as partner proteins. Thus, J20 U-exo and N-exo contain proteins related to lipid- and Aβ-metabolism in the early stages of AD, providing a new insight into the underlying pathological mechanism of early AD.

Serum albumin, cognitive function, motor impairment, and survival prognosis in Parkinson disease

The role of albumin in Parkinson disease (PD) is not well understood, our study will investigate the association between the serum albumin level and risk of dementia, motor impairment, as well as survival outcome in PD. Data were obtained from the publicly available dataset in the DRYAD database (https://datadryad.org/). The original prospective study enrolled patients with PD from a single center in Japan between March 2004 and November 2007. Due to missing values, 242 and 274 participants were included in the study, in which we aimed to, respectively, analyze the relationship between serum albumin and cognitive function as well as motor impairment; additionally, 264 participants were included to assess the association between baseline serum albumin levels and risk of PD-related death with a median follow-up of 5.24 years. Compared to patients of the low tertile of albumin levels, Mini-Mental State Examination (MMSE) of patients of middle tertile increased 2.09 [95% confidence interval (CI) (0.45, 3.73), P = .013], independent of age, sex, PD duration, modified Hoehn-Yahr (mHY) stage, C-reactive protein (CRP) level, and use of nonsteroidal anti-inflammatory drugs (NSAIDs). Further analysis revealed a positive curvilinear association between albumin and MMSE, with cutoff values of 3.9. As concentration serum albumin increased, the risk of severe motor impairment was grown [odds ratio (OR) 0.34 (95% CI 0.14,0.8), P = .013] after adjustment by age, sex, PD duration, MMSE scores, CRP level, and use of NSAIDs. Albumin levels increased per unit of mg/dL, and the risk of PD-related death reduced 0.74-fold with 95% CI (0.15, 0.86) (P = .021), independent of age, sex, PD disease duration, mHY stage, CRP levels, use of NSAIDs, and MMSE. Higher serum albumin levels were significantly association with the better cognitive function when albumin was <3.9 mg/dL, and played a protective role in severe motor impairment and PD-related death.

Altered peripheral factors affecting the absorption, distribution, metabolism, and excretion of oral medicines in Alzheimer's disease

Alzheimer's disease (AD) has traditionally been considered solely a neurological condition. Therefore, numerous studies have been conducted to identify the existence of pathophysiological changes affecting the brain and the blood-brain barrier in individuals with AD. Such studies have provided invaluable insight into possible changes to the central nervous system exposure of drugs prescribed to individuals with AD. However, there is now increasing recognition that extra-neurological systems may also be affected in AD, such as the small intestine, liver, and kidneys. Examination of these peripheral pathophysiological changes is now a burgeoning area of scientific research, owing to the potential impact of these changes on the absorption, distribution, metabolism, and excretion (ADME) of drugs used for both AD and other concomitant conditions in this population. The purpose of this review is to identify and summarise available literature reporting alterations to key organs influencing the pharmacokinetics of drugs, with any changes to the small intestine, liver, kidney, and circulatory system on the ADME of drugs described. By assessing studies in both rodent models of AD and samples from humans with AD, this review highlights possible dosage adjustment requirements for both AD and non-AD drugs so as to ensure the achievement of optimum pharmacotherapy in individuals with AD.

Association Between Blood Biochemical Factors Contributing to Cognitive Decline and B Vitamins in Patients With Alzheimer's Disease

Background

Malnutrition, metabolism stress, inflammation, peripheral organs dysfunction, and B vitamins deficiency significantly contribute to the progression and mortality of Alzheimer's disease (AD). However, it is unclear which blood biochemical indicators are most closely related to cognitive decline and B vitamins deficiency (thiamine, folate, vitamin B12) in patients with AD.

Methods

This was a cross-sectional study of 206 AD patients recruited from six hospitals in China. Thiamine diphosphate (TDP), the bioactive form of thiamine, was measured by high-performance liquid chromatography fluoroscopy (HPLC) at a single center. Levels of biochemical indicators (except TDP) were measured by regular and standard laboratory tests in each hospital. Pearson's rank correlation analysis was used to assess relationships between B vitamins and biochemical indicators. T-test was used to compare the difference between ApoE ε4 and non-ApoE ε4 groups. Differences were considered statistically significant as P < 0.05.

