Impact of the preprocedural nutrition status on the clinical outcomes of patients after pacemaker implantation for bradycardia

The Association of Geriatric Nutritional Risk Index and Chronic Kidney Disease Stages on Survival and Cardiovascular or Limb Events Following Endovascular Therapy

BACKGROUND

There are little available data about the impact of geriatric nutritional risk index (GNRI) on clinical outcomes following endovascular therapy (EVT) in chronic limb-threatening ischemia (CLTI) regarding the severities of renal dysfunction (RD).

AIMS

The aim of this study is to evaluate the impact of GNRI on clinical outcomes following EVT in CLTI regarding the severities of RD.

METHODS

We enrolled 705 consecutive CLTI cases treated with EVT between January 2010 and December 2019 at our hospital. The GNRI on admission was calculated as follows: [14.89 × albumin (g/dL)] + [41.7 × (body weight/ideal body weight)]. Study population were divided into 2 groups based on the median GNRI: low group (GNRI < 92) and high group (GNRI ≥ 92). Next, study population was divided to 3 groups according to estimate glomerular filtration rate (eGFR), which was defined as early RD group (60 ≤ eGFR), advanced RD group (15 ≤ eGFR < 60), and end-stage renal dysfunction (ESRD) group (eGFR < 15). The primary endpoint was 2-year amputation-free survival (AFS).

RESULTS

The median follow-up duration was 25.2 months. Amputation-free survival was significantly lower in the low GNRI group regardless of any severities of RD (59.1% vs 90.2%, Log Rank P<0.001 in early RD group, 59.6% vs 80.8%, Log Rank P=0.011 in advanced RD group, 32.8% vs 61.1%, Log Rank P<0.001 in ESRD group).

CONCLUSION

The decrease of GNRI could predict clinical outcomes in CLTI following EVT regardless of any severities of RD based on eGFR.

CLINICAL IMPACT

The decrease of geriatric nutritional risk index was associated with worse outcomes in chronic limb-threatening ischemia following endovascular therapy regardless of any severities of renal dysfunction. Because both renal dysfunction and chronic limb-threatening ischemia could potentially have any inflammation, the geriatric nutritional risk index, which can reflect both nutrition-related risks and inflammation severity, can be a plausible marker in predicting adverse events after endovascular therapy in chronic limb-threatening ischemia patients with renal dysfunction.

Implication of geriatric nutritional risk index on treatment response and long-term prognosis in patients with cardiac resynchronization therapy

PURPOSE

Geriatric Nutritional Risk Index (GNRI) is a simple tool for assessing the nutritional status of the aging population. This study aims to explore the clinical implication of GNRI on treatment response and long-term clinical outcomes in heart failure (HF) patients receiving cardiac resynchronization therapy (CRT).

METHODS

Patients who underwent CRT implantation or upgrade at our hospital were retrospectively included. The association of GNRI and its tertiles with the echocardiographic response, all-cause mortality or heart transplantation, and the first hospitalization due to HF were investigated.

RESULTS

Totally, 647 patients were enrolled, with a median age of 60 [Interquartile Range (IQR): 52-67] years and mean score of GNRI at 107.9 ± 23.7. Super-response rates increased significantly among the GNRI T1, T2, and T3 groups (25.1%, 29.8% vs. 41.1%, P = 0.002). Patients with higher GNRI were more likely to have better LVEF improvement after multiple adjustments (OR = 1.13, 95% CI: 1.04-1.23, P = 0.010). Higher GNRI was independently associated with a lower risk of all-cause mortality or heart implantation (HR = 0.95, 95% CI: 0.93-0.96, P < 0.001) and HF hospitalization (HR = 0.96, 95% CI: 0.95-0.98, P < 0.001). The inclusion of GNRI enhanced the predictability of all-cause mortality based on traditional model, including sex, New York Heart Association functional class, left bundle branch block, QRS reduction, and N-terminal pro-B-type natriuretic peptide level (C statistics improved from 0.785 to 0.813, P = 0.007).

CONCLUSION

Higher GNRI was associated with better treatment response and long-term prognosis in HF patients with CRT. Evaluation of nutritional status among CRT population is necessary for individualized choice of potential responders.

Prognostic Value of Four Preimplantation Malnutrition Estimation Tools in Predicting Heart Failure Hospitalization of the Older Diabetic Patients with Right Ventricular Pacing

OBJECTIVES

The prognostic value of preimplantation nutritional status is not yet known for older diabetic patients that received right ventricular pacing (RVP). The study aimed to investigate the clinical value of the four malnutrition screening tools for the prediction of heart failure hospitalization (HFH) in older diabetic patients that received RVP.

DESIGN

Retrospective observational cohort study.

