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Aim The role of serum type III procollagen peptide (P3P) level in the acute phase of acute heart failure (AHF) requires clarification. We hypothesized that serum P3P level is temporarily higher during the acute phase, reflecting liver dysfunction due to congestion. Methods and results A total of 800 AHF patients were screened, and data from 643 patients were analysed. Heart failure was diagnosed by the treating physician according to the European Society of Cardiology (ESC) guidelines, and included patients being treated with high-concentration oxygen inhalation (including mechanical support) for orthopnea, inotrope administration, or mechanical support for low blood pressure, and various types of diuretics for peripheral or pulmonary oedema. In all cases, diuretics or vasodilators were administered to treat AHF. The patients were divided into three groups according to their quartile (Q) serum P3P level: low-P3P (Q1, P3P ≤ 0.6 U/mL), mid-P3P (Q2/Q3, 0.6 < P3P <1.2 U/mL), and high-P3P (Q4, P3P ≥ 1.2 U/mL). The plasma volume status (PVS) was calculated using the following formula: ([actual PV ( ideal PV]/ideal PV) × 100 (%). The primary endpoint was 365 day mortality. A Kaplan–Meier curve analysis showed that prognoses, including all-cause mortality and heart failure events within 365 days, were significantly (P < 0.001) worse in the high-P3P group when compared with the mid-P3P and low-P3P groups. A multivariate logistic regression analysis showed that high PVS (Q4, odds ratio [OR]: 4.702, 95% CI: 2.012–20.989, P < 0.001), high fibrosis-4 index (Q4, OR: 2.627, 95% CI: 1.311–5.261, P = 0.006), and low estimated glomerular filtration rate per 10 mL/min/1.73 m2 decrease (OR: 1.996, 95% CI: 1.718–2.326, P < 0.001) were associated with high P3P values. The Kaplan–Meier curve analysis demonstrated a significantly lower survival rate, as well as a higher rate of heart failure events, in the high-P3P and high-PVS groups when compared with the other groups. A multivariate Cox regression model identified high P3P level and high PVS as an independent predictor of 365 day all-cause mortality (hazard ratio [HR]: 2.249; 95% CI: 1.081–3.356; P = 0.026) and heart failure events (HR: 1.586, 95% CI: 1.005–2.503, P = 0.048). Conclusion A high P3P level during the acute phase of AHF served as a comprehensive biomarker of liver dysfunction with volume overload (i.e. liver congestion) and renal dysfunction. A high P3P level at admission may be able to predict adverse outcomes in AHF patients. [ABSTRACT FROM AUTHOR]

Hyperuricemia is known to be associated with adverse outcomes in cardiovascular intensive care patients, but its mechanisms are unknown. A total of 569 emergency department patients were prospectively analyzed and assigned to intensive care (ICU group, n = 431) or other departments (n = 138). Uric acid (UA) levels were significantly higher in the intensive care patients (6.3 [5.1–7.6] mg/dl vs. 5.8 [4.6–6.8] mg/dL). The plasma xanthine oxidoreductase (XOR) activity in the ICU group (68.3 [21.2–359.5] pmol/h/mL) was also significantly higher than that in other departments (37.2 [15.1–93.6] pmol/h/mL). Intensive care patients were divided into three groups according to plasma XOR quartiles (Q1, low-XOR, Q2/Q3, normal-XOR, and Q4, high-XOR group). A multivariate logistic regression model showed that lactate (per 1.0 mmol/L increase, OR 1.326; 95%, CI 1.166–1.508, p < 0.001) and the Acute Physiology and Chronic Health Evaluation II score (per 1.0 point increase, OR 1.095, 95% CI 1.034–1.160, p = 0.002) were independently associated with the high-XOR group. In-hospital mortality was significantly higher in the high-XOR group (n = 28, 26.2%) than in the normal- (n = 11, 5.1%) and low- (n = 9, 8.3%) XOR groups. The high-XOR group (vs. normal-XOR group) was independently associated with the in-hospital mortality (OR 2.934; 95% CI 1.170–7.358; p = 0.022). Serum UA levels and plasma XOR activity were high in patients admitted to intensive care. The enhanced XOR activity may be one of the mechanisms under which hyperuricemia was associated with adverse outcomes in patients requiring cardiovascular intensive care. [ABSTRACT FROM AUTHOR]

