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Prediction in Neurological Outcomes in Cardiac Arrest Patients Before Inducing Targeted Temperature Management: Validation of CAST or cCAST

  • Mitsuaki Nishikimi
Chapter

Abstract

Not only a patient’s family but also ICU physicians need information on the probability of a patient recovering from post-cardiac arrest syndrome (PCAS) before admitting to the intensive care unit (ICU) and initiating targeted temperature management (TTM). In this section, we introduced a novel prediction tool for evaluating the neurological prognosis in patients with PCAS before TTM, called a post-Cardiac Arrest Syndrome for Therapeutic hypothermia score (CAST) and condensed CAST (cCAST). They have been developed using retrospective analyses from data of 151 consecutive adult patients who were admitted to four hospitals within the last 5 years to undergo TTM after cardiac arrest. While the CAST was calculated by using eight factors and logistic regression formula, the cCAST was modified by, though using same factors, more simple formula. The cCAST of 3.5 or lower was associated with a 0.99 (95% CI, 0.94–1.00) sensitivity and a 0.73 (0.61–0.84) specificity predicting for a poor outcome and 6.5 or higher was with a 0.80 (0.71–0.88) and a 0.97 (0.89–1.00). The “cCAST” can be calculated more easily and is useful for estimating the prognosis of PCAS patients, describing patients’ conditions to their family and making the decision before the initiation of TTM, as with the original CAST.

Keywords

Post-cardiac arrest syndrome Neurological prognosis Targeted temperature management CAST cCAST 

