Impact of Social Determinants of Health on Predictive Models for Outcomes After Congenital Heart Surgery

BACKGROUND

Despite documented associations between social determinants of health and outcomes post-congenital heart surgery, clinical risk models typically exclude these factors.

OBJECTIVES

The study sought to characterize associations between social determinants and operative and longitudinal mortality as well as assess impacts on risk model performance.

METHODS

Demographic and clinical data were obtained for all congenital heart surgeries (2006-2021) from locally held Congenital Heart Surgery Collaborative for Longitudinal Outcomes and Utilization of Resources Society of Thoracic Surgeons Congenital Heart Surgery Database data. Neighborhood-level American Community Survey and composite sociodemographic measures were linked by zip code. Model prediction, discrimination, and impact on quality assessment were assessed before and after inclusion of social determinants in models based on the 2020 Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model.

RESULTS

Of 14,173 total index operations across New York State, 12,321 cases, representing 10,271 patients at 8 centers, had zip codes for linkage. A total of 327 (2.7%) patients died in the hospital or before 30 days, and 314 children died by December 31, 2021 (total n = 641; 6.2%). Multiple measures of social determinants of health explained as much or more variability in operative and longitudinal mortality than clinical comorbidities or prior cardiac surgery. Inclusion of social determinants minimally improved models' predictive performance (operative: 0.834-0.844; longitudinal 0.808-0.811), but significantly improved model discrimination; 10.0% more survivors and 4.8% more mortalities were appropriately risk classified with inclusion. Wide variation in reclassification was observed by site, resulting in changes in the center performance classification category for 2 of 8 centers.

CONCLUSIONS

Although indiscriminate inclusion of social determinants in clinical risk modeling can conceal inequities, thoughtful consideration can help centers understand their performance across populations and guide efforts to improve health equity.

Identification and validation of a blood- based diagnostic lipidomic signature of pediatric inflammatory bowel disease

Improved biomarkers are needed for pediatric inflammatory bowel disease. Here we identify a diagnostic lipidomic signature for pediatric inflammatory bowel disease by analyzing blood samples from a discovery cohort of incident treatment-naïve pediatric patients and validating findings in an independent inception cohort. The lipidomic signature comprising of only lactosyl ceramide (d18:1/16:0) and phosphatidylcholine (18:0p/22:6) improves the diagnostic prediction compared with high-sensitivity C-reactive protein. Adding high-sensitivity C-reactive protein to the signature does not improve its performance. In patients providing a stool sample, the diagnostic performance of the lipidomic signature and fecal calprotectin, a marker of gastrointestinal inflammation, does not substantially differ. Upon investigation in a third pediatric cohort, the findings of increased lactosyl ceramide (d18:1/16:0) and decreased phosphatidylcholine (18:0p/22:6) absolute concentrations are confirmed. Translation of the lipidomic signature into a scalable diagnostic blood test for pediatric inflammatory bowel disease has the potential to support clinical decision making.

Development of prognostic scoring system for predicting 1-year mortality among pulmonary tuberculosis patients in South India

BACKGROUND

Development of a prediction model using baseline characteristics of tuberculosis (TB) patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring model for predicting the death among newly diagnosed drug sensitive pulmonary TB patients in South India.

METHODS

We undertook a longitudinal analysis of cohort data under the Regional Prospective Observational Research for Tuberculosis India consortium. Multivariable cox regression using the stepwise backward elimination procedure was used to select variables for the model building and the nomogram-scoring system was developed with the final selected model.

RESULTS

In total, 54 (4.6%) out of the 1181 patients had died during the 1-year follow-up period. The TB mortality rate was 0.20 per 1000 person-days. Eight variables (age, gender, functional limitation, anemia, leukopenia, thrombocytopenia, diabetes, neutrophil-lymphocyte ratio) were selected and a nomogram was built using these variables. The discriminatory power was 0.81 (95% confidence interval: 0.75-0.86) and this model was well-calibrated. Decision curve analysis showed that the model is beneficial at a threshold probability ~15-65%.

CONCLUSIONS

This scoring system could help the clinicians and policy makers to devise targeted interventions and in turn reduce the TB mortality in India.

Outcome prediction in large vessel occlusion ischemic stroke with or without endovascular stroke treatment: THRIVE-EVT

INTRODUCTION

The THRIVE score and the THRIVE-c calculation are validated ischemic stroke outcome prediction tools based on patient variables that are readily available at initial presentation. Randomized controlled trials (RCTs) have demonstrated the benefit of endovascular treatment (EVT) for many patients with large vessel occlusion (LVO), and pooled data from these trials allow for adaptation of the THRIVE-c calculation for use in shared clinical decision making regarding EVT.

METHODS

To extend THRIVE-c for use in the context of EVT, we extracted data from the Virtual International Stroke Trials Archive (VISTA) from 7 RCTs of EVT. Models were built in a randomly selected development cohort using logistic regression that included the predictors from THRIVE-c: age, NIH Stroke Scale (NIHSS) score, presence of hypertension, diabetes mellitus, and/or atrial fibrillation, as well as randomization to EVT and, where available, the Alberta Stroke Program Early CT Score (ASPECTS).

RESULTS

Good outcome was achieved in 366/787 (46.5%) of subjects randomized to EVT and in 236/795 (29.7%) of subjects randomized to control (P < 0.001), and the improvement in outcome with EVT was seen across age, NIHSS, and THRIVE-c good outcome prediction. Models to predict outcome using THRIVE elements (age, NIHSS, and comorbidities) together with EVT, with or without ASPECTS, had similar performance by ROC analysis in the development and validation cohorts (THRIVE-EVT ROC area under the curve (AUC) = 0.716 in development, 0.727 in validation, P = 0.30; THRIVE-EVT + ASPECTS ROC AUC = 0.718 in development, 0.735 in validation, P = 0.12).

CONCLUSION

THRIVE-EVT may be used alongside the original THRIVE-c calculation to improve outcome probability estimation for patients with acute ischemic stroke, including patients with or without LVO, and to model the potential improvement in outcomes with EVT for an individual patient based on variables that are available at initial presentation. Online calculators for THRIVE-c estimation are available at www.thrivescore.org and www.mdcalc.com/thrive-score-for-stroke-outcome.

Global Circumferential and Radial Strain Among Patients With Immune Checkpoint Inhibitor Myocarditis

BACKGROUND

Global circumferential strain (GCS) and global radial strain (GRS) are reduced with cytotoxic chemotherapy. There are limited data on the effect of immune checkpoint inhibitor (ICI) myocarditis on GCS and GRS.

OBJECTIVES

This study aimed to detail the role of GCS and GRS in ICI myocarditis.

METHODS

In this retrospective study, GCS and GRS from 75 cases of patients with ICI myocarditis and 50 ICI-treated patients without myocarditis (controls) were compared. Pre-ICI GCS and GRS were available for 12 cases and 50 controls. Measurements were performed in a core laboratory blinded to group and time. Major adverse cardiovascular events (MACEs) were defined as a composite of cardiogenic shock, cardiac arrest, complete heart block, and cardiac death.

RESULTS

Cases and controls were similar in age (66 ± 15 years vs 63 ± 12 years; P = 0.20), sex (male: 73% vs 61%; P = 0.20) and cancer type (P = 0.08). Pre-ICI GCS and GRS were also similar (GCS: 22.6% ± 3.4% vs 23.5% ± 3.8%; P = 0.14; GRS: 45.5% ± 6.2% vs 43.6% ± 8.8%; P = 0.24). Overall, 56% (n = 42) of patients with myocarditis presented with preserved left ventricular ejection fraction (LVEF). GCS and GRS were lower in myocarditis compared with on-ICI controls (GCS: 17.5% ± 4.2% vs 23.6% ± 3.0%; P < 0.001; GRS: 28.6% ± 6.7% vs 47.0% ± 7.4%; P < 0.001). Over a median follow-up of 30 days, 28 cardiovascular events occurred. A GCS (HR: 4.9 [95% CI: 1.6-15.0]; P = 0.005) and GRS (HR: 3.9 [95% CI: 1.4-10.8]; P = 0.008) below the median was associated with an increased event rate. In receiver-operating characteristic (ROC) curves, GCS (AUC: 0.80 [95% CI: 0.70-0.91]) and GRS (AUC: 0.76 [95% CI: 0.64-0.88]) showed better performance than cardiac troponin T (cTnT) (AUC: 0.70 [95% CI: 0.58-0.82]), LVEF (AUC: 0.69 [95% CI: 0.56-0.81]), and age (AUC: 0.54 [95% CI: 0.40-0.68]). Net reclassification index and integrated discrimination improvement demonstrated incremental prognostic utility of GRS over LVEF (P = 0.04) and GCS over cTnT (P = 0.002).

CONCLUSIONS

GCS and GRS are lower in ICI myocarditis, and the magnitude of reduction has prognostic significance.

