Abstract 230: Improved Prediction of 30-day Mortality after Heart Failure Hospitalization by Utilization of Admission Vital Signs and Laboratory Findings.

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Robert G Zoble ◽  
Benji Torres ◽  
Adam Zoble ◽  
Ramona Gelzer Bell ◽  
Philip Foulis ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Troponin I ◽  
Vital Signs ◽  
Primary Diagnosis ◽  
P Value ◽  
Continuous Variables ◽  
Variable Model ◽  
Laboratory Findings ◽  
C Statistic

Background: Heart failure (HF) is associated with high mortality so early identification of those at high risk may be useful in reducing mortality rates. We sought to develop a simple risk score from data readily available at the time of HF admission. Methods: We studied Veterans hospitalized from January 2004 to December 2009, who were discharged alive with a primary diagnosis of HF (based on ICD-9 coding). For the purposes of these analyses, only the 869 who had complete data for admission vital signs, laboratory parameters, ECG, co-morbidities and ejection fraction were included. Univariate analyses were employed to identify variables associated with mortality at a p-value < 0.10. These variables were then analyzed by MVA to determine independent predictors of mortality. The c-statistic was utilized to determine cutpoints for continuous variables. A risk score was developed by assigning risk points based on the odds ratio for each variable. Model calibration was assessed by the Hosmer-Lemeshow (H-L) statistic and by plotting observed vs. expected mortality (Figure below). Results: Of the 869, 35 (4.0%) died within 30-days of discharge. Twelve independent predictors of 30-day mortality were identified: admission pulse, systolic and diastolic BP, BNP, troponin-I, sodium, glucose, ALT, atrial fibrillation and absence of dyslipdemia diagnosis, and not admitted on an oral anticoagulant or a calcium channel blocker. All vartiables were assigned 1 risk point, except for not on an oral anticoagualnt, which was asigned two points. Patients with a risk score < 6 (57% of the group) had a mortality rate of only 0.4%, while a risk score > 6 (20% of the group) was associated with a 15.3% mortality, corresponding to a 49-fold range. Conclusion: 30-day mortality can be predicted by the developed risk score which has excellent discrimination (c-statistic = 0.87), adequate calibration (H-L = 0.11) and covers a mortality range from 0% to nearly 50%. This risk score also has the advantage of being easily calculated within 24 hours of admission. Validation of the model will be an important next step.

Abstract P83: Predictors of Length of Stay for HF Patients: Results from Get With the Guidelines

2011 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
David J Whellan ◽  
Xin Zhao ◽  
Adrian F Hernandez ◽  
Eric D Peterson ◽  
Deepak L Bhatt ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Length Of Stay ◽  
Vital Signs ◽  
P Value ◽  
Chi Square ◽  
Unit Increase ◽  
History Of ◽  
Multivariable Regression ◽  
Get With The Guidelines

Background: Heart failure (HF) admissions are frequent and result in significant expenditures. Identifying predictors of increased length of stay (LOS), particularly above the median LOS, may help providers set expectations for patients and target resources effectively. Methods: We analyzed HF admissions (n= 70,094) from January 2005 through April 2007 from 246 hospitals in the AHA's Get With The Guidelines-HF program. In a subset with BNP (n=44,535), baseline characteristics, admission vital signs and selected labs (BNP, creatinine, BUN, hemoglobin, and sodium) were included in a multivariable regression analysis to determine factors associated with LOS ≥4 days. Results: Patients were median age of 72, 45% female, 53% had ischemic etiology, and median LVEF was 35%. Median LOS was 4 days (25 th ,75 th 2,6). The most significant predictors of LOS ≥ 4 days were a higher admission BUN, higher heart rate, and lower SBP (Table 1). Age, insurance, race, creatinine, and LVEF were not. Conclusion: Upon admission for HF, certain vital signs, comorbidites, and laboratory values are associated with an increased likelihood of a LOS ≥ 4 days. These observations may be of value in the implementation of interventions aimed at reducing LOS and improving quality of care in HF. Variables Associated With Hospital LOS >/= 4 Days Variable Chi-Square OR Lower (95% CI) Upper (95% CI) P-value Admissioun BUN (/1 unit increase) 221.8 1.01 1.01 1.01 <.001 Admission SBP (/ 10-unit increase) 129.6 0.96 0.95 0.96 <.001 Heart Rate (/ 10-unit increase) 122.4 1.07 1.06 1.09 <.001 History of COPD/Asthma 45.8 1.19 1.13 1.25 <.001 Admission BNP (per 100-unit increase) 37.6 1.01 1.00 1.01 <.001 Female vs. Male 29.7 1.12 1.08 1.17 <.001 History of renal insufficiency 27.4 1.17 1.10 1.24 <.001 History of heart failure 18.0 0.89 0.85 0.94 <.001 Region: (MW vs. NE)
 (S vs NE)
 (W vs. NE) 17.3 0.71
 0.91
 0.71 0.60
 .077
 0.56 0.85
 1.08
 0.88 <.001

