Association between Geriatric Nutritional Risk Index and Depression after Ischemic Stroke

Reply-Letter to the editor

In our previously published article, we focused on an increasing global health issue, the double burden of malnutrition, and conducted a single-center prospective study with 3160 patients to examine the combined effects of obesity and malnutrition on clinical outcomes in patients with ischemic stroke. Ana Patrícia da Silva Sou et al. and Jiqin Wu et al. recently commented on our finding, and we hope this Reply helps to clarify some of the important points we aimed to make in the original article.

Comparison of the performance of different nutritional indicators for predicting poststroke depression in older adults with ischemic stroke

Objective

This study aimed to investigate the relationships between three different nutritional indicators and poststroke depression (PSD) and to analyze the performance of these nutritional indicators in predicting the occurrence of PSD in older adults with ischemic stroke to provide a reference for nurses to identify high-risk patients with PSD early, optimize stroke management, and improve patient prognosis.

Methods

This cohort study prospectively included 239 older adults with ischemic stroke in the Department of Neurology of a hospital in Shenzhen from September 2022 to May 2023. The nutritional status of the patients were evaluated by laboratory indicators, the Mini Nutritional Assessment Short Form (MNA-SF), and the Geriatric Nutrition Risk Index (GNRI). The Hospital Anxiety and Depression Scale-Depression (HADS-D) was used to evaluate PSD. A self-designed questionnaire was used to collect demographic information and disease-related information. Binary logistic regression analysis was performed to analyze factors related to PSD, and receiver operating characteristic curve analysis was also used to compare the performance of these nutritional indicators.

Results

A total of 239 older adults with ischemic stroke were included; the mean age was 71.10 ± 7.41 years, and 66.5% (159/239) were males. The incidence of PSD was 32.6% (78/239). The incidence of PSD in the low-value group was significantly greater than that in the high-value group according to the different nutritional indices, and the difference was statistically significant (all P < 0.05). Binary logistic regression analysis revealed that the albumin (ALB) level (OR = 0.681; 95% CI, 0.508-0.913; P = 0.010), GNRI score (OR = 1.238; 95% CI, 1.034-1.483; P = 0.020), and MNA-SF score (OR = 0.708; 95% CI, 0.614-0.815; P < 0.001) were influencing factors for PSD in this population (P < 0.05). Combined with the ALB, GNRI, and MNA-SF, the area under the ROC curve for predicting the incidence of PSD in older adults with ischemic stroke was the largest and had a high degree of differentiation (AUC, 0.738; sensitivity, 75.6%; specificity, 60.9%).

Conclusion

The nutritional indices ALB, GNRI, and MNA-SF can be used as auxiliary tools to predict the risk of PSD in older adults with ischemic stroke malnutrition. Further validation by nurses in a more diverse patient population is needed to demonstrate the accuracy of the predictions.

Geriatric nutritional risk index as a predictor for fragility fracture risk in elderly with type 2 diabetes mellitus: A 9-year ambispective longitudinal cohort study

BACKGROUND & AIMS

The elderly are prone to fragility fractures, especially those suffering from type 2 diabetes mellitus (T2DM) combined with osteoporosis. Although studies have confirmed the association between GNRI and the prevalence of osteoporosis, the relationship between GNRI and fragility fracture risk and the individualized 10-year probability of osteoporotic fragility fractures estimated by FRAX remains unclear. This study aims to delve into the association between the GNRI and a fragility fracture and the 10-year probability of hip fracture (HF) and major osteoporotic fracture (MOF) evaluated by FRAX in elderly with T2DM.

METHODS

A total of 580 patients with T2DM aged ≥60 were recruited in the study from 2014 to 2023. This research is an ambispective longitudinal cohort study. All participants were followed up every 6 months for 9 years with a median of 3.8 years through outpatient services, medical records, and home fixed-line telephone interviews. According to the tertiles of GNRI, all subjects were divided into three groups: low-level (59.72-94.56, n = 194), moderate-level (94.56-100.22, n = 193), and high-level (100.22-116.45, n = 193). The relationship between GNRI and a fragility fracture and the 10-year probability of HF and MOF calculated by FRAX was assessed by receiver operating characteristic (ROC) analysis, Spearman correlation analyses, restricted cubic spline (RCS) analyses, multivariable Cox regression analyses, stratified analyses, and Kaplan-Meier survival analysis.