Results

Among the biochemical results, in AD population, malnutrition indicators (erythrocyte, hemoglobin, serum albumin, and total protein) were most significantly associated with cognitive function, as was free triiodothyronine (FT3) levels which had been observed in previous study. Malnutrition and FT3 levels depend on age but not apolipoprotein E (ApoE) genotype. Meanwhile, Among the B vitamins, TDP was the most significantly associated with malnutrition indicators and FT3.

Conclusion

Our results indicated that TDP reduction could be a modifiable risk factor for malnutrition and FT3 that contributed to cognitive decline in AD patients. Correcting thiamine metabolism could serve as an optional therapy target for AD treatment.

The impact of uremic toxins on Alzheimer's disease

Alzheimer's disease (AD) is the most common type of dementia, pathologically characterized by accumulation of senile plaques and neurofibrillary tangles. Chronic kidney disease (CKD) is highly prevalent in elderly population closely associated with occurrence of dementia. Recent epidemiological and experimental studies suggest a potential association of CKD with AD. Both diseases share a panel of identical risk factors, such as type 2 diabetes; and hypertension. However, the relationship between CKD and AD is unclear. Lower clearance of a panel of uremic toxin including cystatin-C, guanidine, and adiponectin due to CKD is implied to contribute to AD pathogenesis. In this review we summarize the current evidence from epidemiological, experimental and clinical studies on the potential contribution of uremic toxins to AD pathogenesis. We describe outstanding questions and propose an outlook on the link between uremic toxins and AD.

Incidence of atrial high rate episodes after dual-chamber permanent pacemaker implantation and its clinical predictors

Atrial high rate episodes (AHRE) confers increased morbidity and mortality amongst patients with permanent pacemaker implantation (PPI). The incidence of AHREs and it's clinical predictors in Indian patients without prior history of atrial fibrillation (AF) are not well understood. A total of 100 dual-chamber PPI patients, who had no prior history of AF, underwent pacemaker interrogation starting from a minimum of 1 month after implantation to detect any AHREs. The incidence of AHREs was 17% at a mean follow up 15.2 ± 7.5 months. Only right ventricular apical lead position was found to have an independent association with AHREs (OR: 3.50, 95% CI: 1.02-12.03; p = 0.04).

Predictors of dementia amongst newly diagnosed non-valvular atrial fibrillation patients

Atrial fibrillation (AF) confers a 2-to-3-fold increased risk of developing cognitive dysfunction and dementia, independent of age and past stroke. The purpose of study was to identify risk factors for developing dementia amongst AF patients in India. This was a single-centre, prospective, observational study wherein recently diagnosed, treatment naïve, persistent non-valvular AF patients were enrolled. All patients were screened for dementia using the Mini-Mental state exam. Amongst a total of 108 patients enrolled, 40 (37%) had dementia. The most common cognitive deficits were in attention and calculation followed by memory deficits. Factors independently contributing to dementia were advanced age, female sex, presence of diabetes, elevated pulmonary artery pressures and a lower serum albumin.

Kidney Function and Risk of Physical and Cognitive Impairment in Older Persons with Type 2 Diabetes at an Outpatient Clinic with Geriatric Assessment Implementation

PURPOSE

Diabetes is associated with an increased risk of cognitive and physical functional decline that may impede disease self-management. By incorporating cognitive and physical function assessment, this study aimed to evaluate prevalence and factors associated with cognitive and physical dysfunction in older diabetic people.

METHODS

The cross-sectional study was performed from August 1, 2017 to November 30, 2018. The patients aged 65 years or older with type 2 diabetes mellitus were enrolled and the disease was routinely evaluated by blood hemoglobin A1c (A1C), blood pressure, lipids, and kidney function measured by estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine rate (UACR). Besides, cognitive dysfunction through Mini-mental State Examination (MMSE), and functional disabilities by Activities of Daily Living (ADL) questionnaire were assessed simultaneously.

