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Heart Failure (HF) Market Analysis by Types (Chronic HF and Congestive HF) and Patient Distribution – Forecast 2026

Heart Failure (HF) Market Analysis by Types (Chronic HF and Congestive HF) and Patient Distribution – Forecast 2026

Orbis Research
OrbisResearch.com has published “EpiCast Report: Heart Failure-Epidemiology Forecasts to 2026” reports to its heavy database

Heart Failure (HF) Market, also referred to as congestive cardiac failure, is a heterogeneous condition in which the heart is unable to pump out sufficient blood to meet the metabolic needs of the body. Eventually, without the heart’s pumping action to deliver oxygen and nutrient-rich blood to the cells, fatigue, shortness of breath, and coughing results. Even everyday activities such as walking, climbing stairs, or carrying weight can become tedious.

To forecast the diagnosed incident cases of HF and diagnosed prevalent cases of chronic HF (CHF) in the 7MM, GlobalData epidemiologists selected the best available nationally representative data ascertained through an exhaustive literature search.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of HF will increase from 1,990,569 cases in 2016 to 2,468,827 cases in 2026 at an annual growth rate (AGR) of 2.40%. The US had the highest number of diagnosed incident cases of HF in the 7MM in both 2016 and 2026, at 827,525 cases in 2016, and 1,081,878 cases in 2026.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed prevalent cases of chronic HF (CHF) will increase from 14,403,423 cases in 2016 to 17,127,297 cases in 2026 at an AGR of 1.89%. The US had the highest number of diagnosed prevalent cases of CHF in the 7MM in both 2016 and 2026, at 5,816,242 cases in 2016, and 7,115,415 cases in 2026.

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Scope
– The Heart Failure (HF) EpiCast Report provides an overview of the risk factors and global trends of HF in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiological forecast for the diagnosed incident cases of HF, diagnosed incident cases of HF segmented by ejection fraction and ventricular dysfunction, acute HF hospitalizations, acute HF hospitalizations by worsening HF, advanced HF, and de novo HF, and acute HF hospitalization by patients admitted and discharged, hospital length of stay for acute HF hospitalization, diagnosed prevalent cases of chronic HF (CHF), and diagnosed prevalent cases of CHF segmented by ejection fraction. The diagnosed prevalent cases of CHF, CHF with REF, and CHF with PEF are further classified according to the New York Heart Association (NYHA) functional classes I-IV. The diagnosed incident cases of HF and diagnosed prevalent cases of CHF are segmented by age (at 10-year intervals, for ages 45 years and older) and sex.
– The HF epidemiology report is written and developed by Masters- and PhD-level epidemiologists.
– The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.

Reasons to buy
The Heart Failure EpiCast report will allow you to –
– Develop business strategies by understanding the trends shaping and driving the global HF market.
– Quantify patient populations in the global HF market to improve product design, pricing, and launch plans.
– Organize sales and marketing efforts by identifying the age groups and sex that present the best opportunities for HF therapeutics in each of the markets covered.
– Understand HF cases patient distribution by ejection fraction and NYHA functional classes.

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List of Figures
Figure 1: 7MM, Diagnosed Incident Cases of HF, Both Sexes, Ages ≥45 Years, 2016 and 2026 6
Figure 2: 7MM, Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ≥45 Years, 2016 and 2026 7
Figure 3: 7MM, Age-Standardized Diagnosed Incidence of HF (Cases per 100,000 Population), Men and Women, Ages ≥45 Years, 2016 11
Figure 4: 7MM, Age-Standardized Diagnosed Prevalence of CHF (%), Men and Women, Ages ≥45 Years, 2016 12
Figure 5: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF 14
Figure 6: 7MM, Sources Used and Not Used to Forecast Diagnosed Prevalent Cases of CHF 15
Figure 7: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF by EF 16
Figure 8: 7MM, Sources Used to Forecast Diagnosed Prevalent Cases of CHF by EF 17
Figure 9: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF by Ventricular Dysfunction 18
Figure 10: 7MM, Sources Used to Forecast Hospitalizations for Acute HF 19
Figure 11: 7MM, Sources Used to Forecast Hospitalizations for Acute HF by Worsening CHF, Advanced HF, and de novo 20
Figure 12: 7MM, Sources Used to Forecast Hospital Length of Stay for Acute HF Hospitalization 21
Figure 13: 7MM, Sources Used to Forecast Diagnosed Prevalent Cases of CHF by NYHA Class 22
Figure 14: 7MM, Age-Specific Diagnosed Incident Cases of HF, Both Sexes, Ages ≥45 Years, N, 2016 35
Figure 15: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages ≥45 Years, N, 2016 36
Figure 16: 7MM, Diagnosed Incident Cases of HF by EF, Both Sexes, Ages ≥45 Years, N, 2016 37
Figure 17: 7MM, Diagnosed Incident Cases of HF by VD, Both Sexes, Ages ≥45 Years, N, 2016 38
Figure 18: 7MM, Acute HF Hospitalizations, Both Sexes, Ages ≥45 Years, N, 2016 to 2026 39
Figure 19: 7MM, Acute HF Hospitalizations by Patients Admitted and Discharged, Both Sexes, Ages ≥45 Years, 2016 39

Related Reports By:

Chronic Heart Failure Global Clinical Trials Review, H1, 2017

http://www.orbisresearch.com/reports/index/chronic-heart-failure-global-clinical-trials-review-h1-2017

Congestive Heart Failure (Heart Failure) Global Clinical Trials Review, H1, 2017

http://www.orbisresearch.com/reports/index/congestive-heart-failure-heart-failure-global-clinical-trials-review-h1-2017 

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