Predictor Of All-cause Mortality Research Articles

Controlling nutritional status score in the prediction of cardiovascular disease prevalence, all-cause and cardiovascular mortality in chronic obstructive pulmonary disease population: NHANES 1999–2018

BackgroundMalnutrition is prevalent in chronic obstructive pulmonary disease (COPD) and associated with adverse outcomes, while COPD is intricately linked to cardiovascular disease (CVD), sharing common risk factors. The controlling nutritional status (CONUT) score, a promising tool for assessing malnutrition, warrants investigation into its predictive ability for cardiovascular disease prevalence and mortality in COPD patients.MethodsBased on the National Health and Nutrition Examination Survey (NHANES), this study analyzed 1501 adult COPD patients from 1999 to 2018. The endpoints were CVD prevalence, mortality related to CVD, and overall mortality. We evaluated the correlation of the CONUT score with each outcome using logistic regression and Cox regression models. The prognostic evaluation of patients was conducted using Kaplan-Meier curves in accordance with the CONUT score. We formed the receiver operating characteristic (ROC) curves for evaluating the CONUT score's discriminative capability.ResultsThe prevalence of malnutrition was 21.31% in COPD populations. Logistic analyses suggested a distinct connection between the CONUT score and CVD prevalence (OR:1.86, 95%CI:1.28-2.70) in individuals with COPD. The CONUT score demonstrated a significant correlation with a heightened risk of CVD mortality (HR: 1.86, 95%CI: 1.27-2.74) and overall mortality (HR: 1.50, 95%CI: 1.18-1.91). The prognostic outcomes might be effectively discriminated by the CONUT score, as seen by the Kaplan-Meier curves.ConclusionsIn summary, the CONUT score provides an uncomplicated and readily attainable marker for forecasting CVD prevalence, total mortality, and mortality from CVD among COPD patients.

Long-term follow-up in outpatients with mildly elevated pulmonary artery systolic pressure on echocardiography: a single-centre retrospective cohort study in Shanghai, China

ObjectiveTo investigate the correlation between mildly elevated pulmonary artery systolic pressure (PASP) on echocardiography and mortality, as well as long-term changes in PASP.DesignRetrospective cohort study.SettingShanghai, China, a single centre.ParticipantsA total...

The U-shape relationship between insulin resistance-related indexes and chronic kidney disease: a retrospective cohort study from National Health and Nutrition Examination Survey 2007–2016

BackgroundThere is ongoing debate on the correlation between chronic kidney disease (CKD) and insulin resistance (IR)-related indices. Our objective was to explore the prognostic ability of IR-related indexes for the prevalence of CKD, as well as the mortality from all causes and cardiovascular disease (CVD) in CKD patients.MethodsThe data used in this study came from the National Health and Nutrition Examination Survey (NHANES). Binary logistic regression analysis, Cox proportional hazards model, and restricted cubic spline (RCS) were used to analyze the relationship between IR-related indexes, including metabolic score of IR (METS-IR), homeostatic model assessment for IR (HOMA-IR), triglyceride glucose index (TyG), triglyceride glucose-waist-to-height ratio (TyG-WHtR), triglyceride glucose-body mass index (TyG-BMI), with CKD and its all-cause mortality and CVD mortality. Subgroup analysis was performed to test the stability of the results. Finally, the predictive power of IR-related indexes for CKD was tested by the receiver operating characteristic (ROC) curve.ResultsAmong the recruited 10,660 participants, 15.42% were CKD patients. All IR-related indexes were found to be nonlinearly correlated to the prevalence of CKD in the study. When the TyG index was higher than 9.05, it was positively associated with CKD (OR: 1.77, 95% CI 1.44–2.18). Moreover, increased TyG-WHtR level was correlated with a greater prevalence of CKD when it was higher than 4.3 (OR: 1.31, 95% CI 1.19–1.45). Other IR-related indexes (METS-IR, HOMA-IR, and TyG-BMI) showed fewer notable correlations with CKD. The association of IR-related indexes and the prevalence of CKD remained consistent in most subgroups (P for interactions > 0.05). TyG-WHtR was also the predictor of all-cause mortality in CKD patients (HR: 1.34, 95% CI 1.14–1.58), while other IR-related indexes were not correlated with the all-cause mortality or CVD mortality in CKD patients (P > 0.05). Otherwise, ROC curves showed that TyG-WHtR had more robust diagnostic efficacy than other IR-related indexes (METS-IR, HOMA-IR, TyG, and TyG-BMI) in predicting CKD (area under the curve: 0.630, 95% CI 0.615–0.644).ConclusionsIR-related biomarkers (METS-IR, HOMA-IR, TyG, and TyG-BMI) were positively correlated with the prevalence of CKD. Moreover, TyG-WHtR enhanced CKD and its all-cause mortality prediction. In patients with elevated levels of IR-related indexes, the early detection and intervention of IR may reduce the occurrence of CKD and the prognosis of CKD patients.

