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市場調查報告書

EpiCast Report:心臟衰竭 (HF) - 至2025年的流行病學預測

EpiCast Report: Heart Failure - Epidemiology Forecast to 2025

出版商 GlobalData 商品編碼 258692
出版日期 內容資訊 英文 77 Pages
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EpiCast Report:心臟衰竭 (HF) - 至2025年的流行病學預測 EpiCast Report: Heart Failure - Epidemiology Forecast to 2025
出版日期: 2016年05月01日 內容資訊: 英文 77 Pages
簡介

在全球主要7個國家 (美國、法國、德國、義大利、西班牙、英國、日本),心臟衰竭 (HF) 確診的發病數量,預計從2015年的1,094,344件,增加到2025年的1,400,377件,以2.80%的年度成長率 (AGR) 增加。

本報告提供全球主要7個國家的心臟衰竭 (HF) 調查分析,疾病的背景,危險因素和合併症,全球趨勢,流行病學預測等相關的系統性資訊。

第1章 目錄

第2章 流行病學

  • 疾病的背景
  • 危險因素和合併症
  • 全球趨勢
    • 美國
    • EU5個國家
    • 日本
  • 預測手法
    • 利用之資訊來源
    • 預測的前提條件與手法
    • 未利用之資訊來源
  • 心臟衰竭 (HF) 的流行病學預測
    • 確診的發病數量
    • 確診的患者數
  • 討論
    • 流行病學預測相關考察
    • 分析的限制
    • 分析的優勢

第3章 附錄

圖表

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目錄
Product Code: GDHCER117-16

Heart Failure (HF), 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. HF commonly occurs in people above 50 years of age, and severity increases progressively with age. Symptoms can develop quickly, such as in acute HF, at which time the patient needs to be hospitalized. However, in chronic HF, the symptoms develop gradually. Due to the chronic nature of cardiovascular diseases, many of the risk factors for HF, such as chronic obstructive pulmonary disease (COPD) and anemia, are also comorbid conditions.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of HF will increase from 1,094,344 cases in 2015 to 1,400,377 cases in 2025 at an Annual Growth Rate (AGR) of 2.80%. In the 7MM, GlobalData epidemiologists forecast that the diagnosed prevalent cases of chronic HF will increase from 13,756,453 cases in 2015 to 16,105,489 cases in 2025 at an AGR of 1.71%. The US will have the highest number of diagnosed incident cases of HF and diagnosed prevalent cases of chronic HF among the 7MM throughout the forecast period with 1,052,831 diagnosed incident cases of HF and 6,170,142 diagnosed prevalent cases of chronic HF in 2025. In the 7MM in 2015, 37.59% of the diagnosed prevalent cases of chronic HF are in NYHA Class I, 39.54% in NYHA Class II, 19.11% in NYHA Class III, and 3.75% in NYHA Class IV.

GlobalData epidemiologists utilized comprehensive, country-specific data from national HF registers and peer-reviewed journal articles to arrive at a meaningful, in-depth analysis and forecast for the diagnosed incident cases of HF, as well as the diagnosed prevalent cases of chronic HF. In this analysis, GlobalData epidemiologists provide detailed, clinically relevant segmentations for diagnosed incident and diagnosed prevalent cases of HF. Finally, the same forecast methodology was used across the 7MM, thereby allowing for meaningful global comparisons of the diagnosed incident and diagnosed prevalent cases of HF across these markets.

Scope

  • The Heart Failure (HF) EpiCast Report provides an overview of the risk factors and global trends of HF in the 7MM (US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiology forecast of HF diagnosed incident and diagnosed prevalent cases segmented by age and sex. Diagnosed incident cases are further segmented by ejection fraction, ventricular dysfunction, acute HF hospitalizations (by worsening HF, advanced HF, de novo HF), re-admissions (within 3 months) post-discharge after acute HF hospitalization, and hospital length of stay for acute HF hospitalization in these seven markets. Diagnosed prevalent cases are further segmented by chronic HF (by ejection fraction), and also classified according to the New York Heart Association (NYHA) functional classes I-IV, and American College of Cardiology Foundation/American Heart Association (ACCF/AHA) stages B, C and D in these seven markets.
  • 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 HF 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.
  • Identify the percentage of HF diagnosed incident and diagnosed prevalent cases by various clinical segmentations.

