Analysis of the predictive value of the Geriatric Nutritional Risk Index for osteoporosis in elderly patients with T2DM: a single-center retrospective study

Predictive Value of Preoperative Nutritional Risk Index for Screw Loosening After Lumbar Interbody Fusion in Elderly Patients With Lumbar Spine Diseases

OBJECTIVE

Pedicle screw loosening is one of the common complications in elderly patients undergoing transforaminal lumbar interbody fusion (TLIF) for lumbar spine disease. Malnutrition, prevalent among elderly patients, has been shown to be associated with increased complications. The Geriatric Nutritional Risk Index (GNRI) serves as a simple indicator of nutritional status. However, the relationship between malnutrition, particularly GNRI, and pedicle screw loosening has not been adequately investigated. This study aims to investigate the relationship between GNRI and pedicle screw loosening following TLIF to guide the perioperative nutritional management of patients and prevent postoperative complications.

METHODS

A retrospective review was conducted on clinical data from patients who underwent single-level TLIF between 2014 and 2022. Data collection encompassed patient demographics, preoperative laboratory parameters, surgery-related data, perioperative radiographic data, and patient-reported outcomes were comprehensively documented. All patients were followed up for a minimum of 12 months. The relationship between GNRI and pedicle screw loosening was evaluated by univariate and multivariate Cox regression analysis, restricted cubic spline (RCS) analysis, receiver operating characteristic (ROC) analysis, and Kaplan-Meier survival analysis.

RESULTS

A total of 426 patients were included in the study. The rate of pedicle screw loosening rate was 16.4% at a minimum follow-up of 12 months. Patients with pedicle screw loosening exhibited significantly lower GNRI (89.0 ± 8.0 vs. 99.2 ± 9.3, p < 0.001) and volumetric bone mineral density measured by quantitative computed tomography (QCT-vBMD) (84.2 [interquartile range (IQR) 79.6-92.2] vs. 104.0 [IQR 88.2-126.0] mg/cm3, p < 0.001) compared with those in the non-loosening group. Multivariate Cox regression analysis identified sex (hazard ratio [HR] 1.433, 95% confidence interval [CI] 0.714-2.876, p = 0.027), age (HR 1.062, 95% CI 1.014-1.113, p = 0.012), GNRI (HR 0.841, 95% CI 0.711-0.994, p = 0.043), and QCT-vBMD (HR 0.982, 95% CI 0.967-0.997, p = 0.019) as independent risk factors for screw loosening. RCS analysis showed that GNRI was negatively correlated with screw loosening (p < 0.0001). The area under the curve (AUC) for the GNRI in predicting pedicle screw loosening was 0.794, with a cut-off value of 95.590 (sensitivity, 85.7%; specificity 65.2%). Kaplan-Meier survival analysis identified that the lower-level GNRI group exhibited a higher cumulative incidence of screw loosening (log-rank test, p < 0.0001).

CONCLUSION

The GNRI was an independent risk factor for postoperative screw loosening in elderly patients undergoing TLIF for lumbar spine disease. Preoperative GNRI may potentially serve as a valuable tool in predicting postoperative screw loosening in elderly patients undergoing TLIF.

Association between Geriatric Nutritional Risk Index and all-cause mortality in individuals with osteoporotic fractures: a retrospective cohort study

BACKGROUND

The number of patients with osteoporotic fractures (OPFs) is on the rise because of global aging. However, few studies have examined the connection between Geriatric Nutritional Risk Index (GNRI) and overall mortality among inpatients with OPFs. Thus, our research seeks to investigate the link between GNRI and overall mortality in inpatients with OPFs.

METHODS

A retrospective cohort study was investigated on 3143 Kunshan OPFs residents aged ≥ 50 years. Participants were stratified into malnutrition (GNRI ≤ 98) and no malnutrition groups (GNRI > 98). Multivariate Cox regression analyses were utilized to evaluate the connection between GNRI and overall mortality. No non-linear association was detected through smoothed curve fitting and threshold analysis. Kaplan-Meier curves were employed to compare the cumulative risk of mortality across varying nutritional conditions. Subgroup analyses were conducted to further investigate the effects of age, sex and other clinical and laboratory factors on the link between GNRI and mortality.

RESULTS

3,143 qualified inpatients with OPFs were involved in the final evaluation. Kaplan-Meier curves revealed that the cumulative risk of mortality was markedly elevated in malnutrition group compared to no malnutrition group. In complete adjustments model, malnutrition group showed an adjusted hazard ratio (aHR) of 1.42 [95% CI 1.05, 1.90; P-value = 0.021]. Furthermore, subgroup analyses revealed that no substantial interactions were detected among all variables. (P-interaction > 0.05).

