Cystatin C as a predictor of cardiovascular outcomes in a hypertensive population

Mortality Prediction in Patients With Breast Cancer by Artificial Neural Network Model and Elastic Net Regression

BACKGROUND

Breast cancer (BC) is the most common cancer in women, and it is important to identify models that can accurately predict mortality in patients with this cancer. The aim of the present study was to use the elastic net regression and artificial neural network (ANN) models in diagnosing and predicting factors affecting BC mortality. Study Design: A cross-sectional study.

METHODS

The data of 2,836 people with BC during 2014-2018 were analyzed in this study. Information was registered in the cancer registration system of Kerman University of Medical Sciences. Death status was considered the dependent variable, while age, morphology, tumor differentiation, residence status, and residence place were regarded as independent variables. Sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), precision, and F1-score were used to compare the models.

RESULTS

Based on the test set, the elastic net regression determined factors affecting BC mortality (with sensitivity of 0.631, specificity of 0.814, AUC of 0.629, accuracy of 0.792, precision of 0.318, and F1-score of 0.42) and ANN did so (with sensitivity of 0.66, specificity of 0.748, AUC of 0.704, accuracy of 0.738, precision of 0.265, and F1-score of 0.37).

CONCLUSION

The sensitivity and AUC of the ANN model were higher than those of the elastic net regression, but the specificity, accuracy, precision, and F1-score of the elastic net were higher than those of the ANN. According to the purpose of the study, two models can be used simultaneously. Based on the results of models, morphology, tumor differentiation, and age had a greater effect on death.

Evaluating the Prognostic Significance of Cystatin C Level Variations Pre- and Post-Radiofrequency Catheter Ablation in the Recurrence of Persistent Atrial Fibrillation

OBJECTIVE

To investigate the correlation between persistent atrial fibrillation (AF) recurrence and alterations in cystatin C levels pre- and post-radiofrequency catheter ablation (RFCA).

METHODS

This study encompassed 114 patients diagnosed with persistent AF. Their serum cystatin C levels were assessed both prior to and 3 months after undergoing an RFCA procedure. The variance in cystatin C levels before and after RFCA is represented as ΔCystatin C. Subsequently, we compared these values between two groups: patients who did not experience a recurrence of AF (n = 79) and those who did experience a recurrence (n = 35).

RESULTS

A significant reduction in cystatin C levels post-RFCA in both groups, with a more pronounced decrease observed in the non-recurrence group. Moreover, the recurrence group exhibited larger left atrial diameter and volume before RFCA compared to the non-recurrence group. Cox regression analysis indicated that smaller reductions in serum cystatin C levels and greater left atrial volumes before RFCA were associated with an increased risk of recurrence, after adjusting for covariates. The receiver operating characteristic curve indicated an elevated probability of clinical recurrence of AF post-RFCA in patients with a cystatin C decline < 0.08 mg/L (AUC 0.64). The Kaplan-Meier survival analysis revealed that patients with a cystatin C decline > 0.08 mg/L exhibited significantly higher rates of remaining free from recurrence following RFCA across a 24-month follow-up period (Log-rank test p = 0.003).

CONCLUSIONS

Alterations in ΔCystatin C levels pre and post-RFCA in the initial phase could independently predict the recurrence of AF.

Correlation Between Cystatin C and the Severity of Cardiac Dysfunction in Patients with Systolic Heart Failure

Introduction

To investigate the relationship between cystatin C and cardiac dysfunction severity in patients with systolic heart failure.

Methods

We recruited 100 hospitalized patients with systolic heart failure and 100 age-gender-matched controls. The clinical information of each patient was collected. Blood pressure, heart rate, height, and weight were measured, as were serum concentrations of cholesterol, renal function indices, cystatin C, and B-type natriuretic peptide (BNP). Transthoracic echocardiography was performed on each patient.

Results

Cystatin C and other indices of renal function, such as urea nitrogen, creatinine, and uric acid, were significantly elevated in the serum of patients with heart failure and those with more severe cardiac dysfunction. The stepwise regression analyses showed that cystatin C was positively associated with BNP (β = 0.18, P = 0.04, 95% CI: 21.1 ~ 1420.4) and left atrial diameter (LAD) (β = 0.19, P = 0.04, 95% CI: 0.03 ~ 9.21) and was negatively associated with ejection fraction (β = -0.22, P = 0.023, 95% CI: -12.4 ~ -0.93), while creatinine was only positively correlated with BNP (β = 0.23, P = 0.03, 95% CI: 1.11 ~ 20.7). The Receiver Operating Characteristic (ROC) curves demonstrated significantly more severe cardiac dysfunction (NYHA III/IV) in patients with cystatin C ≥ 0.895mg/L (sensitivity was 83.0%, specificity was 80.9%, AUC = 0.893) and creatinine ≥ 91.5μmol/L (sensitivity was 71.7%, specificity was 70.2%, AUC = 0.764).

