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Objective: The Intermountain Risk Score (IMRS) was evaluated for validation as a mortality predictor and compared with the American Heart Association's Get With The Guidelines-Heart Failure (GWTG-HF) risk score in a rural heart failure (HF) population., Background: IMRS predicts mortality in general populations using common, inexpensive laboratory tests, patient age and sex, but requires validation in patients with HF., Methods: Individuals were selected from the GWTG-HF registry at Essentia Health. This included consecutive HF inpatients age ≥18 years admitted July 2017-June 2019. IMRS was calculated using sex-specific weightings of the complete blood count, basic metabolic profile, and age., Results: A total of 703 individuals (mean age: 74.12, 44.38% female) were studied. The 30-day IMRS predicted 30-day mortality for both sexes (females n=312: OR=1.19 (95% CI 1.08 to 1.32) per +1, p<0.001; males n=391: OR=1.23 (CI 1.12 to 1.36) per +1, p<0.001). The GWTG-HF risk score (only available in n=300, 42.7%) was independent of IMRS for 30-day mortality (OR=1.11 (CI 1.06 to 1.16) per +1, p<0.001). Using thresholds in bivariate modelling, IMRS (high vs low risk, OR=8.25 (CI 2.19 to 31.09), p=0.002) and the GWTG-HF score (tertile 3 vs 1: OR=2.18 (CI 0.84 to 5.68), p=0.11) independently predicted mortality. In multivariable analyses including covariables, IMRS (high vs low risk: OR=6.69 (CI 1.75 to 25.60), p=0.005) and the GWTG-HF score (tertile 3 vs 1: OR=2.62 (CI 0.96 to 7.12), p=0.06) remained predictors of mortality. Results were similar for 1-year mortality., Conclusions: The IMRS and GWTG-HF scores predicted mortality of patients with HF in a large rural healthcare system. Future study of these scores as initial clinical risk estimators for evaluating their utility in improving patient health outcomes and increasing cost effectiveness is warranted., Competing Interests: Competing interests: BDH is an inventor of clinical decision tools that are licensed to CareCentra and Alluceo, the PI of grants involving clinical decision tools that were funded by the Intermountain Research and Medical Foundation, CareCentra, GlaxoSmithKline, and AstraZeneca, a member of the scientific advisory board of Labme.ai, and a co-investigator on a grant funded by the Patient-Centered Outcomes Research Institute (PCORI). The authors declare that no other conflicts of interest or disclosures exist., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: High CHA 2 DS 2 -VASc scores in atrial fibrillation (AF) patients are generally associated with increased risks of stroke and dementia. At lower CHA 2 DS 2 -VASc scores, there remains an unquantifiable cranial injury risk, necessitating an improved risk assessment method within these lower-risk groups., Objective: The purpose of this study was to determine whether sex-specific Intermountain Mortality Risk Scores (IMRS), a dynamic measures of systemic health that comprises commonly performed blood tests, can stratify dementia risk overall and among CHA 2 DS 2 -VASc score strata in AF patients., Methods: Female (n = 34,083) and male (n = 39,998) AF patients with no history of dementia were studied. CHA 2 DS 2 -VASc scores were assessed at the time of AF diagnosis and were stratified into scores of 0-1, 2, and ≥3. Within each CHA 2 DS 2 -VASc score stratum, patients were further stratified by IMRS categories of low, moderate, and high. Multivariable Cox hazard regression was used to determine dementia risk., Results: High-risk IMRS patients were generally older and had higher rates of hypertension, diabetes, heart failure, and prior stroke. Higher CHA 2 DS 2 -VASc score strata (≥3 vs ≤1: women, hazard ratio [HR] 7.77, 95% confidence interval [CI] 5.94-10.17, P < .001; men: HR 4.75, 95% CI 4.15-5.44, P < .001) and IMRS categories (high vs low: women, HR 3.09, 95% CI 2.71-3.51, P < .001; men, HR 2.70, 95% CI 2.39-3.06, P < .001) were predictive of dementia. When stratified by CHA 2 DS 2 -VASc scores, IMRS further identified risk in each stratum., Conclusion: Both CHA 2 DS 2 -VASc scores and IMRS were independently associated with dementia incidence among AF patients. IMRS further stratified dementia risk among CHA 2 DS 2 -VASc score strata, particularly among those with lower CHA 2 DS 2 -VASc scores., (Copyright © 2018 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Aims: Depression is a risk factor for cardiovascular (CV) diseases, incident CV events, and mortality. Among individuals who experience a CV diagnosis or event, whether a subsequent diagnosis of depression is associated with a greater risk of mortality is unknown. Among patients with existing coronary artery disease (CAD), this study evaluated the association of a subsequent depression diagnosis with all-cause mortality., Methods and Results: Patients (N = 24 137) who had angiographically determined CAD (stenosis ≥70%) were studied. Depression after CAD diagnosis was determined by International Classification of Diseases codes and evaluated as a time-varying covariate predicting mortality in multivariable Cox hazard regression models to control for patients' differing lengths of time between CAD diagnosis and depression diagnosis. A total of 3646 (15%) had a depression diagnosis during follow-up. Compared with those without depression, these patients were significantly younger (64 ± 12 vs. 65 ± 12 years), more often female (37% vs. 24%), diabetic (40% vs. 30%), previously diagnosed with depression (26% vs. 5%), and less likely to present with an myocardial infarction (MI) (28% vs. 36%). Death (mean follow-up: 9.7 ± 6.1 years) occurred in 40% of patients (depression: 50% vs. no depression: 38%, P < 0.0001). After adjustment, post-CAD depression was the strongest predictor of death (HR = 2.00, P < 0.0001). This association persisted among subgroups with no prior depression diagnosis (HR = 2.00, P < 0.0001) and by angiography indication: stable angina (HR = 1.84, P < 0.0001), unstable angina (HR = 2.25, P < 0.0001), and MI (HR = 2.09, P < 0.0001)., Conclusion: A depression diagnosis at any time following CAD diagnosis was associated with a two-fold higher risk of death., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions please email: journals.permissions@oup.com.)

