C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial

The Usefulness of the C2HEST Score in Predicting the Clinical Outcomes of COVID-19 in COPD and Non-COPD Cohorts

Patients with chronic obstructive pulmonary disease (COPD) infected with SARS-CoV-2 indicate a higher risk of severe COVID-19 course, which is defined as the need for hospitalization in the intensive care unit, mechanical ventilation, or death. However, simple tools to stratify the risk in patients with COPD suffering from COVID-19 are lacking. The current study aimed to evaluate the predictive value of the C2HEST score in patients with COPD. A retrospective analysis of medical records from 2184 patients hospitalized with COVID-19 at the University Hospital in Wroclaw from February 2020 to June 2021, which was previously used in earlier studies, assessed outcomes such as mortality during hospitalization, all-cause mortality at 3 and 6 months, non-fatal discharge, as well as adverse clinical incidents. This re-analysis specifically examines the outcomes using a COPD split. In the COPD group, 42 deaths were recorded, including 18 in-hospital deaths. In-hospital mortality rates at 3 and 6 months did not significantly differ among C2HEST strata, nor did their impact on subsequent treatment. However, a notable association between the C2HEST score and prognosis was observed in the non-COPD cohort comprising 2109 patients. The C2HEST score's predictive ability is notably lower in COPD patients compared to non-COPD subjects, with COPD itself indicating a high mortality risk. However, C2HEST effectively identifies patients at high risk of cardiac complications during COVID-19, especially in non-COPD cases.

Validation of the MEDIA echo score for the prognosis of heart failure with preserved ejection fraction

There is currently no widely used prognostic score in heart failure (HF) with preserved ejection fraction (HFpEF). The MEDIA echo score, including four variables (pulmonary arterial systolic pressure > 40 mmHg, inferior vena cava collapsibility index < 50%, average E/e' > 9, and lateral mitral annular s' < 7 cm/s), has been proposed as a useful risk stratification tool. This study aimed at further validating the MEDIA echo score in both hospitalised and ambulatory HFpEF patients. The MEDIA echo score ranges from 0 to 4 (each criterion scores 1 point). The associations between MEDIA echo score and cardiovascular outcomes were assessed in two independent HFpEF cohorts, namely patients hospitalised for worsening HFpEF (N = 242, mean age 78 ± 11), and stable ambulatory HFpEF patients (N = 76, mean age 65 ± 8). Using multivariable Cox models, in the worsening HFpEF cohort, patients with a MEDIA echo score of 3-4 displayed a significant increased risk of death (HR 2.10, 95%CI 1.02-4.33, P = 0.043, score 0-1 as reference). In the ambulatory HFpEF cohort, patients with a MEDIA echo score of 2 had a significantly higher risk of death or HF hospitalisation (HR 3.44, 95%CI 1.27-9.30, P = 0.015, score 0 as reference), driven by HF hospitalisation; in that cohort, adding the MEDIA echo score to the clinical model significantly improved reclassification for the combined endpoint (integrated discrimination improvement 6.2%, P = 0.006). The MEDIA echo score significantly predicted the outcome of HFpEF patients in both hospital and ambulatory settings; its use may help refine routine risk stratification on top of well-established prognosticators in stable HFpEF patients.

Development and validation of prediction models for incident atrial fibrillation in heart failure

OBJECTIVES

Accurate prediction of heart failure (HF) patients at high risk of atrial fibrillation (AF) represents a potentially valuable tool to inform shared decision making. No validated prediction model for AF in HF is currently available. The objective was to develop clinical prediction models for 1-year risk of AF.

METHODS

Using the Danish Heart Failure Registry, we conducted a nationwide registry-based cohort study of all incident HF patients diagnosed from 2008 to 2018 and without history of AF. Administrative data sources provided the predictors. We used a cause-specific Cox regression model framework to predict 1-year risk of AF. Internal validity was examined using temporal validation.

