Risk Stratification Of Patients Research Articles

Predictive value of Systematic Coronary Risk Evaluation 2-Diabetes risk model and arterial stiffness for cardiovascular events in the Asian population with type 2 diabetes mellitus.

Individuals with diabetes are at high risk of developing cardiovascular events. The present study investigated the predictive value of the cardio-ankle vascular index (CAVI) when added to the Systematic Coronary Risk Evaluation 2-Diabetes (SCORE2-Diabetes) risk algorithm to predict cardiovascular events in the Asian population. The SCORE2-Diabetes risk was assessed in 1,502 patients with diabetes, aged 40-69 years. Then, we further stratified each 10-year risk category with a CAVI value of 9.0. The primary outcomes (composite of all causes of death, myocardial infarction, stroke and hospitalization for heart failure) were assessed over 5 years. The mean age of the population was 59.8 ± 6.4 years. The proportion of 10-year risk according to the SCORE2-Diabetes risk of low, moderate, high and very high risk identified at 7.2, 30.0, 27.2 and 35.6%, respectively. The mean CAVI value was 8.4 ± 1.4, and approximately 35.4% of the patients had CAVI ≥9.0. The SCORE2-Diabetes risk algorithm independently predicted the primary outcomes in patients with diabetes (hazard ratio 1.18, 95% confidence interval [CI] 1.13-1.22), whereas CAVI did not (hazard ratio 1.03, 95% CI 0.89-1.18). The C-index for the primary outcomes of the SCORE2-Diabetes risk algorithm alone was 0.72 (95% CI 0.67-0.77). The combination of SCORE2-Diabetes and CAVI, both in the continuous value and risk groups, did not improve discrimination (C-index 0.72, 95% CI 0.67-0.77 and 0.68, 95% CI 0.64-0.74, respectively). Adding the CAVI to the SCORE2-Diabetes risk algorithm did not improve individual risk stratification in patients with diabetes.

Three-dimensional telomere profiling predicts risk of progression in smoldering multiple myeloma.

Smoldering multiple myeloma (SMM) is a precursor stage that precedes multiple myeloma (MM). SMM is heterogenous with nearly 40% of patients progressing to MM in the first 5 years. The high rate of progression of SMM patients highlights the need for early intervention, which underscores the importance of identifying SMM patients with the highest risk of progression. Several risk stratification models showed utility in identifying high-risk SMM patients; however, these systems showed limited sensitivity. To date, identifying high-risk SMM patients remains an important clinical need. In this study, we present the 3-dimensional telomere profiling as a structural biomarker capable of stratifying SMM patients as a function of genomic instability. Quantifying telomere dysfunction using the TeloView technology showed utility in risk stratification of cancer patients, particularly hematological malignancies. In this study, we analyzed 168 SMM patients. We report an AUC in ROC analysis of 0.8 using a subset of the patients as a training dataset. We then conducted a blind validation on a different cohort and demonstrated a positive predictive value of 85% and negative predictive value of 73%, with sensitivity and specificity of 83% and 76%, respectively. We examined the correlation between the TeloView prediction and the 20-2-20 scoring system, and cytogenetic abnormalities. We report a correlation of 53% with the 20-2-20 scores and over 60% correlation with cytogenetic abnormalities. The result of this study presents the telomere profiling as an effective biomarker able to stratify SMM patients to their respective risk groups with high sensitivity and specificity.

Stellae-123 gene expression signature improved risk stratification in taiwanese acute myeloid leukemia patients

The European Leukemia Net recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, notwithstanding that gene expression analysis is crucial in the risk stratification of AML. The Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated robust survival predictions in AML patients across four western-population cohorts. This study aims to evaluate the applicability of Stellae-123 in a Taiwanese cohort. The Stellae-123 model was applied to 304 de novo AML patients diagnosed and treated at the National Taiwan University Hospital. We find that the pretrained (BeatAML-based) model achieved c-indexes of 0.631 and 0.632 for the prediction of overall survival (OS) and relapse-free survival (RFS), respectively. Model retraining within our cohort further improve the cross-validated c-indexes to 0.667 and 0.667 for OS and RFS prediction, respectively. Multivariable analysis identify both pretrained and retrained models as independent prognostic biomarkers. We further show that incorporating age, Stellae-123, and ELN classification remarkably improves risk stratification, revealing c-indices of 0.73 and 0.728 for OS and RFS, respectively. In summary, the Stellae-123 gene expression signature is a valuable prognostic tool for AML patients and model retraining can improve the accuracy and applicability of the model in different populations.

MASLD and MASH at the crossroads of hepatology trials and cardiorenal metabolic trials.

