Prognostic Effect of a Novel Simply Calculated Nutritional Index in Acute Decompensated Heart Failure

Ishiwata, Sayaki; Yatsu, Shoichiro; Kasai, Takatoshi; Sato, Akira; Matsumoto, Hiroki; Shitara, Jun; Shimizu, Megumi; Murata, Azusa; Kato, Takao; Suda, Shoko; Hiki, Masaru; Matsue, Yuya; Naito, Ryo; Iwata, Hiroshi; Takagi, Atsutoshi; Daida, Hiroyuki

doi:10.3390/nu12113311

Cited by 15 publications

(21 citation statements)

References 29 publications

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“…The TCBI index, a novel nutritional metabolism index, is calculated from variables reflecting lipid metabolism measured from blood tests. Some studies showed that TCBI was a useful prognostic indicator in patients with a wide range of CVD ( 11 , 40 , 41 ). The most significant advantage of the TCBI is the simplicity of the calculation, which saves time and effort in caring for and treating ICU (intensive care unit) patients ( 40 , 41 ).…”

Section: Discussionmentioning

confidence: 99%

“…Some studies showed that TCBI was a useful prognostic indicator in patients with a wide range of CVD ( 11 , 40 , 41 ). The most significant advantage of the TCBI is the simplicity of the calculation, which saves time and effort in caring for and treating ICU (intensive care unit) patients ( 40 , 41 ). The calculation of TCBI simply requires multiplying three variables, while anyone who calculates GNRI or PNI needs to know the constant values and how to calculate ideal body weight.…”

Section: Discussionmentioning

confidence: 99%

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Association of Four Nutritional Scores With All-Cause and Cardiovascular Mortality in the General Population

et al. 2022

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Background and AimsMalnutrition is a well known risk factor for adverse outcomes in patients with cancer, cardiovascular disease (CVD) and chronic kidney disease, but epidemiological evidence on its relationship with the long-term risk of all-cause mortality and cardiovascular death is limited.MethodsA total of 20,116 adults from the United States National Health and Nutrition Examination Survey 2007–2014 were enrolled. The Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), Controlling Nutritional Status (CONUT) score, and Triglycerides (TG) × Total Cholesterol (TC) × Body Weight (BW) Index (TCBI) were calculated at baseline. Cox regression and the Kaplan–Meier analysis were conducted when participants were divided into three groups according to the tertiles of objective nutritional scores. Restricted cubic spline was performed to further explore the shape of the relationship between all-cause mortality, cardiovascular death, and nutritional scores. In addition, the area under the curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were conducted to assess which nutritional scores have the greatest predictive value for all-cause death and cardiovascular death in the general population.ResultsThe cumulative incidence of all-cause death and cardiovascular death was significantly higher in participants with a higher CONUT score, lower GNRI, and lower PNI. TCBI showed the worst performance on grading and risk assessment. After adjusting confounding factors, the lowest PNI and GNRI tertile and highest COUNT score were independently and significantly associated with increased risk of all-cause death (all P < 0.01) and cardiovascular death (all P < 0.05) analyzed by a multivariate Cox regression model. An L-shaped association between the HR (hazard ratio) of all-cause mortality and nutritional scores (GNRI, PNI and TCBI) was observed in the overall populations. In addition, the PNI had the highest predictive value for all-cause mortality [AUC: 0.684, 95% confidence interval (CI): 0.667–0.701] and cardiovascular death (AUC: 0.710, 95% CI: 0.672–0.749) in the general population compared with other nutritional scores.ConclusionThe poorer the nutritional status of the general population, the higher the all-cause mortality and cardiovascular mortality. The PNI score may provide more useful predictive values than other nutritional scores.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Association of Four Nutritional Scores With All-Cause and Cardiovascular Mortality in the General Population