Conclusion

Cystatin C was significantly correlated with cardiac structure and function in patients with systolic heart failure, and it was more valuable than creatinine to evaluate the severity of heart failure.

Association of serum cystatin C level with coronary atherosclerotic plaque burden: a comprehensive analysis of observational studies and genetic study

BACKGROUND AND AIMS

Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. However, the relationship between serum cystatin C level and coronary atherosclerotic plaque burden is limited. We aimed to evaluate the relationship between circulating cystatin C and coronary atherosclerotic plaque burden.

METHODS

This study was a cross-sectional study based on China community population. Measurements of plaque burden were based on the segment-involvement score (SIS) and segment stenosis score (SSS), which derived from the Coronary Artery Tree Model Depicting Coronary Artery Plaque Scores. Logistic regression model was used to demonstrate the association between cystatin C level and coronary artery plaque burden. Mendelian randomization (MR) analyses were conducted to assess the causal effect of cystatin C level on coronary atherosclerosis risk.

RESULTS

A total of 3,043 objects were included in the present study. The odds risks (OR) of severe plaque burden in the highest serum cystatin C levels (OR: 2.50; Cl:1.59-3.91; P < 0.001) and medium-level cystatin C levels (OR: 1.86; 95% Cl: 1.21-2.88; P = 0.005) were significantly higher after fulled adjusted confounders compared with the lowest levels of serum cystatin C by SSS. The MR analysis showed that genetic predicted cystatin C levels was associated with an increased risk of coronary atherosclerosis (OR, 1.004; 95% CI, 1.002-1.006, P < 0.001) .

CONCLUSION

Elevated serum cystatin C levels were associated with coronary atherosclerotic plaque burden. Cystatin C levels had a causal effect on an increased risk of coronary atherosclerosis at the genetic level. WHAT IS ALREADY KNOWN ON THIS TOPIC?: Coronary artery disease is currently the most common cardiovascular disease and the leading global cause of mortality. Previous studies reported that higher serum cystatin C levels were associated with an increased risk for future cardiovascular events, independent of the normal creatinine levels or estimated glomerular filtration rate (eGFR) values. The presence of high-risk coronary atherosclerotic plaque burden is associated with increased risk of cardiovascular events. However, the association between serum cystatin C and coronary atherosclerotic plaque burden is not very clear. WHAT THIS STUDY ADDS?: Our study demonstrated that the elevated serum cystatin C levels were associated with coronary atherosclerotic plaque burden. In addition, we found that serum cystatin C levels had a causal effect on an increased risk of coronary atherosclerosis at the genetic level. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY?: Current research finds that serum cystatin C levels were associated with coronary atherosclerosis. The metabolic pathway of cystatin C could be a target for new therapies against CAD.

Serum cystatin C and CRP are early predictive biomarkers for emergence of hypoxia in COVID-19

BACKGROUND

In Japan, during the coronavirus disease 2019 (COVID-19) pandemic, patients with non-hypoxia are recommended to recuperate at home or in pre-hospital facilities. However, it was observed that unexpected hypoxia may occur and become severe subsequently in patients whose symptoms were initially expected to improve naturally. The aim of this study is to validate biomarkers that can predict at an early stage the emergence of hypoxia in COVID-19 patients without hypoxia.

METHODS

We retrospectively enrolled 193 patients with COVID-19, excluding patients with hypoxia and severe disease from the onset. Participants were classified into two groups according to the emergence of hypoxia during the clinical course, and the laboratory data were compared to identify biomarkers that could predict early the emergence of hypoxia.

RESULTS

The areas under the curve for serum cystatin C (CysC) and C-reactive protein (CRP) levels for the emergence of hypoxia during the clinical course were higher than those for other biomarkers (CysC, 0.84 and CRP, 0.83). Multivariate analysis showed that high serum CysC and CRP levels were associated with the emergence of hypoxia during the clinical course.