Abbreviations

95% CI

95% confidence interval

CAST

Post-cardiac arrest syndrome for therapeutic hypothermia score

cCAST

condensed CAST

CPC

Cerebral performance categories

ED

Emergency department

GCS

Glasgow Coma Scale

GWR

Gray matter attenuation to white matter attenuation ratio

ICU

Intensive care unit

PCAS

Post-cardiac arrest syndrome

TTM

Targeted temperature management

References

  1. 1.
    Gajarski RJ, Smitko K, Despres R, Meden J, Hutton DW. Cost-effectiveness analysis of alternative cooling strategies following cardiac arrest. Springerplus. 2015;4:427.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Reynolds JC, Frisch A, Rittenberger JC, Callaway CW. Duration of resuscitation efforts and functional outcome after out-of-hospital cardiac arrest: when should we change to novel therapies? Circulation. 2013;128(23):2488–94.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Kaneko T, Kasaoka S, Nakahara T, Sawano H, Tahara Y, Hase M, et al. Effectiveness of lower target temperature therapeutic hypothermia in post-cardiac arrest syndrome patients with a resuscitation interval of </=30 min. J Intensive Care. 2015;3(1):28.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Seeger FH, Toenne M, Lehmann R, Ehrlich JR. Simplistic approach to prognosis after cardiopulmonary resuscitation-value of pH and lactate. J Crit Care. 2013;28(3):317 e313–20.CrossRefGoogle Scholar
  5. 5.
    Mullner M, Sterz F, Domanovits H, Behringer W, Binder M, Laggner AN. The association between blood lactate concentration on admission, duration of cardiac arrest, and functional neurological recovery in patients resuscitated from ventricular fibrillation. Intensive Care Med. 1997;23(11):1138–43.CrossRefPubMedGoogle Scholar
  6. 6.
    Kliegel A, Losert H, Sterz F, Holzer M, Zeiner A, Havel C, et al. Serial lactate determinations for prediction of outcome after cardiac arrest. Medicine (Baltimore). 2004;83(5):274–9.CrossRefGoogle Scholar
  7. 7.
    Grossestreuer AV, Abella BS, Leary M, Perman SM, Fuchs BD, Kolansky DM, et al. Time to awakening and neurologic outcome in therapeutic hypothermia-treated cardiac arrest patients. Resuscitation. 2013;84(12):1741–6.CrossRefPubMedGoogle Scholar
  8. 8.
    Golan E, Barrett K, Alali AS, Duggal A, Jichici D, Pinto R, et al. Predicting neurologic outcome after targeted temperature management for cardiac arrest: systematic review and meta-analysis. Crit Care Med. 2014;42(8):1919–30.CrossRefPubMedGoogle Scholar
  9. 9.
    Young GB. Clinical practice. Neurologic prognosis after cardiac arrest. N Engl J Med. 2009;361(6):605–11.CrossRefPubMedGoogle Scholar
  10. 10.
    Oddo M, Rossetti AO. Early multimodal outcome prediction after cardiac arrest in patients treated with hypothermia. Crit Care Med. 2014;42(6):1340–7.CrossRefPubMedGoogle Scholar
  11. 11.
    Hayakawa K, Tasaki O, Hamasaki T, Sakai T, Shiozaki T, Nakagawa Y, et al. Prognostic indicators and outcome prediction model for patients with return of spontaneous circulation from cardiopulmonary arrest: the Utstein Osaka project. Resuscitation. 2011;82(7):874–80.CrossRefPubMedGoogle Scholar
  12. 12.
    Goto Y, Maeda T, Goto Y. Decision-tree model for predicting outcomes after out-of-hospital cardiac arrest in the emergency department. Crit Care. 2013;17(4):R133.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Adrie C, Cariou A, Mourvillier B, Laurent I, Dabbane H, Hantala F, et al. Predicting survival with good neurological recovery at hospital admission after successful resuscitation of out-of-hospital cardiac arrest: the OHCA score. Eur Heart J. 2006;27(23):2840–5.CrossRefPubMedGoogle Scholar
  14. 14.
    Nishikimi M, Matsuda N, Matsui K, Takahashi K, Ejima T, Liu K, et al. CAST: a new score for early prediction of neurological outcomes after cardiac arrest before therapeutic hypothermia with high accuracy. Intensive Care Med. 2016;42(12):2106–7.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Nishikimi M, Matsuda N, Matsui K, Takahashi K, Ejima T, Liu K, et al. A novel scoring system for predicting the neurologic prognosis prior to the initiation of induced hypothermia in cases of post-cardiac arrest syndrome: the CAST score. Scand J Trauma Resusc Emerg Med. 2017;25(1):49.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
  17. 17.
  18. 18.
    Takahashi N, Satou C, Higuchi T, Shiotani M, Maeda H, Hirose Y. Quantitative analysis of brain edema and swelling on early postmortem computed tomography: comparison with antemortem computed tomography. Jpn J Radiol. 2010;28(5):349–54.CrossRefPubMedGoogle Scholar
  19. 19.
    Nielsen N. Predictive scores, friend or foe for the cardiac arrest patient. Resuscitation. 2012;83(6):669–70.CrossRefPubMedGoogle Scholar
  20. 20.
    Metter RB, Rittenberger JC, Guyette FX, Callaway CW. Association between a quantitative CT scan measure of brain edema and outcome after cardiac arrest. Resuscitation. 2011;82(9):1180–5.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Aschauer S, Dorffner G, Sterz F, Erdogmus A, Laggner A. A prediction tool for initial out-of-hospital cardiac arrest survivors. Resuscitation. 2014;85(9):1225–31.CrossRefPubMedGoogle Scholar
  22. 22.
    Becker LB, Aufderheide TP, Geocadin RG, Callaway CW, Lazar RM, Donnino MW, et al. Primary outcomes for resuscitation science studies: a consensus statement from the American Heart Association. Circulation. 2011;124(19):2158–77.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Nielsen N, Wetterslev J, Cronberg T, Erlinge D, Gasche Y, Hassager C, et al. Targeted temperature management at 33 degrees C versus 36 degrees C after cardiac arrest. N Engl J Med. 2013;369(23):2197–206.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Mitsuaki Nishikimi
    • 1
  1. 1.Department of Emergency and Critical CareNagoya University Graduate School of MedicineNagoyaJapan

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