RESULTS

The population included 27 947 HF patients (mean age 69 years; 34% female). Clinical experts preselected sex, age at HF, NewYork Heart Association (NYHA) class, hypertension, diabetes mellitus, chronic kidney disease, obstructive sleep apnoea, chronic obstructive pulmonary disease and myocardial infarction. Among patients aged 70 years at HF, the predicted 1-year risk was 9.3% (95% CI 7.1% to 11.8%) for males and 6.4% (95% CI 4.9% to 8.3%) for females given all risk factors and NYHA III/IV, and 7.5% (95% CI 6.7% to 8.4%) and 5.1% (95% CI 4.5% to 5.8%), respectively, given absence of risk factors and NYHA class I. The area under the curve was 65.7% (95% CI 63.9% to 67.5%) and Brier score 7.0% (95% CI 5.2% to 8.9%).

CONCLUSION

We developed a prediction model for the 1-year risk of AF. Application of the model in routine clinical settings is necessary to determine the possibility of predicting AF risk among patients with HF more accurately and if so, to quantify the clinical effects of implementing the model in practice.

Liver fibrosis scores and atrial fibrillation incidence in heart failure with preserved ejection fraction

AIM

Non-alcoholic fatty liver disease (NAFLD)-related advanced liver fibrosis (Stage 3 or 4) was reported to be linked to worse prognosis in patients with heart failure with preserved ejection fraction (HFpEF). This study aims to assess the relationship between liver fibrosis scores and new-onset atrial fibrillation (AF) incidence in patients with HFpEF in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) trial.

METHODS AND RESULTS

Baseline liver fibrosis levels, assessed by NAFLD fibrosis score (NFS) or Fibrosis-4 index (FIB-4), with AF incidence were expressed as hazard ratios (HRs) using the Cox proportional hazard model. The risk for advanced fibrosis was estimated to be 21.5% (447/2072) as assessed by FIB-4 (>3.25) and 4.2% (88/2072) as assessed by NFS (>0.676) in HFpEF patients without baseline AF. After a median follow-up of 3.11 years, 106 new-onset AF cases occurred. In multivariate analysis, elevated NFS [NFS = -1.455-0.676: HR 2.44, 95% confidence interval (CI) 1.27-4.68; NFS > 0.676: HR 3.36, 95% CI 1.27-6.80; per 1 unit increase: HR 1.15, 95% CI 1.01-1.32], not FIB-4 (FIB-4 = 1.45-3.25: HR 1.02, 95% CI 0.67-1.55; FIB-4 > 3.25: HR 1.69, 95% CI 0.76-3.79; per 1 unit increase: HR 1.13, 95% CI 0.93-1.37), was associated with increased AF incidence. The NFS (C-index 0.662), not FIB-4 (C-index 0.531), had a moderate predictive ability in predicting incident AF.

CONCLUSIONS

Among patients with HFpEF, the risk of advanced liver fibrosis is associated with an increased incidence of new-onset AF and may be a novel predictor for new-onset AF. Additional studies are needed to confirm our results.

The Usefulness of the C2HEST Risk Score in Predicting Clinical Outcomes among Hospitalized Subjects with COVID-19 and Coronary Artery Disease

Background: Even though coronary artery disease (CAD) is considered an independent risk factor of an unfavorable outcome of SARS-CoV-2-infection, the clinical course of COVID-19 in subjects with CAD is heterogeneous, ranging from clinically asymptomatic to fatal cases. Since the individual C₂HEST components are similar to the COVID-19 risk factors, we evaluated its predictive value in CAD subjects. Materials and Methods: In total, 2183 patients hospitalized due to confirmed COVID-19 were enrolled onto this study consecutively. Based on past medical history, subjects were assigned to one of two of the study arms (CAD vs. non-CAD) and allocated to different risk strata, based on the C₂HEST score. Results: The CAD cohort included 228 subjects, while the non-CAD cohort consisted of 1956 patients. In-hospital, 3-month and 6-month mortality was highest in the high-risk C₂HEST stratum in the CAD cohort, reaching 43.06%, 56.25% and 65.89%, respectively, whereas in the non-CAD cohort in the high-risk stratum, it reached: 26.92%, 50.77% and 64.55%. Significant differences in mortality between the C₂HEST stratum in the CAD arm were observed in post hoc analysis only for medium- vs. high-risk strata. The C₂HEST score in the CAD cohort could predict hypovolemic shock, pneumonia and acute heart failure during hospitalization, whereas in the non-CAD cohort, it could predict cardiovascular events (myocardial injury, acute heart failure, myocardial infract, carcinogenic shock), pneumonia, acute liver dysfunction and renal injury as well as bleedings. Conclusions: The C₂HEST score is a simple, easy-to-apply tool which might be useful in risk stratification, preferably in non-CAD subjects admitted to hospital due to COVID-19.