Improving 30-day readmission continues to be problematic for most hospitals. This study reports the creation and validation of sex-specific inpatient (i) heart failure (HF) risk scores using electronic data from the beginning of inpatient care for effective and efficient prediction of 30-day readmission risk., Methods: HF patients hospitalized at Intermountain Healthcare from 2005 to 2012 (derivation: n=6079; validation: n=2663) and Baylor Scott & White Health (North Region) from 2005 to 2013 (validation: n=5162) were studied. Sex-specific iHF scores were derived to predict post-hospitalization 30-day readmission using common HF laboratory measures and age. Risk scores adding social, morbidity, and treatment factors were also evaluated., Results: The iHF model for females utilized potassium, bicarbonate, blood urea nitrogen, red blood cell count, white blood cell count, and mean corpuscular hemoglobin concentration; for males, components were B-type natriuretic peptide, sodium, creatinine, hematocrit, red cell distribution width, and mean platelet volume. Among females, odds ratios (OR) were OR=1.99 for iHF tertile 3 vs. 1 (95% confidence interval [CI]=1.28, 3.08) for Intermountain validation (P-trend across tertiles=0.002) and OR=1.29 (CI=1.01, 1.66) for Baylor patients (P-trend=0.049). Among males, iHF had OR=1.95 (CI=1.33, 2.85) for tertile 3 vs. 1 in Intermountain (P-trend <0.001) and OR=2.03 (CI=1.52, 2.71) in Baylor (P-trend < 0.001). Expanded models using 182-183 variables had predictive abilities similar to iHF., Conclusions: Sex-specific laboratory-based electronic health record-delivered iHF risk scores effectively predicted 30-day readmission among HF patients. Efficient to calculate and deliver to clinicians, recent clinical implementation of iHF scores suggest they are useful and useable for more precise clinical HF treatment., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: The Intermountain Mortality Risk Score (IMRS), a sex-specific mortality-prediction metric, has proven to be effective in various populations. IMRS is comprised of the complete blood count (CBC), basic metabolic panel (BMP), and age. Whether the addition of factors from the comprehensive metabolic panel (CMP) and white blood cell (WBC) differential count improves risk stratification is unknown., Methods: Patients with baseline complete metabolic panel (CMP) and IMRS measurements were randomly assigned (60%/40%) to independent derivation (n=84,913) and validation (n=56,584) populations. A sex-specific risk score based on IMRS methods was computed in the derivation population using adjusted multivariable regression weights from all significant and noncollinear CMP [expanded IMRS (eIMRS)] and, when available, WBC differential components (eIMRS+diff)., Results: Age averaged 67±16 years for females and 67±15 years for males. Receiver operator characteristic (ROC) c-statistics for 30-day death showed marked improvement for the eIMRS compared to the IMRS in both females [0.895 (0.882, 0.908) vs. 0.865 (0.850, 0.880)] and males [0.861 (0.847, 0.876) vs. 0.824 (0.807, 0.841)]. These results persisted for 1-year death: females [0.854 (0.847, 0.862) vs. 0.828 (0.819, 0.836)] and males [0.835 (0.826, 0.844) vs. 0.796 (0.789, 0.808)]. In addition, the eIMRS significantly improved risk reclassification. Further precision was seen when WBC differential components were included., Conclusions: The addition of the CMP components to the IMRS improved risk prediction. WBC differential also improved risk score predictive ability. These results suggest that the eIMRS may function even better than IMRS as a tool in patient care, risk-adjustment, and clinical research settings for predicting outcomes.