CONCLUSIONS

Elevated serum CysC and CRP levels were associated with the emergence of hypoxia during the clinical course in COVID-19 patients without hypoxia. These findings may help determine the need for hospitalization in initially non-hypoxic COVID-19 patients.

Serum cystatin C is associated with the prognosis in acute myocardial infarction patients after coronary revascularization: a systematic review and meta-analysis

Objective

Our study aimed to assess the association between serum cystatin C levels and prognosis in acute myocardial infarction (AMI) patients after coronary reconstructive surgery.

Methods

We searched PubMed, Embase, and Cochrane Library up to January 21, 2022 without language restriction. Outcomes were major cardiovascular events (MACEs) and mortality. The risk ratio (RR) and 95% confidence interval (CI) were merged by random-effect models.

Results

We included 8 studies with a total of 7,394 subjects in our meta-analysis. Our meta-analysis showed that higher-level of serum cystatin C levels were associated with higher risk of MACEs (RR = 2.52, 95% CI 1.63–3.89, P < 0.001) and mortality (RR = 2.64, 95% CI 1.66–4.19, P < 0.001) in AMI patients after coronary revascularization. Subgroup analysis showed that the serum cystatin C levels were associated with significantly higher risk of MACEs (RR = 2.72, 95% CI 1.32–5.60, P = 0.006) and mortality (RR = 2.98, 95% CI 1.21–7.37, P = 0.020) in AMI patients after percutaneous coronary intervention (PCI). However, in AMI patients after coronary artery bypass surgery, there were no significantly higher risk of MACEs (RR = 2.41, 95% CI 0.98–5.93, P = 0.05) and mortality (RR = 3.15, 95% CI 0.76–13.03, P = 0.10). Further subgroup analysis showed that this significantly higher risk of MACEs and mortality did not change with the study sample size, study population area or study follow-up time.

Conclusion

The meta-analysis demonstrated that higher serum cystatin C levels were associated with significantly higher risk of MACEs and mortality in AMI patients after PCI. It is a biomarker for risk stratification for predicting the prognosis in AMI patients after PCI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02599-5.

JohnMagnusPaulShawJohnCollinsRoryHuntDavidThomsonAndrewHarrisPhillipSullivanDavidSharpeNormanMeierPaulJanusEdwardWestMalcolmBarterPhilipKritharidesLeonardWatsonJohnBeilinLawrenceHankeyGraemeHobbsMichaelThompsonPeterWattsGeraldColquhounDavid. Circulating Cystatin C Is an Independent Risk Marker for Cardiovascular Outcomes, Development of Renal Impairment, and Long-Term Mortality in Patients With Stable Coronary Heart Disease: The LIPID Study

Background

Elevated plasma cystatin C levels reflect reduced renal function and increased cardiovascular risk. Less is known about whether the increased risk persists long‐term or is independent of renal function and other important biomarkers.

Methods and Results

Cystatin C and other biomarkers were measured at baseline (in 7863 patients) and 1 year later (in 6106 patients) in participants in the LIPID (Long‐Term Intervention with Pravastatin in Ischemic Disease) study, who had a previous acute coronary syndrome. Outcomes were ascertained during the study (median follow‐up, 6 years) and long‐term (median follow‐up, 16 years). Glomerular filtration rate (GFR) was estimated using Chronic Kidney Disease Epidemiology Collaboration equations (first GFR‐creatinine, then GFR‐creatinine‐cystatin C). Over 6 years, in fully adjusted multivariable time‐to‐event models, with respect to the primary end point of coronary heart disease mortality or nonfatal myocardial infarction, for comparison of Quartile 4 versus 1 of baseline cystatin C, the hazard ratio was 1.37 (95% CI, 1.07–1.74; P=0.01), and for major cardiovascular events was 1.47 (95% CI, 1.19–1.82; P<0.001). Over 16 years, the association of baseline cystatin C with coronary heart disease, cardiovascular, and all‐cause mortality persisted (each P<0.001) and remained significant after adjustment for estimated GFR‐creatinine‐cystatin C. Cystatin C also predicted the development of chronic kidney disease for 6 years (odds ratio, 6.61; 95% CI, 4.28–10.20) independently of estimated GFR‐creatinine and other risk factors. However, this association was no longer significant after adjustment for estimated GFR‐creatinine‐cystatin C.