Retinal vascular measures from diabetes retinal screening photographs and risk of incident dementia in type 2 diabetes: A GoDARTS study

Objective

Patients with diabetes have an increased risk of dementia. Improved prediction of dementia is an important goal in developing future prevention strategies. Diabetic retinopathy screening (DRS) photographs may be a convenient source of imaging biomarkers of brain health. We therefore investigated the association of retinal vascular measures (RVMs) from DRS photographs in patients with type 2 diabetes with dementia risk.

Research Design and Methods

RVMs were obtained from 6,111 patients in the GoDARTS bioresource (635 incident cases) using VAMPIRE software. Their association, independent of Apo E4 genotype and clinical parameters, was determined for incident all cause dementia (ACD) and separately Alzheimer's disease (AD) and vascular dementia (VD). We used Cox's proportional hazards with competing risk of death without dementia. The potential value of RVMs to increase the accuracy of risk prediction was evaluated.

Results

Increased retinal arteriolar fractal dimension associated with increased risk of ACD (csHR 1.17; 1.08-1.26) and AD (HR 1.33; 1.16-1.52), whereas increased venular fractal dimension (FDV) was associated with reduced risk of AD (csHR 0.85; 0.74-0.96). Conversely, FDV was associated with increased risk of VD (csHR 1.22; 1.07-1.40). Wider arteriolar calibre was associated with a reduced risk of ACD (csHR 0.9; 0.83-0.98) and wider venular calibre was associated with a reduced risk of AD (csHR 0.87; 0.78-0.97). Accounting for competing risk did not substantially alter these findings. RVMs significantly increased the accuracy of prediction.

Conclusions

Conventional DRS photographs could enhance stratifying patients with diabetes at increased risk of dementia facilitating the development of future prevention strategies.

Aortic Pulse Wave Velocity as Adjunct Risk Marker for Assessing Cardiovascular Disease Risk: Prospective Study

BACKGROUND

Aortic pulse wave velocity is a noninvasive measure of aortic stiffness and arterial aging. Its current value in cardiovascular risk estimation practice is unknown. We aimed to establish whether aortic pulse wave velocity identified individuals with higher risk of incident major adverse cardiovascular events and improved performance of the American Heart Association/American College of Cardiology atherosclerotic cardiovascular disease risk score.

METHODS

This prospective analysis included 3837 Whitehall II cohort participants screened in 2008 to 2009, and followed for 11.7 years (mean=10.3, SD=1.81), without history of stroke, myocardial infarction, or coronary heart disease.

RESULTS

Mean age of the sample was 65.0 years (SD=5.6), 2831 participants (73.8%) were male and mean atherosclerotic cardiovascular disease risk score was 13.8%. At the end of follow-up, 411 individuals (10.7%) had suffered a major cardiovascular event. Those in the highest aortic pulse wave velocity quartile were at high risk (hazard ratio, 2.99 [95% CI, 2.25-3.97]) and reached the threshold for statin medication (7.5% risk) after 5 years whereas others reached it after 10 years (difference P<0.001). The addition of aortic pulse wave velocity to the risk score improved the C statistic (0.68 versus 0.67, P=0.03) and net reclassification index (4.6%, P=0.04 and 11.3%, P=0.02).

CONCLUSIONS

Our results show that aortic stiffness predicted major adverse cardiovascular events in a cohort of elderly individuals, improving the performance of a widely used cardiovascular disease risk estimator. Aortic pulse wave velocity measurement is scalable, radiation-free, and easy to perform. Further studies on its applicability in cardiovascular disease risk assessment in primary care settings are needed.

Changes in left ventricle myocardial volume during stress test using cadmium-zinc-telluride cardiac imaging: Implications in coronary artery disease

BACKGROUND

Cadmium-zinc-telluride (CZT) SPECT allows the estimation of left ventricle myocardial volume (LVMV). We tested the clinical relevance of rest-stress LVMV changes (Δ LVMV) in detecting coronary artery disease (CAD, coronary stenosis > 70%), using CZT-SPECT.

METHODS

We prospectively enrolled 512 consecutive patients with known or suspected CAD (mean age: 70.3 ± 9.2 years, 72% male) for stress-rest myocardial perfusion imaging (MPI, single-day stress-rest protocol). We quantified summed stress scores (SSS), summed rest scores, and summed difference scores, together with LVMV and ejection fraction (EF) after stress and at rest. All patients underwent coronary angiography within 30 days.

RESULTS

Two hundred seventy-two patients had CAD at coronary angiography. ΔLVMV ≤ 5 mL, corresponding to 6% of change from rest LVMV, was the best predictor of CAD (AUC = 0.831, 79% sensitivity, 82% specificity), irrespective of the stress protocol (dipyridamole or exercise stress) and independently of MPI-SSS, LV EF, and clinical history (P = 0.004). Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were significant for the addition of ΔLVMV ≤ 5 mL (IDI = 6.1%, P < 0.0001; NRI = 29.7%, P = 0.02) to MPI-SSS, whereas the other parameters were not.

CONCLUSIONS

The evaluation of ΔLVMV using CZT-SPECT can improve the diagnostic accuracy in predicting the presence of CAD when added to conventional MPI.

The importance of including uric acid in the definition of metabolic syndrome when assessing the mortality risk

Introduction

Serum uric acid (SUA) has been depicted as a contributory causal factor in metabolic syndrome (MS), which in turn, portends unfavourable prognosis.

Aim

We assessed the prognostic role of SUA in patients with and without MS.

Methods

We used data from the multicentre Uric Acid Right for Heart Health study and considered cardiovascular mortality (CVM) as death due to fatal myocardial infarction, stroke, sudden cardiac death, or heart failure.

Results

A total of 9589 subjects (median age 58.5 years, 45% males) were included in the analysis, and 5100 (53%) patients had a final diagnosis of MS. After a median follow-up of 142 months, we observed 558 events. Using a previously validated cardiovascular SUA cut-off to predict CVM (> 5.1 mg/dL in women and 5.6 mg/dL in men), elevated SUA levels were significantly associated to a worse outcome in patients with and without MS (all p < 0.0001) and provided a significant net reclassification improvement of 7.1% over the diagnosis of MS for CVM (p = 0.004). Cox regression analyses identified an independent association between SUA and CVM (Hazard Ratio: 1.79 [95% CI, 1.15–2.79]; p < 0.0001) after the adjustment for MS, its single components and renal function. Three specific combinations of the MS components were associated with higher CVM when increasing SUA levels were reported, and systemic hypertension was the only individual component ever-present (all p < 0.0001).

Conclusion

Increasing SUA levels are associated with a higher CVM risk irrespective of the presence of MS: a cardiovascular SUA threshold may improve risk stratification.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00392-021-01815-0.

Predicting the transition to and progression of heart failure with preserved ejection fraction: a weighted risk score using bio-humoural, cardiopulmonary, and echocardiographic stress testing

AIMS 

Risk stratification of heart failure (HF) patients with preserved ejection fraction (HFpEF) can promote a more personalized treatment. We tested the prognostic value of a multi-parametric evaluation, including biomarkers, cardiopulmonary exercise testing-exercise stress echocardiography (CPET-ESE), and lung ultrasound, in HFpEF patients and subjects at risk of developing HF (HF Stages A and B).

BACKGROUND 

Risk stratification of heart failure (HF) patients with preserved ejection fraction (HFpEF) can promote a more personalized treatment.

DESIGN 

We tested the prognostic value of a multi-parametric evaluation, including biomarkers, cardiopulmonary exercise testing-exercise stress echocardiography (CPET-ESE), and lung ultrasound, in HFpEF patients and subjects at risk of developing HF (HF Stages A and B).

METHODS AND RESULTS 

We performed a resting clinical/bio-humoural evaluation and a symptom-limited CPET-ESE in 274 patients (45 Stage A, 68 Stage B, and 161 Stage C-HFpEF) and 30 age- and sex-matched healthy controls. During a median follow-up of 18.5 months, we reported 71 HF hospitalizations and 10 cardiovascular deaths. Cox proportional-hazards regression identified five independent predictors and each was assigned a number of points proportional to its regression coefficient: stress-rest ΔB-lines >10 (3 points), peak oxygen consumption <16 mL/kg/min (2 points), minute ventilation/carbon dioxide production slope ≥36 (2 points), peak systolic pulmonary artery pressure ≥50 mmHg (1 point) and resting N-terminal pro-brain natriuretic peptide (NT-proBNP) >900 pg/mL (1 point). The event-free survival probability for low risk (<3 points), intermediate risk (3-6 points), and high risk (>6 points) were 93%, 52%, and 20%, respectively. The area under the curve (AUC) for the scoring system to predict events was 0.92 (95% CI 0.88-0.96), with an accuracy significantly higher than the individual components of the score (all P < 0.01 vs. individual AUCs).

CONCLUSION 

A weighted risk score including NT-proBNP, markers of cardiopulmonary dysfunction and indices of exercise-induced pulmonary congestion identifies HFpEF patients at increased risk for adverse events and Stage A and B subjects more likely to progress towards more advanced HF stages.

