Association of prognostic nutritional index with the risk of all-cause mortality and cardiovascular mortality in patients with type 2 diabetes: NHANES 1999–2018

Ning, Yachan; Pan, Dikang; Guo, Julong; Su, Zhixiang; Wang, Jingyu; Wu, Sensen; Gu, Yongquan

doi:10.1136/bmjdrc-2023-003564

Cited by 3 publications

(1 citation statement)

References 33 publications

(45 reference statements)

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“…Non-normal data were presented as median (interquartile ranges). For categorical variables, the chi-square test or Fisher’s exact test was used in the univariate analysis, while the t -test or rank-sum test was used for continuous variables ( Ning et al, 2023 ). In the training cohort, multivariate analysis was conducted using the least absolute shrinkage and selection operator (LASSO) logistic regression analysis to identify independent risk factors and construct a prediction nomogram for cognitive impairment.…”

Section: Methodsmentioning

confidence: 99%

A glimpse into the future: revealing the key factors for survival in cognitively impaired patients

Wei,

Pan,

et al. 2024

Front. Aging Neurosci.

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BackgroundDrawing on prospective data from the National Health and Nutrition Examination Survey (NHANES), our goal was to construct and validate a 5-year survival prediction model for individuals with cognitive impairment (CI).MethodsThis study entailed a prospective cohort design utilizing information from the 2011–2014 NHANES dataset, encompassing individuals aged 40 years or older, with updated mortality status as of December 31, 2019. Predictive models within the derivation and validation cohorts were assessed using logistic proportional risk regression, column-line plots, and least absolute shrinkage and selection operator (LASSO) binomial regression models.ResultsThe study enrolled a total of 1,439 participants (677 men, mean age 69.75 ± 6.71 years), with the derivation and validation cohorts consisting of 1,007 (538 men) and 432 (239 men) individuals, respectively. The 5-year mortality rate stood at 16.12% (n = 232). We devised a 5-item column-line graphical model incorporating age, race, stroke, cardiovascular disease (CVD), and blood urea nitrogen (BUN). The model exhibited an area under the curve (AUC) of 0.772 with satisfactory calibration. Internal validation demonstrated that the column-line graph model displayed strong discrimination, yielding an AUC of 0.733, and exhibited good calibration.ConclusionTo sum up, our study successfully developed and internally validated a 5-item nomogram integrating age, race, stroke, cardiovascular disease, and blood urea nitrogen. This nomogram exhibited robust predictive performance for 5-year mortality in individuals with CI, offering a valuable tool for prognostic evaluation and personalized care planning.

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Section: Methodsmentioning

confidence: 99%

A glimpse into the future: revealing the key factors for survival in cognitively impaired patients

Wei,

Pan,

et al. 2024

Front. Aging Neurosci.

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Predictive Ability of Inflammatory Markers on In-Hospital Outcomes in Patients Admitted to Coronary Care Unit (MORCOR-TURK INFLAME)

Kümet,

Özgeyik,

Topuz

et al. 2024

Angiology

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We investigated the prognostic implications of the systemic immune-inflammatory index (SII), atherogenic index of plasma (AIP), C-reactive protein/albumin ratio (CAR), neutrophil–lymphocyte ratio (NLR), prognostic nutritional index (PNI), and triglyceride/glucose index (TGI) in the MORtality predictors in the CORonary Care Units in TURKey (MORCOR-TURK) population. This is the largest registry of coronary care unit (CCU) patients in Turkey (3157 patients admitted to CCU in 50 different centers). The study population was divided into two according to in-hospital survival status; 137 patients (4.3%) died in-hospital follow-up. A significant correlation was found between death and SII, CAR, NLR, and PNI but not for AIP and TGI in logistic regression. In Model 1 (combining parameters proven to be risk predictors), the −2 log-likelihood ratio was 888.439, Nagelkerke R2 was 0.235, and AUC (area under curve) was 0.814 (95% CI: 0.771-0.858). All other models were constructed by adding each inflammatory marker separately to Model 1. Only Model 3 (CAR + Model 1) had a significantly greater AUC than Model 1 (DeLong P = .01). Our study showed that CAR, but not other inflammatory index, is a significant predictor of in-hospital mortality in CCU patients when added to proven risk predictors.

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The effect of prognostic nutritional index on diabetic patients with myocardial infarction

Peng,

Lin,

Luo

et al. 2024

Diabetol Metab Syndr

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Background The prognostic nutritional index (PNI), a simple and comprehensive predictor of nutritional and immunological health, is connected to cancer and cardiovascular disease. The effects of PNI on myocardial infarction (MI) in individuals with diabetes remain unclear. Thus, we aim to investigate the correlation of PNI with predictive outcomes in this specific population group to inform therapeutic decision-making. Methods This prospective observational study included 417 diabetic patients with MI who underwent coronary angiography intervention at Fujian Medical University Union Hospital from May 2017 to May 2020. We collected follow-up and prognostic data from these patients at 6, 12, 18, and 24 months post-procedure via outpatient visits or phone interviews. The main focus of the study was on major adverse cardiovascular events (MACE) in the two years after surgery. Based on the median PNI, patients were categorized into two groups: high PNI (H-PNI) and low PNI (L-PNI). Data were analyzed using IBM SPSS 25.0. Kalpan-Meier survival curves and Cox proportional hazards regression analysis were utilized to examine the associations between preoperative PNI and the prognosis of diabetic patients with MI. Results In the study, 417 participants were observed for two years. Of these patients, 159 (38.1%) had MACE. According to the Kaplan–Meier curves, patients in the L-PNI group had more MACE than those in the H-PNI group (log-rank p < 0.001) and had a heightened susceptibility to all categories of MACE. After adjusting for confounding variables, the corrected hazard ratio for developing unstable angina in the L-PNI group was 2.55 (95% CI 1.57–4.14, p < 0.001). Conclusion Low PNI levels are associated with MACE after coronary angiography intervention in diabetic patients with myocardial infarction. This highlights the prognostic value of PNI and broadens its potential use in larger populations. Trial registration: Not applicable.

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Association of prognostic nutritional index with the risk of all-cause mortality and cardiovascular mortality in patients with type 2 diabetes: NHANES 1999–2018

Cited by 3 publications

References 33 publications

A glimpse into the future: revealing the key factors for survival in cognitively impaired patients

A glimpse into the future: revealing the key factors for survival in cognitively impaired patients

Predictive Ability of Inflammatory Markers on In-Hospital Outcomes in Patients Admitted to Coronary Care Unit (MORCOR-TURK INFLAME)

The effect of prognostic nutritional index on diabetic patients with myocardial infarction

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