RESULTS

Among 863 patients (48.3% men) with a median age of 72.0 years (interquartile range or IQR: 67.0-78.0 years), 159 (18.5%) had cognitive impairment assessed by MMSE, while 40 (4.6%) experienced at least one problem in ADL. With different A1C stratifications, it was shown that both MMSE and ADL scores were associated with glycemic control. Patients with impaired MMSE and ADL scores were older, had lower eGFR, lower blood pressure, and higher UACR levels. After adjustment of possible confounders, it was shown that age and eGFR predicted MMSE and ADL score impairment.

CONCLUSION

By incorporating physical and cognitive function screening program into routine care at a diabetes outpatient clinic, our study found that both cognitive and physical function impairment were common in older diabetic patients, and their relevant factors, including older age, and lower eGFR. It was recommended that in older individuals with diabetes, particularly those with risk factors, an additional assessment of cognitive and physical functions can be integrated into routine clinical process to provide more comprehensive management plans.

Factors that contribute to the cognitive impairment in elderly dialysis patients

AIM

To evaluate the cognitive function in dialysis patients over 60 years old and identify the contributing factors.

METHODS

A group of elderly dialysis patients in the Department of Nephrology, Pan'an People's Hospital between March 2015 and June 2018 were chosen as the subjects for this study. Patients were divided into two groups, those with cognitive impairment and those with normal cognitive function. Results of their Montreal Cognitive Assessment (MoCA) scores, Controlled Oral Word Association Test (COWAT), Wechsler Adult Intelligence Scale Digit Span subtest (WDMS), and Stanford Diagnostic Math Test (SDMT) were reviewed and analyzed.

RESULTS

Among the 110 elderly dialysis patients, 75 patients (68.18%) showed different levels of damage to their cognitive function. Their assessment scores on MoCA (total), MoCA subtests: visuospatial/executive, naming, attention, language, delayed recall, abstraction and orientation, COWAT (total), COWAT1, COWAT2, COWAT3, WMDS-Backward, and SDMT are significantly lower than patients with normal cognitive abilities (p < 0.05). Further analysis showed that the highest percentage (72.00%) of patients had impairment with visuospatial/executive function; and, of the 75 cognitive impaired patients, 37.33% showed cognitive damage in two MoCA subtests simultaneously. Patients with and without cognitive impairment showed a significant (p < 0.05) difference on factors including age, education level, employment status, financial situation, dialysis vintage, serum albumin, and hemoglobin.

CONCLUSION

Elderly patients on dialysis have a higher risk of becoming cognitive impaired. The cognitive impairment in elderly dialysis patients was significantly associated with age, dialysis vintage, and levels of serum albumin and hemoglobin.

Association Between the Prognostic Nutritional Index and Cognitive Function Among Older Adults in the United States: A Population-Based Study

BACKGROUND

Nutritional status has been recognized as an important factor influencing cognitive function-related diseases, but few comprehensive nutrition indicators are available to assess the risk of cognitive decline.

OBJECTIVE

This study aimed to investigate the relationship between the prognostic nutritional index (PNI) and cognitive function in an elderly population, and the differences in nutrient intake between different levels of nutritional risk.

METHODS

Based on cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, we included 2,564 older participants. The lower quartile of each of the four cognitive tests was considered to have cognitive function impairment (CFI). Binary and multivariate logistic regression models were used to estimate the relationship between the PNI and the odds ratio of CFI.

RESULTS

After adjustment for confounding variables, we found that the odds of CFI were significantly lower for participants with normal PNI levels than for those with low PNI levels. In a comparison of global cognitive impairment scores, participants with a normal PNI had lower ratios of poor cognitive performance than those with a low PNI. By comparing the nutrient intake at different PNI levels, we found a reduction in the intake of protein, dietary fiber, total saturated fatty acids, and multiple micronutrients in the low PNI group.

CONCLUSION

Our study shows that the PNI can be a good predictor of the odds of CFI in the elderly population and that it is a convenient indicator of reduced intake of nutrients which may be important to brain health.