We are indebted to our Japanese colleagues for translating the entire book so that it may reach a larger audience.
The project was supervised by:
Dr. Shigeki Fujitani
Dr. Kazuaki Atagi
Dr. Masatoshi Okumura
Specific chapters were translated by:
Dr. Masatoshi Okumura(Chapters 1,2,3)
Dr. Shinsuke Fujiwara(Chapters 4,5)
Dr. Hiromu Naraba (Chapters 6,7,8)
Dr. Kohei Yamada (Chapters 9,10)
Dr. Yoshihisa Fujimoto (Chapters 11,12)
Dr. Junichiro Iio (Chapters 13,14)
Dr. Shota Tanabe (Chapters 15,16)
Dr. Yasunobu Goto (Chapters 17,18)
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Devita M a, Bellomo R, Hillman K, et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med. 2006;34(9):2463-2478. http://www.ncbi.nlm.nih.gov/pubmed/16878033
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Hillman K, Chen J, Cretikos M, et al. Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet. 2005;365(9477):2091-2097. http://www.ncbi.nlm.nih.gov/pubmed/15964445
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Cretikos M, Parr M, Hillman K, et al. Guidelines for the uniform reporting of data for Medical Emergency Teams. Resuscitation. 2006;68(1):11-25. http://www.ncbi.nlm.nih.gov/pubmed/16153768
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Peberdy MA, Cretikos M, Abella BS, et al. Recommended guidelines for monitoring, reporting, and conducting research on medical emergency team, outreach, and rapid response systems: an Utstein-style scientific statement. A Scientific Statement from the International Liaison Committee on Resuscitat. Resuscitation. 2007;75(3):412-433. http://www.ncbi.nlm.nih.gov/pubmed/17993369
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DeVita M a, Smith GB, Adam SK, et al. “Identifying the hospitalised patient in crisis”–a consensus conference on the afferent limb of rapid response systems. Resuscitation. 2010;81(4):375-382. http://www.ncbi.nlm.nih.gov/pubmed/20149516
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National Institute for Health and Care Excellence. (NICE)
Acutely ill adults in hospital: recognising and responding to deterioration. https://www.nice.org.uk/guidance/cg50
Accessed on September 26th, 2016.
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Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.
Crit Care Med. 2016 Feb; 44(2): 368–374 http://www.ncbi.nlm.nih.gov/pubmed/26771782
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Real-Time Risk Prediction on the Wards: A Feasibility Study.
Crit Care Med. 2016 Aug;44(8):1468-73. doi: 10.1097/CCM.0000000000001716 http://www.ncbi.nlm.nih.gov/pubmed/27075140
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Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning.
Acute and Critical Care 2018 August 33(3):117-120 https://www.accjournal.org/journal/view.php?number=1142
Accessed on May 22th, 2019.
説明
Deep learning EWSは、高精度かつ低誤警報で心停止を予測する。DEWSは、あらゆる臨床環境で容易に取得できる4つのバイタルサインと精度を上げるための検査結果を用いる。
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Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting: Retrospective Cohort Study.
Ann Surg. 2018 Jan 12. doi: 10.1097/SLA.0000000000002665.
Annals of Surgery. 269(6):1059–1063, JUN 2019 http://www.ncbi.nlm.nih.gov/pubmed/31082902
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An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest.
J Am Heart Assoc. 2018;7:e008678. DOI: 10.1161/JAHA.118.008678. http://www.ncbi.nlm.nih.gov/pubmed/29945914
DNAR(do not attempt resuscitation)の定義は患者本人または患者の利益にかかわる代理者の意思決定をうけて心肺蘇生法をおこなわないことです。
ただし,患者ないし代理者へのinformed consentと社会的な患者の医療拒否権の保障が前提となります。欧米では実施のためのガイドラインも公表されています。
1995年日本救急医学会救命救急法検討委員会から「DNRとは尊厳死の概念に相通じるもので,癌の末期,老衰,救命の可能性がない患者などで,本人または家族の希望で心肺蘇生法(CPR)をおこなわないこと」,「これに基づいて医師が指示する場合をDNR指示(do not resuscitation order)という」との定義が示されています。
しかし,わが国の実情はいまだ患者の医療拒否権について明確な社会合意が形成されたとはいい難く,またDNR実施のガイドラインも公的な発表はなされていません。
なおAHA Guideline 2000では,DNRが蘇生する可能性が高いのに蘇生治療は施行しないとの印象を持たれ易いとの考えから,attemptを加え,蘇生に成功することがそう多くない中で蘇生のための処置を試みない用語としてDNAR(do not attempt resuscitation)が使用されています。
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The Medical Emergency Team System and not-for-resuscitation orders: results from the MERIT study
Resuscitation. 2008 Dec;79(3):391-7. doi: 10.1016/j.resuscitation.2008.07.021. Epub 2008 Oct 25. http://www.ncbi.nlm.nih.gov/pubmed/18952354
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Enhanced end-of-life care associated with deploying a rapid response team: a pilot study.
J Hosp Med. 2009 Sep;4(7):449-52. doi: 10.1002/jhm.451 http://www.ncbi.nlm.nih.gov/pubmed/19753581
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Rapid response team calls to patients with a pre-existing not for resuscitation order
The rapid response system and end-of-life care.
Curr Opin Crit Care. 2013 Dec;19(6):616-23. doi: 10.1097/MCC.0b013e3283636be2. http://www.ncbi.nlm.nih.gov/pubmed/19753581
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The medical emergency team call: a sentinel event that triggers goals of care discussion
Crit Care Med. 2014 Feb;42(2):322-7. doi: 10.1097/CCM.0b013e3182a27413. http://www.ncbi.nlm.nih.gov/pubmed/23989179
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Pre-existing risk factors for in-hospital death among older patients could be used to initiate end-of-life discussions rather than Rapid Response System calls: A case-control study.
Resuscitation. 2016 Dec;109:76-80. doi: 10.1016/j.resuscitation.2016.09.031. Epub 2016 Oct 18. http://www.ncbi.nlm.nih.gov/pubmed/27769903
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Who Benefits from Aggressive Rapid Response System Treatments Near the End of Life? A Retrospective Cohort Study.
Jt Comm J Qual Patient Saf. 2018 Sep;44(9):505-513. doi: 10.1016/j.jcjq.2018.04.001. Epub 2018 Jun 27. http://www.ncbi.nlm.nih.gov/pubmed/30166034