Derivation and validation of a disease-specific risk score for cardiac risk stratification in chronic kidney disease

Prognostic models for chronic kidney disease: a systematic review and external validation

BACKGROUND

Accurate risk prediction is needed in order to provide personalized healthcare for chronic kidney disease (CKD) patients. An overload of prognosis studies is being published, ranging from individual biomarker studies to full prediction studies. We aim to systematically appraise published prognosis studies investigating multiple biomarkers and their role in risk predictions. Our primary objective was to investigate if the prognostic models that are reported in the literature were of sufficient quality and to externally validate them.

METHODS

We undertook a systematic review and appraised the quality of studies reporting multivariable prognosis models for end-stage renal disease (ESRD), cardiovascular (CV) events and mortality in CKD patients. We subsequently externally validated these models in a randomized trial that included patients from a broad CKD population.

RESULTS

We identified 91 papers describing 36 multivariable models for prognosis of ESRD, 50 for CV events, 46 for mortality and 17 for a composite outcome. Most studies were deemed of moderate quality. Moreover, they often adopted different definitions for the primary outcome and rarely reported full model equations (21% of the included studies). External validation was performed in the Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of Nurse Practitioners trial (n = 788, with 160 events for ESRD, 79 for CV and 102 for mortality). The 24 models that reported full model equations showed a great variability in their performance, although calibration remained fairly adequate for most models, except when predicting mortality (calibration slope >1.5).

CONCLUSIONS

This review shows that there is an abundance of multivariable prognosis models for the CKD population. Most studies were considered of moderate quality, and they were reported and analysed in such a manner that their results cannot directly be used in follow-up research or in clinical practice.

Cardiac Imaging for Coronary Heart Disease Risk Stratification in Chronic Kidney Disease

Chronic kidney disease (CKD), defined as dysfunction of the glomerular filtration apparatus, is an independent risk factor for the development of coronary artery disease (CAD). Patients with CKD are at a substantially higher risk of cardiovascular mortality compared with the age- and sex-adjusted general population with normal kidney function. The risk of CAD and mortality in patients with CKD is correlated with the degree of renal dysfunction including presence of microalbuminuria. A greater cardiovascular risk, albeit lower than for patients receiving dialysis, persists even after kidney transplantation. Congestive heart failure, commonly caused by CAD, also accounts for a significant portion of the cardiovascular-related events observed in CKD. The optimal strategy for the evaluation of CAD in patients with CKD, particularly before renal transplantation, remains a topic of contention spanning over several decades. Although the evaluation of coexisting cardiac disease in patients with CKD is desirable, severe renal dysfunction limits the use of radiographic and magnetic resonance contrast agents due to concerns regarding contrast-induced nephropathy and nephrogenic systemic sclerosis, respectively. In addition, many patients with CKD have extensive and premature (often medial) calcification disproportionate to the severity of obstructive CAD, thereby limiting the diagnostic value of computed tomography angiography. As such, echocardiography, non-contrast-enhanced magnetic resonance, nuclear myocardial perfusion, and metabolic imaging offer a variety of approaches to assess obstructive CAD and cardiomyopathy of advanced CKD without the need for nephrotoxic contrast agents.

Obesity and the risk of cardiovascular and all-cause mortality in chronic kidney disease: a systematic review and meta-analysis

Background

Obesity is a risk factor for cardiovascular disease and death in people without chronic kidney disease (CKD), but the effect of obesity in people with CKD is uncertain.

Methods

Medline and Embase (from inception to January 2015) were searched for cohort studies measuring obesity by body mass index (BMI), waist:hip ratio (WHR) and/or waist circumference (WC) and all-cause and cardiovascular mortality or events in patients with any stage of CKD. Data were summarized using random effects models. Meta-regression was conducted to assess sources of heterogeneity.

Results

Of 4065 potentially eligible citations, 165 studies ( n = 1 534 845 participants) were analyzed. In studies that found a nonlinear relationship, underweight people with CKD (3-5) on hemodialysis experienced an increased risk of death compared with those with normal weight. In transplant recipients, excess risk was observed at levels of morbid obesity (>35 kg/m 2 ). Of studies that found the relationship to be linear, a 1 kg/m 2 increase in BMI was associated with a 3 and 4% reduction in all-cause and cardiovascular mortality in patients on hemodialysis, respectively {adjusted hazard ratio [HR] 0.97 [95% confidence interval (CI) 0.96-0.98] and adjusted HR 0.96 (95% CI 0.92-1.00)}. In CKD Stages 3-5, for every 1 kg/m 2 increase in BMI there was a 1% reduction in all-cause mortality [HR 0.99 (95% CI 0.0.97-1.00)]. There was no apparent association between obesity and mortality in transplanted patients or those on peritoneal dialysis. Sparse data for WHR and WC did not allow further analyses.