Objective: Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients., Methods: Dictated free-text reports from the previous 24 h were analyzed each day with natural language processing (NLP), to help improve the early identification of hospitalized patients with HF. A second application that uses an Intermountain Healthcare-developed predictive score to determine each HF patient's risk for 30-day hospital readmission and 30-day mortality was also developed. That information was included in an identification and predictive risk report, which was evaluated at a 354-bed hospital that treats high-risk HF patients., Results: The addition of NLP-identified HF patients increased the identification score's sensitivity from 82.6% to 95.3% and its specificity from 82.7% to 97.5%, and the model's positive predictive value is 97.45%. Daily multidisciplinary discharge planning meetings are now based on the information provided by the HF identification and predictive report, and clinician's review of potential HF admissions takes less time compared to the previously used manual methodology (10 vs 40 min). An evaluation of the use of the HF predictive report identified a significant reduction in 30-day mortality and a significant increase in patient discharges to home care instead of to a specialized nursing facility., Conclusions: Using clinical decision support to help identify HF patients and automatically calculating their 30-day all-cause readmission and 30-day mortality risks, coupled with a multidisciplinary care process pathway, was found to be an effective process to improve HF patient identification, significantly reduce 30-day mortality, and significantly increase patient discharges to home care., (© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Pulmonary function testing parameters predict cardiovascular and mortality outcomes. Previously, risk scores were created using the basic metabolic profile and complete blood count, including the Intermountain Risk Score (IMRS). This study sought to develop similar pulmonary-specific risk scores for mortality prediction., Methods: Subjects evaluated by spirometry at 5 Intermountain Healthcare hospitals (females: n = 2,943; males: n = 2,495) were randomly assigned to risk score derivation (70% of subjects) or an independent validation set (the remaining 30%). Sex-specific scores used spirometry, age, and metabolic and blood count laboratory data. Cox regression β-coefficients formed the basis of risk score weightings., Results: Among females, pulmonary IMRS was strongly associated with 5-y mortality in the validation set (hazard ratio = 1.24 per +1 risk score, CI 1.16-1.33, P trend < .001), with C-statistics of C = 0.835 and C = 0.757 for derivation and validation, respectively. Among males, validation results were similarly significant (hazard ratio = 1.20 per +1 risk score value, CI 1.11-1.28, P trend < .001), with C = 0.755 and C = 0.699 in derivation and validation sets, respectively. Results were stronger for pulmonary basic metabolic profile risk score, with females having C = 0.815 (derivation) and C = 0.806 (validation), whereas males had C = 0.734 and C = 0.731., Conclusions: Pulmonary-specific IMRS and pulmonary-specific basic metabolic profile risk score provided excellent discrimination of mortality among pulmonary subjects. These risk stratification tools combine familiar, relatively inexpensive, commonly-measured, standardized laboratory parameters with spirometry data. They may be electronically calculated and delivered at the point of care, providing meaningful risk information to assist clinicians in patient evaluations., (Copyright © 2015 by Daedalus Enterprises.)