Prognostic impact of beta-blocker use by N-terminal pro-brain natriuretic peptide level in acute heart failure patients.

Both patients with heart failure (HF) with reduced ejection fraction (HFrEF) and those with HF with preserved ejection fraction (HFpEF) present with elevated N-terminal pro-brain natriuretic peptide (NT-proBNP) and have multiple comorbidities; consequently, the prognostic effect of NT-proBNP according to beta-blocker (BB) use is unknown. This retrospective study evaluated patients admitted for acute HF between January 2012 and December 2017 at Ulsan University Hospital. Clinical, echocardiographic, laboratory and drug prescription data, including BB data, were collected from the hospital database. Information on mortality was collected by reviewing medical records or using national death data. Of the 472 patients evaluated, 216 (45.8%) and 256 (54.2%) patients were and were not prescribed BB at discharge, respectively. A total of 224 (47.5%) patients died within a median follow-up duration of 44months. The Kaplan-Meier analysis showed reduced all-cause mortality with BB in HFrEF (ejection fraction≤40%) but not in HFpEF (ejection fraction>40%). In the multivariate Cox regression analysis, transmitral to tissue Doppler imaging, early diastolic velocity ratio (E/E'), NT-proBNP and BB use were independent predictors of all-cause mortality in HFrEF. Meanwhile, haemoglobin and NT-proBNP levels were independent predictors of HFpEF. The NT-proBNP cut-off value for determining all-cause mortality was set to 4800pg/mL. Among HFrEF patients with NT-proBNP<4800pg/mL, the survival rate was higher for patients with BB use than those with no BB use (log-rank P<0.001). However, in the HFpEF group, the survival rate associated with BB use did not differ according to the NT-proBNP levels. Both HFrEF and HFpEF patients with NT-proBNP levels of ≥4800pg/mL presented with multiple comorbidities, including lower body mass index and haemoglobin levels and higher creatinine levels, NT-proBNP levels and E/E'. In patients with acute HF, BB use is associated with reduced all-cause mortality in those with HFrEF but not in those with HFpEF. HFrEF patients with NT-proBNP levels of <4800pg/mL treated with BB have a higher survival rate than those not treated with BB. However, this benefit is not seen in HFrEF patients with NT-proBNP levels of ≥4800pg/mL or in all HFpEF patients, regardless of the NT-proBNP level. NT-proBNP levels are elevated in multiple comorbid conditions, and these comorbidities may contribute to the attenuated effects of BB on all-cause mortality.

Brain natriuretic peptide is a long-term cardiovascular predictor in carotid endarterectomy

Background In noncardiac surgery, several biomarkers are known to play a role in predicting long-term complications, such as major adverse cardiovascular events (MACE), myocardial infarction, or death. Carotid endarterectomy (CEA) is considered a low to medium-risk surgery for carotid stenosis aimed at preventing stroke events. Brain natriuretic peptide (BNP) is a biomarker with potential prognostic value regarding MACE. Since its role in patients undergoing CEA is unknown, this study aims to assess the potential role of BNP as a short and long-term predictor of all-cause mortality and MACE in patients undergoing CEA. Methods From a prospective database, patients who underwent CEA under regional anesthesia (RA) at a tertiary hospital center were enrolled, and a post hoc analysis was conducted. Patients on which BNP levels were measured up to fifteen days before surgery, and two groups based on the BNP threshold (200 pg/mL) were defined and compared. Kaplan Meier survival curves and adjusted hazard ratios (aHR) were assessed by multivariable Cox regression. The primary outcome was the incidence of long-term MACE and all-cause mortality. Secondary outcomes included the incidence of AMI and AHF. Results A total of 89 patients were evaluated. The mean age of the cohort was 71.2 ± 8.7 years, with 71 (79.8%) males, and presented a median follow-up of 30 [13.5–46.4] months. BNP > 200 pg/mL has demonstrated positive predictive value for MACE (aHR: 5.569, confidence interval (CI): 2.441–12.7, p < 0.001) and all-cause mortality (aHR: 3.469, CI: 1.315–9.150, p = 0.018). Conclusion BNP has been demonstrated to independently predict long-term all-cause mortality, MACE and AMI following CEA. It serves as a low-cost, ready-to-use biomarker, although further studies are necessary.