CONCLUSIONS

Reduced GNRI scores are linked to higher mortality in inpatients with OPFs. The GNRI potentially serve as a predictor for overall mortality risk in this population.

Associations of prognostic nutritional index with cardiovascular all-cause mortality among CVD patients with diabetes or prediabetes: evidence from the NHANES 2005-2018

Background

Immunonutritional status is linked to the prognosis of cardiovascular disease (CVD) and diabetes, but the relationship between immunonutritional disorders and clinical outcomes in CVD patients with diabetes is unclear. This study aims to investigate the association of the novel immunonutritional indicator of prognostic nutritional index (PNI) with all-cause and CVD mortality in diabetic and prediabetic CVD patients.

Method

This is an open-cohort study involving 1,509 CVD patients with diabetes or prediabetes collected from The National Health and Nutrition Examination Survey (NHANES) and initially interviewed between 2005 and 2018. Subjects were followed up until on December 31, 2019. Mortality outcomes and causes of death were obtained from National Death Index (NDI) records. We used restricted cubic spline (RCS) and maximally selected rank statistics method (MSRSM) to assess the nonlinearity of the PNI-mortality association and determine the optimal PNI cutoff for survival outcomes. Additionally, weighted multivariable Cox regression models, subgroup analyses, and interaction tests were employed to examine the relationship between PNI and all-cause and CVD mortality. The predictive accuracy of PNI for survival outcomes was evaluated using time-dependent receiver operating characteristic curve (ROC) analysis.

Results

During a median follow-up of 61 months (interquartile range, 33-103 months), 507 of the 1509 (33.60%) diabetic or prediabetic CVD patients died. A negative and nonlinear association between PNI and all-cause/CVD mortality was identified by RCS analysis in all patients. In the fully-adjusted Cox regression model, in the entire cohort, higher PNI (≥46.5) was significantly associated with reduced risks for all-cause and CVD mortality. A consistent association between PNI and all-cause/CVD mortality was observed in diabetic CVD patients, but not in prediabetic CVD patients. No significant interaction between PNI and other covariates was observed (all P interaction >0.05). Time-dependent ROC curve revealed that the areas under the curve (AUC) of PNI for 1-, 3-, 5-, and 10-year survival rates were 0.66, 0.66, 0.66, and 0.67 for all-cause mortality, and 0.72, 0.70, 0.72, and 0.69 for CVD mortality, respectively.

Conclusion

Increased PNI is significantly associated with reduced risks for all-cause and CVD mortality in diabetic or prediabetic CVD patients, especially for diabetic CVD patients.

The Association Between Nutritional Risk and Bone Stiffness in Elderly Men and Women in a Population-Based Study in Northeast Germany

BACKGROUND

The Geriatric Nutritional Risk Index (GNRI) has shown promising potential for identifying individuals at risk for osteoporosis in various patient cohorts. However, data from the general population confirming or refuting the usefulness of the GNRI as a risk factor for osteoporosis are sparse. We therefore aimed to clarify whether the GNRI is associated with the ultrasound-based bone stiffness index and the osteoporotic fracture risk in a sample of elderly men and women from the general population.

METHODS

Data from 1417 participants in the Study of Health in Pomerania START-2 or TREND-0 aged 65 years or older with quantitative ultrasound measurements at the heel and GNRI values were examined. In cross-sectional linear and logistic regression models, associations between the GNRI and heel stiffness index or ultrasound-based osteoporotic fracture risk were examined. All analyses were repeated after stratification of the study population according to BMI (underweight/normal weight, overweight and obese).

RESULTS

In underweight/normal weight individuals, higher, i.e., better, GNRI values had a positive effect on the stiffness index (β-coefficient per standard deviation increase in GNRI = 2.69, standard error = 1.00, p = 0.007). With increasing GNRI values, underweight/normal weight elderly men and women also had higher chances of a low osteoporotic fracture risk (odds ratio 1.42, 95% confidence interval 1.04-1.94, p = 0.026). Corresponding associations in overweight or obese individuals were absent.

CONCLUSIONS

In elderly men and women with underweight/normal weight, the GNRI is positively associated with the bone stiffness index and the related osteoporotic fracture risk. In this group, the GNRI may prove useful in identifying individuals with an elevated fracture risk.

Low geriatric nutritional risk index is associated with osteosarcopenia in older patients with type 2 diabetes mellitus

BACKGROUND

The association between the geriatric nutritional risk index (GNRI) and osteosarcopenia in older adults with type 2 diabetes mellitus (T2DM) is not clear.

METHODS

A total of 573 individuals with T2DM were included in this cross-sectional study. Osteosarcopenia was defined as the presence of both osteoporosis and sarcopenia. Appendicular skeletal muscle mass and bone mineral density (BMD) was measured by dual energy X-ray absorptiometry to diagnose sarcopenia and osteoporosis. Multivariate analyses were used to assess the association between Geriatric Nutritional Risk Index (GNRI) and osteosarcopenia.