Steatotic liver disease (SLD) is a worldwide public health problem, causing considerable morbidity and mortality. Patients with SLD are at increased risk for major adverse cardiovascular (CV) events, type 2 diabetes mellitus and chronic kidney disease. Conversely, patients with cardiometabolic conditions have a high prevalence of SLD. In addition to epidemiological evidence linking many of these conditions, there is evidence of shared pathophysiological processes. In December 2022, a unique multi-stakeholder, multi-specialty meeting, called MOSAIC (Metabolic multi Organ Science Accelerating Innovation in Clinical Trials) was convened to foster collaboration across metabolic, hepatology, nephrology and CV disorders. One of the goals of the meeting was to consider approaches to drug development that would speed regulatory approval of treatments for multiple disorders by combining liver and cardiorenal endpoints within a single study. Non-invasive tests, including biomarkers and imaging, are needed in hepatic and cardiorenal trials. They can be used as trial endpoints, to enrich trial populations, to diagnose and risk stratify patients and to assess treatment efficacy and safety. Although they are used in proof of concept and phase 2 trials, they are often not acceptable for regulatory approval of therapies. The challenge is defining the optimal combination of biomarkers, imaging and morbidity/mortality outcomes and ensuring that they are included in future trials while minimizing the burden on patients, trialists and trial sponsors. This paper provides an overview of some of the wide array of CV, liver and kidney measurements that were discussed at the MOSAIC meeting.

A bicentric retrospective study of the correlation of EAU BCR risk groups with 18F-PSMA-1007 PET/CT detection in prostate cancer biochemical recurrence

The European Association of Urology (EAU) has proposed a risk stratification for patients harboring biochemical recurrence (BCR) after radical prostatectomy: ISUP < 4 and PSA doubling time (PSAdt) > 12 months for low risk, and ISUP ≥ 4 or PSAdt ≤ 12 months for high risk. This dual-center retrospective study aims to investigate the correlation between the EAU risk stratification for BCR following radical prostatectomy and the detection rate of lesions using 18F-PSMA-1007 PET/CT. Among the 71 included patients (58 high-risk, 13 low-risk), with a median PSA level of 1.43 ng/ml, PET/CT demonstrated a significantly higher positivity in the high-risk group compared to the low-risk group (72.4% vs. 38.0%, p = 0.026). Analysis of recurrence sites revealed a similar proportion of pelvic-confined disease in both groups (24.1% vs. 23.1%, p = 0.935), but a significantly higher incidence of metastatic disease in the high-risk group (51.7% vs. 15.4%, p = 0.017), with detailed findings indicating an increased prevalence of bone metastases in the high-risk BCR group (37.8% vs. 7.7%, p = 0.048). Therefore, PSMA PET/CT offers valuable insights for treatment decisions, aligning with the evolving landscape of prostate cancer management.

Clinical predictive value of the age, creatinine, and ejection fraction score in patients in acute type A aortic dissection after total arch replacement

The age, creatinine, and ejection fraction (ACEF) score has been accepted as a predictor of poor outcome in elective operations. This study aimed to investigate the predictive value of ACEF score in acute type A aortic dissection (AAAD) patients after total arch replacement. A total of 227 AAAD patients from July 2021 and June 2022 were enrolled and divided into Tertiles 1 (ACEF ≤ 0.73), Tertiles 2 (0.73 < ACEF ≤ 0.95), and Tertiles 3 (ACEF > 0.95). Using inverse probability processing weighting (IPTW) to balance the baseline characteristics and compare the outcomes. Cox logistic regression was used to further evaluate the survival prediction ability of ACEF score. The in-hospital mortality was 9.8%. After IPTW, in the baseline characteristics reached an equilibrium, a higher ACEF score before operation still associated with higher in-hospital mortality. After 1 year follow-up, 184 patients (90.6%) survival. Multivariable analysis revealed that ACEF score (adjusted hazard ratio 1.68; 95% confidence interval 1.34–4.91; p = 0.036) and binary ACEF score (adjusted HR 2.26; 95% CI 1.82–6.20; p < 0.001) was independently associated with 1-year survival. In addition, net reclassification improvement (NRI) and integrated differentiation improvement (IDI) verified that the ACEF score and binary ACEF score is an accurate predictive tool in clinical settings. In conclusions, ACEF score could be considered as a useful tool to risk stratification in patients with AAAD before operation in daily clinical work.

Key messages on obesity care from the 2023 ASPEN Physician Preconference Course: A narrative review.