Characterization and Mortality Risk of Impaired Left Ventricular Filling in COPD.

In COPD, impaired left ventricular (LV) filling might be associated with coexisting HFpEF or due to reduced pulmonary venous return indicated by small LV size. We investigate the all-cause mortality associated with small LV or HFpEF and clinical features discriminating between both patterns of impaired LV filling. We performed transthoracic echocardiography (TTE) in patients with stable COPD from the COSYCONET cohort to define small LV as LVEDD below the normal range and HFpEF features according to recommendations of the European Society of Cardiology. We assessed the E/A and E/e' ratios, NT-pro-BNP, hs-Troponin I, FEV1, RV, DLCo, and discriminated patients with small LV from those with HFpEF features or no relevant cardiac dysfunction as per TTE (normalTTE). The primary outcome was all-cause mortality after four and a half year. In 1752 patients with COPD, the frequency of small LV, HFpEF-features, and normalTTE was 8%, 16%, and 45%, respectively. Patients with small LV or HFpEF features had higher all-cause mortality rates than patients with normalTTE, HR: 2.75 (95% CI: [1.54 - 4.89]) and 2.16 (95% CI: [1.30 - 3.61]), respectively. Small LV remained an independent predictor of all-cause mortality after adjusting for confounders including exacerbation frequency and measures of RV, DLCo, or FEV1. Compared to normalTTE, patients with small LV had reduced LV filling, as indicated by lowered E/A. Yet in contrast to patients with HFpEF-features, patients with small LV had normal LV filling pressure (E/e') and lower levels of NT-pro-BNP and hs-Troponin I. In COPD, both small LV and HFpEF-features are associated with increased all-cause mortality and represent two distinct patterns of impaired LV filling.

Characterization and Mortality Risk of Impaired Left Ventricular Filling in COPD.

In COPD, impaired left ventricular (LV) filling might be associated with coexisting HFpEF or due to reduced pulmonary venous return indicated by small LV size. We investigate the all-cause mortality associated with small LV or HFpEF and clinical features discriminating between both patterns of impaired LV filling. We performed transthoracic echocardiography (TTE) in patients with stable COPD from the COSYCONET cohort to define small LV as LVEDD below the normal range and HFpEF features according to recommendations of the European Society of Cardiology. We assessed the E/A and E/e' ratios, NT-pro-BNP, hs-Troponin I, FEV1, RV, DLCo, and discriminated patients with small LV from those with HFpEF features or no relevant cardiac dysfunction as per TTE (normalTTE). The primary outcome was all-cause mortality after four and a half year. In 1752 patients with COPD, the frequency of small LV, HFpEF-features, and normalTTE was 8%, 16%, and 45%, respectively. Patients with small LV or HFpEF features had higher all-cause mortality rates than patients with normalTTE, HR: 2.75 (95% CI: [1.54 - 4.89]) and 2.16 (95% CI: [1.30 - 3.61]), respectively. Small LV remained an independent predictor of all-cause mortality after adjusting for confounders including exacerbation frequency and measures of RV, DLCo, or FEV1. Compared to normalTTE, patients with small LV had reduced LV filling, as indicated by lowered E/A. Yet in contrast to patients with HFpEF-features, patients with small LV had normal LV filling pressure (E/e') and lower levels of NT-pro-BNP and hs-Troponin I. In COPD, both small LV and HFpEF-features are associated with increased all-cause mortality and represent two distinct patterns of impaired LV filling.

Multinational evaluation of anthropometric age (AnthropoAge) as a measure of biological age in the USA, England, Mexico, Costa Rica, and China: a population-based longitudinal study.

To validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts. We analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE). Using data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ∼39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke. AnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America.

