Blood kidney injury molecule-1 predicts short and longer term kidney outcomes in patients undergoing diagnostic coronary and/or peripheral angiography-Results from the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) study.

BACKGROUND: Kidney injury is common in patients with cardiovascular disease. OBJECTIVES: We determined whether blood measurement of kidney injury molecule-1 (KIM-1), would predict kidney outcomes in patients undergoing angiographic procedures for various indications. METHODS: One thousand two hundred eight patients undergoing coronary and/or peripheral angiography were prospectively enrolled; blood was collected for KIM-1 measurement. Peri-procedural acute kidney injury (AKI) was defined as AKI within 48 hours of contrast exposure. Non-procedural AKI was defined as AKI beyond 48 hours. Development of chronic kidney disease (CKD) was defined as progression to an estimated glomerular filtration rate (eGFR) <60 milliliters/minute/1.73 m2 by study conclusion. Univariate and multivariable Cox proportional hazards models were used to identify predictors of non-procedural AKI, while univariate and multivariable logistic regression analysis was used to evaluate peri-procedural AKI and predictors of progression to CKD. RESULTS: During mean follow up of 4 years, peri-procedural AKI occurred in 5.0%, non-procedural AKI in 27.3%, and 12.4% developed new reduction in eGFR <60 mL/min/1.73 m2. Higher KIM-1 concentrations were associated with prevalent comorbidities associated with risk in cardiovascular disease and worse left ventricular function. In adjusted analyses, elevated pre- and post-procedural KIM-1 concentrations predicted not only peri-procedural AKI (odds ratio [OR] 1.54, 95% confidence interval [CI] 1.09-2·18, P = .01 and OR 1.54, 95% CI 1.10-2.15, P = .01, respectively) and non-procedural AKI (hazard ratio [HR] 1·49, 95% CI 1·24-1·78, P < .001 and HR 1.46, 95% CI 1.23-1.74, P < .001, respectively), but also progression to CKD (OR 1.99, 95% CI 1.32-2.99, P = .001 and OR 2·02, 95% CI 1·35-3·03, P = .001, respectively). CONCLUSIONS: In a typical at-risk population undergoing coronary and/or peripheral angiography, blood concentrations of KIM-1 may predict incident peri-procedural and non-procedural AKI, as well as progression to CKD.

Incident Type 2 Myocardial Infarction in a Cohort of Patients Undergoing Coronary or Peripheral Arterial Angiography.

BACKGROUND: Despite growing recognition of type 2 myocardial infarction (T2MI; related to supply/demand mismatch), little is known about its risk factors or its association with outcome. METHODS: A single-center cohort of patients undergoing coronary or peripheral angiography with or without intervention was prospectively enrolled and followed for incident type 1 and T2MI, and major adverse cardiovascular events (MACE, a composite of all-cause death, nonfatal myocardial infarction [MI], heart failure, stroke, transient ischemic attack, peripheral arterial complication, and cardiac arrhythmia), as well. T2MI was adjudicated using criteria from the Third Universal Definition of MI. Baseline characteristics, blood samples, and angiography information were obtained. Major end points subsequent to first MI were assessed using landmark analyses to compare the rates of first events only where everyone with a prior history of any MACE before MI were censored and adjusted for follow-up times. Cox proportional hazard models were used for time-to-event analyses with age and sex forced into all models and additional covariates evaluated by using the stepwise option for the selection. RESULTS: One thousand two hundred fifty-one patients were enrolled and followed for a median of 3.4 years. Of these patients, 152 (12.2%) had T2MI during follow-up; T2MI was frequently recurrent. Multivariable predictors of T2MI were older age, lower systolic blood pressure, history of coronary artery disease, heart failure, chronic obstructive pulmonary disease, diabetes mellitus, nitrate use, and elevated concentrations of glucose, N-terminal pro-B type natriuretic peptide, and cystatin C. Patients with T2MI had higher rates of subsequent adverse events than those without T2MI (per 100 person-years: MACE, 53.7 versus 21.1, P<0.001; all-cause death, 23.3 versus 3.3, P<0.001; cardiovascular death, 17.5 versus 2.6, P<0.001; heart failure events, 22.4 versus 7.4, P<0.001); these rates are similar to those seen in patients with type 1 MI. Incident diagnosis of T2MI strongly predicted risk for subsequent MACE (adjusted hazard ratio, 1.90; 95% confidence interval, 1.46-2.48; P<0.001), all-cause death (adjusted hazard ratio, 2.96; 95% confidence interval, 2.01-4.36; P<0.001), and cardiovascular death (adjusted hazard ratio, 2.16; 95% confidence interval, 1.36-3.43; P=0.001). CONCLUSIONS: T2MI is common and associated with poor prognosis. Studies evaluating treatment strategies for management of T2MI are needed. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00842868.