Usefulness of C2HEST Score in Predicting Clinical Outcomes of COVID-19 in Heart Failure and Non-Heart-Failure Cohorts

Background: Patients with heart failure represent a vulnerable population for COVID-19 and are prone to having worse prognoses and higher fatality rates. Still, the clinical course of the infection is dynamic, and complication occurrence in particular in patients with heart failure is fairly unpredictable. Considering that individual components of the C2HEST (C2: Coronary Artery Diseases (CAD)/Chronic obstructive pulmonary disease (COPD); H: Hypertension; E: Elderly (Age ≥ 75); S: Systolic HF; T: Thyroid disease) are parallel to COVID-19 mortality risk factors, we evaluate the predictive value of C2HEST score in patients with heart failure (HF) Material and Methods: The retrospective medical data analysis of 2184 COVID-19 patients hospitalized in the University Hospital in Wroclaw between February 2020 and June 2021 was the basis of the study. The measured outcomes included: in-hospital mortality, 3-month and 6-month all-cause-mortality, non-fatal end of hospitalization, and adverse in-hospital clinical events. Results: The heart failure cohort consists of 255 patients, while 1929 patients were assigned to the non-HF cohort. The in-hospital, 3-month, and 6-month mortality rates were highest in the HF cohort high-risk C2HEST stratum, reaching 38.61%, 53.96%, and 65.36%, respectively. In the non-HF cohort, in-hospital, 3-month, and 6-month mortalities were also highest in the high-risk C2HEST stratum and came to 26.39%, 52.78%, and 65.0%, respectively. An additional point in the C2HEST score increased the total death intensity in 10% of HF subjects (HR 1.100, 95% CI 0.968−1.250 p = 0.143) while in the non-HF cohort, the same value increased by 62.3% (HR 1.623, 95% CI 1.518−1.734 p < 0.0001). Conclusions: The C2HEST score risk in the HF cohort failed to show discriminatory performance in terms of mortality and other clinical adverse outcomes during hospitalization. C2HEST score in the non-HF cohort showed significantly better performance in terms of predicting in-hospital and 6-month mortality and other non-fatal clinical outcomes such as cardiovascular events (myocardial injury, acute heart failure, myocardial infarction, cardiogenic shock), pneumonia, sepsis, and acute renal injury.

Mimicking Metabolic Disturbance in Establishing Animal Models of Heart Failure With Preserved Ejection Fraction

Heart failure (HF), the terminal state of different heart diseases, imposed a significant health care burden worldwide. It is the last battlefield in dealing with cardiovascular diseases. HF with preserved ejection fraction (HFpEF) is a type of HF in which the symptoms and signs of HF are mainly ascribed to diastolic dysfunction of left ventricle, whereas systolic function is normal or near-normal. Compared to HF with reduced ejection fraction (HFrEF), the diagnosis and treatment of HFpEF have made limited progress, partly due to the lack of suitable animal models for translational studies in the past. Given metabolic disturbance and inflammatory burden contribute to HFpEF pathogenesis, recent years have witnessed emerging studies focusing on construction of animal models with HFpEF phenotype by mimicking metabolic disorders. These models prefer to recapitulate the metabolic disorders and endothelial dysfunction, leading to the more detailed understanding of the entity. In this review, we summarize the currently available animal models of HFpEF with metabolic disorders, as well as their advantages and disadvantages as tools for translational studies.

