Despite the global impact of macrophage activation in vascular disease, the underlying mechanisms remain obscure. Here we show, with global proteomic analysis of macrophage cell lines treated with either IFNγ or IL-4, that PARP9 and PARP14 regulate macrophage activation. In primary macrophages, PARP9 and PARP14 have opposing roles in macrophage activation. PARP14 silencing induces pro-inflammatory genes and STAT1 phosphorylation in M(IFNγ) cells, whereas it suppresses anti-inflammatory gene expression and STAT6 phosphorylation in M(IL-4) cells. PARP9 silencing suppresses pro-inflammatory genes and STAT1 phosphorylation in M(IFNγ) cells. PARP14 induces ADP-ribosylation of STAT1, which is suppressed by PARP9. Mutations at these ADP-ribosylation sites lead to increased phosphorylation. Network analysis links PARP9–PARP14 with human coronary artery disease. PARP14 deficiency in haematopoietic cells accelerates the development and inflammatory burden of acute and chronic arterial lesions in mice. These findings suggest that PARP9 and PARP14 cross-regulate macrophage activation.

The TCB index (triglycerides × total cholesterol × body weight), a novel simply calculated nutritional index based on serum triglycerides (TGs), serum total cholesterol (TC), and body weight (BW), was recently reported to be a useful prognostic indicator in patients with coronary artery disease. Thus, this study aimed to investigate the relationship between TCBI and long-term mortality in acute decompensated heart failure (ADHF) patients. Patients with a diagnosis of ADHF who were consecutively admitted to the cardiac intensive care unit in our institution from 2007 to 2011 were targeted. TCBI was calculated using the formula TG (mg/dL) × TC (mg/dL) × BW (kg)/1000. Patients were divided into two groups according to the median TCBI value. An association between admission TCBI and mortality was assessed using univariable and multivariable Cox proportional hazard analyses. Overall, 417 eligible patients were enrolled, and 94 (22.5%) patients died during a median follow-up period of 2.2 years. The cumulative survival rate with respect to all-cause, cardiovascular, and cancer-related mortalities was worse in patients with low TCBI than in those with high TCBI. In the multivariable analysis, although TCBI was not associated with cardiovascular and cancer mortalities, the association between TCBI and reduced all-cause mortality (hazard ratio: 0.64, 95% confidence interval: 0.44–0.94, p = 0.024) was observed. We computed net reclassification improvement (NRI) when TCBI or Geriatric Nutritional Risk Index (GNRI) was added on established predictors such as hemoglobin, serum sodium level, and both. TCBI improved discrimination for all-cause mortality (NRI: 0.42, p < 0.001; when added on hemoglobin and serum sodium level). GNRI can improve discrimination for cancer mortality (NRI: 0.96, p = 0.002; when added on hemoglobin and serum sodium level). TCBI, a novel and simply calculated nutritional index, can be useful to stratify patients with ADHF who were at risk for worse long-term overall mortality.

Background: A poor nutritional status has been gathering intense clinical interest recently as it has been suggested to associate with adverse outcomes in patients in the intensive care unit (ICU). However, there is still no established nutritional index dominantly used in clinical practice. We have previously proposed a novel nutritional index, which can be calculated using serum levels of triglycerides, total cholesterol, and body weight (TCBI). In this study, to expand the application of TCBI for critical patients, we investigated the usefulness of TCBI to predict prognosis in hemodynamically unstable patients with percutaneously implantable mechanical circulatory support (MCS) devices in the ICU. Patients and Methods: This is a retrospective analysis of a multicenter registry consisting of three Juntendo University hospitals in Japan involving patients who received MCS devices, including intra-aortic balloon pumping (IABP) with or without veno-arterial extracorporeal membrane oxygenation (VA-ECMO), between 2012 and 2016 (n = 439). The median follow-up period was 298 days. Results: Spearman’s correlation coefficient between TCBI and the geriatric nutritional risk index (GNRI) was 0.44 (p < 0.0001), indicating a moderate positive correlation for these two variables. Unadjusted Kaplan–Meier analysis demonstrated reduced risks of all-cause and cardiovascular mortalities in patients with higher tertiles of TCBI. Furthermore, adjusted multivariate Cox proportional hazard analyses revealed that the highest tertile TCBI was an independent predictor for the reduced risk of all-cause mortality (hazard ratio (HR): 0.22, 95% confidence interval: 0.10–0.48, p < 0.0001) and cardiovascular mortality (0.20, 0.09–0.45, p < 0.0001). Conclusion: A novel and simple to calculate nutritional index, TCBI, can be applicable as a prognostic indicator in hemodynamically unstable patients requiring MCS devices.