Background: Chronic kidney disease (CKD) is a common disorder with a variable clinical course and it is associated with increased mortality. The Intermountain Risk Score (IMRS) is an electronic risk calculator that utilizes complete blood count (CBC) and basic metabolic panel (BMP) values to predict mortality in various healthcare populations. We hypothesized that IMRS would predict mortality in patients with CKD even with adjustment for serum phosphate and urinary albumin., Methods: Three thousand eight hundred seventy-two patients with CKD classes IIIA-V had IMRS calculated retrospectively and survival analysis was performed investigating 1- and 5-year mortality. Kaplan-Meier survival curves were generated for predefined IMRS groups of low, medium and high risk for CKD patients overall and by sex and CKD stage. Serum phosphate and urinary albumin/creatinine ratios were modeled in multivariate Cox-proportional hazard models. Receiver operator characteristic curves were used to determine c-statistics for mortality., Results: For all patients with CKD, mortality was significantly greater for those with medium- or high-risk compared to low-risk IMRS categories, among each CKD stage. Overall, IMRS was predictive of mortality at both 1 and 5 years, even when adjusted for CKD stage and predicted mortality more accurately than CKD stage alone. Albuminuria was not independently associated with mortality and serum phosphate weakly predicted mortality., Conclusion: IMRS is a strong predictor of mortality in patients with CKD and is robustly complementary to CKD stage in refining risk prediction. Given the universal availability and low cost of the CBC and BMP, IMRS may be of a substantial value in CKD risk assessment and management., (© 2016 S. Karger AG, Basel.)

Purpose: Intermountain Risk Score (IMRS) uses the admission complete blood count and basic metabolic profile to predict mortality. Intermountain Risk Score has been validated in medical patients but has not been evaluated in trauma. This study tested whether IMRS is predictive of mortality in a trauma population at a level I trauma center., Methods: Admitted trauma patients with complete blood count and basic metabolic profile from October 2005 to December 2011 were evaluated. Thirty-day and 1-year IMRS were calculated using multivariable modeling. Mortality was determined using the medical record and Social Security Administration death data., Results: Three thousand six hundred thirty-seven females and 5901 males were evaluated. Intermountain Risk Score was highly predictive of death at 30 days (c-statistics, c = 0.772 for females; c = 0.783 males) and 1 year (c = 0.778 for females; c = 0.831 males). Cox regression analysis, adjusted for injury severity score, blunt vs penetrating, and length of stay, showed increased mortality risks among patients in the moderate- and high-risk IMRS-defined groups at both 30 days and 1 year, with hazard ratios ranging from 4.96 to 57.88 (all P < .001)., Conclusion: Intermountain Risk Score strongly predicts mortality in trauma patients at this single level I trauma center. The ability to accurately determine a patient's mortality risk at admission makes IMRS a potentially clinically important tool., (Copyright © 2014 Elsevier Inc. All rights reserved.)

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.

The Intermountain Risk Score (IMRS) encapsulates the mortality risk information from all components of the complete blood count (CBC) and basic metabolic profile (BMP), along with age. To individualize the IMRS more clearly, this study evaluated whether IMRS weightings for 1-year mortality predict age-specific survival over more than a decade of follow-up. Sex-specific 1-year IMRS values were calculated for general medical patients with CBC and BMP laboratory tests drawn during 1999-2005. The population was divided randomly 60% (N = 71,921, examination sample) and 40% (N = 47,458, validation sample). Age-specific risk thresholds were established, and both survival and life expectancy were compared across low-, moderate-, and high-risk IMRS categories. During 7.3 ± 1.8 years of follow-up (range, 4.5-11.1 years), the average IMRS of decedents was higher than censored in all age/sex strata (all P < 0.001). For examination and validation samples, every age stratum had incrementally lower survival for higher risk IMRS, with hazard ratios of 2.5-8.5 (P < 0.001). Life expectancies were also significantly shorter for higher risk IMRS (all P < 0.001): For example, among 50-59 year-olds, life expectancy was 7.5, 6.8, and 5.9 years for women with low-, moderate-, and high-risk IMRS (with mortality in 5.7%, 16.3%, and 37.0% of patients, respectively). In Men, life expectancy was 7.3, 6.8, and 5.4 for low-, moderate-, and high-risk IMRS (with patients having 7.3%, 19.5%, and 40.0% mortality), respectively. IMRS significantly stratified survival and life expectancy within age-defined subgroups during more than a decade of follow-up. IMRS may be used to stratify age-specific risk of mortality in research, clinical/preventive, and quality improvement applications. A web calculator is located at http://intermountainhealthcare.org/IMRS., (Copyright © 2011 Mosby, Inc. All rights reserved.)