Comparison of clinical characteristics of patients with pandemic SARS-CoV-2-related and community-acquired pneumonias in Hungary - a pilot historical case-control study

The distinction between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related and community-acquired pneumonias poses significant difficulties, as both frequently involve the elderly. This study aimed to predict the risk of SARS-CoV-2-related pneumonia based on clinical characteristics at hospital presentation. Case-control study of all patients admitted for pneumonia at Semmelweis University Emergency Department. Cases (n = 30) were patients diagnosed with SARS-CoV-2-related pneumonia (based on polymerase chain reaction test) between 26 March 2020 and 30 April 2020; controls (n = 82) were historical pneumonia cases between 1 January 2019 and 30 April 2019. Logistic models were built with SARS-CoV-2 infection as outcome using clinical characteristics at presentation. Patients with SARS-CoV-2-related pneumonia were younger (mean difference, 95% CI: 9.3, 3.2-15.5 years) and had a higher lymphocyte count, lower C-reactive protein, presented more frequently with bilateral infiltrate, less frequently with abdominal pain, diarrhoea, and nausea in age- and sex-adjusted models. A logistic model using age, sex, abdominal pain, C-reactive protein, and the presence of bilateral infiltrate as predictors had an excellent discrimination (AUC 0.88, 95% CI: 0.81-0.96) and calibration (p = 0.27-Hosmer-Lemeshow test). The clinical use of our screening prediction model could improve the discrimination of SARS-CoV-2 related from other community-acquired pneumonias and thus help patient triage based on commonly used diagnostic approaches. However, external validation in independent datasets is required before its clinical use.

The Glycemic Gap and 90-Day Mortality in Community-acquired Pneumonia. A Prospective Cohort Study

Rationale: Hyperglycemia is associated with mortality in patients with community-acquired pneumonia (CAP), and hyperglycemia may be a biomarker of severity. However, hyperglycemia has a major disadvantage because the association is diminished in patients with diabetes mellitus (DM). This hampers the use of hyperglycemia as a biomarker. Accounting for habitual glucose levels could overcome this disadvantage.Objectives: We hypothesized that the glycemic gap (the difference between plasma glucose and the estimated average glucose) may be associated with mortality irrespective of DM.Methods: Among 1,933 adults with CAP included in a prospective multicenter cohort, we investigated the association between the glycemic gap and 90-day mortality. Hemoglobin A_1c was used to estimate the average glucose. The association was assessed with Cox proportional hazard models after adjustment for age, sex, CURB-65 (Confusion, urea >7 mmol/L, respiratory rate ≥30 breaths/minute, systolic blood pressure <90 mmHg or diastolic blood pressure ≤60 mmHg and age ≥65 years), and comorbidities. In the prespecified analysis the absolute and relative glycemic gaps were used as a continuous variable. In a post hoc analysis, the absolute and relative glycemic gaps were used as a categorical variable grouped according to quartiles.Results: In the post hoc analysis, patients with the lowest (negative) and highest (positive) absolute glycemic gap quartiles had increased risk of 90-day mortality (hazard ratio, 2.6; 95% confidence interval, 1.02-6.65; and hazard ratio, 2.5; 95% confidence interval, 1.01-6.06, respectively). A similar association was found for the relative glycemic gap. The associations were independent of age, CURB-65 score, sex, or number of comorbidities and not modified by DM.Conclusions: Patients with the highest and lowest glycemic gap may have an increased risk of 90-day mortality, and the association was not modified by DM. These associations were found in an exploratory post hoc analysis and should be validated in other populations before further conclusions can be made.

Peak oxygen uptake and incident coronary heart disease in a healthy population: the HUNT Fitness Study

AIMS

The majority of previous research on the association between cardiorespiratory fitness (CRF) and cardiovascular disease (CVD) is based on indirect assessment of CRF in clinically referred predominantly male populations. Therefore, our aim was to examine the associations between VO2peak measured by the gold-standard method of cardiopulmonary exercise testing and fatal and non-fatal coronary heart disease (CHD) in a healthy and fit population.

METHODS AND RESULTS

Data on VO2peak from 4527 adults (51% women) with no previous history of cardiovascular or lung disease, cancer, and hypertension or use of antihypertensive medications participating in a large population-based health-study (The HUNT3 Study), were linked to hospital registries and the cause of death registry. Average VO2peak was 36.0 mL/kg/min and 44.4 mL/kg/min among women and men, and 83.5% had low 10-year risk of CVD at baseline. Average follow-up was 8.8 years, and 147 participants reached the primary endpoint. Multi-adjusted Cox-regression showed 15% lower risk for the primary endpoint per one-MET (metabolic equivalent task) higher VO2peak [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77-0.93], with similar results across sex. The highest quartile of VO2peak had 48% lower risk of event compared with the lowest quartile (multi-adjusted HR 0.52, 95% CI 0.33-0.82). Oxygen pulse and ventilatory equivalents of oxygen and carbon dioxide also showed significant predictive value for the primary endpoint.

CONCLUSION

VO2peak was strongly and inversely associated with CHD across the whole fitness continuum in a low-risk population sample. Increasing VO2peak may have substantial benefits in reducing the burden of CHD.

Prognostic Utility of the New Definition of Difficult-to-Treat Resistance Among Patients With Gram-Negative Bloodstream Infections

Background

To compare the prognostic utility of the new definition of difficult-to-treat resistance (DTR) vs established definitions in a cohort of patients with Gram-negative bloodstream infections (GNBSIs).

Methods

This was a retrospective single-center study of adult patients with monomicrobial GNBSI, hospitalized from 2013 to 2016. DTR was defined as isolate demonstrating intermediate or resistant phenotype to all reported agents in the carbapenem, beta-lactam, and fluoroquinolone classes. Carbapenem resistance (CR) was defined according to 2015 Centers for Disease Control and Prevention criteria. Each isolate was further classified according to the Magiorakos et al. criteria as non-multidrug-resistant (non-MDR), MDR, extensively drug-resistant (XDR), or pan-drug-resistant (PDR). The primary outcome was all-cause 30-day mortality.

Results

Overall, 1576 patients were analyzed. Enterobacteriaceae accounted for 88.7% of BSIs, with Escherichia coli (n = 941) and Klebsiella pneumoniae (n = 326) being the most common pathogens. Pseudomonas aeruginosa was the most common nonfermentative bacteria (n = 130, 8.2%). Overall, 11% of strains were defined as DTR and 13% as CR. Episodes were further classified as non-MDR (68.8%), MDR (21.9%), XDR (8.8%), and PDR (0.4%). The prevalence rates of DTR, CR, and XDR were similar among Enterobacteriaceae and Acinetobacter baumannii, whereas they differed in P. aeruginosa. All the analyzed resistance definitions significantly improved prediction of 30-day mortality when introduced into a baseline multivariate model, to a similar degree: 9%, 10%, and 11% for DTR, Magiorakos, and CR definitions, respectively.

Conclusions

DTR seems a promising tool to identify challenging GNBSIs, mainly those due to P. aeruginosa. With the availability of new agents for CR infections, further multicenter assessments of DTR are needed.

B-type natriuretic peptide trumps other prognostic markers in patients assessed for coronary disease

BACKGROUND

Risk prediction for patients with suspected coronary artery disease is complex due to the common occurrence of prior cardiovascular disease and extensive risk modification in primary care. Numerous markers have the potential to predict prognosis and guide management, but we currently lack robust 'real-world' evidence for their use.

METHODS

Prospective, multicentre observational study of consecutive patients referred for elective coronary angiography. Clinicians were blinded to all risk assessments, consisting of conventional factors, radial artery pulse wave analysis, 5-minute heart rate variability, high-sensitivity C-reactive protein and B-type natriuretic peptide (BNP). Blinded, independent adjudication was performed for all-cause mortality and the composite of death, myocardial infarction or stroke, analysed with Cox proportional hazards regression.

RESULTS

Five hundred twenty-two patients were assessed with median age 66 years and 21% prior revascularization. Median baseline left ventricular ejection fraction was 64%, and 62% had ≥ 50% stenosis on angiography. During 5.0 years median follow-up, 30% underwent percutaneous and 16% surgical revascularization. In multivariate analysis, only age and BNP were independently associated with outcomes. The adjusted hazard ratio per log unit increase in BNP was 2.15 for mortality (95% CI 1.45-3.19; p = 0.0001) and 1.27 for composite events (1.04-1.54; p = 0.018). Patients with baseline BNP > 100 pg/mL had substantially higher mortality and composite events (20.9% and 32.2%) than those with BNP ≤ 100 pg/mL (5.6% and 15.5%). BNP improved both classification and discrimination of outcomes (p ≤ 0.003), regardless of left ventricular systolic function. Conversely, high-sensitivity C-reactive protein, pulse wave analysis and heart rate variability were unrelated to prognosis at 5 years after risk modification and treatment of coronary disease.