et al. 2022

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“…In hospitalized critical patients with mechanical circulatory support devices, TCBI was an independent predictor of all-cause mortality ( Minami-Takano et al, 2019 ). In patients with acute decompensated heart failure, TCBI can improve the prognostic prediction over traditional risk factors such as hemoglobin and serum sodium level ( Ishiwata et al, 2020 ). Similarly, our study contributes to the existing literature on the relation of TCBI with DCM outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…Some simplified nutritional screening tools such as the Geriatric Nutritional Risk Index (GNRI), the prognostic nutritional index (PNI), and the Controlling Nutritional Status (CONUT), have been found to predict the outcome of heart failure ( Lin et al, 2016 ). Recently, a novel nutritional index, triglycerides × total cholesterol × body weight index (TCBI), has been proposed to be a useful prognostic indicator in patients with CAD ( Doi et al, 2018 ; Kim et al, 2021 ), acute decompensated heart failure ( Ishiwata et al, 2020 ), and critically ill patients ( Minami-Takano et al, 2019 ). However, in patients with DCM, the prognostic value of TCBI has not yet been studied.…”

Section: Introductionmentioning

confidence: 99%

A novel nutritional index as a predictor of mortality in dilated cardiomyopathy: a retrospective study

Wang

Qing

Chen

et al. 2022

PeerJ

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Background Research has associated nutritional status with the prognosis of cardiovascular diseases. This study aimed to investigate the prognostic value of a novel nutritional index, triglycerides × total cholesterol × body weight index (TCBI), in patients with dilated cardiomyopathy (DCM). Methods This retrospective cohort study enrolled 445 patients with DCM. The median follow-up period was 2.8 years, and the primary endpoint was all-cause death. Results During follow-up, the all-cause mortality was observed in 135 out of 445 patients (30.3%). In Kaplan–Meier survival analysis, the third TCBI tertile had a lower mortality risk (T3 vs. T2 vs. T1: 16.9% vs. 35.1% vs. 38.9%; log-rank P < 0.001). In the multivariable Cox regression analysis, patients in the third tertile were associated with a decreased mortality, whereas there was no significant difference between the T2 and T1 groups. Moreover, TCBI could significantly improve risk stratification (continuous net reclassification improvement and integrated discrimination improvement) over the Geriatric Nutritional Risk Index (GNRI) and N-terminal pro-brain natriuretic peptide (NT-proBNP). Conclusions TCBI is independently associated with long-term survival in patients with DCM. Combination of TCBI and other biomarkers, such as GNRI and NT-proBNP, can significantly improve prognostic prediction. Further studies with larger sample size are required to validate our results.

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“…A novel and more precise scoring system has been recently proposed: The Geriatric Nutritional Risk Index (GNRI) [ 9 ]. It has been validated in institutionalized patients [ 10 ], dialysis patients [ 11 ], and patients with heart failure [ 12 ]. GNRI scoring includes serum albumin; therefore, it may be better correlated with systemic inflammation in the elderly.…”

Section: Introductionmentioning

confidence: 99%

Identification of Mortality Risks in the Advancement of Old Age: Application of Proportional Hazard Models Based on the Stepwise Variable Selection and the Bayesian Model Averaging Approach

2021

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Identifying factors that affect mortality requires a robust statistical approach. This study’s objective is to assess an optimal set of variables that are independently associated with the mortality risk of 433 older comorbid adults that have been discharged from the geriatric ward. We used both the stepwise backward variable selection and the iterative Bayesian model averaging (BMA) approaches to the Cox proportional hazards models. Potential predictors of the mortality rate were based on a broad range of clinical data; functional and laboratory tests, including geriatric nutritional risk index (GNRI); lymphocyte count; vitamin D, and the age-weighted Charlson comorbidity index. The results of the multivariable analysis identified seven explanatory variables that are independently associated with the length of survival. The mortality rate was higher in males than in females; it increased with the comorbidity level and C-reactive proteins plasma level but was negatively affected by a person’s mobility, GNRI and lymphocyte count, as well as the vitamin D plasma level.

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Prognostic Effect of a Novel Simply Calculated Nutritional Index in Acute Decompensated Heart Failure

Cited by 15 publications

References 29 publications

Association of Four Nutritional Scores With All-Cause and Cardiovascular Mortality in the General Population

Association of Four Nutritional Scores With All-Cause and Cardiovascular Mortality in the General Population

A novel nutritional index as a predictor of mortality in dilated cardiomyopathy: a retrospective study

Identification of Mortality Risks in the Advancement of Old Age: Application of Proportional Hazard Models Based on the Stepwise Variable Selection and the Bayesian Model Averaging Approach

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