| Project/Area Number |
18K08122
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 53020:Cardiology-related
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| Research Institution | Hokkaido University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | 心不全 / 国際比較 / 予後モデル |
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| Outline of Final Research Achievements |
We simultaneously accessed to individual patient-level data in registry of hospitalized heart failure (HHF) between Japan and the United Kingdom (UK). As a consequence, The UK HHF patients had worse clinical outcome compared to those in Japan even after adjustment for prognostic covariates. Also, the calibration of published prediction models derived from United States (US) HHF patients appeared moderately accurate and unbiased when applied to British patients but consistently overestimated mortality in Japan. Furthermore, we compared national claim databases in Japan, Taiwan, UK and US to clarify differences in patient characteristics, healthcare resource utilization (HRU) and clinical outcomes of patients with HHF. Importantly, the rate of HRU during hospitalization was the highest in Japan among all countries. Moreover, Japanese HHF patients had longer length of hospital stay, higher in-hospital mortality, while lower 30-days readmission rate compared to other countries.
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| Academic Significance and Societal Importance of the Research Achievements |
人種や医療システムの異なる多国間（特にアジア欧米間）では心不全患者の臨床像、治療などの診療実態が大きく異なることから、普遍的な予後予測モデルを作成・適用することが困難であることが示唆され、同様の人種・食生活・医療システムを持つ集団毎に予後予測モデルを作成し、検証してゆく必要性があると考えられる。また、わが国では入院中に多くの医療資源（特に侵襲的検査・治療等）が使用されており、その是非を検証する研究を行うことで医療費削減につながる可能性がある。
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