Aims: The importance of true worsening renal failure (WRF), which is associated with a poor prognosis, had been suggested in patients with acute heart failure (AHF). The aim of the present study was to establish the biomarker strategy for the prediction of true WRF in AHF. Methods and results: Two hundred eighty‐one patients with AHF were analysed. Their biomarkers were measured within 30 min of admission. Patients were assigned to the non‐WRF (n = 168), pseudo‐WRF (n = 56), or true‐WRF (n = 57) groups using the criteria of both acute kidney injury on admission and increasing serum creatinine value during the first 7 days. A Kaplan–Meier curve showed that the survival and heart failure event rate of the true‐WRF group within 1000 days was significantly lower than that of the non‐WRF and pseudo‐WRF groups (P ≤ 0.001). The multivariate Cox regression model also indicated that true WRF was an independent predictor of 1000 day mortality and heart failure events [hazard ratio: 4.315, 95% confidence interval (CI): 2.466–7.550, P ≤ 0.001, and hazard ratio: 2.834, 95% CI: 1.893–4.243, P ≤ 0.001, respectively]. The serum heart‐type fatty acid‐binding protein (s‐HFABP) levels were significantly higher in the true‐WRF group than in the non‐WRF and pseudo‐WRF groups (P ≤ 0.001). The multivariate logistic regression model indicated that the predictive biomarker for the true‐WRF group was the s‐HFABP level (odds ratio: 5.472, 95% CI: 2.729–10.972, P ≤ 0.001). The sensitivity and specificity for indicating the presence of true WRF were 73.7% and 76.8% (area under the curve = 0.831) for s‐HFABP in whole patients, respectively, and 94.7% and 72.7% (area under the curve = 0.904) in non‐chronic kidney disease (CKD) patients, respectively. Conclusions: Cardiac biomarkers, especially the s‐HFABP, might predict the development of true WRF in AHF patients. Furthermore, the predictive value was higher in AHF patients without CKD than in those with CKD. [ABSTRACT FROM AUTHOR]

Patients with heart failure (HF) are sometimes classified as malnourished, but the prognostic value of nutritional status in acute HF (AHF) remains largely unstudied. 1214 patients who were admitted to the intensive care unit between January 2000 and June 2016 were screened based on their serum albumin, lymphocyte count, and total cholesterol measures. A total of 458 HF patients were enrolled in this study. The Prognostic Nutritional Index (PNI) is calculated as 10 × serum albumin (g/dL) + 0.005 × lymphocyte count (per mm) (lower = worse). The Controlling Nutritional Status (CONUT) score is points based, and is calculated using serum albumin, total cholesterol, and lymphocyte count (range 0-12, higher = worse). Patients were divided into three groups according to PNI: high-PNI (PNI < 35, n = 331), middle-PNI (35 ≤ PNI < 38, n = 50), and low-PNI (PNI ≥ 38, n = 77). They were also divided into four groups according to CONUT score: normal-CONUT (0-1, n = 128), mild-CONUT (2-4, n = 179), moderate-CONUT (5-8, n = 127), and severe-CONUT (≥9, n = 24). The PNI, which exhibited a good balance between sensitivity and specificity for predicting in-hospital mortality [66.1 and 68.4%, respectively; area under the curve (AUC) 0.716; 95% confidence interval (CI) 0.638-0.793), was 39.7 overall, while the CONUT score was 5 overall (61.4 and 68.4%, respectively; AUC 0.697; 95% CI 0.618-0.775). A Kaplan-Meier curve indicated that the prognosis, including all-cause death, was significantly ( p < 0.001) poorer in low-PNI patients than in high-PNI groups and was also significantly poorer in severe-CONUT patients than in normal-CONUT and mild-CONUT groups. A multivariate Cox regression model showed that the low-PNI and severe-CONUT categories were independent predictors of 365-day mortality [hazard ratio (HR) 2.060, 95% CI 1.302-3.259 and HR 2.238, 95% CI 1.050-4.772, respectively). Malnutrition, as assessed using both the PNI and the CONUT score, has a prognostic impact in patients with severely decompensated AHF. [ABSTRACT FROM AUTHOR]