Obesity is a challenging chronic disease process that continues to affect a large percentage of the population at large. With the advent of new therapeutic options and interventions and a deeper scientific understanding of obesity as a complex illness, there is hope in curtailing this evolving pandemic. In this article, we present key medical information to engage and empower nutrition-focused providers to manage obesity and its nutrition complications. The topics summarized here were presented during the 2023 American Society for Parenteral and Enteral Nutrition Preconference Physician Course and include pathophysiology and hormonal regulation of obesity, multidisciplinary care planning and nutrition risk stratification of patients, and common approaches to treatment, including lifestyle modifications, antiobesity medications, and procedures from the perspective of the nutrition specialist.

Noninvasive Atherosclerotic Phenotyping: The Next Frontier into Understanding the Pathobiology of Coronary Artery Disease.

Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease. Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation.

Machine learning with electrocardiograms to optimize mortality risk stratification in patients with suspected acute coronary syndrome

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute (NHLBI) and National Center for Advancing Translational Sciences (NCATS). Background The importance of risk stratification in patients with suspected acute coronary syndrome (ACS) extends beyond diagnosis and immediate treatment. It influences the precision of care delivery and the allocation of resources to those at highest risk of adverse events. Purpose We sought to evaluate the prognostic value of electrocardiogram (ECG) feature-based machine learning models to risk-stratify long-term mortality in those with suspected ACS. Methods This was a multicenter prospective observational cohort study of consecutive, non-traumatic patients evaluated at the emergency department for suspected ACS. The derivation cohort included 4,015 patients from a University Medical Center (age 59±16 years, 47% women, 80% training with 10-fold cross-validation and 20% testing). Ascertainment of all-cause death was based on numerous data sources, including the Centers for Disease Control and Prevention’s National Death Index registry. We trained six machine learning methods for survival analysis using 73 morphological ECG features from presenting prehospital 10-second 12-lead ECGs. We used predicted risk scores in a variational Bayesian Gaussian mixture model to define three risk groups corresponding to low, moderate, and high-risk and compared the resulting classification performance against the HEART score. The external testing cohort included 3,095 patients from a University (age 59±15 years, 44% women). Results The mortality rate was 20.3% in the derivation cohort after an average follow-up period of 3.53 years (IQR 1.75 - 5.32). Extra Survival Trees outperformed other forecasting models during cross-validation. In the internal testing cohort, the derived risk groups were significantly predictive of survival (Kaplan-Meier log-rank test statistic = 121.14, p&amp;lt;0.001), outperforming the classification performance using the HEART score (Figure 1). Our machine learning-based risk stratification model detected &amp;gt;90% of death events missed by low-risk HEART score (Figure 2). Ruling-out the low-risk group, it achieved a negative predictive value of 93.4% with a sensitivity of 85.9% (compared to 89.0% and 75.0%, respectively, for the HEART score). This classification performance generalized well to our external testing cohort. Compared to those in the low-risk group, patients at moderate (OR = 3.62 [1.35-9.74]) and high (OR = 6.12 [2.38-15.75]) risk had significantly higher odds of 30-day cardiovascular death (n=109, 3.5%). Conclusions Using only features from the 10-second 12-lead ECG, we derived and externally validated a machine learning model that stratifies the mortality risk of patients during long-term follow up. This model outperformed current standard of care based on the HEART score. Future work should validate the potential of this decision-support tool in influencing treatment plans and resource allocation.Figure 1.Clustering performanceFigure 2.Sankey diagram

