OBJECTIVE: To explore the relationship between the geriatric nutritional risk index (GNRI) and cognitive function. METHODS: A cross-sectional study method was conducted. People aged ≥ 60 years from the National Health and Nutrition Examination Survey (NHANES) databases from 1999 to 2002 and 2011 to 2014 were included as study subjects. The participants were divided into three groups based on their GNRI scores: a medium-high risk group (82 ≤ GNRI < 92), a low risk group (92 ≤ GNRI < 98), and a no-risk group (GNRI ≥ 98). Demographic characteristics (gender, age, race, education), chronic diseases [chronic bronchitis, emphysema, thyroid problems, coronary heart disease, angina pectoris, stroke, hypertension, diabetes mellitus, and depression score on the patient health questionnaire (PHQ-9)], lifestyle habits (history of smoking, hours of sleep), etc., were collected. Cognitive function was assessed using the consortium to establish a registry for Alzheimer's disease word learning subtest (CERAD-WL), animal fluency test (AFT), and digit symbol substitution test (DSST) for the 2011-2014 data, while only the DSST was used for the 1999-2002 data. Differences in the above information among the GNRI cohorts were compared. Factors affecting cognitive function in the population were analyzed using multifactorial Logistic regression. RESULTS: 2 653 participants from 2011 to 2014 and 2 380 participants from 1999 to 2002 were enrolled, with a total of 5 033 participants in the study. There were statistically significant differences in age, stroke, diabetes mellitus, DSST score, AFT score, CERAD score test 1 recall (Cst1), and CERAD score test 2 recall (Cst2) among the GNRI groups. Multifactorial Logistic regression analysis of data from 2011 to 2014 showed that in model 3 (DSST score, age, gender, race, marriage, education, hours of sleep, history of smoking, emphysema, thyroid problems, chronic bronchitis, coronary heart disease, angina pectoris, hypertension, diabetes mellitus, depression score on the PHQ-9, and stroke) adjusted for all covariates, GNRI was a protective factor for DSST [odds ratio (OR) = 1.03, 95% confidence interval (95%CI) was 1.00 to 1.05, P = 0.03]; Logistic regression analyse for 1999 to 2002 and 2011 to 2014 showed a significant association even after adjustment for covariates (OR = 1.02, 95%CI was 1.00 to 1.03, P = 0.02). Subgroup Logistic regression analyses of the total population from 2011 to 2014 showed a significant association between GNRI and DSST scores (OR = 1.02, 95%CI was 1.01 to 1.03, P < 0.001), with significant associations in the age subgroups of 60 to 64 years old, across gender, non-Hispanic Whites and Blacks, by education, and by marital status associations were significant (all P < 0.05). Subgroup Logistic regression analyse of the total populations from 1999 to 2002 and 2011 to 2014 showed a significant association between the GNRI and DSST score (OR = 1.01, 95%CI was 1.01 to 1.02, P < 0.001), but did not show a significant year difference (interaction P = 0.503), and the newly found in the smoking population the association was also more significant (P < 0.01). CONCLUSION The GNRI correlates with the presence of cognitive functions related to processing speed, sustained attention, and executive function, and may be able to serve as an indicator for the assessment or prediction of related cognitive functions.
Humans ; Cross-Sectional Studies ; Aged ; Middle Aged ; Nutrition Surveys ; Cognition ; Female ; Male ; Nutritional Status ; Risk Factors ; Geriatric Assessment

Objective Acute kidney injury (AKI) frequently occurs after catheter-based interventional procedures and increases mortality. How-ever, the implications of AKI before thoracic endovascular aneurysm repair (TEVAR) of type B acute aortic dissection (AAD) remain un-clear. This study evaluated the incidence, predictors, and in-hospital outcomes of AKI before TEVAR in patients with type B AAD. Meth-ods Between 2009 and 2013, 76 patients were retrospectively evaluated who received TEVAR for type B AAD within 36 h from symptom onset. The patients were classified into no-AKI vs. AKI groups, and the severity of AKI was further staged according to kidney disease:im-proving global outcomes criteria before TEVAR. Results The incidence of preoperative AKI was 36.8%. In-hospital complications was significantly higher in patients with preoperative AKI compared with no-AKI (50.0%vs. 4.2%, respectively;P<0.001), including acute renal failure (21.4%vs. 0, respectively;P<0.001), and they increased with severity of AKI (P<0.001). The maximum levels of body tem-perature and white blood cell count were significantly related to maximum serum creatinine level before TEVAR. Multivariate analysis showed that systolic blood pressure on admission (OR:1.023;95%CI:1.003–1.044;P=0.0238) and bilateral renal artery involvement (OR:19.076;95%CI:1.914–190.164;P=0.0120) were strong predictors of preoperative AKI. Conclusions Preoperative AKI frequently oc-curred in patients with type B AAD, and correlated with higher in-hospital complications and enhanced inflammatory reaction. Systolic blood pressure on admission and bilateral renal artery involvement were major risk factors for AKI before TEVAR.