Background: No cardiac biomarkers for detecting acute kidney injury (AKI) on admission in non-surgical intensive care patients have been reported. The aim of the present study is to elucidate the role of cardiac biomarkers for quickly identifying the presence of AKI on admission.Methods: Data for 1183 patients who underwent the measurement of cardiac biomarkers, including the serum heart-type fatty acid-binding protein (s-HFABP) level, in the emergency department were screened, and 494 non-surgical intensive care patients were enrolled in this study. Based on the RIFLE classification, which was the ratio of the serum creatinine value recorded on admission to the baseline creatinine value, the patients were assigned to a no-AKI (n = 349) or AKI (Class R [n = 83], Class I [n = 36] and Class F [n = 26]) group on admission. We evaluated the diagnostic value of the s-H-FABP level for detecting AKI and Class I/F. The mid-term prognosis, as all-cause death within 180 days, was also evaluated.Results: The s-H-FABP levels were significantly higher in the Class F (79.2 [29.9 to 200.3] ng/mL) than in the Class I (41.5 [16.7 to 71.6] ng/mL), the Class R (21.1 [10.2 to 47.9] ng/mL), and no-AKI patients (8.8 [5.4 to 17.7] ng/mL). The most predictive values for detecting AKI were Q2 (odds ratio [OR]: 3.743; 95 % confidence interval [CI]: 1.693-8.274), Q3 (OR: 9.427; 95 % CI: 4.124-21.548), and Q4 (OR: 28.000; 95 % CI: 11.245-69.720), while those for Class I/F were Q3 (OR: 5.155; 95 % CI: 1.030-25.790) and Q4 (OR: 22.978; 95 % CI: 4.814-109.668). The s-HFABP level demonstrating an optimal balance between sensitivity and specificity (70.3 and 72.8 %, respectively; area under the curve: 0.774; 95 % CI: 0.728-0.819) was 15.7 ng/mL for AKI and 20.7 ng/mL for Class I/F (71.0 and 83.1 %, respectively; area under the curve: 0.818; 95 % CI: 0.763-0.873). The prognosis was significantly poorer in the high serum HFABP with AKI group than in the other groups.Conclusions: The s-H-FABP level is an effective biomarker for detecting AKI in non-surgical intensive care patients. [ABSTRACT FROM AUTHOR]

Background and purpose: The role of an arterial blood gas analysis in acute heart failure (AHF) remains unclear. The acid-base balance could help to treat AHF, and it might help to distinguish different types of AHF, while it might be associated with the AHF prognosis. The present study was conducted to determine the relationship between the arterial blood gas sample at the time of hospital admission and clinical findings on admission, outcomes. Methods and results: Six hundred twenty-one patients with AHF admitted to the intensive care unit were analyzed. Patients were assigned to an alkalosis group (n = 99, pH>7.45), normal group (n = 178, 7.35 < pH >; 7.45), and acidosis group (n = 344, pH < 7.35). The clinical findings on admission and outcomes (in-hospital mortality and any-cause death within 2 years) were compared between the three groups. The white blood cell counts (WBC), serum levels of total protein, albumin, and glucose were significantly lower, and the serum levels of C-reactive protein (CRP) and total bilirubin were significantly higher in the alkalosis group. Patients with orthopnea were significantly fewer, and the systolic blood pressure (SBP) and heart rate (HR) were significantly lower in the alkalosis group. The results of a multivariate logistic regression model for in-hospital mortality found that alkalosis was an independent risk factor (p = 0.017, odds ratio: 2.589; 95% confidence interval: 1.186-5.648). The Kaplan-Meier curves showed the prognosis for any-cause death to be significantly poorer in the alkalosis group than in the normal group (p = 0.026). Conclusions: The factors associated with alkalosis AHF were high CRP, bilirubin, and low WBC, glucose, total protein, and albumin. The patients with alkalosis AHF were less likely to have orthopnea with low SBP and HR. They suggested that the patients with alkalosis AHF might have experienced AHF for a few days and were associated with high mortality. [ABSTRACT FROM AUTHOR]

The prevalence of atrial fibrillation (AF) has been increasing in aging societies. The prognostic impact of AF associated with worsening heart failure (HF) remains obscure. We analyzed 1170 acute heart failure (AHF) patients who required intensive care. Patients were assigned to two groups according to the prevalence of AF: no episode of AF (n = 940) and pre-existing AF (Group-1, n = 230). Patients with no episode of AF (n = 940) were further divided into two groups according to presence of new-onset of AF after admission (Group-2a, n = 258) or not (Group-2b, n = 682). Kaplan-Meier curve analysis showed that prognosis, including all-cause mortality and HF-events within 1000 days, was significantly poorer in the Group-1 compared to the Group-2b. However, a multivariate Cox regression model showed that the Group-1 was not an independent predictor of 1000-day mortality and HF-events. Furthermore, Kaplan-Meier curve analysis showed that prognosis, including all-cause mortality and HF-events within 1000 days, was significantly poorer in the Group-2a than in the Group-2b. A multivariate Cox regression model revealed that the Group-2a was an independent predictor of 1000-day mortality (HR: 1.403, 95% CI: 1.018–1.934) and HF-events (HR: 1.352, 95% CI: 1.071–1.708). A multivariate logistic regression model showed that only age (≥75 years old) was independently associated with new-onset of AF after admission (odds ratio: 1.556, 95% CI: 1.130–2.143). New-onset AF associated with worsening HF increases with age and is independently-associated with adverse outcome in patients with AHF. • The prognostic impact of AF associated with worsening heart failure (HF) is not obscured. • A multivariate Cox regression model showed that the pre-AF was not an independent predictor of 1000-day mortality and HF event. • A multivariate Cox regression model revealed that the new-onset AF group was an independent predictor of 1000-day mortality. • A multivariate logistic regression model showed that only age was independently associated with new onset of AF after admission. [ABSTRACT FROM AUTHOR]