Conclusions

Cystatin C independently predicted major cardiovascular events, development of chronic kidney disease, and cardiovascular and all‐cause mortality. Prediction of long‐term mortality was independent of improved estimation of GFR.

Registration

URL: https://anzctr.org.au; Unique identifier: ACTRN12616000535471.

Cystatin C predicts the risk of incident cerebrovascular disease in the elderly: A meta-analysis on survival date studies

BACKGROUND

Stroke is the third leading cause of global year of life lost in all-age and second-ranked cause of disability adjusted life years in middle-aged and elder population. Therefore, it is critical to study the relationship between vascular-related risk factors and cerebrovascular diseases. Several cross-sectional studies have shown that Cystatin C (Cys C) is an independent risk factor for cerebrovascular diseases and levels of Cys C are significantly higher in stroke patients than in healthy individuals. In this meta-analysis, we introduce a Cox proportional hazards model to evaluate the causality between Cys C and the risk of cerebrovascular accident in the elderly.

METHODS

We searched PubMed, EMBASE, the Web of Science, and the Cochrane Library from 1985 to 2019 for studies on the relationship between serum Cys C and incidence stroke with Cox proportional hazards models. We conducted a subgroup analysis of the selected studies to determine a connection between atherosclerosis and stroke. Finally, 7 research studies, including 26,768 patients without a history of cerebrovascular, were studied.

RESULTS

After comparing the maximum and minimum Cys C levels, the hazard ratio for all types of stroke, including ischemic and hemorrhagic stroke, was 1.18 (95% confidence interval 1.04-1.31) with moderate heterogeneity (I2 = 43.0%; P = .119) in a fixed-effect model after pooled adjustment for other potential risk factors. In the subgroup analysis, the hazard ratio and 95% confidence interval for Cys C stratified by atherosclerosis was 1.85 (0.97-2.72). As shown in Egger linear regression test, there was no distinct publication bias (P = .153).

CONCLUSION

Increased serum Cys C is significantly associated with future stroke events in the elderly, especially in patients with carotid atherosclerosis. Thus, serum levels of Cys C could serve as a predicted biomarker for stroke attack.

Cystatin C-Based Renal Function in Predicting the Long-Term Outcomes of Chronic Total Occlusion After Percutaneous Coronary Intervention

Renal function estimated by various biomarkers predicting for adverse cardiovascular events has not been well-identified in received percutaneous coronary intervention (PCI) for chronic total occlusion (CTO), the advanced stages of atherosclerosis. We aim to determine whether the serum cystatin C-based-estimated glomerular filtration rate (eGFR) can have an improved predictive value in patients with CTO lesions undergoing PCI as compared with multiple creatinine-based estimates of kidney function. Six hundred and seventy-one patients received CTO PCI were retrospectively included in the study. The eGFR was calculated by modification of diet in renal disease equation for Chinese (cMDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations at baseline, respectively. Then, the cohort was categorized into three groups according to standard KDIGO kidney stages based on eGFR. The primary endpoint was all-cause mortality, and the secondary endpoint was cardiac death. Strikingly, cystatin C-based eGFR showed a better performance with the greater area being under the receiver operating characteristic (ROC) curve (0.73 for all-cause mortality and 0.73 for cardiac death, separately) and a better assessment for survival free from adverse event across renal levels among four eGFR equations. Compared with eGFR calculated by other formulas, serum cystatin C-based eGFR showed the highest prognostic value for both all-cause mortality (adjusted HR 3.6, 95% CI 1.6-8.1, P = 0.002) and cardiac death (adjusted HR 2.9, 95% CI 1.0-8.1, P = 0.028). Moreover, cystatin C-based eGFR significantly improved the risk reclassification of event with a high value of net reclassification improvement and integrated discrimination improvement. This study may prove that cystatin C-based eGFR is a better predictor of both all-cause mortality and cardiac death than other equations in populations with CTO undergoing PCI.