Nocturnal Hypoxemic Burden in Patients with Heart Failure: Emerging Prognostic Role of Its Non-Specific Component

BackgroundNocturnal hypoxemic burden has been shown to be a robust, independent predictor of all-cause mortality in patients with heart failure and reduced ejection fraction (HFrEF) and to occur in a severe form even in patients with low or negligible frequency of respiratory events (apneas/hypopneas). This suggests the existence of two components of hypoxemic burden: one unrelated to respiratory events and the other related. The aim of this study was to characterize these two components and to evaluate their prognostic value. MethodsNocturnal hypoxemic burden was assessed in a cohort of 280 patients with HFrEF by measuring the percentage of sleep with an oxygen saturation (SpO2) <90% (T90), and the area of the SpO2 curve below 90% (Area90). Both indices were also recalculated within the sleep segments associated with respiratory events (event-related component: T90Eve, Area90Eve) and outside these segments (non-specific component: T90Nspec, Area90Nspec). The outcome of the survival analysis (Cox regression) was all-cause mortality. ResultsDuring a median follow-up of 60 months, 87 patients died. T90, Area90, and their components were significant in univariate analysis (p<0.05 all). However, when these indices were adjusted for known risk factors, T90, T90Nspec, Area90, and Area90Nspec remained statistically significant (p=0.018, hazard ratio (HR)=1.12, 95%CI=(1.02, 1.23); p=0.007, HR=1.20, 95%CI=(1.05, 1.37); p=0.020, HR=1.05, 95%CI=(1.01, 1.10); p=0.0006, HR=1.15, 95%CI=(1.06, 1.25)), whereas T90Eve and Area90Eve did not (p=0.27, p=0.28). These results were internally validated using bootstrap resampling. ConclusionsBy demonstrating a significant independent association of non-specific hypoxemic burden with all-cause mortality, this study suggests that this component of total nocturnal hypoxemic burden may play an important prognostic role in patients with HFrEF.

Accurate prediction of all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease using electronic health records

Introduction and ObjectivesDespite the huge clinical burden of MASLD, validated tools for early risk stratification are lacking, and heterogeneous disease expression and a highly variable rate of progression to clinical outcomes result in prognostic uncertainty. We aimed to investigate longitudinal electronic health record-based outcome prediction in MASLD using a state-of-the-art machine learning model. Patients and Methodsn = 940 patients with histologically-defined MASLD were used to develop a deep-learning model for all-cause mortality prediction. Patient timelines, spanning 12 years, were fully-annotated with demographic/clinical characteristics, ICD-9 and -10 codes, blood test results, prescribing data, and secondary care activity. A Transformer neural network (TNN) was trained to output concomitant probabilities of 12-, 24-, and 36-month all-cause mortality. In-sample performance was assessed using 5-fold cross-validation. Out-of-sample performance was assessed in an independent set of n = 528 MASLD patients. ResultsIn-sample model performance achieved AUROC curve 0.74–0.90 (95 % CI: 0.72–0.94), sensitivity 64 %-82 %, specificity 75 %–92 % and Positive Predictive Value (PPV) 94 %-98 %. Out-of-sample model validation had AUROC 0.70–0.86 (95 % CI: 0.67–0.90), sensitivity 69 %–70 %, specificity 96 %–97 % and PPV 75 %–77 %. Key predictive factors, identified using coefficients of determination, were age, presence of type 2 diabetes, and history of hospital admissions with length of stay >14 days. ConclusionsA TNN, applied to routinely-collected longitudinal electronic health records, achieved good performance in prediction of 12-, 24-, and 36-month all-cause mortality in patients with MASLD. Extrapolation of our technique to population-level data will enable scalable and accurate risk stratification to identify people most likely to benefit from anticipatory health care and personalized interventions.

External validation of a 2-year all-cause mortality prediction tool developed using machine learning in patients with stage 4-5 chronic kidney disease.