RESULTS

Of 580 participants, 102 experienced fragile fracture events (17.59%). ROC analysis demonstrated that the optimal GNRI cut-off value was 98.58 with a sensitivity of 75.49% and a specificity of 47.49%, respectively. Spearman partial correlation analyses revealed that GNRI was positively related to 25-hydroxy vitamin D [25-(OH) D] (r = 0.165, P < 0.001) and bone mineral density (BMD) [lumbar spine (LS), r = 0.088, P = 0.034; femoral neck (FN), r = 0.167, P < 0.001; total hip (TH), r = 0.171, P < 0.001]; negatively correlated with MOF (r = -0.105, P = 0.012) and HF (r = -0.154, P < 0.001). RCS analyses showed that GNRI was inversely S-shaped dose-dependent with a fragility fracture event (P < 0.001) and was Z-shaped with the 10-year MOF (P = 0.03) and HF (P = 0.01) risk assessed by FRAX, respectively. Multivariate Cox regression analysis demonstrated that compared with high-level GNRI, moderate-level [hazard ratio (HR) = 1.950; 95% confidence interval (CI) = 1.076-3.535; P = 0.028] and low-level (HR = 2.538; 95% CI = 1.378-4.672; P = 0.003) had an increased risk of fragility fracture. Stratified analysis exhibited that GNRI was negatively correlated with the risk of fragility fracture, which the stratification factors presented in the forest plot were not confounding factors and did not affect the prediction effect of GNRI on the fragility fracture events in this overall cohort population (P for interaction > 0.05), despite elderly females aged ≥70, with body mass index (BMI) ≥24, hypertension, and with or without anemia (all P < 0.05). Kaplan-Meier survival analysis identified that the lower-level GNRI group had a higher cumulative incidence of fragility fractures (log-rank, all P < 0.001).

CONCLUSION

This study confirms for the first time that GNRI is negatively related to a fragility fracture and the 10-year probability of osteoporotic fragility fractures assessed by FRAX in an inverse S-shaped and Z-shaped dose-dependent pattern in elderly with T2DM, respectively. GNRI may serve as a valuable predictor for fragility fracture risk in elderly with T2DM. Therefore, in routine clinical practice, paying attention to the nutritional status of the elderly with T2DM and giving appropriate dietary guidance may help prevent a fragility fracture event.

Predictive Value of Nutritional Risk for All-Cause Death and Functional Outcomes in Chinese Elderly Patients with Acute Stroke: A 3-Year Follow-Up Study

Purpose

To explore the predictive value of nutritional risk for all-cause death and functional outcomes among elderly acute stroke patients.

Patients and Methods

A total of 479 elderly acute stroke patients were enrolled in this study. The nutritional risk of patients was screened by the GNRI and NRS-2002. The primary outcome was all-cause death, and the secondary outcome was poor prognosis defined as a modified Rankin Scale (mRS) score ≥3.

Results

Based on the NRS-2002, patients with nutritional risk had a higher risk of all-cause death at 3 months (adjusted OR: 3.642, 95% CI 1.046~12.689) and at 3 years (adjusted OR: 2.266, 95% CI 1.259~4.076) and a higher risk of adverse functional outcomes at 3 months (adjusted OR: 2.748, 95% CI 1.518~4.972. Based on the GNRI, compared to those without nutritional risk, patients with mild malnutrition also had a higher risk of all-cause death at 3 months (adjusted OR: 7.186, 95% CI 1.550~33.315) and at 3 years (adjusted OR: 2.255, 95% CI 1.211~4.199) and a higher risk of adverse functional outcomes at 3 months (adjusted OR: 1.947, 95% CI 1.030~3.680), so patients with moderate and severe malnutrition had a higher risk of all-cause death at 3 months (adjusted OR: 6.535, 95% CI 1.380~30.945) and at 3 years (adjusted OR: 2.498, 95% CI 1.301~4.799) and a higher risk of adverse functional outcomes at 3 months (adjusted OR: 2.213, 95% CI 1.144~4.279).