Aims: The complete blood count (CBC) and basic metabolic profile are common, low-cost blood tests, which have previously been used to create and validate the Intermountain Risk Score (IMRS) for mortality prediction. Mortality is the most definitive clinical endpoint, but medical care is more easily applied to modify morbidity and thereby prevent death. This study tested whether IMRS is associated with clinical morbidity endpoints., Methods and Results: Patients seen for coronary angiography (n = 3927) were evaluated using a design similar to a genome-wide association study. The Bonferroni correction for 102 tests required a P-value of ≤ 4.9 × 10⁻⁴ for significance. A second set of angiography patients (n = 10 413) was used to validate significant findings from the first patient sample. In the first patient sample, IMRS predicted heart failure (HF) (P(trend) = 1.6 × 10(-26)), coronary disease (P(trend) = 2.6 × 10(-11)), myocardial infarction (MI) (P(trend) = 3.1 × 10(-25)), atrial fibrillation (P(trend) = 2.5 × 10(-20)), and chronic obstructive pulmonary disease (P(trend) = 4.7 × 10⁻⁴). Even more, IMRS predicted HF readmission [hazard ratio (HR) = 2.29/category, P(trend) = 1.2 × 10⁻⁶), incident HF (HR = 1.88/category, P(trend) = 0.02), and incident MI (HR = 1.56/category, P(trend) = 4.7 × 10⁻⁴). These findings were verified in the second patient sample., Conclusion: Intermountain Risk Score, a predictor of mortality, was associated with morbidity endpoints that often lead to mortality. Further research is required to fully characterize its clinical utility, but its low-cost CBC and basic metabolic profile composition may make it ideal for initial risk estimation and prevention of morbidity and mortality. An IMRS web calculator is freely available at http://intermountainhealthcare.org/IMRS.

Background: The basic metabolic profile (BMP) is a common blood test containing information about standard blood electrolytes and metabolites. Although individual variables are checked for cardiovascular health and risk, combining them into a total BMP-derived score, as to maximize BMP predictive ability, has not been previously attempted., Methods: Patients (N = 279,337) that received a BMP and had long-term follow-up for death were studied. Risk models were created in a training group (60% of study population, n = 167,635), validated in a test group (40% of study population, n = 111,702), and confirmed in the NHANES III (Third National Health and Nutrition Examination Survey) participants (N = 17,752). The BMP models were developed for 30-day, 1-year, and 5-year death using logistic regression with adjustment for age and sex. The BMP parameters were categorized as low, normal, or high based on the standard range of normal. Glucose was categorized as normal, intermediate, and high. Creatinine >or=2 mg/dL was further categorized as very high., Results: Average age was 53.2 +/- 20.1 years, and 44.3% were male. The areas under the curve for the training and test groups for 30-day, 1-year, and 5-year death were 0.887 and 0.882, 0.850 and 0.848, and 0.858 and 0.847, respectively. The predictive ability of these risk scores was further confirmed in the NHANES III population and independent of the Framingham Risk Score., Conclusion: In large, prospectively followed populations, a highly significant predictive ability for death was found for a BMP risk model. We propose a total BMP score as an optimization of this routine baseline test to provide an important new addition to risk prediction.

A recent European case-control study suggested that statins increase the risk for polyneuropathy, a rare but serious neurologic condition. This risk was assessed in 272 patients with idiopathic polyneuropathy and 1,360 matched controls in the Intermountain Health Care electronic database. It was found that statin use before diagnosis was not significantly greater in patients than controls (odds ratio 1.30, 95% confidence interval 0.3 to 2.1, p = 0.27), nor were doses different between patients and controls.

Purpose: Low socioeconomic status (SES) predicts coronary artery disease (CAD) onset, but its value among patients with CAD is uncertain. Geographic measures (e.g., residential neighborhood) may predict risk, but this requires further evaluation., Methods: A cohort of 3410 patients with significant, angiographically-defined CAD (> or =1 lesion of > or =70% stenosis) joined a registry during the period between 1993 and 2000 and was followed for 6.7 years (median 3.7 years). A geographic SES measure-residential economic status (RES)-and insurance type were examined for association with mortality or myocardial infarction (MI)., Results: In Cox regression adjusting for 17 covariates, lower RES quartile was associated with increased death/MI (p-trend<0.001), death (p-trend=0.001), and MI (p-trend=0.07). First RES quartile (vs. fourth) predicted death/MI (hazard ratio [HR]=1.32, 95% confidence interval [CI]=1.07-1.62, p=0.01) and death (HR=1.46, CI=1.12-1.91, p=0.006), but not MI (HR=1.18, p=0.31). Compared with private insurance, self-pay (HR=1.88, p=0.053), charity care (HR=1.71, p<0.001), and Medicaid (HR=1.43, p=0.24), but not Medicare (HR=0.95, p=0.68), were associated with death/MI., Conclusions: Both geographic (RES) and economic (insurance) measures of SES independently predicted risk of death/MI in a large population with angiographically-defined CAD. This suggests that SES remains a significant predictor of health outcomes after CAD has developed, and that geographic measures of SES deserve further evaluation.