Predicting new-onset HF in patients undergoing coronary or peripheral angiography: results from the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) study.

AIMS: Methods to identify patients at risk for incident HF would be welcome as such patients might benefit from earlier interventions. METHODS AND RESULTS: From a registry of 1251 patients referred for coronary and/or peripheral angiography, we sought to identify independent predictors of incident HF during follow-up and develop a clinical and biomarker strategy to predict this outcome. There were 991 patients free of prevalent HF at baseline. Cox proportional hazard models were developed to predict adjudicated diagnosis of incident HF. Model discrimination and reclassification were evaluated. At follow-up, 177 (18%) developed new-onset HF. Independent predictors of new-onset HF included five clinical variables (age, male sex, heart rate, history of atrial fibrillation/flutter, and history of hypertension) and two biomarkers (amino-terminal pro-B type natriuretic peptide and ST2). The c-statistic for the model without biomarkers was 0.69; including biomarkers increased the c-statistic to 0.76 (P < 0.001). A score was developed from the model. Patients in the highest score quintile had shortest time to incident HF compared with lower quintiles (log-rank P < 0.001). Following 100 bootstrap iterations, internal validation was confirmed with Harrell's c-statistic of 0.77. Use of angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and beta-blockers at enrollment was associated with substantial attenuation of predictive value of the risk score. CONCLUSIONS: Patients undergoing coronary/peripheral angiographic procedures are a population at high risk for incident HF. We describe an accurate clinical and biomarker strategy for predicting incident HF and possibly intervening in such patients (NCT00842868).

A clinical and proteomics approach to predict the presence of obstructive peripheral arterial disease: From the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) Study.

BACKGROUND: Peripheral arterial disease (PAD) is a global health problem that is frequently underdiagnosed and undertreated. Noninvasive tools to predict the presence and severity of PAD have limitations including inaccuracy, cost, or need for intravenous contrast and ionizing radiation. HYPOTHESIS: A clinical/biomarker score may offer an attractive alternative diagnostic method for PAD. METHODS: In a prospective cohort of 354 patients referred for diagnostic peripheral and/or coronary angiography, predictors of ≥50% stenosis in ≥1 peripheral vessel (carotid/subclavian, renal, or lower extremity arteries) were identified from >50 clinical variables and 109 biomarkers. Machine learning identified variables predictive of obstructive PAD; a score derived from the final model was developed. RESULTS: The score consisted of 1 clinical variable (history of hypertension) and 6 biomarkers (midkine, kidney injury molecule-1, interleukin-23, follicle-stimulating hormone, angiopoietin-1, and eotaxin-1). The model had an in-sample area under the receiver operating characteristic curve of 0.85 for obstructive PAD and a cross-validated area under the curve of 0.84; higher scores were associated with greater severity of angiographic stenosis. At optimal cutoff, the score had 65% sensitivity, 88% specificity, 76% positive predictive value (PPV), and 81% negative predictive value (NPV) for obstructive PAD and performed consistently across vascular territories. Partitioning the score into 5 levels resulted in a PPV of 86% and NPV of 98% in the highest and lowest levels, respectively. Elevated score was associated with shorter time to revascularization during 4.3 years of follow-up. CONCLUSIONS: A clinical/biomarker score demonstrates high accuracy for predicting the presence of PAD.

Single-Molecule Counting of High-Sensitivity Troponin I in Patients Referred for Diagnostic Angiography: Results From the CASABLANCA (Catheter Sampled Blood Archive in Cardiovascular Diseases) Study.