Conclusion

Nutritional risk increases the risk of poor short-term and long-term outcomes in elderly patients with acute stroke. For elderly stroke patients, we should pay attention to early nutritional risk screening, and effective intervention should be provided to improve the prognosis of such patients.

Geriatric Nutrition Risk Index as a predictor of cardiovascular and all-cause mortality in older Americans with diabetes

BACKGROUND AND AIMS

Few studies have examined the relationship between malnutrition, as defined by the Geriatric Nutrition Risk Index (GNRI), and all-cause mortality and cardiovascular mortality events, particularly in persons with diabetes. The study aimed at the association between GNRI and all-cause mortality and cardiovascular mortality in older Americans with diabetes.

METHODS

Data from this retrospective study were obtained from the National Health and Nutrition Examination (NHANES) 1999-2016. Using data from The NHANES Public-Use Linked Mortality Files to assess all-cause mortality (ACM) and cardiovascular mortality (CVM). After excluding participants younger than 60 years and without diabetes, and with missing follow-up data, 4400 cases were left in this study. Persons with diabetes were divided by GNRI into 3 groups: GNRI ≥ 98; 92 ≤ GNRI < 98; and GNRI < 92; (No; Low; Moderate/Severe (M/S) group). We used Cox proportional hazard regression model to explore the predictive role of GNRI on ACM and CVM in elderly persons with diabetes. Restricted cubic splines to investigate the existence of a dose-response linear relationship between them.

RESULT

During a median follow-up period of 89 months, a total of 538 (12.23%) cardiovascular deaths occurred and 1890 (42.95%) all-cause deaths occurred. Multifactorial COX regression analysis showed all-cause mortality (hazard ratio [HR]: 2.58, 95% CI: 1.672-3.994, p < 0.001) and cardiovascular mortality (HR: 2.29, 95% CI: 1.063-4.936, p = 0.034) associated with M/S group risk of malnutrition in GNRI compared to no group. A negative association between GNRI and all-cause mortality was observed across gender and ethnicity. However, the same negative association between GNRI and cardiovascular mortality was observed only for males (HR:0.94, 95% CI:0.905-0.974, p < 0.001) and other races (HR:0.92, 95% CI:0.861-0.976, p = 0.007). And there was no significant correlation between low malnutrition and cardiovascular mortality (p = 0.076). Restricted cubic splines showed a nonlinear relationship between GNRI and all-cause mortality and cardiovascular mortality (non-linear p < 0.001, non-linear p = 0.019).

CONCLUSIONS

Lower GNRI levels are associated with mortality in older patients with diabetes. GNRI may be a predictor of all-cause mortality and cardiovascular mortality risk in older patients with diabetes.

Malnutrition and poststroke depression in patients with ischemic stroke

BACKGROUND

Identifying high-risk patients based on modifiable clinical characteristics, such as malnutrition, is critical to intervening with these variables to reduce the risk of post-stroke depression (PSD). The aim of this study was to investigate the effect of nutritional status on the risk of incident PSD and the trajectory of PSD risk.

METHODS

Consecutive patients with acute ischemic stroke were recruited in this observational cohort and followed up for 1 year. Multivariate logistic regressions and multilevel mixed-effects logistic regressions with random intercepts and slopes were used to investigate the effects of nutritional indexes [the Controlling Nutritional Status (CONUT) score, the Nutritional Risk Index (NRI), and the Prognostic Nutritional Index (PNI)] and body mass index (BMI) on the risk of incident PSD and the trajectory of PSD risk over the 12-month observation period.