Introduction: CHA2DS2‐VASc and CHADS2 are computationally simple risk prediction tools used to guide anticoagulation decisions for stroke prophylaxis, but they have modest risk discrimination ability and use static dichotomous variables. The Intermountain Mortality Risk Scores (IMRS) are dynamic decision tools using standard clinical laboratory tests. This study derived new stroke prediction scores using variables from both CHA2DS2‐VASc and IMRS. Methods and Results: In outpatients with first atrial fibrillation (AF) diagnosis at the Intermountain Healthcare (females, n = 26 063 males, n = 29 807), sex‐specific "IMRS‐VASc" scores were derived using variables from CHA2DS2‐VASc, warfarin use, the complete blood count, and the comprehensive metabolic profile. Validation was performed in an independent Intermountain outpatient AF cohort (females, n = 11 021; males, n = 12 641). Stroke occurred among 3.1% and 3.1% of females and 2.3% and 2.5% of males in derivation and validation groups, respectively. IMRS‐VASc stratified stroke with similar ability in derivation (c‐statistics, females: c = 0.703, males: c = 0.697) and validation groups (females: c = 0.681, males: c = 0.685). CHA2DS2‐VASc (females: c = 0.581 and c = 0.605; males: c = 0.616 and c = 0.613 in derivation and validation, respectively) and CHADS2 (females: c = 0.581 and c = 0.608; males: c = 0.620 and c = 0.621 in derivation and validation, respectively) were substantially weaker stroke predictors. IMRS was the strongest mortality predictor (females: c = 0.783 and c = 0.782; males: c = 0.796 and c = 0.794 in derivation and validation, respectively) and all scores were poor at predicting bleeding risk. Conclusions: A temporally dynamic risk score, IMRS‐VASc was derived and validated as a predictor of stroke in outpatients with AF. IMRS‐VASc requires further validation and the evaluation of its use in guiding care and treatment decisions for patients with AF. [ABSTRACT FROM AUTHOR]

Background: Chronic kidney disease (CKD) is a common disorder with a variable clinical course and it is associated with increased mortality. The Intermountain Risk Score (IMRS) is an electronic risk calculator that utilizes complete blood count (CBC) and basic metabolic panel (BMP) values to predict mortality in various healthcare populations. We hypothesized that IMRS would predict mortality in patients with CKD even with adjustment for serum phosphate and urinary albumin.Methods: Three thousand eight hundred seventy-two patients with CKD classes IIIA-V had IMRS calculated retrospectively and survival analysis was performed investigating 1- and 5-year mortality. Kaplan-Meier survival curves were generated for predefined IMRS groups of low, medium and high risk for CKD patients overall and by sex and CKD stage. Serum phosphate and urinary albumin/creatinine ratios were modeled in multivariate Cox-proportional hazard models. Receiver operator characteristic curves were used to determine c-statistics for mortality.Results: For all patients with CKD, mortality was significantly greater for those with medium- or high-risk compared to low-risk IMRS categories, among each CKD stage. Overall, IMRS was predictive of mortality at both 1 and 5 years, even when adjusted for CKD stage and predicted mortality more accurately than CKD stage alone. Albuminuria was not independently associated with mortality and serum phosphate weakly predicted mortality.Conclusion: IMRS is a strong predictor of mortality in patients with CKD and is robustly complementary to CKD stage in refining risk prediction. Given the universal availability and low cost of the CBC and BMP, IMRS may be of a substantial value in CKD risk assessment and management. [ABSTRACT FROM AUTHOR]