Conclusions

Being obese may be protective for all-cause mortality in the predialysis and hemodialysis populations, while being underweight suggests increased risk, but not in transplant recipients.

A clinical-genetic approach to assessing cardiovascular risk in patients with CKD

Background

Coronary heart disease (CHD) is the primary cause of death in individuals with chronic kidney disease (CKD), but current equations for assessing coronary risk have low accuracy in this group. We have reported that the addition of a genetic risk score (GRS) to the Framingham risk function improved its predictive capacity in the general population. The aims of this study were to evaluate the association between this GRS and coronary events in the CKD population and to determine whether the addition of the GRS to coronary risk prediction functions improves the estimation of coronary risk at the earliest possible stages of kidney disease.

Methods

A total of 632 CKD patients, aged 35–74 years, who had Stage 4–5 CKD, were on dialysis, had a functioning renal transplant or had returned to dialysis after transplant failure were included and followed up for a mean of 9.3 years. The transitions between disease states and the development of coronary events were registered. The increase in predictive ability that was obtained by including the GRS was measured as the improvement in the C-statistic and as the net reclassification index.

Results

The GRS was independently associated with the risk of CHD (hazards ratio 1.34; 95% confidence interval 1.04–1.71; P = 0.022), especially in Stages 4 and 5 CKD, and kidney transplant patients. A coronary risk prediction function that incorporated chronic kidney disease (CKD) disease state, age, sex and the GRS had significantly greater predictive capacity (AUC 70.1, P = 0.01) and showed good reclassification (net reclassification improvement 28.6).

Conclusion

This new function, combining genetic and clinical data, identifies CKD patients with a high risk of coronary events more accurately, allowing us to prevent such events more effectively.

Do clinical symptoms and signs predict reduced renal function among hospitalized adults?

BACKGROUND

Reduced renal function manifests as reduced glomerular filtration rate (GFR), which is estimated using the serum creatinine levels. This condition is frequently encountered among hospitalized adults. Renal dysfunction remains clinically asymptomatic, until late in the course of disease, and its symptoms and screening strategies are poorly defined.

AIM

We conducted this study to understand if the presence of renal dysfunction related clinical symptom and signs (either alone or in combination) can predict reduced GFR. Further, we aimed to determine if the combination of symptoms and signs are useful for prediction of different levels of reduced GFR.

SUBJECTS AND METHODS

We performed a cross-sectional clinical prediction study and included all consecutive patients admitted to the medical wards of the hospital. We used a renal dysfunction related clinical predictors as index tests and low estimated GFR ([eGFR] < 60 ml/min/1.73 m(2)) as a reference standard. We identified symptoms with a high likelihood ratio (LR) for prediction of low eGFR and constructed different risk score models. We plotted receiver operating curves for each score and used area under the curve (AUC) for comparison. The score with the highest AUC was considered as most discriminant. All statistical analysis was performed using the statistical software STATA (version 11.0, lake drive, Texas, USA).

RESULTS

A total of 341 patients participated in the study. None of the predictor variables had statistically significant LRs for eGFR less than 60 ml/min or eGFR less than 30 ml/min. Positive LRs were significant for prediction of eGFR < 15 ml/min for the presence of hypertension, vomiting pruritis, peripheral edema, hyperpigmentation, peripheral neuropathy and severe anemia. The best predictive model for eGFR less than 15 ml/min/1.73 m(2), included Age > 45 years, the presence of hypertension, vomiting, peripheral edema, hyperpigmentation, and severe anemia and had AUC of 0.82.

CONCLUSION

Clinical symptoms and signs are poorly predictive of reduced renal function, except for very low eGFR of less than 15 ml/min/1.73 m(2).

Panoptic total cardiovascular risk prediction using all predictors versus optimized risk assessment using variable subsets

Cardiovascular disease remains the primary cause of mortality and morbidity in the developed world. Risk scores can provide clinical risk stratification and many exist for use in cardiovascular disease prevention and treatment. Cardiovascular risk scores predict mortality, coronary heart disease and other vascular disease using risk predictors such as patient age, sex, BMI, smoking history, cholesterol level, blood pressure, glucose level or diabetes diagnosis, family history of cardiovascular disease and creatinine. While the risk scores in existence are excellent for risk stratification, actual use in a clinical environment is lagging behind the rate of new risk score creation. Future research should focus on how to utilize risk scores most effectively and efficiently in clinical practice.