Identification of clinically relevant features in hypertensive patients using penalized regression: a case study of cardiovascular events

Appropriate management of hypertensive patients relies on the accurate identification of clinically relevant features. However, traditional statistical methods may ignore important information in datasets or overlook possible interactions among features. Machine learning may improve the prediction accuracy and interpretability of regression models by identifying the most relevant features in hypertensive patients. We sought the most relevant features for prediction of cardiovascular (CV) events in a hypertensive population. We used the penalized regression models least absolute shrinkage and selection operator (LASSO) and elastic net (EN) to obtain the most parsimonious and accurate models. The clinical parameters and laboratory biomarkers were collected from the clinical records of 1,471 patients receiving care at Mostoles University Hospital. The outcome was the development of major adverse CV events. Cox proportional hazards regression was performed alone and with penalized regression analyses (LASSO and EN), producing three models. The modeling was performed using 10-fold cross-validation to fit the penalized models. The three predictive models were compared and statistically analyzed to assess their classification accuracy, sensitivity, specificity, discriminative power, and calibration accuracy. The standard Cox model identified five relevant features, while LASSO and EN identified only three (age, LDL cholesterol, and kidney function). The accuracies of the models (prediction vs. observation) were 0.767 (Cox model), 0.754 (LASSO), and 0.764 (EN), and the areas under the curve were 0.694, 0.670, and 0.673, respectively. However, pairwise comparison of performance yielded no statistically significant differences. All three calibration curves showed close agreement between the predicted and observed probabilities of the development of a CV event. Although the performance was similar for all three models, both penalized regression analyses produced models with good fit and fewer features than the Cox regression predictive model but with the same accuracy. This case study of predictive models using penalized regression analyses shows that penalized regularization techniques can provide predictive models for CV risk assessment that are parsimonious, highly interpretable, and generalizable and that have good fit. For clinicians, a parsimonious model can be useful where available data are limited, as such a model can offer a simple but efficient way to model the impact of the different features on the prediction of CV events. Management of these features may lower the risk for a CV event. Graphical Abstract In a clinical setting, with numerous biological and laboratory features and incomplete datasets, traditional statistical methods may ignore important information and overlook possible interactions among features. Our aim was to identify the most relevant features to predict cardiovascular events in a hypertensive population, using three different regression approaches for feature selection, to improve the prediction accuracy and interpretability of regression models by identifying the relevant features in these patients.

Cardiovascular risk assessment in prediabetic patients in a hypertensive population: The role of cystatin C

BACKGROUND

The aim of our study was to determine whether prediabetes increases cardiovascular (CV) risk compared to the non-prediabetic patients in our hypertensive population. Once this was achieved, the objective was to identify relevant CV prognostic features among prediabetic individuals.

METHODS

We included hypertensive 1652 patients. The primary outcome was a composite of incident CV events: cardiovascular death, stroke, heart failure and myocardial infarction. We performed a Cox proportional hazard regression to assess the CV risk of prediabetic patients compared to non-prediabetic and to produce a survival model in the prediabetic cohort.

RESULTS

The risk of developing a CV event was higher in the prediabetic cohort than in the non-prediabetic cohort, with a hazard ratio (HR) = 1.61, 95% CI 1.01-2.54, p = 0.04. Our Cox proportional hazard model selected age (HR = 1.04, 95% CI 1.02-1.07, p < 0.001) and cystatin C (HR = 2.4, 95% CI 1.26-4.22, p = 0.01) as the most relevant prognostic features in our prediabetic patients.

CONCLUSIONS

Prediabetes was associated with an increased risk of CV events, when compared with the non-prediabetic patients. Age and cystatin C were found as significant risk factors for CV events in the prediabetic cohort.

Novel Biomarkers to Detect Target Organ Damage in Acute Hypertension

PURPOSE OF REVIEW

Early lowering of blood pressure is advised for patients with severe hypertension associated with signs of impending or progressive organ damage, whereas aggressive treatment is not recommended in patients with asymptomatic severe hypertension. As treatment goals for asymptomatic hypertension and true hypertensive emergency drastically differ, it is essential to identify patients with evidence of impending or progressive organ damage. Biomarkers may assist providers in identifying high-risk patients who would benefit from early blood pressure reduction.

RECENT FINDINGS

In this review, we discuss both currently available and investigational biomarkers that may help identify patients who might benefit from more aggressive therapy. We focus on serum and urinary biomarkers associated with acute cardiovascular, renal, and cerebrovascular damage. There is a dearth of literature regarding the use of biomarkers to assess acute hypertension-related target organ damage. We are primarily forced to draw conclusions on the use of biomarkers from studies of related conditions such as acute heart failure. Further research is needed on the clinical significance of abnormal levels of novel biomarkers of renal, cardiac, and cerebral dysfunction in the setting of severe hypertension, particularly in those patients without overt clinical signs of organ failure.