Chronic kidney disease (CKD) is associated with increased mortality. Individual mortality prediction could be of interest to improve individual clinical outcomes. Using an independent regional dataset, the aim of the present study was to externally validate the recently published 2-year all-cause mortality prediction tool developed using machine learning. A validation dataset of stage 4 or 5 CKD outpatients was used. External validation performance of the prediction tool at the optimal cutoff-point was assessed by the area under the receiver operating characteristic curve (AUC-ROC), accuracy, sensitivity, and specificity. A survival analysis was then performed using the Kaplan-Meier method. Data of 527 outpatients with stage 4 or 5 CKD were analyzed. During the 2years of follow-up, 91 patients died and 436 survived. Compared to the learning dataset, patients in the validation dataset were significantly younger, and the ratio of deceased patients in the validation dataset was significantly lower. The performance of the prediction tool at the optimal cutoff-point was: AUC-ROC = 0.72, accuracy = 63.6%, sensitivity = 72.5%, and specificity = 61.7%. The survival curves of the predicted survived and the predicted deceased groups were significantly different (p < 0.001). The 2-year all-cause mortality prediction tool for patients with stage 4 or 5 CKD showed satisfactory discriminatory capacity with emphasis on sensitivity. The proposed prediction tool appears to be of clinical interest for further development.

Coronary Artery Disease Is A Stronger Predictor of All-Cause Mortality Than Left Ventricular Ejection Fraction Among Patients With Newly Diagnosed Heart Failure: Insights From the WDHR.

In patients with newly diagnosed heart failure (HF) and left ventricular ejection fraction (LVEF) <50%, little is known whether LVEF per se or presence of coronary artery disease (CAD) provides independent prognostic information on all-cause mortality. Using the WDHR (Western Denmark Heart Registry), we identified 3620 patients with newly diagnosed HF and LVEF 10% to 49% referred for first-time coronary angiography as part of general workup of HF. Patients were stratified by LVEF (10%-35% versus 36%-49%) and presence of CAD. We estimated 10-year all-cause mortality risk and calculated hazard ratios adjusted for relevant comorbidities and risk factors (aHRs). CAD was present in 1592 (44%) patients. Lower LVEF was associated with a relative 15% increased 10-year mortality: 37% for LVEF 36% to 49% versus 42% for LVEF 10% to 35% (aHR, 1.15 [95% CI, 0.99-1.34]). This result did not change when stratified into those with CAD (52% versus 56%; aHR, 1.11 [95% CI, 0.91-1.35]) and those without CAD (27% versus 33%; aHR, 1.24 [95% CI, 0.97-1.57]). In comparison, presence and extent of CAD were associated with a relative 43% increased 10-year mortality (CAD versus no CAD, 55.0% versus 31.5%; aHR, 1.43 [95% CI, 1.25-1.64]). Compared with a matched general population, excess mortality risk was higher for patients with HF and CAD (54.7% versus 26.3%; aHR, 2.10 [95% CI, 1.85-2.39]) versus those with HF and no CAD (31.4% versus 17.2%; aHR, 1.76 [95% CI, 1.52-2.02]). Among newly diagnosed patients with HF and LVEF <50%, presence and extent of CAD are associated with substantial higher all-cause mortality risk than lower LVEF.

Effect of low-dose terazosin on arterial stiffness improvement: A pilot study.

Arterial stiffness, a prominent hallmark of ageing arteries, is a predictor of all-cause mortality. Strategies for promoting healthy vascular ageing are encouraged. Here we conducted a pilot study to evaluate the potential effects of low-dose Terazosin on arterial stiffness. We enrolled patients aged over 40 with elevated arterial stiffness, defined as a brachial-ankle pulse wave velocity (baPWV) ≥1400 cm/s, who were administered Terazosin (0.5 and 1.0 mg/day) from December 2020 to June 2023. Treatment responses were assessed every 3 months. Linear regression analysis was used to characterise the improvement. We matched cases who took Terazosin for 1 year with Terazosin-free controls using propensity score matching (PSM). Our findings demonstrate that Terazosin administration significantly affected arterial stiffness. (1) Arterial stiffness significantly improved (at least a 5% reduction in baPWV) in 50.0% of patients at 3 months, 48.6% at 6 months, 59.3% at 9 months, and 54.4% at 12 months, respectively. (2) Those with higher baseline baPWV and hypertension exhibited a significantly reduced risk of non-response. (3) Terazosin was associated with a reduction of baPWV at 1-year follow-up (linear regression: β = -165.16, p < 0.001). This pilot study offers valuable insights into the potential significance of Terazosin in improving arterial stiffness and paves the way for future randomised clinical trials in combating vascular ageing.

NHANES 2011-2014: Objective Physical Activity is the Strongest Predictor of All-Cause Mortality.