Prognostic Value of Cardiac Troponin I In Infective Endocarditis

2021 ◽  
Vol 23 (Supplement_D) ◽  
Author(s):  
Salma M Thabet ◽  
Marwa Meshaal ◽  
Yasser Yazied ◽  
Yasser Sharaf
Keyword(s):  
Heart Failure ◽  
Infective Endocarditis ◽  
Cardiac Troponin ◽  
Prognostic Value ◽  
Troponin I ◽  
Cardiac Troponin I ◽  
P Value ◽  
Significant Relation ◽  
P Values ◽  
Septic Pulmonary Embolism

Abstract Aim The aim of this study is to assess the prognostic value of cardiac troponin I as a predictor of in-hospital morbidity and mortality in patients with infective endocarditis. Methods This study included 48 patients with definite and possible IE according to modified Duke’s criteria for diagnosis of IE. This prospective longitudinal study was conducted on patients admitted to the cardiovascular department of Cairo University hospitals. All patients were subjected to full history taking and clinical examination, all laboratory and radiological investigations which included chest radiography, echocardiogram and other diagnostic procedures as needed for diagnosis and follow-up of IE were done with emphasis on cardiac troponin I level on admission. Results Troponin I was found to be statistically significant predictor for heart failure (NYHA III/IV), septic pulmonary embolism and in-hospital mortality in infective endocarditis patients by univariate and multivariate regression analysis with P values 0.023, 0.037and 0.002 respectively. Tricuspid valve vegetations had showed significant relation to troponin I levels with p value 0.033. Also it was found that SOFA score on first day of admission showed significant relation to troponin I level with P value 0.045 and 0.004 for prediction of hospital stay duration. Shock and intracranial hemorrhage showed borderline significance with P values 0.097, 0.069. On other hand, troponin I as predictor of pulmonary edema, mechanical complications, systemic embolization, acute kidney injury and presence of aortic root abscess had no statistical significance in our studied patients. Conclusions This study showed that there is as significant predictive value of elevated cardiac troponin I with heart failure, septic pulmonary embolism and all cause in-hospital mortality. In addition, it was significant predictor of the length of hospital stay, lymphocytosis and SOFA score. These results are emphasizing that cTn I level may predict higher risk patients who would need early and aggressive control of infection medically alone or combined with surgery in IE patients.

scholarly journals Improving risk stratification in heart failure with preserved ejection fraction by combining two validated risk scores

Open Heart ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. e000961 ◽  
Author(s):  
Kalyani Anil Boralkar ◽  
Yukari Kobayashi ◽  
Kegan J Moneghetti ◽  
Vedant S Pargaonkar ◽  
Mirela Tuzovic ◽  
...  
Keyword(s):  
Heart Failure ◽  
Ejection Fraction ◽  
Risk Score ◽  
Multivariable Analysis ◽  
Laboratory Data ◽  
Primary Diagnosis ◽  
Risk Scores ◽  
Preserved Ejection Fraction ◽  
Hospitalised Patients ◽  
All Cause Mortality

IntroductionThe Intermountain Risk Score (IMRS) was developed and validated to predict short-term and long-term mortality in hospitalised patients using demographics and commonly available laboratory data. In this study, we sought to determine whether the IMRS also predicts all-cause mortality in patients hospitalised with heart failure with preserved ejection fraction (HFpEF) and whether it is complementary to the Get with the Guidelines Heart Failure (GWTG-HF) risk score or N-terminal pro-B-type natriuretic peptide (NT-proBNP).Methods and resultsWe used the Stanford Translational Research Integrated Database Environment to identify 3847 adult patients with a diagnosis of HFpEF between January 1998 and December 2016. Of these, 580 were hospitalised with a primary diagnosis of acute HFpEF. Mean age was 76±16 years, the majority being female (58%), with a high prevalence of diabetes mellitus (36%) and a history of coronary artery disease (60%). Over a median follow-up of 2.0 years, 140 (24%) patients died. On multivariable analysis, the IMRS and GWTG-HF risk score were independently associated with all-cause mortality (standardised HRs IMRS (1.55 (95% CI 1.27 to 1.93)); GWTG-HF (1.60 (95% CI 1.27 to 2.01))). Combining the two scores, improved the net reclassification over GWTG-HF alone by 36.2%. In patients with available NT-proBNP (n=341), NT-proBNP improved the net reclassification of each score by 46.2% (IMRS) and 36.3% (GWTG-HF).ConclusionIMRS and GWTG-HF risk scores, along with NT-proBNP, play a complementary role in predicting outcome in patients hospitalised with HFpEF.

