| Project/Area Number |
15K10989
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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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| Research Field |
Emergency medicine
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| Research Institution | The University of Tokyo (2017)
Yokohama City University (2015-2016) |
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Principal Investigator |
Morimura Naoto 東京大学, 医学部附属病院, 教授 (20239685)
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| Co-Investigator(Kenkyū-buntansha) |
後藤 隆久 横浜市立大学, 医学研究科, 教授 (00256075)
坂本 哲也 帝京大学, 医学部, 教授 (40365979)
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| Research Collaborator |
OHI Yasufumi
SAKAI Takuma
SATO Kousuke
NOGAKI Ayako
SHINOHARA Mahumi
MATSUMOTO Jun
ABE Takeshi
FUJII Hiroto
DOI Tomoki
MUGURUMA Takashi
HARUNARI Nobuyuki
IMAKI Shouhei
TAKEUCHI Ichiro
|
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | 毛細血管再充満時間 / Capillary refill time / 敗血症 / 組織還流 / ショック / モニタリング / capillary refill time / 解析・評価 / 救命 |
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| Outline of Final Research Achievements |
By applying the principle of pulse oximeter, capillary refilling time (Q-CRT) and absorbance change (ΔAb) quantified from transmitted light change of near-infrared light and red light before and after nail bed compression and blood lactate values or sepsis were examined. Ambulatory outpatient medical cases, the ΔAb value was significantly lower in the lactic acid value≧2mmol/L group than in the 2mmol/L group, the sensitivity for predicting hyperlactatemia was 64%, the specificity was 75% It was. Q-CRT cut-off value in sepsis prediction is 3.3 seconds, sensitivity is 55%, specificity 82%. The prediction precision was equivalent to q - SOFA and showed higher specificity than SIRS. ΔAb is an excellent indicator for diagnosis of hyperlactatemia, and it was shown that Q-CRT is a useful parameter for prediction of sepsis.
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