Abstract: Background: Some components of the complete blood count and basic metabolic profile are commonly used risk predictors. Many of their components are not commonly used, but they might contain independent risk information. This study tested the ability of a risk score combining all components to predict all-cause mortality. Methods: Patients with baseline complete blood count and basic metabolic profile measurements were randomly assigned (60%/40%) to independent training (N = 71,921) and test (N = 47,458) populations. A third population (N = 16,372) from the Third National Health and Nutrition Examination Survey and a fourth population of patients who underwent coronary angiography (N = 2558) were used as additional validation groups. Risk scores were computed in the training population for 30-day, 1-year, and 5-year mortality using age- and sex-adjusted weights from multivariable modeling of all complete blood count and basic metabolic profile components. Results: Area under the curve c-statistics were exceptional in the training population for death at 30 days (c = 0.90 for women, 0.87 for men), 1 year (c = 0.87, 0.83), and 5-years (c = 0.90, 0.85) and in the test population for death at 30 days (c = 0.88 for women, 0.85 for men), 1 year (c = 0.86, 0.82), and 5 years (c = 0.89, 0.83). In the test, the Third National Health and Nutrition Examination Survey, and the angiography populations, risk scores were highly associated with death (P <.001), and thresholds of risk significantly stratified all 3 populations. Conclusion: In large patient and general populations, risk scores combining complete blood count and basic metabolic profile components were highly predictive of death. Easily computed in a clinical laboratory at negligible incremental cost, these risk scores aggregate baseline risk information from both the popular and the underused components of ubiquitous laboratory tests. [Copyright &y& Elsevier]

Background: Variants at the 9p21 locus have been associated with coronary heart disease, but their precise disease phenotype and utility for clinical risk assessment are uncertain. Methods: Consenting patients with early-onset angiographic coronary artery disease (CAD) (n = 1,011) were compared with matched subjects (n = 545) free of angiographic disease and with a random population sample (n = 565). Cases and controls were genotyped for 4 variants, and ORs for angio-CAD were determined. Findings were validated in a separate set of cases and controls (n = 1,452). Results: Alleles were highly correlated (r 2 ≥ 0.9), and all predicted angio-CAD compared with both control groups. Genotype at rs2383206 (minor allele frequency 45.9%), the most predictive (P < .0001), was associated with an adjusted odds ratio for angio-CAD of 1.39 (95% CI, 1.05–1.85) for heterozygote and 1.73 (1.26–2.37) for homozygote risk-allele carriers and explained 21% of population attributable risk and was independent of traditional risk factors and myocardial infarction. For the comparison of combined cases versus combined control samples (N = 3,573), CAD was predicted by high-risk allele homozygosity at P = 9 × 10−8. Despite this, extent of disease was not increased. Applied to patients with intermediate Framingham risk scores, 9p21 genotyping modified risk classification in 24%. Conclusions: Variants at the 9p21 locus robustly predict angiographic CAD prevalence, independent of standard risk factors, but not CAD extent or myocardial infarction; provide pathophysiological insights; and may be clinically useful in refining coronary heart disease risk classification. [Copyright &y& Elsevier]