scholarly journals Performance Assessment Across Different Care Settings of A Novel Heart Failure Hospitalisation Risk Score For Type 2 Diabetes Patients Developed Using Administrative Claims Only

2021 ◽  
Author(s):  
Alessandro Guazzo ◽  
Enrico Longato ◽  
Giovanni Sparacino ◽  
Bruno Franco-Novelletto ◽  
Maurizio Cancian ◽  
...  
Keyword(s):  
Heart Failure ◽  
Type 2 Diabetes ◽  
Risk Score ◽  
Cox Regression ◽  
Cardiovascular Complications ◽  
P Value ◽  
Administrative Claims ◽  
Administrative Dataset ◽  
Heart Failure Hospitalisation

Abstract Predicting the risk of cardiovascular complications, in particular heart failure hospitalisation (HHF), can improve the management of type 2 diabetes (T2D). Most predictive models proposed so far rely on clinical data not available at the higher Institutional level. Therefore, it is of interest to assess the risk of HHF in people with T2D using administrative claims data only, which are more easily obtainable and could allow public health systems to identify high-risk individuals. In this paper, the administrative claims of >175,000 patients with T2D were used to develop a new risk score for HHF based on Cox regression. Internal validation on the administrative data cohort yielded satisfactory results in terms of discrimination (max AUROC=0.792, C-index=0.786) and calibration (Hosmer-Lemeshow test p-value<0.05). The risk score was then tested on data gathered from two independent centers (one diabetes outpatient clinic and one primary care network) to demonstrate its applicability to different care settings in the medium-long term. Thanks to the large size and broad demographics of the administrative dataset used for training, the proposed model was able to predict HHF without significant performance loss concerning bespoke models developed within each setting using more informative, but harder-to-acquire clinical variables.

The effect of dapagliflozin across the spectrum of baseline risk: a post-hoc analysis of DAPA-HF

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
K.F Docherty ◽  
P.S Jhund ◽  
O Bengtsson ◽  
D.L Demets ◽  
S.E Inzucchi ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Primary Outcome ◽  
Cardiovascular Death ◽  
Baseline Risk ◽  
P Value ◽  
Funding Source ◽  
Composite Outcome ◽  
Primary Composite Outcome ◽  
Outcome Event

Abstract Background In DAPA-HF, compared to placebo, the sodium-glucose cotransporter 2 (SGLT-2) inhibitor, dapagliflozin, reduced the risk of cardiovascular death or worsening heart failure in patients with heart failure with reduced ejection fraction (HFrEF). The majority of patients in DAPA-HF reported mild functional limitation, however there is significant heterogeneity in prognosis among these patients. Purpose To examine the effect of dapagliflozin compared with placebo across the spectrum of baseline risk in DAPA-HF. Methods The primary composite outcome of DAPA-HF was time-to-first cardiovascular death or worsening heart failure event (hospitalization for heart failure or outpatient visit requiring intravenous therapy). We examined whether the effect of dapagliflozin was modified by baseline risk, as determined by the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure) risk score based upon 13 predictive variables giving a potential maximum score of 57. The number needed to treat (NNT) to over a median follow-up of 18.2 months was calculated by applying the overall relative risk reduction in DAPA-HF (26%, 95% CI 15–35) to the proportion of patients with a primary outcome event in the placebo group of each MAGGIC risk score category (defined by quintiles of score). Results The MAGGIC risk score was calculable for 4740 of 4744 patients in DAPA-HF. The median score was 22 (range 3–43). The event rate for the primary outcome was 7.2 per 100 patient-years in the lowest risk score quintile and 25.7 in the highest. A 1-point increase in score was associated with an 8% increase in the risk of a primary outcome event (p&lt;0.001). Dapagliflozin, compared to placebo, reduced the risk of the primary outcome across quintiles of the MAGGIC risk score (Figure - Interaction p value=0.69) and when the score was analysed as a continuous variable (Interaction p value=0.56). The NNT to prevent one primary event was 39 (95% CI 29–68) in the lowest quintile of risk scores, compared with 14 (11–25) in the highest quintile (Figure). Similar results were found for the individual components of the primary composite outcome and for all-cause mortality. Conclusions DAPA-HF included patients with a wide spectrum of risk. Treatment with dapagliflozin, compared to placebo, reduced the risk of cardiovascular death or worsening heart failure, irrespective of baseline risk as measured by the MAGGIC risk score. Funding Acknowledgement Type of funding source: Private company. Main funding source(s): DAPA-HF was funded by AstraZeneca