Bleeding risk stratification in patients admitted for acute coronary syndrome

Abstract Funding Acknowledgements None. Introduction The risk of hemorrhagic events should always be accounted for in patients admitted with acute coronary syndromes (ACS). With the increasing frailty of these patients, it is important to identify them and minimize the risk of such events. Purpose Identify high-risk patients admitted for ACS for hemorrhagic events during their hospital stay. Methods Multicenter retrospective study, data collected from 1/10/2010 and 31/12/2020 with ACS diagnosis. Patients were divided into 3 groups according to hemoglobin (Hb) and platelet (Plat) levels. Group 1 – Hb &amp;lt;8g/dl, Plat &amp;lt;150x109/L; Group 2 – Hb 8-12g/dl, Plat 150-450x109/L; Group 3 – Hb ≥12g/dl, Plat ≥450x109/L. We further divided these patients according to a composite endpoint. Group A without the composite endpoint; Group B with composite endpoint. This composite endpoint was defined as major hemorrhage, intracranial hemorrhage, need of blood transfusions and a Hb decrease of ≥ 2g/dl. Results 19409 patients were enrolled, of those 4707 (24.3%) had the composite endpoint. Group B was older (68±13 vs 66±12, p&amp;lt;0.001), had higher rates of arterial hypertension (72.5% vs 68.2%, p&amp;lt;0.001), diabetes mellitus (35.6% vs 30.7%, p&amp;lt; 0.001), stroke (9.0% vs 6.6%, p &amp;lt; 0.001) and previous haemorrhage (p= 0.004). No statistically significant differences regarding previous MI (p= 0.240). Hb levels &amp;lt;8g/dL (8.1% vs 0.6%, p&amp;lt;0.001) were associated with a higher risk of hemorrhagic events but not lower levels of Plat, instead higher levels (&amp;gt; 450x109/L) were event associated (1.8% vs 0.9%, p&amp;lt;0.001). The choice of femoral access was related to an increased risk of hemorrhagic events (p&amp;lt;0.001). Logistic regression confirmed that the Hb levels &amp;lt; 12g/dL when compared with normal levels were related to the composite endpoint proportionally to the degree of anemia, the lower the level of Hb the more likely these events occur, Hb &amp;lt;8g/dL p&amp;lt;0.001, OR 4.02, CI (95%) 2.50-6.47 and Hb 8-12g/dL, p&amp;lt;0.001, OR 0.761, CI (95%) 0.693-0.837. Survival analysis also showed that cardiovascular (CV) mortality and re-admission at 1 year were related to the degree of anemia. Conclusion Lower levels of Hb correlated well and proportionally to the occurrence of the composite endpoint as well as cardiovascular (CV) mortality and re-admission at 1 year. Contrarily to expected lower levels of Plat did not correlate with a higher risk of hemorrhagic events but instead thrombocytosis did, as a paradoxical risk of bleeding has been noted in patients with thrombocytosis, especially extreme thrombocytosis.

McConnell's sign predicts normotensive shock in patients with acute pulmonary embolism

Abstract Funding Acknowledgements None. Background Patients with intermediate-risk acute pulmonary embolism (PE) have mortality rates ranging from 3-15%, with incidence of normotensive shock occurring in up to 30% of patients.1-3 Existing risk models often fall short in accurately identifying those at heightened risk of normotensive shock and those who might derive benefit from advanced therapeutic interventions including catheter based therapies. Diagnosis of normotensive shock typically necessitates invasive right heart catheterization, however, McConnell's sign has been associated with higher risk PEs.4 Consequently, our objective was to assess the relationship between McConnell's sign, a readily available bedside point-of-care tool, and its predictive value in identifying normotensive shock in patients diagnosed with acute intermediate-risk PE. Methods All patients with intermediate-risk PE who underwent percutaneous mechanical thrombectomy (MT) between August 2020 and April 2023 at a large academic public hospital were included in the study. Normotensive shock was defined as patients with systolic blood pressure (SBP) ≥ 90mmHg in the absence of vasopressor support with pre-procedural invasive measures of CI £ 2.2 L/min/m2 and clinical evidence of hypoperfusion (i.e. elevated lactate, oliguria). The primary outcome was the association between McConnell’s sign and normotensive shock. Results A total of 49 patients with intermediate-risk PE underwent MT, 9 patients had incomplete data, resulting in a final cohort of 40 patients (mean age: 57 ± 13 years; 45% female). A total of 29/40 (72.5%) patients had McConnell’s sign. Patients with McConnell’s sign had higher rates of obesity (59% vs 18% p=0.02), higher heart rate (114 vs 99 beats/min, p=0.008), higher rates of elevated lactate (86% vs 55%, p=0..038), lower cardiac index (1.9 vs 3.1 L/min/m2, p=0.003), and higher rates of normotensive shock (76% vs 27%, p=0.005). There was no statistically significant difference in age, sex, race, rates of saddle emboli, left ventricular ejection fraction, pulmonary artery systolic pressure, presenting blood pressure, sPESI and composite pulmonary embolism shock score scores in patients with or without McConnell’s sign. In patients with normotensive shock, 22/25 (88%) had McConnell’s sign and only 53.3% had McConnell’s sign without shock (Figure 1). Patients with McConnell’s sign had an increased odds (OR 8.38, CI: 1.73-40.53; p=0.008, AUC 0.70, 95% CI: 0.56-0.85) of normotensive shock. Conclusion This is the first study to suggest that McConnell’s sign can effectively identify those in the intermediate-risk group who are at risk for normotensive shock. Further studies are needed to validate this non-invasive technique that can be rapidly performed at bedside with high reproducibility and whether it can help risk-stratify patients who may benefit from advanced PE therapies.