Background: Diabetes and prediabetic conditions are growing cardiovascular risk factors. Better understanding and earlier recognition and treatment of dysglycemia-related risk are health priorities. We assessed the predictive value of 3 proposed new markers for diabetes and cardiovascular risk. We tested whether the plasma levels of (1) asymmetric dimethylarginine (ADMA), (2) cortisol/cortisone (Cl/Cn) ratio, and (3) C-peptide predicted glycemic status, coronary artery disease, and death or myocardial infarction (MI) in a nested case-control cohort (N = 850) with normal fasting glucose (< 110 mg/dL), impaired fasting glucose (110-125), or diabetic (> or = 126) status.Methods: High-sensitivity C-reactive protein (hsCRP) served as a control risk marker. Follow-up averaged 2.6 +/- 1.4 years. High-pressure liquid chromatography with pre-column derivitization and fluorescence was used to assay ADMA, liquid chromatography/tandem mass spectrometry for Cl and Cn, and chemiluminescent immunoassay for C-peptide.Results: Asymmetric dimethylarginine levels were positively associated with glycemic category (P < .001). Quartiles 2 to 4 ADMA also conferred increased risk of death/MI independent of hsCRP and other risk factors (adjusted hazard ratio, 2.1; P = .002). Cortisol/Cortisone ratios (P = .013) and C-peptide (P = .047) were associated with glycemic categories but less strongly than ADMA. Quartiles 2 to 4 Cl/Cn were protective against incident death/MI (adjusted hazard ratio, 0.48; P < .001), whereas C-peptide did not predict outcomes.Conclusions: Among a high coronary risk case-control cohort, ADMA (strongly), Cl/Cn (moderately), and C-peptide (weakly) predicted glycemic categories. Asymmetric dimethylarginine and Cl/Cn also predicted clinical outcome independent of and more strongly than hsCRP. Asymmetric dimethylarginine and Cl/Cn represent promising new candidate markers of dysglycemia and associated cardiovascular risk. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text. Background: Myocardial perfusion imaging, including positron emission tomography/computed tomography (PET/CT), is often used to assess for high-grade coronary artery disease (CAD) requiring revascularization. The use of coronary artery calcium (CAC) to predict risk of major adverse cardiovascular events in asymptomatic patients is accepted. However, little is known regarding the use of CAC in PET/CT patients without known CAD in identifying patients unlikely to need revascularization. Here, we determined whether the absence of CAC, using low-dose attenuation correction CT obtained during the PET/CT, identifies patients unlikely to undergo coronary revascularization within 90 days of a PET/CT. Methods: Patients, without a history of CAD and no elevation in troponin, referred for PET/CT at Intermountain Medical Center were studied (n=5528). The presence of CAC was visually assessed using low-dose attenuation correction CT. The association between CAC and 90-day high-grade CAD and revascularization were assessed. Longer-term (up to 4 years) major adverse cardiovascular events, including all-cause death, myocardial infarction, and late revascularization (>90 days), were examined. Results: There were 2510 (45.4%) patients in CAC-present group and 3018 (54.6%) patients in CAC-absent group. The CAC-absent group, compared with the CAC-present group, was less likely to undergo coronary angiography (3.4% versus 10.2%, P <0.0001), have high-grade CAD (0.5% versus 6.5%, P <0.0001), and receive revascularization (0.4% versus 5.8%, [adjusted odds ratio =0.09; 95% CI, 0.05–0.16]; P <0.0001). In patients with an ischemic burden >10%, the CAC-absent group was associated with reduced revascularization (P <0.0001). Longer-term major adverse cardiovascular events were lower in the CAC-absent (2.4%) compared with the CAC-present (6.9%) group (adjusted hazard ratio, 0.45 [95% CI, 0.34–0.60]; P <0.0001). Conclusions: The absence of CAC on low-dose attenuation correction CT identifies PET/CT patients unlikely to have high-grade CAD or require revascularization within 90 days and unlikely to experience longer-term major adverse cardiovascular events. The prognostic value of CAC, beyond ischemic burden, suggests its potential as a first-step screening tool in intermediate-risk patients to identify those who do not need coronary revascularization. [ABSTRACT FROM AUTHOR]

To determine whether sex and age affect serum C-reactive protein level and its prognostic value in patients with coronary artery disease.In a consecutive series of 2254 patients with angiographically defined coronary artery disease, baseline C-reactive protein and predictive value for incident death or nonfatal myocardial infarction by sex and age (<55 and ≥55 years) were compared. C-reactive protein levels were measured by fluorescence polarization immunoassay with use of a medium-sensitivity method. Patients were followed for a mean (±SD) of 3.1 ± 2.2 years. Comparisons used ln-transformed C-reactive protein and linear and time-to-event regression analyses, adjusting for confounders.Overall, women had higher geometric mean C-reactive protein levels than did men (1.47 vs. 1.30 mg/dL, P <0.001), even after adjustment for age, hyperlipidemia, diabetes, prior myocardial infarction, body mass index, and heart failure (P = 0.002). High C-reactive protein levels were associated with increased mortality or myocardial infarction among men (adjusted hazard ratio [HR] = 1.9; 95% confidence interval [CI]: 1.5 to 2.3) but not among women (HR = 1.0; 95% CI: 0.69 to 1.4). Among patients aged <55 years, C-reactive protein level was similarly predictive in men and women (HR = 2.2 vs. 2.7), whereas in patients ≥55 years of age, it remained predictive for men (HR = 1.8; 95% CI: 1.5 to 2.3) but not women (HR = 0.93; 95% CI: 0.63 to 1.4).We found that the prognostic value of C-reactive protein in coronary artery disease patients varied by sex and age. This sex-age interaction may have important implications for C-reactive protein–based secondary risk assessment and requires further investigation. [Copyright &y& Elsevier]