SETTING AND PARTICIPANTS

This study was conducted between January 2017 and January 2018 at the Fuwai Hospital, Beijing, China, and included older (age ≥ 65 years) diabetic patients that received RVP for the first time Measurements: The Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI), Naples Prognostic Score (NPS), and the Controlling Nutritional Status (CONUT) score were used to estimate the preimplantation nutritional status of the patients. Univariate and multivariate Cox proportional hazard regression analyses were performed to investigate the association between preimplantation malnutrition and HFH.

RESULTS

Overall, 231 older diabetic patients receiving RVP were included. The median follow-up period after RVP was 53 months. HFH was reported for 19.9% of the included patients. Our results showed preimplantation malnutrition for 18.2%, 15.2%, 86.6% and 66.2% of the included patients based on the PNI, GNRI, NPS, and CONUT score, respectively. The cumulative rate of HFH during follow-up period was significantly higher for patients in the preimplantation malnutrition group based on the PNI (log-rank = 13.0, P = 0.001), GNRI (log-rank = 8.5, P = 0.01), and NPS (log-rank = 15.7, P < 0.001) compared to the normal nutrition group, but was not statistically significant for those in the preimplantation malnutrition group based on the CONUT score (log-rank = 2.7, P = 0.3). As continuous variables, all the nutritional indices showed significant correlation with HFH (all P < 0.05). However, multivariate analysis showed that only GNRI was independently associated with HFH (HR = 0.97, 95% CI: 0.937-0.997, P = 0.032). As categorical variables, PNI, GNRI, and NPS showed significant correlation with HFH. After adjustment of confounding factors, moderate-to-severe degree of malnutrition was an independent predictor of HFH based on the PNI (HR = 4.66, 95% CI: 1.03-21.00, P = 0.045) and GNRI (HR = 3.02, 95% CI: 1.02-9.00, P = 0.047).

CONCLUSION

Preimplantation malnutrition was highly prevalent in older diabetic patients that received RVP. The malnutrition prediction tools, PNI and GNRI, showed significant prognostic value in accurately predicting HFH in older diabetic patients with RVP.

Predictors of Pacemaker-Induced Cardiomyopathy and Importance of Nutritional Status and Prognostic Nutritional Index

Background

Long-term right ventricular (RV) pacing may cause progressive left ventricular systolic dysfunction, and malnutrition is related to adverse cardiovascular outcomes in patients with heart failure. We aimed to evaluate the relationship between immunonutritional status and the development of pacing-induced cardiomyopathy (PICMP).

Methods

This study included 434 patients who underwent permanent pacemaker (PPM) implantation and had preserved left ventricular ejection fraction (LVEF) of > 40%. At six months of follow-up, the patients with LVEF < 40% were defined as having PICMP. Baseline prognostic nutritional index (PNI) was calculated based on serum albumin and lymphocyte count.

Results

Overall, 16.5% of the our study patients developed PICMP. The PICMP group had more males (p = 0.013), lower baseline LVEF values (p = 0.014) and lower baseline PNI levels (p < 0.001). RV pacing ratios and paced QRS intervals were higher in the PICMP group (p < 0.001 for both), but the types of implanted pacemakers were similar for all patients (p = 0.709). According to regression analyses, baseline LVEF (p = 0.020), PNI (p < 0.001), C-reactive protein level (p = 0.012), RV pacing ratio (p < 0.001) and paced QRS interval (p = 0.001) were independent predictors of PICMP development. A cut-off PNI value ≤ 43.2 at the time of PPM implantation could predict PICMP development with a sensitivity of 85.5% and specificity of 86.7% (p < 0.001).

Conclusions

Identifying poor nutritional status using the PNI may be an important concept to predict PICMP development, and optimizing nutritional status might help to reduce adverse outcomes in these patients.

Predictors of outcomes in hospitalized patients undergoing pacemaker insertion: Analysis from the national inpatient database (2016-2017)

BACKGROUND

Pacemaker implantation in the U.S. is rising due to an aging population. The aim of this analysis was to identify risk factors associated with increased mortality and complications in hospitalized patients requiring pacemaker implantation.

METHODS

We performed a retrospective analysis using the National Inpatient Sample database, identifying hospitalized patients who underwent pacemaker implantation using International Classification of Disease, Tenth Revision, Clinical Modification codes. Independent predictors of inpatient mortality were identified using multivariate logistic regression analysis.