Stratification of arrhythmic risk in patients admitted for acute coronary syndrome: the role of the machine learning-derived PRAISE score

Abstract Funding Acknowledgements None. Background Patients with acute coronary syndrome (ACS) have a high arrhythmic burden, and either ventricular and supraventricular arrhythmias are very common during hospitalization[1]. Patients who develop arrhythmias show higher mortality and worse prognosis. The PRAISE (Prediction of Adverse Events Following an Acute Coronary Syndrome) score is a machine-learning based model for predicting 1-year all cause death, recurrent acute myocardial infarction and major bleedings in patients after ACS[2]. To date, its role to predict arrhythmic complications in ACS remains unknown. Purpose We hypothesized that patients with higher PRAISE score have a higher arrhythmic burden. Aim was to evaluate in a prospective protocol the PRAISE score capability for identifying patients with ACS at higher risk of arrhythmic complications during in-hospital stay. Methods A total of 365 consecutive patients admitted to our cardiac intensive care unit for ACS and undergoing percutaneous coronary intervention were enrolled. All patient was monitored by continuous electrocardiogram during hospitalization. The PRAISE score was obtained for each patient &amp;lt;24 hours from admission. Patients were divided into 2 groups based on the results of the PRAISE score for all-cause of death as patients without high PRAISE score (e.g. with low to intermediate risk, n=350) and patients with high PRAISE score (e.g. with high risk, n=15). The occurrence of atrial fibrillation (AF) and ventricular arrhythmias (VAs) up to discharge was recorded. AF was defined by detection of at least one episode of uncoordinated atrial electrical activation and irregular R-R intervals, in absence of distinct repeating P waves and with irregular atrial activations lasting at least 5 minutes. We considered as VAs all episodes of ventricular non-sustained tachycardia, sustained ventricular tachycardia and ventricular fibrillation. Results ROC curve analysis indicated a significant relationship between high PRAISE score and risk of both in-hospital AF (AUC 0.89, 95%CI 0.82-0.94, p=0.0001) and VAs (AUC 0.69, 95%CI 0.64-0.75, p=0.0001). A high PRAISE score had a specificity of 99% for AF and 92% for VAs. By Kaplan-Meier analysis, patients with high PRAISE score more frequently developed AF (30% vs 4% in those without high score; log rank p=0.00001) and VAs (77% vs 35%; log rank p=0.00001). Multivariate analysis showed that a high PRAISE score was an independent predictor of both AF (HR 4.08, 95%CI 1.14-14.58, p=0.030) and VAs (HR 2.36, 95%CI 1.08-5.14, p=0.030). Conclusions In patients hospitalized for ACS, the PRAISE score has a comprehensive capability to identify with high specificity those patients prone to develop arrhythmic events during hospitalization. This may be important in order to stratify patients with higher arrhythmic risk in whom individualized strategies may improve the clinical outcome.Baseline features of the populationKaplan-Meier anaysis

Rediscovery of the implication of albuminuria in heart failure: emerging classic index for cardiorenal interaction.

The development of new drugs and device therapies has led to remarkable advancements in heart failure (HF) treatment in the past couple of decades. However, it becomes increasingly evident that guideline-directed medical therapy cannot be one-size-fits-all across a wide range of ejection fractions (EFs) and various aetiologies. Therefore, classifications solely relying on EF and natriuretic peptide make optimization of treatment challenging, and there is a growing exploration of new indicators that enable efficient risk stratification of HF patients. Particularly when considering HF as a multi-organ interaction syndrome, the cardiorenal interaction plays a central role in its pathophysiology, and albuminuria has gained great prominence as its biomarker, independent from glomerular filtration rate. Albuminuria has been shown to exhibit a linear correlation with cardiovascular disease and HF prognosis in multiple epidemiological studies, ranging from normal (<30mg/g) to high levels (>300mg/g). However, on the other hand, it is only recently that the details of the pathological mechanisms that give rise to albuminuria have begun to be elucidated, including the efficient compaction/tightening of the glomerular basement membrane by podocytes and mesangial cells. Interestingly, renal disease, diabetes, and HF damage these components associated with albuminuria, and experimental models have demonstrated that recently developed HF drugs reduce albuminuria by ameliorating these pathological phenotypes. In this review, facing the rapid expansion of horizons in HF treatment, we aim to clarify the current understanding of the pathophysiology of albuminuria and explore the comprehensive understanding of albuminuria by examining the clinically established evidence to date, the pathophysiological mechanisms leading to its occurrence, and the outcomes of clinical studies utilizing various drug classes committed to specific pathological mechanisms to put albuminuria as a novel axis to depict the pathophysiology of HF.