RESULTS

A total of 538 patients were included in the final analysis. Worsening CONUT [odds ratio (OR) = 1.36; confidence interval (CI): 1.15-1.61], NRI (OR = 0.91; CI: 0.87-0.96) and PNI (OR = 0.89; CI: 0.84-0.95) scores were significantly associated with an increased risk of incident PSD. Moderate and severe risk malnutrition statuses were associated with higher incidences of PSD regardless of the malnutrition index (CONUT, NRI or PNI). Additionally, PSD risk decreased over time with a significant two-way interaction between time and CONUT, NRI, and PNI, implying that patients with elevated exposure to malnutrition showed a slower decline in PSD risk. BMI had no significant effect on the occurrence and development of PSD.

CONCLUSION

Malnutrition, but not BMI, was associated with a higher probability of incident PSD and was more likely to lead to a slower rate of decline in PSD risk.

The Assessment of the Risk of Malnutrition (Undernutrition) in Stroke Patients

Malnutrition is common in stroke patients, as it is associated with neurological and cognitive impairment as well as clinical outcomes. Nutritional screening is a process with which to categorize the risk of malnutrition (i.e., nutritional risk) based on validated tools/procedures, which need to be rapid, simple, cost-effective, and reliable in the clinical setting. This review focuses on the tools/procedures used in stroke patients to assess nutritional risk, with a particular focus on their relationships with patients' clinical characteristics and outcomes. Different screening tools/procedures have been used in stroke patients, which have shown varying prevalence in terms of nutritional risk (higher in rehabilitation units) and significant relationships with clinical outcomes in the short- and long term, such as infection, disability, and mortality. Indeed, there have been few attempts to compare the usefulness and reliability of the different tools/procedures. More evidence is needed to identify appropriate approaches to assessing nutritional risk among stroke patients in the acute and sub-acute phase of disease or during rehabilitation; to evaluate the impact of nutritional treatment on the risk of malnutrition during hospital stay or rehabilitation unit; and to include nutritional screening in well-defined nutritional care protocols.

Association of a low vitamin D status with risk of post-stroke depression: A meta-analysis and systematic review

Background

Although post-stroke depression (PSD) affects one-third of patients following an acute stroke, pooled evidence addressing the correlation between a low vitamin D status and the risk of PSD remains inconclusive.

Methods

Comprehensive database search of Medline, EMBASE, Cochrane library, and Google Scholar was performed from inception to December 2022. The primary outcome was the association of PSD risk with a low vitamin D status, while the secondary outcomes included the relationship between PSD and other risk factors.

Results

Analysis of seven observational studies published between 2014 and 2022 with 1,580 patients showed pooled incidences of vitamin D deficiency (defined as 25[OH] D levels < 50 nmol/L) and PSD of 60.1 and 26.1%, respectively. Patients with PSD had a lower circulating vitamin D concentration compared to those without [mean difference (MD) =-13.94 nmol/L, 95% CI: -21.83 to -6.05, p = 0.0005, I ² = 91%, six studies, 1,414 patients]. Meta-analysis also demonstrated a correlation between a low vitamin D level and an increased PSD risk [odd ratio (OR) = 3.25, 95% CI: 1.57-6.69, p = 0.001, I ² = 78.7%, 1,108 patients], the heterogeneity of which was found to be associated with the incidence of vitamin D deficiency but not female proportion on meta-regression. Besides, female gender (OR = 1.78, 95% CI: 1.3-2.44, p = 0.003, I ² = 31%, five studies, 1,220 patients), hyperlipidemia (OR = 1.55, 95% CI: 1.01-2.36, p = 0.04, I ² = 0%, four studies, 976 patients), and high National Institutes of Health Stroke Scale (NIHSS) scores (MD = 1.45, 95% CI: 0.58-2.32, p = 0.001, I ² = 82%, five studies, 1,220 patients) were potential risk factors for PSD. For the primary outcome, the certainty of evidence was very low. Regarding secondary outcomes, the certainty of evidence was low for BMI, female gender, hypertension, diabetes, and stroke history, and very low for age, level of education, hyperlipidemia, cardiovascular disease, and NIHSS scores.

Conclusion

The results suggested an association of a low circulating vitamin D level with an increased risk of PSD. Besides, female gender, hyperlipidemia, high NIHSS score were related to an increased risk or occurrence of PSD. The current study may imply the necessity of routine circulating vitamin D screening in this population.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022381580.

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.