RESULTS

The patients were divided into four groups: robust (n = 367), osteoporosis alone (n = 154), sarcopenia alone (n = 29), and osteosarcopenia (n = 23). The GNRI was the lowest in osteosarcopenia group and was positively correlated with skeletal muscle index (SMI) (r = 0.122, p = 0.004), grip strength (r = 0.154, p < 0.001), gait speed (r = 0.123, p = 0.004), and BMD of lumbar spine 2-4, femoral neck, and total hip (r = 0.137, p = 0.002; r = 0.096, p = 0.028; r = 0.086, p = 0.049, respectively). In the logistic regression model low GNRI was significantly associated with an increased risk of osteosarcopenia (adjusted OR, 4.164; 95% CI, 1.283-13.514, p = 0.018). Age provided a discriminatory effect of osteosarcopenia with an area under the curve (AUC) of 0.764. When GNRI values were added to the model, the value of the ROC curve was further improved, with an AUC of 0.842.

CONCLUSION

Low GNRI was associated with an increased risk of osteosarcopenia in older adults with T2DM. Comprehensive clinical evaluation of nutritional status by a simple tool such as GNRI might be helpful for early identification of those at high risk for osteosarcopenia in older diabetic individuals.

Geriatric nutritional risk index predicts postoperative prognosis in older patients with hip fracture: A meta-analysis

BACKGROUND

Hip fracture is common in elderly individuals and is accompanied by a relatively high mortality rate. However, it is currently difficult to accurately predict postoperative prognosis for older patients with hip fractures. The aim of this meta-analysis was to further determine the prognostic value of the geriatric nutritional risk index (GNRI) for patients who underwent hip fracture surgery.

METHODS

The Medline, EMBASE, Web of Science, and CNKI databases were searched up to September 19, 2023, for available studies. The primary and secondary outcomes were the mortality and complication rates, respectively. Hazard ratios (HRs) and relative risks with corresponding 95% confidence intervals (CIs) were separately combined to assess the associations between the GNRI and mortality and complication rates. All the statistical analyses were performed with STATA 15.0 and SPSS 22.0 software.

RESULTS

A total of 9 studies with 3959 patients were included. The pooled results demonstrated that a lower GNRI was significantly related to an increased risk of postoperative mortality (HR = 0.82, 95% CI = 0.72-0.92, P = .001). In addition, the GNRI predicted the risk of overall postoperative complications (52% vs 35.5%, P = .04) and pneumonia (33.3% vs 13.6%, P = .010).

CONCLUSION

The GNRI might serve as a novel prognostic indicator for older patients with hip fractures, and a lower GNRI indicates an increased risk of postoperative mortality and complication rates.

Establishment and validation of a nomogram clinical prediction model for osteoporosis in senile patients with type 2 diabetes mellitus

This study aimed to develop a predictive nomogram model to estimate the odds of osteoporosis (OP) in elderly patients with type 2 diabetes mellitus (T2DM) and validate its prediction efficiency. The hospitalized elderly patients with T2DM from the Affiliated Hospital of North Sichuan Medical University between July 2022 and March 2023 were included in this study. We sorted them into the model group and the validation group with a ratio of 7:3 randomly. The selection operator regression (LASSO) algorithm was utilized to select the optimal matching factors, which were then included in a multifactorial forward stepwise logistic regression to determine independent influencing factors and develop a nomogram. The discrimination, accuracy, and clinical efficacy of the nomogram model were analyzed utilizing the receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve analysis (DCA). A total of 379 study participants were included in this study. Gender (OR = 8.801, 95% CI 4.695-16.499), Geriatric Nutritional Risk Index (GNRI) < 98 (OR = 4.698, 95% CI 2.416-9.135), serum calcium (Ca) (OR = 0.023, 95% CI 0.003-0.154), glycated hemoglobin (HbA1c) (OR = 1.181, 95% CI 1.055-1.322), duration of diabetes (OR = 1.076, 95% CI 1.034-1.119), and serum creatinine (SCr) (OR = 0.984, 95% CI 0.975-0.993) were identified as independent influencing factors for DOP occurrence in the elderly. The area under the curve (AUC) of the nomogram model was 0.844 (95% CI 0.797-0.89) in the modeling group and 0.878 (95% CI 0.814-0.942) in the validation group. The nomogram clinical prediction model was well generalized and had moderate predictive value (AUC > 0.7), better calibration, and better clinical benefit. The nomogram model established in this study has good discrimination and accuracy, allowing for intuitive and individualized analysis of the risk of DOP occurrence in elderly individuals. It can identify high-risk populations and facilitate the development of effective preventive measures.