Development of a Prognostic Risk Model Based on Oxidative StressRelated Genes for Platinum-Resistant Ovarian Cancer Patients

Introduction: Ovarian Cancer (OC) is a heterogeneous malignancy with poor outcomes. Oxidative stress plays a crucial role in developing drug resistance. However, the relationships between Oxidative Stress-related Genes (OSRGs) and the prognosis of platinum-resistant OC remain unclear. This study aimed to develop an OSRGs-based prognostic risk model for platinum-resistant OC patients. Methods: Gene Set Enrichment Analysis (GSEA) was performed to determine the expression difference of OSRGs between platinum-resistant and -sensitive OC patients. Cox regression analyses were used to identify the prognostic OSRGs and establish a risk score model. The model was validated by using an external dataset. Machine learning was used to determine the prognostic OSRGs associated with platinum resistance. Finally, the biological functions of selected OSRG were determined via in vitro cellular experiments. Results: Three gene sets associated with oxidative stress-related pathways were enriched (p &lt; 0.05), and 105 OSRGs were found to be differentially expressed between platinum-resistant and - sensitive OC (p &lt; 0.05). Twenty prognosis-associated OSRGs were identified (HR: 0:562-5.437; 95% CI: 0.319-20.148; p &lt; 0.005), and seven independent OSRGs were used to construct a prognostic risk score model, which accurately predicted the survival of OC patients (1-, 3-, and 5-year AUC=0.69, 0.75, and 0.67, respectively). The prognostic potential of this model was confirmed in the validation cohort. Machine learning showed five prognostic OSRGs (SPHK1, PXDNL, C1QA, WRN, and SETX) to be strongly correlated with platinum resistance in OC patients. Cellular experiments showed that WRN significantly promoted the malignancy and platinum resistance of OC cells. Conclusion: The OSRGs-based risk score model can efficiently predict the prognosis and platinum resistance of OC patients. This model may improve the risk stratification of OC patients in the clinic.

In-hospital trimethylamine N-oxide (TMAO) variation predicts major adverse cardiovascular events in myocardial infarction survivors

Abstract Funding Acknowledgements None. Background Trimethylamine N-oxide (TMAO), a gut microbiota result of the fermentation of animal foods rich in choline, L-carnitine and phosphatidylcholine (red meat, egg yolk, dairy food), is associated with alterations in lipid metabolism, increased foam cell formation, promotion of inflammation, oxidative stress, platelet aggregation and thrombosis. To date the data evaluating TMAO as a predictor of mortality and ischemic events in patients with acute myocardial infarction (AMI) based on one-time measurement of TMAO levels lead to conflicting results. TMAO levels are fluctuating and in addition to diet, genetic factors, general condition and some co-morbidities affect its circulating levels. Purpose Since, there is a need for better risk stratification of AMI patients before the hospital discharge for more personalised treatment, we evaluated in-hospital variation in TMAO levels and its impact on outcome. Methods Blood samples from 149 consecutive AMI patients were collected on admission and on discharge. The endpoint was a three-point major adverse cardiovascular events (MACE) composed as all-cause mortality, reinfarction and development of heart failure. Results The majority of AMI patients were male (77%), hospitalized for first coronary event, with mean age 64(11) years. Median circulating TMAO level was significantly higher on admission than on discharge, (7.81 [3.47 –19.98] vs 3.45 [2.3 – 4.78] μM, respectively, p&amp;lt;0.001). In order to evaluate the impact of TMAO variation during the hospital stay on outcome, we estimated TMAO cut-off value by continuous hazard ratio analysis; values above the 3.45 μM were associated with incident of MACE in a linear fashion (Fig. 1a). Subsequently, we stratified AMI patients in 2 groups: 1) LL/HL (low-low/high-low) that included 75 (50.3%) patients whose TMAO levels remained low or were high and decreased during hospitalization and 2) HH/LH (high-high/low-high) including 74 patients (49.7%) patients whose TMAO levels remained elevated or were initially low, but rose above the estimated threshold during hospitalisation (Fig. 1b). Thirty-two (21.5%) patients reached the combined endpoint during the median follow-up of 30 months. The Kaplan-Meier analysis demonstrated that patients from the HH/LH group had a higher likelihood of experiencing MACE (p=0.05) (Fig. 2a). The multivariate Cox analysis revealed that patients in the HH/LH group had over twice the risk of MACE compared to those in the LL/HL group. Furthermore, older age and worse left ventricular systolic function were identified as independent predictors of MACE during long-term follow-up (Fig. 2b). Conclusions AMI patients with permanently elevated or increasing levels of TMAO have a worse outcome. The novelty and the strength of our study is the fact that the direction of variation of TMAO during the index hospitalisation identifies patients at higher risk of MACE during 30 months follow-up.