Objectively measured physical activity (PA) is a modifiable risk factor for mortality. Understanding the predictive performance of PA is essential to establish potential targets for early intervention to reduce mortality among older adults. The study used a subset of the National Health and Nutrition Examination Survey (NHANES) 2011-2014 data consisting of participants aged 50 to 80 years old (n = 3653, 24297.5 person-years of follow-up, 416 deaths). Eight accelerometry derived features and 14 traditional predictors of all-cause mortality were compared and ranked in terms of their individual and combined predictive performance using the 10-fold cross-validated Concordance (C) from Cox regression. The top three predictors of mortality in univariate analysis were PA related: average MIMS in the 10 most active hours (C = 0.697), total MIMS per day (C = 0.686), and average log transformed MIMS in the most 10 active hours of the day (C = 0.684), outperforming age (C = 0.676) and other traditional predictors of mortality. In multivariate regression, adding objectively measured PA to the top performing model without PA variables increased concordance from C = 0.776 to C = 0.790 (p < 0.001). These findings highlight the importance of PA as a risk marker of mortality and are consistent with prior studies, confirming the importance of accelerometer-derived activity measures beyond total volume.

Prognostic Impact of High-Molecular-Weight von Willebrand Factor Multimer Ratio in Classical Low-Flow Low-Gradient Aortic Stenosis.

High-molecular-weight (HMW) von Willebrand factor (VWF) multimer deficiency occurs in classical low-flow, low-gradient (LF/LG) aortic stenosis (AS) due to shear force-induced proteolysis. The prognostic value of HMW VWF multimer deficiency is unknown. Therefore, we sought to evaluate the impact of HMW VWF multimer deficiency on clinical outcome. In this prospective research study, a total of 83 patients with classical LF/LG AS were included. All patients underwent dobutamine stress echocardiography to distinguish true-severe (TS) from pseudo-severe (PS) classical LF/LG AS. HMW VWF multimer ratio was calculated using densitometric Western blot band quantification. The primary endpoint was all-cause mortality. Mean age was 79 ± 9 years, and TS classical LF/LG AS was diagnosed in 73% (n = 61) and PS classical LF/LG AS in 27% (n = 22) of all patients. Forty-six patients underwent aortic valve replacement (AVR) and 37 were treated conservatively. During a mean follow-up of 27 ± 17 months, 47 deaths occurred. Major bleeding complications after AVR (10/46; 22%) were more common in patients with HMW VWF multimer ratio &lt;1 (8/17; 47%) in comparison to patients with a normal multimer pattern (2/29; 7%) at baseline (p = 0.003). In a multivariable Cox regression analysis, HMW VWF multimer deficiency was a predictor of all-cause mortality (HR: 3.02 [95% CI: 1.31-6.96], p = 0.009) in the entire cohort. This association was driven by higher mortality rates in the AVR group (multivariable-adjusted HR: 9.4; 95% CI 2.0-43.4, p = 0.004). This is the first study to demonstrate the predictive value of HMW VWF multimer ratio for risk stratification in patients with classical LF/LG AS. HMW VWF multimer deficiency was associated with an increased risk of all-cause mortality and major bleeding complications after AVR.

Predictors of overall mortality after endovascular abdominal aortic repair - A single centre study.