Screening for cardiovascular disease in patients with advanced chronic kidney disease

Cardiovascular disease remains the major cause of mortality and morbidity in patients with advanced chronic kidney disease (CKD) and after renal transplantation. The mechanisms for cardiotoxicity are multiple. Identifying high-risk patients remains a challenge. Given, the poor long-term outcome of dialysis patients who do not receive renal transplantation and the lower supply of donor kidneys relative to demand, optimal selection of renal transplantation candidates is crucial. This requires a clear understanding of the validity of cardiac tests in this patient group. This paper explores the strengths and weaknesses of currently available diagnostic tools in patients with advanced CKD. Echocardiography is very useful for the detection of cardiomyopathy and prognosis. Stress echocardiography, myocardial perfusion imaging and coronary angiography are the best tools for the assessment of coronary artery disease. All predict outcome. No single gold standard investigation exists. At present, there is not an optimal technique for predicting sudden cardiac death in this patient group. Ultimately, the choice of cardiac test will always be determined by patient preference, local expertise and availability.

The diagnostic and prognostic value of tissue Doppler imaging during dobutamine stress echocardiography in end-stage renal disease

OBJECTIVE

To determine whether a quantitative measurement of peak systolic velocity (PSV) during dobutamine stress echocardiography (DSE) detects severe coronary artery disease (CAD) and predicts mortality in patients with end-stage renal disease.

METHODS

One hundred and forty renal transplant candidates had DSE and coronary angiography. DSE analysis was performed using conventional visual wall motion assessment, longitudinal PSV, and combining the two modalities. Failure of PSV to rise by more than 50% predicted an ischemic response. Significant CAD was defined as luminal stenosis greater than 70%.

RESULTS

The number of positive DSE studies according to conventional, PSV, and combined criteria was 41 (30%), 42 (31%), and 46 (34%) respectively. Forty patients (29%) had significant CAD at angiography. The sensitivity, specificity, positive and negative predictive values for conventional DSE analysis were 84, 91, 86, and 90% respectively. The same values for PSV analysis were 86, 92, 86, and 91%, respectively. The same values for the combination of visual and PSV analysis were 88, 94, 87, and 92% respectively. The differences between the three methods were not statistically significant. Sensitivity for single-vessel CAD (P=0.05) and circumflex artery disease (P=0.05) diagnosis was higher with PSV compared with conventional DSE analysis. Failure of PSV to rise by more than 50% during DSE was associated with significantly increased mortality (P=0.001).

CONCLUSION

A quantitative interpretation of DSE, based on the percentage rise of PSV during stress, accurately detects CAD and predicts prognosis in end-stage renal disease.

Risk stratification of patients with chronic kidney disease: results of screening strategies incorporating clinical risk scoring and dobutamine stress echocardiography

BACKGROUND

Cardiac disease is the principal cause of death in patients with chronic kidney disease (CKD). Ischemia at dobutamine stress echocardiography (DSE) is associated with adverse events in these patients. We sought the efficacy of combining clinical risk evaluation with DSE.

METHODS

We allocated 244 patients with CKD (mean age 54 years, 140 men, 169 dialysis-dependent at baseline) into low- and high-risk groups based on two disease-specific scores and the Framingham risk model. All underwent DSE and were further stratified according to DSE results. Patients were followed over 20 +/- 14 months for events (death, myocardial infarction, acute coronary syndrome).

RESULTS

There were 49 deaths and 32 cardiac events. Using the different clinical scores, allocation of high risk varied from 34% to 79% of patients, and 39% to 50% of high-risk patients had an abnormal DSE. In the high-risk groups, depending on the clinical score chosen, 25% to 44% with an abnormal DSE had a cardiac event, compared with 8% to 22% with a normal DSE. Cardiac events occurred in 2.0%, 3.1%, and 9.7% of the low-risk patients, using the two disease-specific and Framingham scores, respectively, and DSE results did not add to risk evaluation in this subgroup. Independent DSE predictors of cardiac events were a lower resting diastolic blood pressure, angina during the test, and the combination of ischemia with resting left ventricular dysfunction.

CONCLUSION

In CKD patients, high-risk findings by DSE can predict outcome. A stepwise strategy of combining clinical risk scores with DSE for CAD screening in CKD reduces the number of tests required and identifies a high-risk subgroup among whom DSE results more effectively stratify high and low risk.