Incremented Amyloid-beta values predict mortality during long-term follow-up in patients with acute myocardial infarction, both STEMI and NSTEMI

Abstract Funding Acknowledgements None. Background Both the amyloid-β (Aβ) isoforms, namely Aβ1-40 and Aβ1-42 are implicated in the pathogenesis of Alzheimer’s disease through different mechanisms. While Aβ42 easily forms oligomers in brain, Aβ1-40 is more abundant in circulation where it exerts a pro-inflammatory role. Recently, Aβ1-40 has raised interest in the cardiovascular field for its contribution to atherosclerosis, more specifically through plaque formation and destabilization. However, to date, the prognostic role of Aβ1-40 in patients with acute myocardial infarction (AMI) is limited to NSTEMI. Purpose Since there is a need for better risk stratification of AMI patients, we analyzed the impact of plasma Aβ1-40 on long-term mortality in a cohort of real-world patients with AMI, including STEMI and NSTEMI. Further, we sought to identify predictors for elevated Aβ1-40 levels. Methods Blood samples were obtained from patients hospitalized for AMI and Aβ1-40 levels were evaluated with Human Aβ40 ELISA Kit. The endpoint was all-cause mortality. Results Our population included 1119 consecutive patients, with a mean age of 67 years, 72% male, 2/3 of them had a first ischemic event and 68.4% had STEMI diagnosis. The median plasma Aβ1-40 concentration on admission was 86.9 [54.5-128.9] pg/ml and there was no difference in Aβ1-40 levels between NSTEMI and STEMI (93.6 [61.2-130.9] Vs. 85.3 [52.9-128.7] pg/ml, respectively, p=0.1). At logistic regression multivariate analysis, higher Aβ1-40 levels were predicted by older age, worse left ventricular systolic function, HbA1C &amp;gt; 39 mmol/mol and GFR&amp;lt;60ml/min/m 2 (Fig.1a). From the final multivariable model, a nomogram for prediction of high levels of Aβ1-40 was computed (Fig.1b). One hundred ninety-three patients (17.2%) died, during the median follow-up of 57 [30 - 80] months. Patients who died had significantly higher levels of Aβ1-40 compared to alive patients (113.1 [67.9 – 159.5] Vs. 83.9 [52.5 – 122.6] pg/ml, p&amp;lt;0.01). Higher plasma Aβ1-40 values were associated with increased mortality risk, in both STEMI and NSTEMI (p&amp;lt;0.01) (Fig.2a). Further, at Cox multivariate analysis including the whole population, Aβ1-40 levels were predictive of mortality (HR 1.03, p=0.02), together with older age, higher Il-1β, GFR&amp;lt;60ml/min/m 2 and worse left ventricular systolic function (Fig.2b). The predictive value of our final model was superior to GRACE score for up to 60 months (AUC 0.830 (0.793 – 0.868) Vs 0.797 (0.756 – 0.837), respectively, p=0.03, Fig.2c), after which they were comparable. Conclusions Elevated levels of Aβ1-40 values are independent predictors of long-term mortality in a real-world cohort including both STEMI and NSTEMI patients.

Prognostic Value of [99mTc]Tc-DPD Quantitative SPECT/CT in Patients with Suspected and Confirmed Amyloid Transthyretin-Related Cardiomyopathy and Preserved Left Ventricular Function.

Quantitative 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid ([99mTc]Tc-DPD) SPECT may be used for risk-stratifying patients with amyloid transthyretin-related cardiomyopathy (ATTR-CM). We aimed to analyze the predictive value of quantitative [99mTc]Tc-DPD SPECT/CT in suspected and confirmed ATTR-CM according to different disease stages. Methods: The study enrolled consecutive patients with suspected ATTR-CM who were referred to a single tertiary center and underwent quantitative [99mTc]Tc-DPD SPECT/CT allowing SUVmax and SUVpeak analysis. Patients were divided into 2 groups according to left ventricular ejection fraction (LVEF) at baseline (i.e., ≥50% and <50%). Clinical, laboratory, and echocardiographic parameters and major adverse cardiac events (i.e., all-cause death, sustained ventricular tachyarrhythmia, hospitalization for heart failure, implantation of a cardioverter defibrillator) were investigated for any correlation with quantitative uptake values. Results: In total, 144 patients with suspected ATTR-CM were included in the study (98 with LVEF ≥ 50% and 46 with LVEF < 50%), of whom 99 were diagnosed with ATTR-CM (68.8%; 69 with LVEF ≥ 50% and 30 with LVEF < 50%). A myocardial SUVmax of at least 7 was predictive of major adverse cardiac events at 21.9 ± 13.0 mo of follow-up (hazard ratio, 2.875; 95% CI, 1.23-6.71; P = 0.015) in patients with suspected or confirmed ATTR-CM (global χ2 = 6.892, P = 0.02) and an LVEF of at least 50%. SUVmax was not predictive in patients with an LVEF of less than 50% and suspected or confirmed ATTR-CM. Conclusion: In patients with suspected or confirmed ATTR-CM and preserved LVEF, representing an early disease stage, quantitative [99mTc]Tc-DPD SPECT should be considered to improve early-stage risk stratification.