CONCLUSIONS

Conventional risk factors and other markers of arterial compliance, inflammation and autonomic function have limited value for prediction of outcomes in risk-modified patients assessed for coronary disease. BNP can independently identify patients with subtle impairment of cardiac function that might benefit from more intensive management.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT00403351 Registered on 22 November 2006.

Improving the post-acute care discharge score (PACD) by adding patients' self-care abilities: A prospective cohort study

Background

Reducing delays in hospital discharge is important to improve transition processes and reduce health care costs. The recently proposed post-acute care discharge score focusing on the self-care abilities before hospital admission allows early identification of patients with a need for post-acute care. New limitations in self-care abilities identified during hospitalization may also indicate a risk. Our aim was to investigate whether the addition of the post-acute care discharge score and a validated self-care instrument would improve the prognostic accuracy to predict post-acute discharge needs in unselected medical inpatients.

Methods

We included consecutive adult medical and neurological inpatients. Logistic regression models with area under the receiver operating characteristic curve were calculated to study associations of post-acute discharge score and self-care index with post-acute discharge risk. We calculated joint regression models and reclassification statistics including the net reclassification index and integrated discrimination improvement to investigate whether merging the self-care index and the post-acute discharge score leads to better diagnostic accuracy.

Results

Out of 1342 medical and 402 neurological patients, 150 (11.18%) and 94 (23.38%) have reached the primary endpoint of being discharged to a post-acute care facility. Multivariate analysis showed that the self-care index is an outcome predictor (OR 0.897, 95%CI 0.864–0.930). By combining the self-care index and the post-acute care discharge score discrimination for medical (from area under the curve 0.77 to 0.83) and neurological patients (from area under the curve 0.68 to 0.78) could be significantly improved. Reclassification statistics also showed significant improvements with regard to net reclassification index (14.2%, p<0.05) and integrated discrimination improvement (4.83%, p<0.05).

Conclusions

Incorporating an early assessment of patients’ actual intrahospital self-care ability to the post-acute care discharge score led to an improved prognostic accuracy for identifying adult, medical and neurological patients at risk for discharge to a post-acute care facility.

A multi-stage association study of plasma cytokines identifies osteopontin as a biomarker for acute coronary syndrome risk and severity

Cytokines play a critical role in the pathogenesis and development of cardiovascular diseases. However, data linking cytokines to risk and severity of acute coronary syndrome (ACS) are still limited. We measured plasma profile of 280 cytokines using a quantitative protein microarray in 12 ACS patients and 16 healthy controls, and identified 15 differentially expressed cytokines for ACS. Osteopontin, chemokine ligand 23, brain derived neurotrophic factor and C-reactive protein (CRP) were further validated using immunoassay in two independent case-control studies with a total of 210 ACS patients and 210 controls. We further examined their relations with incident ACS among 318 case-control pairs nested within the Dongfeng-Tongji cohort, and found plasma osteopontin and CRP concentrations were associated with incident ACS, and the multivariable-adjusted odds ratio (95% confidence interval) was 1.29 (1.06-1.57) per 1-SD increase for osteopontin and 1.30 (1.02-1.66) for CRP, respectively. Higher levels of circulating osteopontin were also correlated with higher severity of ACS, and earlier ACS onset time. Adding osteopontin alone or in combination with CRP modestly improved the predictive ability of ACS beyond the Framingham risk scores. Our findings suggested that osteopontin might be a biomarker for incident ACS, using osteopontin adds moderately to traditional cardiovascular risk factors.

Derivation and external validation of a clinical version of the German Diabetes Risk Score (GDRS) including measures of HbA1c

OBJECTIVE

The German Diabetes Risk Score (GDRS) is a diabetes prediction model which only includes non-invasively measured risk factors. The aim of this study was to extend the original GDRS by hemoglobin A1c (HbA1c) and validate this clinical GDRS in the nationwide German National Health Interview and Examination Survey 1998 (GNHIES98) cohort.

RESEARCH DESIGN AND METHODS

Extension of the GDRS was based on the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study with baseline assessment conducted between 1994 and 1998 (N=27 548, main age range 35-65 years). Cox regression was applied with the original GDRS and HbA1c as independent variables. The extended model was evaluated by discrimination (C-index (95% CI)), calibration (calibration plots and expected to observed (E:O) ratios (95% CI)), and reclassification (net reclassification improvement, NRI (95% CI)). For validation, data from the GNHIES98 cohort with baseline assessment conducted between 1997 and 1999 were used (N=3717, age range 18-79 years). Missing data were handled with multiple imputation.

RESULTS

After 5 years of follow-up 593 incident cases of type 2 diabetes occurred in EPIC-Potsdam and 86 in the GNHIES98 cohort. In EPIC-Potsdam, the C-index for the clinical GDRS was 0.87 (0.81 to 0.92) and the overall NRI was 0.26 (0.21 to 0.30), with a stronger improvement among cases compared with non-cases (NRI_cases: 0.24 (0.19 to 0.28); NRI_non-cases: 0.02 (0.01 to 0.02)). Almost perfect calibration was observed with a slight tendency toward overestimation, which was also reflected by an E:O ratio of 1.07 (0.99 to 1.16). In the GNHIES98 cohort, discrimination was excellent with a C-index of 0.91 (0.88 to 0.94). After recalibration, the calibration plot showed underestimation of diabetes risk in the highest risk group, while the E:O ratio indicated overall perfect calibration (1.02 (0.83 to 1.26)).

CONCLUSIONS

The clinical GDRS provides the opportunity to apply the original GDRS as a first step in risk assessment, which can then be extended in clinical practice with HbA1c whenever it was measured.

External Validation and Update of a Prediction Rule for the Duration of Sickness Absence Due to Common Mental Disorders

Purpose The objective of the present study was to validate an existing prediction rule (including age, education, depressive/anxiety symptoms, and recovery expectations) for predictions of the duration of sickness absence due to common mental disorders (CMDs) and investigate the added value of work-related factors. Methods A prospective cohort study including 596 employees who reported sick with CMDs in the period from September 2013 to April 2014. Work-related factors were measured at baseline with the Questionnaire on the Experience and Evaluation of Work. During 1-year follow-up, sickness absence data were retrieved from an occupational health register. The outcome variables of the study were sickness absence (no = 0, yes = 1) at 3 and 6 months after reporting sick with CMDs. Discrimination between workers with and without sickness absence was investigated at 3 and 6 months with the area under the receiver operating characteristic curve (AUC). Results A total of 220 (37 %) employees agreed to participate and 211 (35 %) had complete data for analysis. Discrimination was poor with AUC = 0.69 and AUC = 0.55 at 3 and 6 months, respectively. When 'variety in work' was added as predictor variable, discrimination between employees with and without CMD sickness absence improved to AUC = 0.74 (at 3 months) and AUC = 0.62 (at 6 months). Conclusions The original prediction rule poorly predicted CMD sickness absence duration. After adding 'variety in work', the prediction rule discriminated between employees with and without CMD sickness absence 3 months after reporting sick. This new prediction rule remains to be validated in other populations.

Right atrial volume by cardiovascular magnetic resonance predicts mortality in patients with heart failure with reduced ejection fraction

Background

Right Atrial Volume Index (RAVI) measured by echocardiography is an independent predictor of morbidity in patients with heart failure (HF) with reduced ejection fraction (HFrEF). The aim of this study is to evaluate the predictive value of RAVI assessed by cardiac magnetic resonance (CMR) for all-cause mortality in patients with HFrEF and to assess its additive contribution to the validated Meta-Analysis Global Group in Chronic heart failure (MAGGIC) score.

Methods and results

We identified 243 patients (mean age 60 ± 15; 33% women) with left ventricular ejection fraction (LVEF) ≤ 35% measured by CMR. Right atrial volume was calculated based on area in two- and four -chamber views using validated equation, followed by indexing to body surface area. MAGGIC score was calculated using online calculator. During mean period of 2.4 years 33 patients (14%) died. The mean RAVI was 53 ± 26 ml/m²; significantly larger in patients with than without an event (78.7±29 ml/m² vs. 48±22 ml/m², p<0.001). RAVI (per ml/m²) was an independent predictor of mortality [HR = 1.03 (1.01–1.04), p = 0.001]. RAVI has a greater discriminatory ability than LVEF, left atrial volume index and right ventricular ejection fraction (RVEF) (C-statistic 0.8±0.08 vs 0.55±0.1, 0.62±0.11, 0.68±0.11, respectively, all p<0.02). The addition of RAVI to the MAGGIC score significantly improves risk stratification (integrated discrimination improvement 13%, and category-free net reclassification improvement 73%, both p<0.001).

Conclusion

RAVI by CMR is an independent predictor of mortality in patients with HFrEF. The addition of RAVI to MAGGIC score improves mortality risk stratification.