Validation of Risk Scores for Predicting Atrial Fibrillation Detected After Stroke Based on an Electronic Medical Record Algorithm: A Registry-Claims-Electronic Medical Record Linked Data Study

Background

Poststroke atrial fibrillation (AF) screening aids decisions regarding the optimal secondary prevention strategies in patients with acute ischemic stroke (AIS). We used an electronic medical record (EMR) algorithm to identify AF in a cohort of AIS patients, which were used to validate eight risk scores for predicting AF detected after stroke (AFDAS).

Methods

We used linked data between a hospital stroke registry and a deidentified database including EMRs and administrative claims data. EMR algorithms were constructed to identify AF using diagnostic and medication codes as well as free clinical text. Based on the optimal EMR algorithm, the incidence rate of AFDAS was estimated. The predictive performance of 8 risk scores including AS5F, C₂HEST, CHADS₂, CHA₂DS₂-VASc, CHASE-LESS, HATCH, HAVOC, and Re-CHARGE-AF scores, were compared using the C-index, net reclassification improvement, integrated discrimination improvement, calibration curve, and decision curve analysis.

Results

The algorithm that defines AF as any positive mention of AF-related keywords in electrocardiography or echocardiography reports, or presence of diagnostic codes of AF was used to identify AF. Among the 5,412 AIS patients without known AF at stroke admission, the incidence rate of AFDAS was 84.5 per 1,000 person-year. The CHASE-LESS and AS5F scores were well calibrated and showed comparable C-indices (0.741 versus 0.730, p = 0.223), which were significantly higher than the other risk scores.

Conclusion

The CHASE-LESS and AS5F scores demonstrated adequate discrimination and calibration for predicting AFDAS. Both simple risk scores may help select patients for intensive AF monitoring.

Mortality Predictive Value of the C2HEST Score in Elderly Subjects with COVID-19-A Subanalysis of the COLOS Study

Senility has been identified among the strongest risk predictors for unfavorable COVID-19-outcome. However, even in the elderly population, the clinical course of infection in individual patients remains unpredictable. Hence, there is an urgent need for developing a simple tool predicting adverse COVID-19-outcomes. We assumed that the C2HEST-score could predict unfavorable clinical outcomes in the elderly subjects with COVID-19-subjects. Methods: We retrospectively analyzed 1047 medical records of patients at age > 65 years, hospitalized at the medical university center due to COVID-19. Subsequently, patients were divided into three categories depending on their C2HEST-score result. Results: We noticed significant differences in the in-hospital and 3-month and 6-month mortality-which was the highest in high-risk-C2HEST-stratum reaching 35.7%, 54.4%, and 65.9%, respectively. The medium-risk-stratum mortalities reached 24.1% 43.4%, and 57.6% and for low-risk-stratum 14.4%, 25.8%, and 39.2% respectively. In the C2HEST-score model, a change from the low to the medium category increased the probability of death intensity approximately two-times. Subsequently, transfer from the low-risk to the high-risk-stratum raised all-cause-death-intensity 2.7-times. Analysis of the secondary outcomes revealed that the C2HEST-score has predictive value for acute kidney injury, acute heart failure, and cardiogenic shock. Conclusions: C2HEST-score analysis on admission to the hospital may predict the mortality, acute kidney injury, and acute heart failure in elderly subjects with COVID-19.

C2HEST score for atrial fibrillation risk prediction models: a Diagnostic Accuracy Tests meta-analysis

BACKGROUND

This meta-analysis aimed to assess the value of the C₂HEST score to facilitate population screening and detection of AF risk in millions of populations and validate risk scores and their composition and discriminatory power for identifying people at high or low risk of AF. We searched major indexing databases, including Pubmed/Medline, ISI web of science, Scopus, Embase, and Cochrane central, using ("C2HEST" OR "risk scoring system" OR "risk score") AND ("atrial fibrillation (AF)" OR "atrial flutter" OR "tachycardia, supraventricular" OR "heart atrium flutter") without any language, study region or study type restrictions between 1990 and 2021 years. Analyses were done using Meta-DiSc. The title and abstract screening were conducted by two independent investigators.