Table of Contents

1. Table of Contents

  • 1.1. List of Tables
  • 1.2. List of Figures

2. Epidemiology

  • 2.1. Disease Background
  • 2.2. Risk Factors and Comorbidities
  • 2.3. Global Trends
    • 2.3.1. US
    • 2.3.2. 5EU
    • 2.3.3. Japan
  • 2.4. Forecast Methodology.
    • 2.4.1. Sources Used Tables
    • 2.4.2. Forecast Assumptions and Methods
    • 2.4.3. Sources Not Used
  • 2.5. Epidemiological Forecast for HF (2015-2025)
    • 2.5.1. Diagnosed Incident Cases
    • 2.5.2. Diagnosed Prevalent Cases
  • 2.6. Discussion
    • 2.6.1. Epidemiological Forecast Insight
    • 2.6.2. Limitations of the Analysis
    • 2.6.3. Strengths of the Analysis

3. Appendix

  • 3.1. Bibliography
  • 3.2. About the Authors
    • 3.2.1. Epidemiologists
    • 3.2.2. Reviewers
    • 3.2.3. Global Director of Therapy Analysis and Epidemiology
    • 3.2.4. Global Head of Healthcare
  • 3.3. About GlobalData
  • 3.4. About EpiCast
  • 3.5. Disclaimer

List of Tables

  • Table 1: Risk Factors and Comorbidities for HF
  • Table 2: NYHA Functional Classes I-IV
  • Table 3: ACCF/AHA Stages A, B, C, and D
  • Table 4: 7MM, Sources of Epidemiological Data Used for the Forecast of HF Diagnosed Incident Cases
  • Table 5: 7MM, Sources of Epidemiological Data Used for the Forecast of Chronic HF Diagnosed Prevalent Cases
  • Table 6: 7MM, Sources of Epidemiological Data Used for the Classification of Diagnosed Prevalent Cases of Chronic HF According to the NYHA Functional Classes I-IV
  • Table 7: 7MM, Sources of Epidemiological Data Used for Forecast of HF Diagnosed Incident Cases of Acute HF Hospitalizations
  • Table 8: 7MM, Sources Not Used in Epidemiological Analysis of HF
  • Table 9: 7MM, Diagnosed Incident Cases of HF, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Table 10: 7MM, Age-Specific Diagnosed Incident Cases of HF, Both Sexes, N (Row %), 2015
  • Table 11: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages ≥45 Years, N (Row %), 2015
  • Table 12: 7MM, Diagnosed Incident Cases of Acute HF Hospitalizations, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Table 13: 7MM, Readmissions (Within Three Months) Post-Discharge After Acute HF Hospitalization Among Diagnosed Incident Cases of Acute HF, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Table 14: 7MM, Diagnosed Prevalent Cases of Chronic HF, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Table 15: 7MM, Age-Specific Diagnosed Prevalent Cases of Chronic HF, Both Sexes, N (Row %), 2015
  • Table 16: 7MM, Sex-Specific Diagnosed Prevalent Cases of Chronic HF, Ages ≥45 Years, N (Row %), 2015

List of Figures

  • Figure 1: 7MM, Diagnosed Incident Cases of HF, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Figure 2: 7MM, Diagnosed Incident Cases of HF by Age Group, Both Sexes, N, 2015
  • Figure 3: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages ≥45 Years, N, 2015
  • Figure 4: 7MM, Age-Standardized Diagnosed Incidence of HF (Cases per 100,000 Population), Ages ≥45 Years, by Sex, 2015
  • Figure 5: 7MM, Diagnosed Incident Cases of HF Segmented by EF, Ages ≥45 Years, Both Sexes, N, 2015
  • Figure 6: 7MM, Diagnosed Incident Cases of HF Segmented by Ventricular Dysfunction, Ages ≥45 Years, Both Sexes, N, 2015
  • Figure 7: 7MM, Diagnosed Incident Cases of Acute HF Hospitalizations, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Figure 8: 7MM, Diagnosed Incident Cases of Acute HF Hospitalizations, Ages ≥45 Years, Both Sexes, N, 2015
  • Figure 9: 7MM, Readmissions (Within Three Months) Post-Discharge After Acute HF Hospitalization Among Diagnosed Incident Cases of Acute HF, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Figure 10: 7MM, Hospital Length Of Stay For Acute HF Hospitalization, Ages ≥45 Years, Both Sexes, Days, 2015
  • Figure 11: 7MM, Diagnosed Prevalent Cases of Chronic HF, Ages ≥45 Years, Both Sexes, N, 2015-2025
  • Figure 12: 7MM, Age-Specific Diagnosed Prevalent Cases of Chronic HF, Both Sexes, N, 2015
  • Figure 13: 7MM, Sex-Specific Diagnosed Prevalent Cases of Chronic HF, Ages ≥45 Years, N, 2015
  • Figure 14: 7MM, Age-Standardized Diagnosed Prevalence of Chronic HF (%), Ages ≥45 Years, by Sex, 2015
  • Figure 15: 7MM, Diagnosed Prevalent Cases of Chronic HF Segmented by EF, Ages ≥45 Years, Both Sexes, N, 2015
  • Figure 16: 7MM, Diagnosed Prevalent Cases of Chronic HF Segmented by NYHA Classes, Ages ≥45 Years, Both Sexes, N, 2015
  • Figure 17: 7MM, Diagnosed Prevalent Cases of Chronic HF Segmented by ACCF/AHA Stages, Ages ≥45 Years, Both Sexes, N, 2015
  • Figure 18: 7MM, Prevalent Cases of Comorbidities Among Diagnosed Prevalent Cases of Chronic HF, Both Sexes, Ages ≥45 Years, N, 2015
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