Plasma Proteomic Profile Predicts Survival in Heart Failure with Reduced Ejection Fraction

2021 ◽  
Author(s):  
Hongsheng Gui ◽  
Ruicong She ◽  
Jasmine Luzum ◽  
Jia Li ◽  
Timothy D. Bryson ◽  
...  
Keyword(s):  
Heart Failure ◽  
Ejection Fraction ◽  
Risk Stratification ◽  
Risk Score ◽  
Cox Regression ◽  
Clinical Score ◽  
Cardiovascular Death ◽  
Reduced Ejection Fraction ◽  
C Statistic ◽  
Kaplan Meier

Background - It remains unclear whether the plasma proteome adds value to established predictors in heart failure (HF) with reduced ejection fraction (HFrEF). We sought to derive and validate a plasma proteomic risk score for survival in HFrEF patients (HFrEF-PRS). Methods - Patients meeting Framingham criteria for HF with EF<50% were enrolled (n=1017) and plasma underwent SOMAscan® profiling (4453 targets). Patients were randomly divided 2:1 into derivation and validation cohorts. The HFrEF-PRS was derived using Cox regression of all-cause mortality adjusted for clinical score and N-Terminal pro-B-Type Natriuretic Peptide (NTproBNP), then was tested in the validation cohort. Risk stratification improvement was evaluated by C-statistic, integrated discrimination index (IDI), continuous net reclassification index (NRI), and median improvement in risk score (MIRS) for 1-year and 3-year mortality. Results - Participants' mean age was 68 years, 48% identified as African American, 35% were female and 296 deaths occurred. In derivation (n=681), 128 proteins associated with mortality, 8 comprising the optimized HFrEF-PRS. In validation (n=336) the HFrEF-PRS associated with mortality (hazard ratio (HR) =2.27 [95% Confidence interval (95%CI) 1.84-2.82], p =6.3x10 -14 ), Kaplan-Meier curves differed significantly between HFrEF-PRS quartiles ( p =2.2x10 -6 ), and it remained significant after adjustment for clinical score and NTproBNP (HR=1.37, 95%CI 1.05-1.79, p =0.021). The HFrEF-PRS improved metrics of risk stratification (C-statistic change=0.009, p =0.612; IDI=0.041, p =0.010; NRI=0.391, p =0.078; MIRS=0.039, p =0.016) and associated with cardiovascular death and HF phenotypes (e.g. 6-minute walk distance, EF change). Most HFrEF-PRS proteins had little known connection to HFrEF. Conclusions - A plasma multi-protein score improved risk stratification in HFrEF patients and identified novel candidates.

Abstract 17063: Enhanced Prediction of Heart Failure 30-Day Readmission Risk With Four Readily-Available Clinical Variables

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Nicholas Wettersten ◽  
Machelle Wilson ◽  
Kathleen Tong ◽  
Javier E López
Keyword(s):  
Heart Failure ◽  
Standard Of Care ◽  
Categorical Variables ◽  
P Value ◽  
Continuous Variables ◽  
Clinical Predictors ◽  
Clinical Variables ◽  
Academic Center ◽  
Multivariate Prediction ◽  
Readmission Risk