RESULTS

There were 242,980 hospitalizations with pacemaker implantation during 2016 and 2017. The most frequently encountered indications for hospitalizations involving pacemaker insertion included sick sinus syndrome (SSS) (27.60%), complete atrioventricular (AV) block (21.57%), and second-degree AV block (7.83%). Chronic liver disease was associated with the highest adjusted odds of inpatient mortality (aOR = 5.76, 95% CI: 4.46 to 7.44, p < .001). Comorbid anemia had the highest statistically significant adjusted odds ratio (aOR) for predictors of post-procedural cardiac complications (aOR = 3.17, 95% CI: 2.81 to 3.58, p < .001). Mortality in hospitalized patients needing pacemaker implantation was 1.05%. About 3.36% of hospitalizations developed post procedural circulatory complications (PPCC), 2.45% developed sepsis, and 1.84% developed mechanical complications of cardiac electronic devices.

CONCLUSIONS

We identified several predictors of inpatient mortality in hospitalized patients undergoing pacemaker implantation, including chronic liver disease, protein-calorie malnutrition, chronic heart failure, anemia, and history of malignancy. Anemia, chronic liver disease, and congestive heart failure were independent predictors of adverse outcomes in such patients.

Geriatric nutritional risk index as a predictor of arrhythmia recurrence after catheter ablation of atrial fibrillation

BACKGROUND AND AIMS

The nutritional risk of patients who undergo atrial fibrillation (AF) ablation varies. Its impact on the recurrence after ablation is unclear. We sought to evaluate the relationship between the nutritional risk and arrhythmia recurrence in patients who undergo AF ablation.

METHODS AND RESULTS

We enrolled 538 patients (median 67 years, 69.9% male) who underwent their first AF ablation. Their nutritional risk was evaluated using the pre-procedural geriatric nutritional risk index (GNRI), and the patients were classified into two groups: No-nutritional risk (GNRI ≧ 98) and Nutritional risk (GNRI < 98). The primary endpoint was a recurrence of an arrhythmia, and its relationship to the nutritional risk was evaluated. We used propensity-score matching to adjust for differences between patients with a GNRI-based nutritional risk and those without a nutritional risk. A nutritional risk was found in 10.6% of the patients, whereas the remaining 89.4% had no-nutritional risk. During a mean follow-up of 422 days, 91 patients experienced arrhythmia recurrences. The patients with a nutritional risk had a significantly higher arrhythmia recurrence rate both in the entire study cohort (Log-rank p = 0.001) and propensity-matched cohort (Log-rank p = 0.006). In a Cox proportional hazard analysis, the nutritional risk independently predicted arrhythmia recurrences in the entire study cohort (hazard ratio [HR]: 3.91, 95% confidence interval [CI]: 1.84-8.35, p < 0.001) and propensity-matched cohort (HR: 6.49, 95% CI: 1.42-29.8, p = 0.016).

CONCLUSION

A pre-procedural malnutrition risk was significantly associated with increased arrhythmia recurrences in patients who underwent AF ablation.

Optimal cut-off value of preprocedural geriatric nutritional risk index for predicting the clinical outcomes of patients undergoing endovascular revascularization for peripheral artery disease

BACKGROUND

Malnutrition measured by the geriatric nutritional risk index (GNRI) was reported to be associated with poor prognosis for patients with peripheral artery disease (PAD). However, the optimal cut-off value of preprocedural GNRI for critical limb ischemia (CLI) and intermittent claudication (IC) is unknown. We aimed to determine its optimal cut-off value for CLI or IC patients requiring endovascular revascularization.

METHODS

We explored data of 2246 patients (CLI: n = 1061, IC: n = 1185) registered in the Tokyo-taMA peripheral vascular intervention research COmraDE (TOMA-CODE) registry, which prospectively enrolled consecutive PAD patients who underwent endovascular revascularization in 34 hospitals in Japan from August 2014 to August 2016. The optimal cut-off values of GNRI were assessed by the survival classification and regression tree (CART) analyses, and the survival curve analyses for major adverse cardiovascular and limb events (MACLEs) were performed for these cut-off values.

RESULTS

In addition to the first cut-off value of 96.2 in CLI and 85.6 in IC, the survival CART provided an additional cut-off value of 78.2 in CLI and 106.0 in IC for further risk stratification. The survival curve was significantly stratified by the GNRI-based malnutrition status in both CLI [high risk: 47.7% (51/107), moderate: 30.1% (118/392), and low: 10.2% (53/520), log-rank p < 0.001] and IC [high risk: 14.3% (7/49), moderate: 4.5% (29/646), and low: 0.5% (2/407), log-rank p < 0.001]. The multivariate Cox-proportional hazard analysis showed that a higher GNRI was significantly associated with a better outcome in both CLI [hazard ratio (HR) per 1-point increase: 0.97, 95% CI: 0.96-0.98, p < 0.001] and IC (HR: 0.94, 95% CI: 0.91-0.97, p < 0.001).

CONCLUSIONS

Preprocedural nutritional status significantly stratified future events in patients with PAD. Given that the optimal cut-off value of GNRI in CLI was almost 10-points lower than that of IC, using a disease-specific cut-off value is important for risk stratification.