Prediction of Cardiovascular Mortality by Estimated Cardiorespiratory Fitness Independent of Traditional Risk Factors: The HUNT Study

OBJECTIVE

To assess the predictive value of estimated cardiorespiratory fitness (eCRF) and evaluate the additional contribution of traditional risk factors in cardiovascular disease (CVD) mortality prediction.

PARTICIPANTS AND METHODS

The study included healthy men (n=18,721) and women (n=19,759) aged 30 to 74 years. A nonexercise algorithm estimated cardiorespiratory fitness. Cox proportional hazards models evaluated the primary (CVD mortality) and secondary (all-cause, ischemic heart disease, and stroke mortality) end points. The added predictive value of traditional CVD risk factors was evaluated using the Harrell C statistic and net reclassification improvement.

RESULTS

After a median follow-up of 16.3 years (range, 0.04-17.4 years), there were 3863 deaths, including 1133 deaths from CVD (734 men and 399 women). Low eCRF was a strong predictor of CVD and all-cause mortality after adjusting for established risk factors. The C statistics for eCRF and CVD mortality were 0.848 (95% CI, 0.836-0.861) and 0.878 (95% CI, 0.862-0.894) for men and women, respectively, increasing to 0.851 (95% CI, 0.839-0.863) and 0.881 (95% CI, 0.865-0.897), respectively, when adding clinical variables. By adding clinical variables to eCRF, the net reclassification improvement of CVD mortality was 0.014 (95% CI, -0.023 to 0.051) and 0.052 (95% CI, -0.023 to 0.127) in men and women, respectively.

CONCLUSION

Low eCRF is independently associated with CVD and all-cause mortality. The inclusion of traditional clinical CVD risk factors added little to risk discrimination and did not improve the classification of risk beyond this simple eCRF measurement, which may be proposed as a practical and cost-effective first-line approach in primary prevention settings.

Gait speed and one-leg standing time each add to the predictive ability of FRAX

Gait speed or one-leg standing time (OLST) as additional predictors in FRAX. Population 351 elderly women followed 10 years. Both could improve predictions. The area under curve (AUC) for FRAX is 0.59, OLST is 0.69 and gait speed is 0.71. The net reclassification index (NRI) for classification to highest risk quartile or lowest three quartiles was 0.24 for gait speed and non-significant for OLST.

INTRODUCTION

The risk of falls and bone strength are two main determinants of hip fracture risk. The fracture risk assessment tool FRAX, however, lacks direct measures of fall risk¹. A short OLST and a slow gait speed are both fall-related risk factors for hip fractures. The aim of this study was to investigate whether the addition to FRAX of either gait speed or OLST could improve the predictive ability for hip fractures, compared to FRAX alone.

METHODS

A population-based sample of 351 women aged between 69 and 79 years were tested for one-leg standing time with eyes open and mean gait speed over a 15 + 15-m walk. Fracture and mortality data were obtained from health care registers.

RESULTS

The AUC for the receiver operating characteristic (ROC) increased from 0.61 to 0.71 when gait speed was added to FRAX. The AUC was 0.69 for OLST added to FRAX. The highest quartile of hip fracture risks according to FRAX had an absolute 10-year risk of ≥15%. The population was divided into one group with a hip fracture risk of ≥15% and one group with a fracture risk of <15%. NRI for addition of gait speed to FRAX was 0.24 (p = 0.023), while NRI was 0.08 (p = 0.544) for addition of OLST to FRAX.

CONCLUSION

Gait speed tended to improve the predictive ability of FRAX more than OLST, but they both added value to FRAX.

Cardiac Time Intervals Measured by Tissue Doppler Imaging M-mode: Association With Hypertension, Left Ventricular Geometry, and Future Ischemic Cardiovascular Diseases

BACKGROUND

We hypothesized that the cardiac time intervals reveal reduced myocardial function in persons with hypertension and are strong predictors of future ischemic cardiovascular diseases in the general population.

METHODS AND RESULTS

In a large community-based population study, cardiac function was evaluated in 1915 participants by using both conventional echocardiography and tissue Doppler imaging (TDI). The cardiac time intervals, including the isovolumic relaxation time (IVRT), isovolumic contraction time (IVCT), and ejection time (ET), were obtained by TDI M-mode through the mitral leaflet. IVCT/ET, IVRT/ET, and myocardial performance index [MPI=(IVRT+IVCT)/ET] were calculated. After multivariable adjustment for clinical variables the IVRT, IVRT/ET, and MPI, remained significantly impaired in persons with hypertension (n=826) compared with participants without hypertension (n=1082). Additionally, they displayed a significant dose-response relationship, between increasing severity of elevated blood pressure and increasing left ventricular mass index (P<0.001 for all). Further, during follow-up of a median of 10.7 years, 435 had an ischemic cardiovascular disease (ischemic heart disease, peripheral arterial disease, or stroke). The IVRT/ET and MPI were powerful and independent predictors of future cardiovascular disease, especially in participants with known hypertension. They provide prognostic information incremental to clinical variables from the Framingham Risk Score, the SCORE risk chart, and the European Society of Hypertension/European Society of Cardiology risk chart.

CONCLUSION

The cardiac time intervals identify impaired cardiac function in individuals with hypertension, not only independent of conventional risk factors but also in participants with a normal conventional echocardiographic examination. The IVRT/ET and MPI are independent predictors of future cardiovascular disease especially in participants with known hypertension.

Clinical diagnosis of symptomatic midfoot osteoarthritis: cross-sectional findings from the Clinical Assessment Study of the Foot

OBJECTIVE

To derive a multivariable diagnostic model for symptomatic midfoot osteoarthritis (OA).

METHODS

Information on potential risk factors and clinical manifestations of symptomatic midfoot OA was collected using a health survey and standardised clinical examination of a population-based sample of 274 adults aged ≥50 years with midfoot pain. Following univariable analysis, random intercept multi-level logistic regression modelling that accounted for clustered data was used to identify the presence of midfoot OA independently scored on plain radiographs (dorso-plantar and lateral views), and defined as a score of ≥2 for osteophytes or joint space narrowing in at least one of four joints (first and second cuneometatarsal, navicular-first cuneiform and talonavicular joints). Model performance was summarised using the calibration slope and area under the curve (AUC). Internal validation and sensitivity analyses explored model over-fitting and certain assumptions.

RESULTS

Compared to persons with midfoot pain only, symptomatic midfoot OA was associated with measures of static foot posture and range-of-motion at subtalar and ankle joints. Arch Index was the only retained clinical variable in a model containing age, gender and body mass index. The final model was poorly calibrated (calibration slope, 0.64, 95% CI: 0.39, 0.89) and discrimination was fair-to-poor (AUC, 0.64, 95% CI: 0.58, 0.70). Final model sensitivity and specificity were 29.9% (95% CI: 22.7, 38.0) and 87.5% (95% CI: 82.9, 91.3), respectively. Bootstrapping revealed the model to be over-optimistic and performance was not improved using continuous predictors.

CONCLUSIONS

Brief clinical assessments provided only marginal information for identifying the presence of radiographic midfoot OA among community-dwelling persons with midfoot pain.

Left Ventricular Systolic Dysfunction by Longitudinal Strain Is an Independent Predictor of Incident Atrial Fibrillation: A Community-Based Cohort Study

BACKGROUND

The increasing prevalence of atrial fibrillation (AF) represents a public health issue. Identifying new predictors of AF is therefore necessary to plan preventive strategies. We investigated whether left ventricular (LV) systolic dysfunction by global longitudinal strain (GLS), a predictor of cardiovascular events, may predict new-onset AF in a population setting.

METHODS AND RESULTS

Participants (n=675; mean age, 71±9 years; 60% women) in sinus rhythm from the population-based Northern Manhattan Study (NOMAS) underwent 2- and 3-dimensional echocardiography as part of the Cardiac Abnormalities and Brain Lesions (CABL) study. LV systolic function was assessed by LV ejection fraction and speckle-tracking GLS. During a mean follow-up of 63.6±18.7 months, 32 (4.7%) new confirmed cases of AF occurred. Lower GLS (adjusted hazard ratio/unit decrease, 1.22; 95% confidence interval, 1.04-1.43; P=0.015) and increased left atrial volume index (LAVi; adjusted hazard ratio/unit increase, 1.12; 95% confidence interval, 1.07-1.17; P<0.001) were significantly associated with incident AF, whereas LV ejection fraction was not (P=0.176). Abnormal GLS (>-14.7%) was associated with risk of new-onset AF with an adjusted hazard ratio of 3.2 (95% confidence interval, 1.4-7.5; P=0.007). The coexistence of abnormal GLS/abnormal LAVi was associated with a 28.6% incidence of AF (adjusted hazard ratio, 12.1; 95% confidence interval, 3.3-44.8; P<0.001) compared with participants with normal GLS/normal LAVi (AF incidence, 2.0%). AF incidence was intermediate in those with either abnormal GLS or abnormal LAVi (9.3% and 11.1%, respectively). GLS prognostic value for incident AF was incremental over risk factors and LAVi.