Introduction: Heart failure (HF) readmissions, with ~25% within 30 days of discharge, can be reduced with costly post-hospitalization interventions. Determining which patients will benefit from these interventions remains a critical challenge. Hypothesis: We aimed to devise a simple model to predict 30-day HF readmission risk. Methods: Patients ≥21 years of age admitted for HF to a single academic center from July 1st, 2008 to December 31st, 2009 were identified by billing codes for HF. Patients were excluded if they died within 90 days, were transferred, discharged to hospice or prison, or later admitted electively or for a surgical emergency not related to HF. Demographics, co-morbidities, laboratories, vitals, and discharge medications (27 variables) were tested as predictors for risk of 30 day readmission. First, independent univariate testing of categorical variables was performed utilizing a retention p-value of < 0.2. Next, continuous variables and retained categorical variables were tested in a multivariable model with retention of variables with p-value < 0.1. False discovery rate was controlled by the method of Benjamini and Hochberg. Statistical analyses were performed using SAS® software version 9.3. Results: Of 1253 HF admissions, 657 (55.8% men, age 60.9 ± 13.8 men, 66.8 ± 14.5 women) met criteria with complete data. Twenty percent were readmitted within 30 days. Odds for readmission increased 1.6% for every 100 pg/ml increase in BNP (p=0.082), 5.6% for each additional discharge medication (p=0.003), 200% if not discharged on an ACE-I/ARB (p=0.001), and 7% for every 10 mmHg increase in systolic blood pressure at discharge compared to admission (p=0.078). Conclusion: One laboratory value and 3 clinical variables were predictive of 30-day HF readmission risk in a multivariate prediction model. The 3 clinical predictors provoke the idea that “in hospital” care is a predictor and potential target for intervention to reduce 30-day readmission risk. Future validation studies should help define standard-of-care interventions that could still be improved to reduce readmission rates in HF patients as well as address the relative cost of more intense hospital interventions over outpatient interventions.

PIERS calculator- predicting adverse maternal outcome in preeclampsia

2017 ◽  
Vol 6 (4) ◽  
pp. 1200
Author(s):  
Shubha Srivastava ◽  
Bharti Chaudhary Parihar ◽  
Neha Jain
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Perinatal Outcome ◽  
Health Workers ◽  
Expectant Management ◽  
Maternal Outcome ◽  
P Value ◽  
Risk Category ◽  
Specialist Care ◽  
Laboratory Findings

Background: Preeclampsia is a multisystem, highly variable disorder unique to pregnancy. For preeclampsia arising remote from term, supportive and temporizing measures are used to improve perinatal outcome. However, the magnitude of the maternal risks associated with expectant management is unclear. The PIER (preeclampsia integrated estimate of risk) score is a recently designed tool which assesses maternal signs, symptoms, and laboratory findings to generate a valid and reliable algorithm for predicting maternal and perinatal outcome in patients with preeclampsia.Methods: The present study was a prospective hospital based observational study carried out in Department of Obstetrics and Gynecology, Sultania Zanana Hospital, Gandhi Medical College, Bhopal. A total of 125 women with preeclampsia who fulfilled the inclusion criteria were included in the study. Along with history and examination, all relevant and required investigations were done. The fullPIERS calculator was used to calculate the risk of adverse maternal outcome.Results: In the present study, 82(65.6%) women were in the low risk category and only 4 (4.87%) had adverse maternal outcome. High risk patients were 6 (4.8%) and amongst them 5 (83.33%) women had adverse maternal outcome (p-value <0.00001). The result was statistically significant in identifying high risk cases in our study.Conclusions: The fullPIERS calculator gave good results in prediction of adverse maternal outcome according to risk score in women with preeclampsia in our study. It will help the clinicians better manage the patients with preeclampsia specially remote from term and also help health workers in primary and secondary care centres to identify women who are or may become severely ill and who need specialist care and prevent delays in transporting these women to facilities where they can receive appropriate care.

P5451Catestatin and chronic heart failure patients with an acute decompensation event: clinical characteristics and 30-day all-cause mortality

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
J A Borovac ◽  
D Glavas ◽  
Z Susilovic Grabovac ◽  
D Rusic ◽  
L Stanisic ◽  
...  
Keyword(s):  
Heart Failure ◽  
Clinical Characteristics ◽  
Troponin I ◽  
High Sensitivity ◽  
Decompensated Heart Failure ◽  
Functional Class ◽  
P Value ◽  
Ckd Stage ◽  
All Cause Mortality ◽  
Acute Decompensation