Diabetes mellitus is considered an important risk factor for cardiovascular diseases. High hemoglobin A1c (HbA1c) levels, which indicate poor glycemic control, have been associated with occurrence of cardiovascular diseases. There are few parameters which can predict cardiovascular risk in patients with well-controlled diabetes. Low 1,5-anhydroglucitol (1,5-AG) levels are considered a clinical marker of postprandial hyperglycemia. We hypothesized that low 1,5-AG levels could predict long-term mortality in acute coronary syndrome (ACS) patients with relatively low HbA1c levels. The present study followed a retrospective observational study design. We enrolled 388 consecutive patients with ACS admitted to the cardiac intensive care unit at the Juntendo University Hospital from January 2011 to December 2013. Levels of 1,5-AG were measured immediately before emergency coronary angiography. Patients with early stent thrombosis, no significant coronary artery stenosis, malignancy, liver cirrhosis, a history of gastrectomy, current steroid treatment, moderately to severely reduced kidney function (estimated glomerular filtration rate < 45 ml/min/1.73 m2; chronic kidney disease stage 3B, 4, and 5), HbA1c levels ≥ 7.0%, and those who received sodium glucose co-transporter 2 inhibitor therapy were excluded. During the 46.9-month mean follow-up period, nine patients (4.5%) died of cardiovascular disease. The 1,5-AG level was significantly lower in the cardiac death group compared with that in the survivor group (12.3 ± 5.3 vs. 19.2 ± 7.7 µg/ml, p < 0.01). Kaplan–Meier survival analysis showed that low 1,5-AG levels were associated with cardiac mortality (p = 0.02). Multivariable Cox regression analysis showed that 1,5-AG levels were an independent predictor of cardiac mortality (hazard ratio 0.76; 95% confidence interval 0.41–0.98; p = 0.03). Low 1,5-AG levels, which indicate postprandial hyperglycemia, predict long-term cardiac mortality even in ACS patients with HbA1c levels < 7.0%.

Background: Delirium is a common occurrence in patients admitted to the intensive care unit and is related to mortality and morbidity. Malnutrition is a predisposing factor for the development of delirium. Nevertheless, whether the nutritional status on admission anticipates the development of delirium in patients with acute cardiovascular diseases remains unknown. Objective: This study aims to assess the correlation between the nutritional status on admission using the nutritional index and the development of delirium in the coronary intensive care unit. Design: We examined 653 consecutive patients (mean age: 70 ± 14 years) admitted to the coronary intensive care unit of Juntendo University Hospital between January 2015 and December 2016. We evaluated three nutritional indices frequently used to assess the nutritional status, i.e., Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT). We defined delirium as patients with a delirium score >4 using the Intensive Care Delirium Screening Checklist. Results: Delirium was present in 58 patients. All nutritional indices exhibited a tendency for malnutrition in the delirium group compared with the non-delirium group (GNRI, 86.5 ± 9.38 versus 91.6 ± 9.89; PNI, 36.4 ± 6.95 versus 41.6 ± 7.62; CONUT, 5.88 ± 3.00 versus 3.61 ± 2.56; for all, p < 0.001). Furthermore, the maximum delirium score increased progressively from the low- to the high-risk group, as evaluated by each nutritional index (GNRI, PNI, CONUT; for all, p < 0.001). A multivariate analysis revealed that the PNI and CONUT were independent risk factors for the occurrence of delirium. Conclusions: A marked correlation exists between the nutritional index on admission, especially PNI and CONUT, and the development of delirium in patients with acute cardiovascular diseases, suggesting that malnutrition assessment upon admission could help identify patients at high risk of developing delirium.