CONCLUSIONS

LV systolic dysfunction by GLS was a powerful and independent predictor of incident AF. GLS assessment may improve AF risk stratification in addition to established parameters.

Utility of a genetic risk score to predict recurrent cardiovascular events 1 year after an acute coronary syndrome: A pooled analysis of the RISCA, PRAXY, and TRIUMPH cohorts

BACKGROUND

Limited evidence exists regarding the utility of genetic risk scores (GRS) in predicting recurrent cardiovascular events after acute coronary syndrome (ACS). We sought to determine whether a GRS would predict early recurrent cardiovascular events within 1 year of ACS.

METHODS & RESULTS

Participants admitted with acute coronary syndromes from the RISCA, PRAXY, and TRIUMPH cohorts, were genotyped for 30 single nucleotide polymorphisms (SNPs) associated with coronary artery disease (CAD) or myocardial infarction (MI) in prior genome wide association studies. A 30 SNP CAD/MI GRS was constructed. The primary endpoint was defined as all-cause mortality, recurrent ACS or cardiac re-hospitalization within 1 year of ACS admission. Results across all cohorts for the 30 SNP CAD/MI GRS were pooled using a random-effects model. There were 1040 patients from the RISCA cohort, 691 patients from the PRAXY cohort, and 1772 patients from the TRIUMPH cohort included in the analysis and 389 occurrences of the primary endpoint of recurrent events at 1-year post-ACS. In unadjusted and fully adjusted analyses, a 30 SNP GRS was not significantly associated with recurrent events (HR per allele 0.97 (95%CI 0.91-1.03) for RISCA, HR 0.99 (95%CI 0.93-1.05) for PRAXY, 0.98 (95%CI 0.94-1.02) for TRIUMPH, and 0.98 (95%CI 0.95-1.01) for the pooled analysis). Addition of this GRS to the GRACE risk model did not significantly improve risk prediction.

CONCLUSION

The 30 MI SNP GRS was not associated with recurrent events 1-year post ACS in pooled analyses across cohorts and did not improve risk discrimination or reclassification indices. Our results suggest that the genetic etiology of early events post-ACS may differ from later events.

Associations of Coronary Heart Disease with Common Carotid Artery Near and Far Wall Intima-Media Thickness: The Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Intima-media thickness (IMT) measured on ultrasound images of the common carotid artery (CCA) is associated with cardiovascular risk factors and events. Given the physics of ultrasound, CCA far wall IMT measurements are favored over near wall measurements, but this theoretical advantage is not well studied.

METHODS

A total of 6,606 members of the Multi-Ethnic Study of Atherosclerosis, a longitudinal cohort study (mean age, 62.1 years; 52.7% women) who had near wall and far wall CCA IMT measurements. Multivariate linear regression models were used to estimate model goodness of fit of Framingham risk factors with near wall IMT, far wall IMT, and combined mean IMT. Multivariate Cox proportional hazards models were used to estimate hazard ratios for incident coronary heart disease events for each IMT variable. Change in Harrell's C statistic was used to compare the incremental value of each IMT variable when added to Framingham risk factors.

RESULTS

Mean IMT had the strongest association with risk factors (R(2) = 0.31), followed by near wall (R(2) = 0.26) and far wall (R(2) = 0.22) IMT. Far wall IMT improved the prediction of coronary artery disease events over the Framingham risk factors (change in C statistic, 0.012; 95% CI, 0.006-0.017; P < .001), as did mean IMT (P = .004), but near wall IMT did not.

CONCLUSIONS

Far wall CCA IMT showed the strongest association with incident coronary heart disease, whereas mean IMT had the strongest associations with risk factors. This difference might affect the selection of appropriate IMT variables in different studies.

Cross-national validation of prognostic models predicting sickness absence and the added value of work environment variables

PURPOSE

To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated.

METHODS

2,562 municipal eldercare workers (95% women) participated in the Working in Eldercare Survey. Predictor variables were measured by questionnaire at baseline in 2005. Prognostic models were validated for predictions of high (≥30) SA days and high (≥3) SA episodes retrieved from employer records during 1-year follow-up. The accuracy of predictions was assessed by calibration graphs and the ability of the models to discriminate between high- and low-risk workers was investigated by ROC-analysis. The added value of work environment variables was measured with Integrated Discrimination Improvement (IDI).

RESULTS

1,930 workers had complete data for analysis. The models underestimated the risk of high SA in eldercare workers and the SA episodes model had to be re-calibrated to the Danish data. Discrimination was practically useful for the re-calibrated SA episodes model, but not the SA days model. Physical workload improved the SA days model (IDI = 0.40; 95% CI 0.19-0.60) and psychosocial work factors, particularly the quality of leadership (IDI = 0.70; 95% CI 053-0.86) improved the SA episodes model.

CONCLUSIONS

The prognostic model predicting high SA days showed poor performance even after physical workload was added. The prognostic model predicting high SA episodes could be used to identify high-risk workers, especially when psychosocial work factors are added as predictor variables.

Risk reclassification analysis investigating the added value of fatigue to sickness absence predictions

Background

Prognostic models including age, self-rated health and prior sickness absence (SA) have been found to predict high (≥30) SA days and high (≥3) SA episodes during 1-year follow-up. More predictors of high SA are needed to improve these SA prognostic models. The purpose of this study was to investigate fatigue as new predictor in SA prognostic models by using risk reclassification methods and measures.

Methods

This was a prospective cohort study with 1-year follow-up of 1,137 office workers. Fatigue was measured at baseline with the 20-item checklist individual strength and added to the existing SA prognostic models. SA days and episodes during 1-year follow-up were retrieved from an occupational health service register. The added value of fatigue was investigated with Net Reclassification Index (NRI) and integrated discrimination improvement (IDI) measures.

Results

In total, 579 (51 %) office workers had complete data for analysis. Fatigue was prospectively associated with both high SA days and episodes. The NRI revealed that adding fatigue to the SA days model correctly reclassified workers with high SA days, but incorrectly reclassified workers without high SA days. The IDI indicated no improvement in risk discrimination by the SA days model. Both NRI and IDI showed that the prognostic model predicting high SA episodes did not improve when fatigue was added as predictor variable.

Conclusion

In the present study, fatigue increased false-positive rates which may reduce the cost-effectiveness of interventions for preventing SA.

Electrocardiographic deep terminal negativity of the P wave in V(1) and risk of sudden cardiac death: the Atherosclerosis Risk in Communities (ARIC) study

Background

Identifying individuals at risk for sudden cardiac death (SCD) is of critical importance. Electrocardiographic (ECG) deep terminal negativity of P wave in V₁ (DTNPV1), a marker of left atrial abnormality, has been associated with increased risk of all‐cause and cardiovascular mortality. We hypothesized that DTNPV1 is associated with increased risk of sudden cardiac death (SCD).

Methods and Results

This analysis included 15 375 participants (54.1±5.8 years, 45% men, 73% whites) from the Atherosclerosis Risk in Communities (ARIC) study. DTNPV1 was defined from the resting 12‐lead ECG as presence of biphasic P wave (positive/negative) in V₁ with the amplitude of the terminal negative phase >100 μV, or one small box on ECG scale. After a median of 14 years of follow‐up, 311 cases of SCD occurred. In unadjusted Cox regression, DTNPV1 was associated with an 8‐fold increased risk of SCD (HR 8.21; [95%CI 5.27 to 12.79]). Stratified by race and study center, and adjusted for age, sex, coronary heart disease (CHD), and ECG risk factors, as well as atrial fibrillation (AF), stroke, CHD, and heart failure (HF) as time‐updated variables, the risk of SCD associated with DTNPV1 remained significant (2.49, [1.51–4.10]). DTNPV1 improved reclassification: additional 3.4% of individuals were appropriately reclassified into a higher SCD risk group, as compared with traditional CHD risk factors alone. In fully adjusted models DTNPV1 was associated with increased risk of non‐fatal events: AF (5.02[3.23–7.80]), CHD (2.24[1.43–3.53]), HF (1.90[1.19–3.04]), and trended towards increased risk of stroke (1.88[0.99–3.57]).

Conclusion

DTNPV1 is predictive of SCD suggesting its potential utility in risk stratification in the general population.

Stratification of risk for hospital admissions for injury related to fall: cohort study

OBJECTIVE

To determine whether the ability to stratify an individual patient's hazard for falling could facilitate development of focused interventions aimed at reducing these adverse outcomes.

DESIGN

Clinical and sociodemographic data from electronic health records were utilized to derive multiple logistic regression models of hospital readmissions for injuries related to falls. Drugs used at admission were summarized based on reported adverse effect frequencies in published drug labeling.

SETTING

Two large academic medical centers in New England, United States.

PARTICIPANTS

The model was developed with 25,924 individuals age ≥ 40 with an initial hospital discharge. The resulting model was then tested in an independent set of 13,032 inpatients drawn from the same hospital and 36,588 individuals discharged from a second large hospital during the same period.

