Heart Failure Epidemiology Analysis and Forecast to 2032

• 1. Heart Failure: Executive Summary
• 1.1 Catalyst
• 1.2 Related reports
• 1.3 Upcoming reports
• 2. Epidemiology
• 2.1 Disease background
• 2.2 Risk factors and comorbidities
• 2.3 Global and historical trends
• 2.4 7MM forecast methodology

  • 2.4.1 Sources
  • 2.4.2 Forecast assumptions and methods.
  • 2.4.3 Forecast assumptions and methods: diagnosed incident cases of HF – 7MM
  • 2.4.4 Forecast assumptions and methods: diagnosed incident cases of HF by EF
  • 2.4.5 Forecast assumptions and methods: hospitalizations for acute HF.
  • 2.4.6 Forecast assumptions and methods: acute HF hospitalizations based on presentation.
  • 2.4.7 Forecast assumptions and methods: hospital LoS days for acute HF hospitalizations.
  • 2.4.8 Forecast assumptions and methods: re-admissions within 30 days post-discharge after acute HF hospitalization.
  • 2.4.9 Forecast assumptions and methods: diagnosed prevalent cases of HF – 7MM.
  • 2.4.10 Forecast assumptions and methods: diagnosed prevalent cases of HF by EF
  • 2.4.11 Forecast assumptions and methods: diagnosed prevalent cases of HF by NYHA classes.
  • 2.4.12 Forecast assumptions and methods: diagnosed prevalent cases of HF-PEF (LVEF ≥50%) by NYHA class.
  • 2.4.13 Forecast assumptions and methods: diagnosed prevalent cases of HF-mrEF (LVEF = 40–49%) by NYHA class
  • 2.4.14 Forecast assumptions and methods: diagnosed prevalent cases of HF-REF (LVEF <40%) by NYHA class.
  • 2.4.15 Forecast assumptions and methods: diagnosed prevalent cases of HF by ACCF/AHA stages.

• 2.5 Epidemiological forecast for heart failure (2022–32)

  • 2.5.1 Diagnosed incident cases of HF.
  • 2.5.2 Age-specific diagnosed incident cases of HF
  • 2.5.3 Sex-specific diagnosed incident cases of HF
  • 2.5.4 Diagnosed incident cases of HF by EF
  • 2.5.5 Hospitalizations for acute HF
  • 2.5.6 Acute HF hospitalizations based on presentation.
  • 2.5.7 Hospital LoS for acute HF
  • 2.5.8 Re-admissions within 30 days post-discharge after acute HF
  • 2.5.9 Diagnosed prevalent cases of HF.
  • 2.5.10 Age-specific diagnosed prevalent cases of HF
  • 2.5.11 Sex-specific diagnosed prevalent cases of HF
  • 2.5.12 Diagnosed prevalent cases of HF by EF
  • 2.5.13 Diagnosed prevalent cases of HF by NYHA classes
  • 2.5.14 Diagnosed prevalent cases of HF-PEF (LVEF ≥50%) by NYHA class
  • 2.5.15 Diagnosed prevalent cases of HF-mrEF (LVEF = 40–49%) by NYHA class
  • 2.5.16 Diagnosed prevalent cases of HF-REF (LVEF <40%) by NYHA class.
  • 2.5.17 Diagnosed prevalent cases of HF by ACCF/AHA stages.

• 2.6 Discussion

  • 2.6.1 Epidemiological forecast insight
  • 2.6.2 COVID-19 impact.
  • 2.6.3 Limitations of the analysis
  • 2.6.4 Strengths of the analysis

• 3. Appendix
• 3.1 Bibliography
• 3.2 About the Authors

  • 3.2.1 Epidemiologist
  • 3.2.2 Reviewers
  • 3.2.3 Vice President of Disease Intelligence and Epidemiology

• 4. Contact Us

Table 1: Summary of newly added data types

Table 2: Summary of updated data types

Table 3: Risk factors and comorbidities for HF

Figure 1: 7MM, diagnosed incident cases of HF, both sexes, N, all ages, 2022 and 2032

Figure 2: 7MM, diagnosed prevalent cases of HF, both sexes, N, ages ≥40 years, 2022 and 2032

Figure 3: 7MM, diagnosed incidence of HF (cases per 100,000 population), men and women, all ages, 2022

Figure 4: 7MM, diagnosed prevalence of HF (%), men and women, all ages, 2022

Figure 5: 7MM, sources used and not used to forecast the diagnosed incident cases of HF

Figure 6: 7MM, sources used to forecast the diagnosed incident cases of HF by EF

Figure 7: 7MM, sources used to forecast the hospitalizations for acute HF

Figure 8: 7MM, sources used to forecast the hospitalizations for acute HF by presentation

Figure 9: 7MM, sources used to forecast the hospital LoS for acute HF

Figure 10: 7MM, sources used to forecast the re-admissions within 30 days post-discharge after acute HF hospitalization

Figure 11: 7MM, sources used to forecast the diagnosed prevalent cases of HF

Figure 12: 7MM, sources used to forecast the diagnosed prevalent cases of HF by EF

Figure 13: 7MM, sources used to forecast the diagnosed prevalent cases of HF by NYHA classes

Figure 14: 7MM, sources used to forecast the diagnosed prevalent cases of HF-PEF, HF-mrEF, and HF-REF by NYHA class

Figure 15: 7MM, sources used to forecast the diagnosed prevalent cases of HF by ACCF/AHA stages

Figure 16: 7MM, diagnosed incident cases of HF, N, both sexes, all ages, 2022

Figure 17: 7MM, diagnosed incident cases of HF by age, N, both sexes, 2022

Figure 18: 7MM, diagnosed incident cases of HF by sex, N, all ages, 2022

Figure 19: 7MM, diagnosed incident cases of HF by EF, N, both sexes, all ages, 2022

Figure 20: 7MM, hospitalizations for acute HF, N, both sexes, all ages, 2022

Figure 21: 7MM, acute HF hospitalizations based on presentation, N, both sexes, all ages, 2022

Figure 22: 7MM, hospital LoS for acute HF, days, both sexes, all ages, 2022

Figure 23: 7MM, re-admissions within 30 days post-discharge after acute HF hospitalization, N, both sexes, all ages, 2022

Figure 24: 7MM, diagnosed prevalent cases of HF, N, both sexes, all ages, 2022

Figure 25: 7MM, diagnosed prevalent cases of HF by age, N, both sexes, 2022

Figure 26: 7MM, diagnosed prevalent cases of HF by sex, N, all ages, 2022

Figure 27: 7MM, diagnosed prevalent cases of HF by EF, N, both sexes, all ages, 2022

Figure 28: 7MM, diagnosed prevalent cases of HF by NYHA classes, N, both sexes, all ages, 2022

Figure 29: 7MM, diagnosed prevalent cases of HF-PEF (LVEF ≥50%) by NYHA class, N, both sexes, all ages, 2022

Figure 30: 7MM, diagnosed prevalent cases of HF-mrEF (LVEF = 40–49%) by NYHA class, N, both sexes, all ages, 2022

Figure 31: 7MM, diagnosed prevalent cases of HF-REF (LVEF <40%) by NYHA class, N, both sexes, all ages, 2022

Figure 32: 7MM, diagnosed prevalent cases of HF by ACCF/AHA stages, N, both sexes, all ages, 2022