Unique ID issued by UMIN | UMIN000028958 |
---|---|
Receipt number | R000033133 |
Scientific Title | Prediction of cardiac arrest time of palliative care patients in the intensive care unit. A single center retrospective cohort study. |
Date of disclosure of the study information | 2017/09/02 |
Last modified on | 2022/09/07 10:06:21 |
Prediction of cardiac arrest time of palliative care patients in the intensive care unit. A single center retrospective cohort study.
Algorithm of predicticting time of cardiac arrest.
Prediction of cardiac arrest time of palliative care patients in the intensive care unit. A single center retrospective cohort study.
Algorithm of predicticting time of cardiac arrest.
Japan |
Terminal phase disease in the intensive care unit
Emergency medicine | Intensive care medicine |
Others
NO
The aim of this study is to predict cardiac arrest time in the terminal situation.
Efficacy
Conduction of predicting cardiac arrest time.
Observational
20 | years-old | <= |
Not applicable |
Male and Female
Patients who determined as terminal phase condition were enrolled to this study. Inclusion criteria is to confirm cardiac arrest with continuous arterial pressure monitoring in the intensive care unit.
Less than 20 years old, insufficient data were excluded.
20
1st name | Shunsuke |
Middle name | |
Last name | Takaki |
Yokohama City University Hospital
Intensive Care Unit
236-0004
3-9 Fukuura Kanazawaku Yokohama
045-787-2918
shunty5323@i.softbank.jp
1st name | ayako |
Middle name | |
Last name | higashijima |
Yokohama City University
Department of Critical Care
236-0004
3-9 Fukuura Kanazawaku Yokohama
045-787-2918
shunty5323@gmail.com
Yokohama City University
Self funding
Yokohama City University
Self funding
Yokohama City University Hospital
3-9 Fukuura Kanazawaku
08023779787
shunty5323@gmail.com
NO
済生会神奈川県病院
2017 | Year | 09 | Month | 02 | Day |
Unpublished
Enrolling by invitation
2017 | Year | 03 | Month | 01 | Day |
2017 | Year | 03 | Month | 29 | Day |
2017 | Year | 03 | Month | 30 | Day |
2023 | Year | 03 | Month | 31 | Day |
Analysis of retrospective data are runnning.
We enrolled saiseikai kanagawa prefecture hospital as new new institution for collecting data.
2017 | Year | 09 | Month | 01 | Day |
2022 | Year | 09 | Month | 07 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000033133