MAIN OUTCOME MEASURE

Hospital readmissions for injury related to falls.

RESULTS

Among 25,924 discharged individuals, 680 (2.6%) were evaluated in the emergency department or admitted to hospital for a fall within 30 days of discharge, 1635 (6.3%) within 180 days of discharge, 2360 (9.1%) within one year, and 3465 (13.4%) within two years. Older age, female sex, white or African-American race, public insurance, greater number of drugs taken on discharge, and score for burden of adverse effects were each independently associated with hazard for fall. For drug burden, presence of a drug with a frequency of adverse effects related to fall of 10% was associated with 3.5% increase in odds of falling over the next two years (odds ratio 1.04, 95% confidence interval 1.02 to 1.05). In an independent testing set, the area under the receiver operating characteristics curve was 0.65 for a fall within two years based on cross sectional data and 0.72 with the addition of prior utilization data including age adjusted Charlson comorbidity index. Portability was promising, with area under the curve of 0.71 for the longitudinal model in a second hospital system.

CONCLUSIONS

It is potentially useful to stratify risk of falls based on clinical features available as artifacts of routine clinical care. A web based tool can be used to calculate and visualize risk associated with drug treatment to facilitate further investigation and application.

Different lipid variables predict incident coronary artery disease in patients with type 1 diabetes with or without diabetic nephropathy: the FinnDiane study

OBJECTIVE

To study the ability of lipid variables to predict incident coronary artery disease (CAD) events in patients with type 1 diabetes at different stages of nephropathy.

RESEARCH DESIGN AND METHODS

Patients (n = 3,520) with type 1 diabetes and available lipid profiles participating in the Finnish Diabetic Nephropathy Study (FinnDiane) were included in the study. During a follow-up period of 10.2 years (8.6-12.0), 310 patients suffered an incident CAD event.

RESULTS

Apolipoprotein B (ApoB)/ApoA-I ratio was the strongest predictor of CAD in normoalbuminuric patients (hazard ratio 1.43 [95% CI 1.17-1.76] per one SD increase), and ApoB was the strongest in macroalbuminuric patients (1.47 [1.19-1.81]). Similar results were seen when patients were stratified by sex or glycemic control. LDL cholesterol was a poor predictor of CAD in women, normoalbuminuric patients, and patients with HbA1c below the median (8.3%, 67 mmol/L). The current recommended triglyceride cutoff of 1.7 mmol/L failed to predict CAD in normoalbuminuric patients, whereas the cohort median 0.94 mmol/L predicted incident CAD events.

CONCLUSIONS

In patients with type 1 diabetes, the predictive ability of the lipid variables differed substantially depending on the patient's sex, renal status, and glycemic control. In normoalbuminuric patients, the ratios of atherogenic and antiatherogenic lipoproteins and lipids were the strongest predictors of an incident CAD event, whereas in macroalbuminuric patients, no added benefit was gained from the ratios. Current treatment recommendations may need to be revised to capture residual CAD risk in patients with type 1 diabetes.

Associations of pentraxin 3 with cardiovascular disease: the Multi-Ethnic Study of Atherosclerosis

OBJECTIVE

Pentraxin 3 (PTX3) is probably a specific marker of vascular inflammation. However, associations of PTX3 with cardiovascular disease (CVD) risk have not been well studied in healthy adults or multi-ethnic populations. We examined associations of PTX3 with CVD risk factors, measures of subclinical CVD, coronary artery calcification (CAC) and CVD events in the Multi-Ethnic Study of Atherosclerosis.

APPROACH AND RESULTS

Two thousand eight hundred and thirty-eight participants free of prevalent CVD with measurements of PTX3 were included in the present study. After adjustment for age, sex, and ethnicity, PTX3 was positively associated with age, obesity, insulin, systolic blood pressure, C-reactive protein (CRP), and carotid intima-media thickness (all P < 0.045). A one standard deviation increase in PTX3 level (1.62 ng mL(-1) ) was associated with the presence of CAC in fully adjusted models including multiple CVD risk factors (relative risk of 1.05; 95% confidence interval [CI] 1.01-1.08). In fully adjusted models, a standard deviation higher level of PTX3 was associated with an increased risk of myocardial infarction (hazard ratio [HR] 1.51; 95% [CI] 1.16-1.97), combined CVD events (HR 1.23; 95% [CI] 1.05-1.45), and combined CHD events (HR 1.33; 95% [CI] 1.10-1.60), but not stroke, CVD-related mortality, or all-cause death.

CONCLUSIONS

In these apparently healthy adults, PTX3 was associated with CVD risk factors, subclinical CVD, CAC and incident coronary heart disease events independently of CRP and CVD risk factors. These results support the hypothesis that PTX3 reflects different aspects of inflammation than CRP, and may provide additional insights into the development and progression of atherosclerosis.

Mean platelet volume on admission improves risk prediction in patients with acute coronary syndromes

Our aim was to evaluate the incremental predictive value of adding mean platelet volume (MPV) to the Global Registry of Acute Coronary Events (GRACE) risk score. The MPV and GRACE score were determined on admission in 509 consecutive patients with acute coronary syndrome (ACS). Six-month mortality or nonfatal myocardial infarction (MI) was the study end point. Overall, 61 (12%) patients reached the combined end point. Cox multivariate analysis showed that an elevated MPV was an independent predictor of 6-month mortality or MI in patients with ACS. The addition of MPV to the GRACE model improved its global fit and discriminatory capacity. The new model including MPV allowed adequate reclassification of 16% of the patients. In conclusion, the inclusion of MPV into the GRACE risk score could allow improved risk classification, thereby refining risk stratification of patients with ACS.

Updating and prospective validation of a prognostic model for high sickness absence

OBJECTIVES

To further develop and validate a Dutch prognostic model for high sickness absence (SA).

METHODS

Three-wave longitudinal cohort study of 2,059 Norwegian nurses. The Dutch prognostic model was used to predict high SA among Norwegian nurses at wave 2. Subsequently, the model was updated by adding person-related (age, gender, marital status, children at home, and coping strategies), health-related (BMI, physical activity, smoking, and caffeine and alcohol intake), and work-related (job satisfaction, job demands, decision latitude, social support at work, and both work-to-family and family-to-work spillover) variables. The updated model was then prospectively validated for predictions at wave 3.

RESULTS

1,557 (77 %) nurses had complete data at wave 2 and 1,342 (65 %) at wave 3. The risk of high SA was under-estimated by the Dutch model, but discrimination between high-risk and low-risk nurses was fair after re-calibration to the Norwegian data. Gender, marital status, BMI, physical activity, smoking, alcohol intake, job satisfaction, job demands, decision latitude, support at the workplace, and work-to-family spillover were identified as potential predictors of high SA. However, these predictors did not improve the model's discriminative ability, which remained fair at wave 3.

CONCLUSIONS

The prognostic model correctly identifies 73 % of Norwegian nurses at risk of high SA, although additional predictors are needed before the model can be used to screen working populations for risk of high SA.

Identification of IGFBP-7 by urinary proteomics as a novel prognostic marker in early acute kidney injury

Early diagnosis of acute kidney injury (AKI) and accurate prognostic stratification is a prerequisite for optimal medical management. To identify novel prognostic markers of AKI, urine was collected on the first day of AKI in critically ill patients. Twelve patients with early recovery and 12 matching patients with late/non-recovery were selected and their proteome analyzed by gel electrophoresis and mass spectrometry. We identified eight prognostic candidates including α-1 microglobulin, α-1 antitrypsin, apolipoprotein D, calreticulin, cathepsin D, CD59, insulin-like growth factor-binding protein 7 (IGFBP-7), and neutrophil gelatinase-associated lipocalin (NGAL). Subsequent quantification by ELISA showed that IGFBP-7 was the most potent predictor of renal recovery. IGFBP-7 and NGAL were then chosen for further analyses in an independent verification group of 28 patients with and 12 control patients without AKI. IGFBP-7 and NGAL discriminated between early and late/non-recovery patients and patients with and without AKI. Significant upregulation of the urinary markers predicted mortality (IGFBP-7: AUC 0.68; NGAL: AUC 0.81), recovery (IGFBP-7: AUC 0.74; NGAL: AUC 0.70), and severity of AKI (IGFBP-7: AUC 0.77; NGAL: AUC 0.69), and were associated with the duration of AKI. IGFBP-7 was a more accurate predictor of renal outcome than NGAL. Thus, IGFBP-7 is a novel prognostic urinary marker that warrants further investigation.

[Useful tests to assess the clinical usefulness of new prognostic markers: the example of heart failure]

INTRODUCTION

Identification of risk factors is one of the most frequent questions in medical research currently. Several reports showed "significant" and "independent" prognostic factors in a variety of human conditions, however, those were not tested about predictive information in addition to standard risk markers. Recently novel statistical approaches (reclassification) have been developed to test the performance and usefulness of new risk factors and prognostic markers. There are several established methods to test the prognostic models.