A current and ongoing challenge is to reduce patient mortality after endovascular abdominal aortic repair (EVAR). This study aimed to assess the predictors of all-cause mortality after EVAR. Data regarding the demographic characteristics, comorbidities, laboratory values, selected anatomical factors, post-EVAR treatment, surveillance and complications of patients who underwent elective EVAR for non-ruptured abdominal aortic aneurysm (AAA) between January 2010 and January 2021 were evaluated. Mortality was assessed until 10 October 2023. Multivariate analyses were performed after adjusting for age, hypertension, diabetes mellitus, dyslipidaemia, sex, smoking, number of lumbar arteries, patency of inferior mesenteric artery (IMA), IMA diameter and reinterventions. This study included 196 patients (183 men and 13 women) with a mean age of 72.4 ± 7.67 years. The overall mortality rate during a mean follow-up period of 5.75 ± 3.1 years was 50.0% (N = 98). The 2-, 5- and 10-year mortality rates were 9.7%, 32.0% and 66.6%, respectively. The mortality rates decreased by 59% in patients with reinterventions (hazard ratio [HR]: 0.41; 95% confidence interval [CI]: 0.23-0.73; p = .002) and by 59% in patients treated with angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs) (HR: 0.41; 95% CI: 0.26-0.66; p < .001). Chronic anticoagulation was associated with 2.09-fold higher mortality (HR: 2.09; 95% CI: 1.19-3.67; p = .010), and coronary artery disease (CAD) was associated with 1.74-fold higher mortality (HR: 1.74; 95% CI: 1.09-2.78; p = .021). Pre-EVAR AAA diameter and 1-year post-EVAR sac diameter were positively associated with mortality (HR: 1.05; 95% CI: 1.03-1.08; p < .001, and HR: 1.05; 95% CI: 1.03-1.07; p < .001, respectively), that is, an increase of pre-EVAR and/or 1-year post-EVAR AAA diameter by 1mm was associated with a 5% higher risk of all-cause mortality. Reinterventions and treatment with ACE inhibitors or ARBs may be associated with decreased post-EVAR mortality. A greater pre-EVAR, a post-EVAR AAA diameter, CAD and chronic anticoagulation were associated with higher all-cause mortality post-EVAR.

Right Ventriculoarterial Coupling Surrogates and Long-Term Survival in LVAD Recipients: Results of the ASSIST-ICD Multicentric Registry

Prediction of outcomes remains an unmet need in candidates for LVADs. The development of right-heart failure portends an excess in mortality rates, but imaging parameters of right ventricular systolic function have failed to demonstrate a prognostic role. By integrating pulmonary pressure, right ventriculoarterial coupling could fill this gap. The ASSIST-ICD registry was used to test right ventriculoarterial coupling as a surrogate parameter at implantation for the prediction of all-cause mortality. The ratio of the tricuspid annular-plane systolic excursion over the estimated systolic pulmonary pressure (TAPSE/sPAP) was not associated with long-term survival in univariate analysis (P = 0.89), nor was the pulmonary artery pulsatility index (PAPi) (P = 0.13). Conversely, the ratio of the right atrial pressure over the pulmonary capillary wedge pressure (RAP/PCWP) was associated with all-cause mortality (P < 0.01). After taking tricuspid regurgitation severity, LVAD indication, LVAD model, age, blood urea nitrogen levels, and pulmonary vascular resistance into account, RAP/PCWP remained associated with survival (HR 1.35 [1.10 - 1.65]; P < 0.01). Among pre-implant RVAC surrogates, only RAP/PCWP was associated with long-term all-cause mortality in LVAD recipients. This association was independent of established risk factors.

Modified NUTRIC Score as a Predictor of All-cause Mortality in Critically Ill Patients: A Systematic Review and Meta-analysis.

The purpose of our meta-analysis was to look at the impact of modified nutrition risk in the critically ill (mNUTRIC) on mortality in patients with critical illness. Literature relevant to this meta-analysis was searched in PubMed, Web of Science, and Cochrane Library till 26 August 2023. Prospective or retrospective studies, patients >18 years of age, studies that reported on mortality and mNUTRIC (mNUTRIC cut-off score) were included. The QUIPS tool was used to evaluate the risk for bias in prognostic factors. A total of 31 studies on mNUTRIC score, involving 13,271 patients were included. The summary area under the curve (sAUC) of 0.80 (95% CI: 0.76-0.83) illustrates the mNUTRIC score's strong discrimination. The pooled sensitivity was 0.79 (95% CI: 0.74-0.84) and pooled specificity was 0.68 (95% CI: 0.63-0.73). We found no discernible variation in the mNUTRIC's prediction accuracy among cut-off values of <5 and >5 in our subgroup analysis and sAUC values were 0.82 (95% CI: 0.78-0.85) and 0.78 (95% CI: 0.74-0.81), respectively. We observed that mNUTRIC can discriminate between critically ill individuals and predict their mortality. CRD42023460292. Prakash J, Verma S, Shrivastava P, Saran K, Kumari A, Raj K, et al. Modified NUTRIC Score as a Predictor of All-cause Mortality in Critically Ill Patients: A Systematic Review and Meta-analysis. Indian J Crit Care Med 2024;28(5):495-503.

Echocardiographic Predictive Factors of Worsening Outcome in Type 1 Cardiorenal Syndrome.