RESULTS

Totally 679 records were found through the initial search, of which ultimately, nine articles were included in the qualitative and quantitative analyses. The risk of AF accompanied every one-point increase of C₂HEST score (OR 1.03, 95% CI 1.01-1.05, p < 0.00001), with a high heterogeneity across studies (I² = 100%). The SROC for C₂HEST score in the prediction of AF showed that the overall area under the curve (AUC) was 0.91 (95% CI 0.85-0.96), AUC in Asian population was 0.87 (95% CI: 0.78-0.95) versus non-Asian 0.95 (95% CI 0.91-0.99), and in general population was 0.92 (95% CI 0.85-0.99) versus those with chronic conditions 0.83 (95% CI 0.71-0.95), respectively.

CONCLUSIONS

The results of this research support the idea that this quick score has the opportunity for use as a risk assessment in patients' AF screening strategies.

Association of Chronic Obstructive Pulmonary Disease With Arrhythmia Risks: A Systematic Review and Meta-Analysis

Background: A large number of studies have shown that the arrhythmia risks may be the potential causes of death among chronic obstructive pulmonary disease (COPD) patients. However, the association of COPD with risks of arrhythmias has never been systematically reviewed. Therefore, we performed a meta-analysis to assess the relationship between COPD and arrhythmia risks.

Methods: An updated systematic retrieval was carried out within the databases of Embase and PubMed until June 27, 2021.The random-effects model was used to pool studies due to the potential heterogeneity across the included studies. The risk ratios (RRs) with 95% confidence intervals (CIs) were regarded as effect estimates.

Results: A total of 21 studies were included in our meta-analysis. In the pooled analysis by the random-effects model, the results showed that COPD was significantly related to the risk of atrial fibrillation (AF) (RR = 1.99, 95% CI: 1.46–2.70), ventricular arrhythmias (VA) (RR = 2.01, 95% CI: 1.42–2.85), and sudden cardiac death (SCD) (RR = 1.68, 95% CI: 1.28–2.21). The corresponding results were not changed after exclusion one study at a time. The pooled results were also stable when we re-performed the analysis using the fixed-effects model.

Conclusions: Our current data suggested that COPD was associated with increased risks of AF, VA, and SCD.

Refining age stratum of the C2HEST score for predicting incident atrial fibrillation in a hospital-based Chinese population

BACKGROUND

The C₂HEST score (C₂: coronary artery disease [CAD] / chronic obstructive pulmonary disease [COPD] (1 point each); H: Hypertension; E: Elderly (Age≥75, doubled); S: Systolic heart failure (doubled); T: Thyroid disease (hyperthyroidism)) has been validated to predict incident atrial fibrillation (AF). Its performance in the hospital-based Chinese population has never been evaluated.

METHODS

Risk factors for incident AF were investigated in a hospital-based population. Comparison of the C₂HEST score and other clinical scores with the capacity of predicting incident AF was conducted using area under the curves (AUC), net reclassification index (NRI), integrated discriminative improvement (IDI), and decision curve analysis (DCA). An age-stratified criterion was used to refine the C₂HEST score to form a modified C₂HEST score (mC₂HEST). The performance of the mC₂HEST score was also evaluated.

RESULTS

A total of 23,523 patients entered the study with 520 developed AF during 2.84 ± 3.56 years of follow-up. Risk factors for incident AF included age, male sex, hypertension, CAD, COPD, previous ischemic stroke, hyperthyroidism, and heart failure. Age ≥65 years has significantly increased the risk of AF, which was considered as the age cutoff for a modified C₂HEST score (mC₂HEST). The risk of AF increased by 89% per one-point increase of the mC₂HEST score. The mC₂HEST score showed better predictive performance (AUC of 0.809) compared with the original C₂HEST (AUC of 0.752), CHA₂DS₂-VASc (0.756), HATCH (0.722), and HAVOC (0.758) scores, also as estimated by IDI, NRI and DCA. Among those enrolled after 2012, the mC₂HEST score had numerically higher AUC (0.849) compared with the C₂HEST score (0.826) and the other scores.

CONCLUSION

In a hospital-based Chinese population, by refining the age strata of the original C₂HEST score, the mC₂HEST score had significantly increased predictive accuracy and discriminative capability for incident AF. The clinical benefits of the application of novel mC₂HEST score needs further validation in multiple settings.