AIM

The aim of this work was to present the application of these novel statistical approaches by re-analyzing previously reported results of the authors.

METHOD

The authors analyzed the prognostic role of two markers: red cell distribution width and heat shock protein 70 in patients with heart failure. Using Cox regression analyses the authors have reported previously that both markers are independent predictors. In the present study they re-analyzed the role of red cell distribution width and heat shock protein 70 by reclassification tests.

RESULTS

Incorporating red cell distribution width to the reference model the authors found a significant improvement in discrimination . However, the reclassification analysis provided ambiguous results with heat shock protein 70.

CONCLUSIONS

Interpretation of results on new prognostic factors has to be done carefully, and appropriate reclassification approaches may help to confirm clinical usefulness only.

The value of carotid artery plaque and intima-media thickness for incident cardiovascular disease: the multi-ethnic study of atherosclerosis

BACKGROUND

Carotid artery plaques are associated with coronary artery atherosclerotic lesions. We evaluated various ultrasound definitions of carotid artery plaque as predictors of future cardiovascular disease (CVD) and coronary heart disease (CHD) events.

METHODS AND RESULTS

We studied the risk factors and ultrasound measurements of the carotid arteries at baseline of 6562 members (mean age 61.1 years; 52.6% women) of the Multi-Ethnic Study of Atherosclerosis (MESA). ICA lesions were defined subjectively as >0% or ≥25% diameter narrowing, as continuous intima-media thickness (IMT) measurements (maximum IMT or the mean of the maximum IMT of 6 images) and using a 1.5-mm IMT cut point. Multivariable Cox proportional hazards models were used to estimate hazard ratios for incident CVD, CHD, and stroke. Harrell's C-statistics, Net Reclassification Improvement, and Integrated Discrimination Improvement were used to evaluate the incremental predictive value of plaque metrics. At 7.8-year mean follow-up, all plaque metrics significantly predicted CVD events (n=515) when added to Framingham risk factors. All except 1 metric improved the prediction of CHD (by C-statistic, Net Reclassification Improvement, and Integrated Discrimination Improvement. Mean of the maximum IMT had the highest NRI (7.0%; P=0.0003) with risk ratio of 1.43/mm; 95% CI 1.26-1.63) followed by maximum IMT with an NRI of 6.8% and risk ratio of 1.27 (95% CI 1.18-1.38).

CONCLUSION

Ultrasound-derived plaque metrics independently predict cardiovascular events in our cohort and improve risk prediction for CHD events when added to Framingham risk factors.

Novel risk factors and the prediction of type 2 diabetes in the Atherosclerosis Risk in Communities (ARIC) study

OBJECTIVE

The objective of this study was to determine potential added value of novel risk factors in predicting the development of type 2 diabetes beyond that provided by standard clinical risk factors.

RESEARCH DESIGN AND METHODS

The Atherosclerosis Risk in Communities (ARIC) Study is a population-based prospective cohort study in four U.S. communities. Novel risk factors were either measured in the full cohort or in a case-control sample nested within the cohort. We started with a basic prediction model, previously validated in ARIC, and evaluated 35 novel risk factors by adding them independently to the basic model. The area under the curve (AUC), net reclassification index (NRI), and integrated discrimination index (IDI) were calculated to determine if each of the novel risk factors improved risk prediction.

RESULTS

There were 1,457 incident cases of diabetes with a mean of >7.6 years of follow-up among 12,277 participants at risk. None of the novel risk factors significantly improved the AUC. Forced expiratory volume in 1 s was the only novel risk factor that resulted in a significant NRI (0.54%; 95% CI: 0.33-0.86%). Adiponectin, leptin, γ-glutamyl transferase, ferritin, intercellular adhesion molecule 1, complement C3, white blood cell count, albumin, activated partial thromboplastin time, factor VIII, magnesium, hip circumference, heart rate, and a genetic risk score each significantly improved the IDI, but net changes were small.

CONCLUSIONS

Evaluation of a large panel of novel risk factors for type 2 diabetes indicated only small improvements in risk prediction, which are unlikely to meaningfully alter clinical risk reclassification or discrimination strategies.

Assessing improvement in disease prediction using net reclassification improvement: impact of risk cut-offs and number of risk categories

Net reclassification improvement (NRI) has received much attention for comparing risk prediction models, and might be preferable over the area under the receiver operating characteristics (ROC) curve to indicate changes in predictive ability. We investigated the influence of the choice of risk cut-offs and number of risk categories on the NRI. Using data of the European Prospective Investigation into Cancer and Nutrition-Potsdam study, three diabetes prediction models were compared according to ROC area and NRI with varying cut-offs for two and three risk categories and varying numbers of risk categories. When compared with a basic model, including age, anthropometry, and hypertension status, a model extension by waist circumference improved discrimination from 0.720 to 0.831 (0.111 [0.097-0.125]) while increase in ROC-AUC from 0.831 to 0.836 (0.006 [0.002-0.009]) indicated moderate improvement when additionally considering diet and physical activity. However, NRI based on these two model comparisons varied with varying cut-offs for two (range: 5.59-23.20%; -0.79 to 4.09%) and three risk categories (20.37-40.15%; 1.22-4.34%). This variation was more pronounced in the model extension showing a larger difference in ROC-AUC. NRI increased with increasing numbers of categories from minimum NRIs of 18.41 and 0.46% to approximately category-free NRIs of 79.61 and 19.22%, but not monotonically. There was a similar pattern for this increase in both model comparisons. In conclusion, the choice of risk cut-offs and number of categories has a substantial impact on NRI. A limited number of categories should only be used if categories have strong clinical importance.

Performance of an adipokine pathway-based multilocus genetic risk score for prostate cancer risk prediction

Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance.

Use of postoperative creatinine to predict sustained kidney injury in patients undergoing mesothelioma surgery

BACKGROUND AND OBJECTIVES

AKI leads to increased morbidity and mortality and progression to chronic kidney injury is a frequent consequence of AKI. Surgical treatment of mesothelioma is associated with increased risk for kidney injury. However, sustained kidney injury may limit therapeutic options for treating residual cancer. This study hypothesized that patients with significant serum creatinine (sCr) elevation within 48 hours of surgery would be at risk for sustained kidney injury. The goal was to determine the best acute sCr measure predictive of sustained kidney injury defined as a 50% increase in sCr from baseline measured 2-4 weeks after surgery.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

In a prospective, observational cohort of surgical patients with mesothelioma, receiver operator characteristic curves were generated for the 24- and 48-hour absolute difference and relative sCr change over baseline in the derivation cohort (n=279). The prediction was tested in a validation cohort (n=207). The ability of various other AKI definitions to predict sustained kidney injury was evaluated.

RESULTS

Sustained kidney injury occurred in 9.8% of patients in the derivation cohort. A ≥59% increase in sCr 48 hours after surgery was most predictive of sustained kidney injury (c statistic=0.78). Among other AKI definitions, a sCr increase of 0.3 mg/dl in 24 hours or 0.5 mg/dl increase in 48 hours (Waikar and Bonventre criteria) also reliably predicted sustained kidney injury.

CONCLUSIONS

Development of clinically significant sustained kidney injury can be predicted by acute postoperative sCr elevation in patients treated for mesothelioma.

Prediction of fracture risk in men: a cohort study

FRAX is a tool that identifies individuals with high fracture risk who will benefit from pharmacological treatment of osteoporosis. However, a majority of fractures among elderly occur in people without osteoporosis and most occur after a fall. Our aim was to accurately identify men with a high future risk of fracture, independent of cause. In the population-based Uppsala Longitudinal Study of Adult Men (ULSAM) and using survival analysis we studied different models' prognostic values (R(2)) for any fracture and hip fracture within 10 years from age 50 (n = 2322), 60 (n = 1852), 71 (n = 1221), and 82 (n = 526) years. During the total follow-up period from age 50 years, 897 fractures occurred in 585 individuals. Of these, 281 were hip fractures occurring in 189 individuals. The rates of any fracture were 5.7/1000 person-years at risk from age 50 years and 25.9/1000 person-years at risk from age 82 years. Corresponding hip fractures rates were 2.9 and 11.7/1000 person-years at risk. The FRAX model included all variables in FRAX except bone mineral density. The full model combining FRAX variables, comorbidity, medications, and behavioral factors explained 25% to 45% of all fractures and 80% to 92% of hip fractures, depending on age. The corresponding prognostic values of the FRAX model were 7% to 17% for all fractures and 41% to 60% for hip fractures. Net reclassification improvement (NRI) comparing the full model with the FRAX model ranged between 40% and 53% for any fracture and between 40% and 87% for hip fracture. Within the highest quintile of predicted fracture risk with the full model, one-third of the men will have a fracture within 10 years after age 71 years and two-thirds after age 82 years. We conclude that the addition of comorbidity, medication, and behavioral factors to the clinical components of FRAX can substantially improve the ability to identify men at high risk of fracture, especially hip fracture.