Type 1 cardiorenal syndrome (CRS) is defined as acute decompensated heart failure (AHF) leading to secondary acute kidney injury. Few studies have evaluated the reliability of transthoracic echocardiography (TTE) in assessing outcomes in patients with type 1 CRS. We sought to identify echocardiographic predictors of outcomes (death and rehospitalization) in patients with type 1 CRS. This was a prospective longitudinal monocentric study, conducted from December 2020 to December 2022 in the cardiology department of the Internal Security Forces Hospital in Marsa, Tunisia. 68 patients with type 1 CRS were included prospectively. Physical, biological, and echocardiographic data were collected during the index hospitalization and at 3 and 6 months of follow-up. The mean age was 69 ± 10.1 years with a male predominance (72.0%). The mortality rate during initial hospitalization for AHF was 11.7%. The all-cause mortality rate at six months was 22.0%. The rehospitalization rate was 38.0%. Severe tricuspid regurgitation (p = 0.031), the subaortic velocity time integral (LVOT-VTI) with a cut-off value of 16, a sensitivity (Se) of 65%, and a specificity (Sp) of 85% (Area under the curve (AUC) = 0.818, p < 0.001), the right ventricular fractional area change (RV-FAC) with a cut-off value of 16, a Se of 60% and a Sp of 81% (AUC = 0.775, p < 0.001) were independent predictors of the cumulative rates of rehospitalization and mortality at six months. Left ventricular ejection fraction (LVEF) < 35% (HR = 0.828, 95% CI: 0.689-0.995, p = 0.044) and the RV-FAC (HR = 0.564, 95% CI: 0.361-0.881, p = 0.012) were independent predictors of all-cause mortality. LVOT-VTI (AUC = 0.766, p < 0.001) was a significantly independent predictor of rehospitalization. This study confirmed that type 1 CRS is associated with a poor prognosis. LVEF, LVOT-VTI, and RV-FAC are simple, reproducible, and sensitive ultrasound parameters for predicting outcomes in patients with type 1 CRS.

Machine learning for development of ECG-based prediction models for atrial fibrillation, thromboembolism and mortality in patients with heart failure

Abstract Background Heart failure (HF) is a worldwide epidemic affecting more than 64 million people. Given its massive burden both socially and economically, early identification of individuals at risk for complications is important. Purpose To test the predictive performance of non-invasive models from 12-lead digitalized electrocardiography (ECG) and cycle ergometer for adverse outcome in individuals with heart failure. Methods 598 Patients scheduled for right heart catheterization due to unexplained dyspnea were screened. All ECG recorded at admission were further analysed using the software "ECG-Precision-Analysis V-1-2023" to measure the duration of amplified p-wave (APWD at 175mm/sec, 80mm/mV) and to confirm the diagnosis of inter-atrial block. Ergometer was performed in a supine position with increasing intensity adapted to individual capacity (25 or 50W). The maximum physical capacity (Watt-max) was determined. Follow-up (FU) was scheduled at 12-,36-, 60- and 120-month after discharge with the primary endpoint as MACCE (a composite of new onset of AF, ischemic stroke and peripheral embolism) in at baseline event-free patients and the secondary endpoint as all-cause mortality in the total cohort. Three machine learning (ML) algorithms (COX regression, BSR and LASSO regression) were used to select candidate variables and establish predictive models for MACCE and all-cause mortality. Model evaluation was performed in terms of discriminatory power using C-statistics for each endpoint. Results Prediction models developed using machine learning (ML) algorithms (COX regression, BSR and LASSO regression) identified Watt-max and/or APWD as core components for MACCE and mortality prediction . APWD and Watt-max were key components of ML models for prediction of thromboembolic risk and AF (MACCE) and reached accurate diagnostic performances (C-statistics up to 0.74), moreover, another model consisted of APWD and aIAB (advanced inter-atrial block) was established to serve as a reference to ML models with moderate performance for MACCE (mean C-statistics &amp;lt;0.70). All ML models for prediction of all-cause mortality included Watt-max and achieved C-statistics &amp;gt; 0.75. Conclusions In patients with heart failure, the combination of APWD, aIAB and maximum excercice capacity allow to identify patients at risk for AF and stroke, whereas mortality is predominantly predicted by maximum exercise capacity but not APWD.Kaplan-Meier curves for MACCE/MortalitytimeROC curves for MACCE/Mortality