Evaluating the utility of ZNF331 promoter methylation as a prognostic and predictive marker in stage III colon cancer: results from CALGB 89803 (Alliance)

ABSTRACT While epigenomic alterations are common in colorectal cancers (CRC), few epigenomic biomarkers that risk-stratify patients have been identified. We thus sought to determine the potential of ZNF331 promoter hypermethylation (mZNF331) as a prognostic and predictive marker in colon cancer. We examined the association of mZNF331 with clinicopathologic features, relapse, survival, and treatment efficacy in patients with stage III colon cancer treated within a randomized adjuvant chemotherapy trial (CALGB/Alliance89803). Residual tumour tissue was available for genomic DNA extraction and methylation analysis for 385 patients. ZNF331 promoter methylation status was determined by bisulphite conversion and fluorescence-based real-time polymerase chain reaction. Kaplan-Meier estimator and Cox proportional hazard models were used to assess the prognostic and predictive role of mZNF331 in this well-annotated dataset, adjusting for clinicopathologic features and standard molecular markers. mZNF331 was observed in 267/385 (69.4%) evaluable cases. Histopathologic features were largely similar between patients with mZNF331 compared to unmethylated ZNF331 (unmZNFF31). There was no significant difference in disease-free or overall survival between patients with mZNF331 versus unmZNF331 colon cancers, even when adjusting for clinicopathologic features and molecular marker status. Similarly, there was no difference in disease-free or overall survival across treatment arms when stratified by ZNF331 methylation status. While ZNF331 promoter hypermethylation is frequently observed in CRC, our current study of a small subset of patients with stage III colon cancer suggests limited applicability as a prognostic marker. Larger studies may provide more insight and clarity into the applicability of mZNF331 as a prognostic and predictive marker.

Association of Triglyceride Glucose-Derived Indexes with Recurrent Events Following Atherosclerotic Cardiovascular Disease.

Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indexes of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Distribution of the TyAG and TyAG-BMI indexes shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Multi-Center Assessment of Lymph-Node Density and Nodal-Stage to Predict Disease-Specific Survival in Patients with Bladder Cancer Treated by Radical Cystectomy

BACKGROUND: Prognostic tools in pathological-node (pN) patients after radical cystectomy (RC) are needed. OBJECTIVES: To evaluate the prognostic impact of lymph node (LN)-density on disease-specific survival (DSS) in patients with bladder cancer (BC) undergoing RC with pelvic lymph node dissection. METHODS: We analyzed a multi-institutional cohort of 1169 patients treated with upfront RC for cT1-4aN0M0 urothelial BCat nine centers. LN-densitywas calculated as the ratio of the number of positive LNs×100% to the number of LNs removed. The optimal LN-density cut-off value was defined by creating a time-dependent receiver operating characteristic (ROC) curve in pN patients. Univariable and multivariable Cox’ regression analyses were used to assess the effect of conventional Tumor Nodes Metastasis (TNM) nodal staging system, LN-density and other LN-related variables on DSS in the pN-positive cohort. RESULTS: Of the 1169 patients, 463 (39.6%) patients had LN-involvement. The area under the ROC curve was 0.60 and the cut-off for LN-density was set at 20%, 223 of the pN-positive patients (48.2%) had a LN-density.20%. In multivariable models, the number of LN-metastases (HR 1.03, p = 0.005) and LN-density, either as continuous (HR 1.01, p = 0.013) or as categorical variable (HR 1.37, p = 0.014), were independently associated with worse DSS, whereas pN-stage was not. CONCLUSIONS: LN-density.20% was an independent predictor of worse DSS in BC patients with LN-involvement at RC. The integration of LN-density and other LN-parameters rather than only conventional pN-stage may contribute to a more refined risk-stratification in BC patients with nodal involvement.