Abstract Background Catestatin (CST) is a cardiovascular regulator with pleiotropic systemic functions that might affect the course of acutely decompensated heart failure (ADHF). Purpose To determine the association of serum CST with the 30-day all-cause mortality and to compare clinical and laboratory parameters between ADHF patients within the lowest vs. highest quartile of CST concentration. Methods Eighty-two consecutive ADHF patients, as adjudicated per ESC 2016 HF criteria, were enrolled in the study during 2018–2019. Results Mean age of the enrolled cohort was 70.8±9.3 years and 54.9% were women. Seventy percent of patients were in NYHA III functional class and nearly half had a reduced LVEF. Median CST value was 5.6 ng/mL (IQR 3, 12). During the 30-day follow-up, ten patients died (12.2%) due to all causes. CST levels were significantly higher among patients that died compared to survivors (21.9±6.3 vs. 10.2±1.5 ng/mL, p=0.0139, respectively). Patients in the highest CST quartile had higher mortality and disease burden accompanied by more prominent laboratory abnormalities, compared to patients in the lowest CST quartile. Compared groups did not significantly differ in terms of dosages and type of baseline HF pharmacotherapy. Table 1. Clinical characteristics Variable Lowest CST quartile (<3 ng/mL) Highest CST quartile (>12 ng/mL) p-value Age, years 72.8±8.3 70.0±7.9 0.281 Women, % 45.0 60.0 0.342 LVEF, biplane Simpson, % 39.0 41.0 0.645 30-day all-cause mortality, % 0.0 20.0 0.035 Mean NYHA functional class 2.83±0.38 3.21±0.42 0.007 Mean CKD stage, CKD-EPI 2.37±0.83 3.06±0.99 0.029 Mean arterial pressure, mmHg 99.7±17.8 100.1±19.2 0.953 NT-proBNP, pmol/L 535.3±522.4 1550.0±992.2 0.040 C-reactive protein, mg/L 9.37±7.47 32.90±18.35 0.015 High-sensitivity cardiac Troponin I, ng/L 20.60±18.05 30.02±27.38 0.256 Creatinine, μmol/L 102.9±38.9 150.6±91.2 0.038 Urea, mmol/L 9.6±3.5 14.3±7.1 0.012 Neutrophil-to-lymphocyte ratio 3.6±1.9 5.4±3.1 0.045 Hemoglobin, g/L 137.3±17.4 124.6±18.8 0.038 Figure 1. CST and 30-day mortality Conclusions Higher levels of catestatin measured during the hospitalization event among ADHF patients are associated with 30-day all-cause mortality and worse in-hospital profile thus might facilitate short-term prognosis. Acknowledgement/Funding None

scholarly journals Implications of the ACC/AHA risk score for prediction of heart failure: the Rotterdam Study

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Banafsheh Arshi ◽  
Jan C. van den Berge ◽  
Bart van Dijk ◽  
Jaap W. Deckers ◽  
M. Arfan Ikram ◽  
...  
Keyword(s):  
Heart Failure ◽  
Primary Prevention ◽  
Risk Score ◽  
Heart Association ◽  
Risk Scores ◽  
Study Cohort ◽  
Rotterdam Study ◽  
Cox Models ◽  
Net Reclassification Improvement ◽  
C Statistic

Abstract Background Despite the growing burden of heart failure (HF), there have been no recommendations for use of any of the primary prevention models in the existing guidelines. HF was also not included as an outcome in the American College of Cardiology/American Heart Association (ACC/AHA) risk score. Methods Among 2743 men and 3646 women aged ≥ 55 years, free of HF, from the population-based Rotterdam Study cohort, 4 Cox models were fitted using the predictors of the ACC/AHA, ARIC and Health-ABC risk scores. Performance of the models for 10-year HF prediction was evaluated. Afterwards, performance and net reclassification improvement (NRI) for adding NT-proBNP to the ACC/AHA model were assessed. Results During a median follow-up of 13 years, 429 men and 489 women developed HF. The ARIC model had the highest performance [c-statistic (95% confidence interval [CI]): 0.80 (0.78; 0.83) and 0.80 (0.78; 0.83) in men and women, respectively]. The c-statistic for the ACC/AHA model was 0.76 (0.74; 0.78) in men and 0.77 (0.75; 0.80) in women. Adding NT-proBNP to the ACC/AHA model increased the c-statistic to 0.80 (0.78 to 0.83) in men and 0.81 (0.79 to 0.84) in women. Sensitivity and specificity of the ACC/AHA model did not drastically change after addition of NT-proBNP. NRI(95%CI) was − 23.8% (− 19.2%; − 28.4%) in men and − 27.6% (− 30.7%; − 24.5%) in women for events and 57.9% (54.8%; 61.0%) in men and 52.8% (50.3%; 55.5%) in women for non-events. Conclusions Acceptable performance of the model based on risk factors included in the ACC/AHA model advocates use of this model for prediction of HF risk in primary prevention setting. Addition of NT-proBNP modestly improved the model performance but did not lead to relevant discrimination improvement in clinical risk reclassification.

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