| Project/Area Number |
17591889
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Emergency medicine
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| Research Institution | Hiroshima University |
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Principal Investigator |
TANIGAWA Koichi Hiroshima University, Graduate School of Biomedical sciences, Professor (90258624)
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| Co-Investigator(Kenkyū-buntansha) |
KAWAMOTO Masashi Hiroshima University, Graduate School of Biomedical sciences, Associate Professor (40127642)
SAKAI Hiroshi Hiroshima University, Graduate School of Biomedical sciences, Research Associate (40363072)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 2006: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2005: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | Intensive Care / Heart rate variability / cardiac arrest / prediction / Heart Rate Variability / 有害イベント |
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| Research Abstract |
We prospectively enrolled patients who were admitted to our ICU collecting HRV data in the PMS system. During one year study period from April 2006 through March 2007, 1346 patients were admitted to our ICU. Our data showed that increased LF/HF ratio was observed just before cardiac arrest, and suggested that increased activities of sympathetic nervous system may precede cardiac arrest. These results may indicate the possibility to predict unexpected cardiac arrest by monitoring LF/HF ratio. However, LF/HF ratio may increase in other patho-physiological status, and the specificity in predicting cardiac arrest would be discussed in comparison with these events. In addition, the patterns of LH/HF in such situations would require to be determined. The major obstacle in this study was the rarity of unexpected cardiac arrest in ICU. We experienced only two cases of unexpected cardiac arrest during the study period. The volume of data was apparently inadequate in order to obtain sufficient data. Once we obtain sufficient data, we would be able to develop a human information monitoring system which enables to predict fatal events such as cardiac arrest. For this goal, multi-center studies in collaboration with ICUs in other hospitals would be needed. The current PIMS system has several limitations i. e., data sampling frequency, accuracy in analyzing graphic data, and deviation in placement of ECG electrodes to patients. Ideal data sampling frequency would be 500Hz and relevant network systems would be desirable.
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