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

Sun, Silu; Tao, Simin; Xi, Xiaoyan; Jiang, Tao; Zhu, Qian; Zhou, Yan; Li, Hui

doi:10.1186/s13018-023-04237-y

Cited by 4 publications

(1 citation statement)

References 46 publications

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“…Moreover, compared with BMI, ALB, and age, GNRI is a more powerful predictor of OP complicating T2DM. It has also been shown that high GNRI (with no nutritional risk) is an independent protective factor for OP in elderly T2DM patients, and it is a stronger predictor of OP in elderly T2DM patients than nutritional scores such as COUNT and PNI 25 . GNRI is used to assess the nutritional status and risk of malnutrition in elderly patients 26 .…”

Section: Discussionmentioning

confidence: 99%

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

Li,

Zhou,

Wen

et al. 2024

Sci Rep

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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.

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Section: Discussionmentioning

confidence: 99%

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

Li,

Zhou,

Wen

et al. 2024

Sci Rep

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

Liu,

Xie

2024

Medicine

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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.

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

Duan,

Chhetri,

Sun

et al. 2024

BMC Musculoskelet Disord

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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.

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

Cited by 4 publications

References 46 publications

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

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

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

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

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