@article {7140, title = {Predicting Heart Failure With Preserved and Reduced Ejection Fraction: The International Collaboration on Heart Failure Subtypes.}, journal = {Circ Heart Fail}, volume = {9}, year = {2016}, month = {2016 Jun}, abstract = {

BACKGROUND: Heart failure (HF) is a prevalent and deadly disease, and preventive strategies focused on at-risk individuals are needed. Current HF prediction models have not examined HF subtypes. We sought to develop and validate risk prediction models for HF with preserved and reduced ejection fraction (HFpEF, HFrEF).

METHODS AND RESULTS: Of 28,820 participants from 4 community-based cohorts, 982 developed incident HFpEF and 909 HFrEF during a median follow-up of 12 years. Three cohorts were combined, and a 2:1 random split was used for derivation and internal validation, with the fourth cohort as external validation. Models accounted for multiple competing risks (death, other HF subtype, and unclassified HF). The HFpEF-specific model included age, sex, systolic blood pressure, body mass index, antihypertensive treatment, and previous myocardial infarction; it had good discrimination in derivation (c-statistic 0.80; 95\% confidence interval [CI], 0.78-0.82) and validation samples (internal: 0.79; 95\% CI, 0.77-0.82 and external: 0.76; 95\% CI: 0.71-0.80). The HFrEF-specific model additionally included smoking, left ventricular hypertrophy, left bundle branch block, and diabetes mellitus; it had good discrimination in derivation (c-statistic 0.82; 95\% CI, 0.80-0.84) and validation samples (internal: 0.80; 95\% CI, 0.78-0.83 and external: 0.76; 95\% CI, 0.71-0.80). Age was more strongly associated with HFpEF, and male sex, left ventricular hypertrophy, bundle branch block, previous myocardial infarction, and smoking with HFrEF (P value for each comparison <=0.02).

CONCLUSIONS: We describe and validate risk prediction models for HF subtypes and show good discrimination in a large sample. Some risk factors differed between HFpEF and HFrEF, supporting the notion of pathogenetic differences among HF subtypes.

}, issn = {1941-3297}, doi = {10.1161/CIRCHEARTFAILURE.115.003116}, author = {Ho, Jennifer E and Enserro, Danielle and Brouwers, Frank P and Kizer, Jorge R and Shah, Sanjiv J and Psaty, Bruce M and Bartz, Traci M and Santhanakrishnan, Rajalakshmi and Lee, Douglas S and Chan, Cheeling and Liu, Kiang and Blaha, Michael J and Hillege, Hans L and van der Harst, Pim and van Gilst, Wiek H and Kop, Willem J and Gansevoort, Ron T and Vasan, Ramachandran S and Gardin, Julius M and Levy, Daniel and Gottdiener, John S and de Boer, Rudolf A and Larson, Martin G} } @article {7549, title = {Predictors and outcomes of heart failure with mid-range ejection fraction.}, journal = {Eur J Heart Fail}, year = {2017}, month = {2017 Dec 11}, abstract = {

AIMS: While heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF) are well described, determinants and outcomes of heart failure with mid-range ejection fraction (HFmrEF) remain unclear. We sought to examine clinical and biochemical predictors of incident HFmrEF in the community.

METHODS AND RESULTS: We pooled data from four community-based longitudinal cohorts, with ascertainment of new heart failure (HF) classified into HFmrEF [ejection fraction (EF) 41-49\%], HFpEF (EF >=50\%), and HFrEF (EF <=40\%). Predictors of incident HF subtypes were assessed using multivariable Cox models. Among 28 820 participants free of HF followed for a median of 12 years, there were 200 new HFmrEF cases, compared with 811 HFpEF and 1048 HFrEF. Clinical predictors of HFmrEF included age, male sex, systolic blood pressure, diabetes mellitus, and prior myocardial infarction (multivariable adjusted P~<= 0.003 for all). Biomarkers that predicted HFmrEF included natriuretic peptides, cystatin-C, and high-sensitivity troponin (P~<= 0.0004 for all). Natriuretic peptides were stronger predictors of HFrEF [hazard ratio (HR) 2.00 per 1 standard deviation increase, 95\% confidence interval (CI) 1.81-2.20] than of HFmrEF (HR 1.51, 95\% CI 1.20-1.90, P~= 0.01 for difference), and did not differ in their association with incident HFmrEF and HFpEF (HR 1.56, 95\% CI 1.41-1.73, P~= 0.68 for difference). All-cause mortality following the onset of HFmrEF was worse than that of HFpEF (50 vs. 39 events per 1000 person-years, P~= 0.02), but comparable to that of HFrEF (46 events per 1000 person-years, P~= 0.78).

CONCLUSIONS: We found overlap in predictors of incident HFmrEF with other HF subtypes. In contrast, mortality risk after HFmrEF was worse than HFpEF, and similar to HFrEF.

}, issn = {1879-0844}, doi = {10.1002/ejhf.1091}, author = {Bhambhani, Vijeta and Kizer, Jorge R and Lima, Jo{\~a}o A C and van der Harst, Pim and Bahrami, Hossein and Nayor, Matthew and de Filippi, Christopher R and Enserro, Danielle and Blaha, Michael J and Cushman, Mary and Wang, Thomas J and Gansevoort, Ron T and Fox, Caroline S and Gaggin, Hanna K and Kop, Willem J and Liu, Kiang and Vasan, Ramachandran S and Psaty, Bruce M and Lee, Douglas S and Brouwers, Frank P and Hillege, Hans L and Bartz, Traci M and Benjamin, Emelia J and Chan, Cheeling and Allison, Matthew and Gardin, Julius M and Januzzi, James L and Levy, Daniel and Herrington, David M and van Gilst, Wiek H and Bertoni, Alain G and Larson, Martin G and de Boer, Rudolf A and Gottdiener, John S and Shah, Sanjiv J and Ho, Jennifer E} }