BACKGROUND: The meaning of high-sensitivity troponin I (hsTnI) concentrations in patients without acute myocardial infarction (MI) requires clarity. We hypothesized that among patients referred for diagnostic coronary angiography without acute MI, hsTnI concentrations would correlate with prevalent coronary artery disease (CAD) and predict incident cardiovascular events and mortality. METHODS AND RESULTS: We measured hsTnI using a single-molecule counting assay (99th percentile, 6 ng/L) in samples from 991 patients obtained at the time of angiography. Concentrations of hsTnI were assessed relative to the severity of CAD and prognosis during mean follow-up of 3.7 years. Median hsTnI concentration was 4.19 ng/L; 38% of patients had hsTnI concentrations ≥99th percentile. Across increasing hsTnI quartiles, patients had higher prevalence of angiographic CAD; in multivariate models, hsTnI ≥99th percentile independently predicted obstructive CAD (odds ratio: 2.57; P<0.001) and incident MI (hazard ratio [HR]: 2.68; P<0.001), cardiovascular death (HR: 2.29; P=0.001), and all-cause death (HR: 1.84; P=0.004). In those with >70% coronary stenosis, hsTnI ≥99th percentile independently predicted incident MI (HR: 1.87; P=0.01), cardiovascular mortality (HR: 2.74; P=0.001), and the composite end point of MI and all-cause death (HR: 2.06; P<0.001). In participants with coronary stenosis <70%, hsTnI ≥99th percentile even more strongly predicted incident MI (HR: 8.41; P<0.001), cardiovascular mortality (HR: 3.60; P=0.03), and the composite end point of MI and all-cause death (HR: 3.62; P<0.001). CONCLUSIONS: In a large prospective cohort of patients who were free of prevalent MI and undergoing diagnostic coronary angiography, hsTnI concentrations were associated with higher prevalence of CAD and predicted incident MI, cardiovascular death, and all-cause death. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00842868.

A Clinical and Biomarker Scoring System to Predict the Presence of Obstructive Coronary Artery Disease.

BACKGROUND: Noninvasive models to predict the presence of coronary artery disease (CAD) may help reduce the societal burden of CAD. OBJECTIVES: From a prospective registry of patients referred for coronary angiography, the goal of this study was to develop a clinical and biomarker score to predict the presence of significant CAD. METHODS: In a training cohort of 649 subjects, predictors of ≥70% stenosis in at least 1 major coronary vessel were identified from >200 candidate variables, including 109 biomarkers. The final model was then validated in a separate cohort (n = 278). RESULTS: The scoring system consisted of clinical variables (male sex and previous percutaneous coronary intervention) and 4 biomarkers (midkine, adiponectin, apolipoprotein C-I, and kidney injury molecule-1). In the training cohort, elevated scores were predictive of ≥70% stenosis in all subjects (odds ratio [OR]: 9.74; p < 0.001), men (OR: 7.88; p <0.001), women (OR: 24.8; p < 0.001), and those with no previous CAD (OR: 8.67; p < 0.001). In the validation cohort, the score had an area under the receiver-operating characteristic curve of 0.87 (p < 0.001) for coronary stenosis ≥70%. Higher scores were associated with greater severity of angiographic stenosis. At optimal cutoff, the score had 77% sensitivity, 84% specificity, and a positive predictive value of 90% for ≥70% stenosis. Partitioning the score into 5 levels allowed for identifying or excluding CAD with >90% predictive value in 42% of subjects. An elevated score predicted incident acute myocardial infarction during 3.6 years of follow up (hazard ratio: 2.39; p < 0.001). CONCLUSIONS: We described a clinical and biomarker score with high accuracy for predicting the presence of anatomically significant CAD. (The CASABLANCA Study: Catheter Sampled Blood Archive in Cardiovascular Diseases; NCT00842868).

Usefulness of Multiple Biomarkers for Predicting Incident Major Adverse Cardiac Events in Patients Who Underwent Diagnostic Coronary Angiography (from the Catheter Sampled Blood Archive in Cardiovascular Diseases [CASABLANCA] Study).

We sought to develop a multiple biomarker approach for prediction of incident major adverse cardiac events (MACE; composite of cardiovascular death, myocardial infarction, and stroke) in patients referred for coronary angiography. In a 649-participant training cohort, predictors of MACE within 1 year were identified using least-angle regression; over 50 clinical variables and 109 biomarkers were analyzed. Predictive models were generated using least absolute shrinkage and selection operator with logistic regression. A score derived from the final model was developed and evaluated with a 278-patient validation set during a median of 3.6 years follow-up. The scoring system consisted of N-terminal pro B-type natriuretic peptide (NT-proBNP), kidney injury molecule-1, osteopontin, and tissue inhibitor of metalloproteinase-1; no clinical variables were retained in the predictive model. In the validation cohort, each biomarker improved model discrimination or calibration for MACE; the final model had an area under the curve (AUC) of 0.79 (p <0.001), higher than AUC for clinical variables alone (0.75). In net reclassification improvement analyses, addition of other markers to NT-proBNP resulted in significant improvement (net reclassification improvement 0.45; p = 0.008). At the optimal score cutoff, we found 64% sensitivity, 76% specificity, 28% positive predictive value, and 93% negative predictive value for 1-year MACE. Time-to-first MACE was shorter in those with an elevated score (p <0.001); such risk extended to at least to 4 years. In conclusion, in a cohort of patients who underwent coronary angiography, we describe a novel multiple biomarker score for incident MACE within 1 year (NCT00842868).