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급성 저산소뇌병증의 예후 예측인자로서확산강조영상의 역할

Role of Diffusion-Weighted Imaging as a Prognostic Indicator in Acute Hypoxic Encephalopathy

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초록

Background: Diffusion-weighted image (DWI) might be useful to predict the prognosis of acute hypoxic encephalopathy. The aim of our study was to test whether the early change and extent of DWI abnormalities can be an indicator of the clinical outcome of hypoxic encephalopathy. Methods: Forty-four patients who were diagnosed as hypoxic encephalopathy due to the cardiorespiratory arrest were retrospectively identified. Clinical variables were determined, and the DWI abnormalities were counted by four areas: cortex, subcortical white matter, cerebellum and deep grey matter, and were divided into three groups by the extent of lesions. Prognosis was classified as 'poor' (Glasgow coma scale (GSC) at 30 days after arrest <9 or death) and 'good' (GSC at 30 days after arrest ≥9). Results: GCS at day 3 (p<0.001), presence of seizure (p=0.01), and presence of lesion (p<0.001) were significantly different in prognosis, but statistically there is no association with the extent of lesions and prognosis (p=0.26). Conclusions: Presence of early DWI changes could predict the clinical outcome of hypoxic encephalopathy after cardiorespiratory arrest.

Abstract

Background: Diffusion-weighted image (DWI) might be useful to predict the prognosis of acute hypoxic encephalopathy. The aim of our study was to test whether the early change and extent of DWI abnormalities can be an indicator of the clinical outcome of hypoxic encephalopathy. Methods: Forty-four patients who were diagnosed as hypoxic encephalopathy due to the cardiorespiratory arrest were retrospectively identified. Clinical variables were determined,and the DWI abnormalities were counted by four areas: cortex, subcortical white matter, cerebellum and deep grey matter, and were divided into three groups by the extent of lesions. Prognosis was classified as 'poor' (Glasgow coma scale (GSC) at 30 days after arrest <9 or death) and 'good' (GSC at 30 days after arrest ≥9). Results: GCS at day 3 (p<0.001), presence of seizure (p=0.01), and presence of lesion (p<0.001) were significantly different in prognosis,but statistically there is no association with the extent of lesions and prognosis (p=0.26). Conclusions: Presence of early DWI changes could predict the clinical outcome of hypoxic encephalopathy after cardiorespiratory arrest.

참고문헌 (28)

  1. Pusswald G, "Neurological rehabilitation of severely disabled cardiac arrest survivors. Part II. Life situation of patients and families after treatment", Resuscitation, 47, pp.241~248 (2000)
  2. Levy DE, "Predicting outcome from hypoxic-ischemic coma", JAMA, 253, pp.1420~1426 (1985)
  3. Nikolov NM, "Mild therapeutic hypothermia to improve the neurologic outcome after cardiac arrest", N Engl J Med, 346, pp.549~556 (2002)
  4. Bernard SA, "Treatment of comatose survivors of out-ofhospital cardiac arrest with induced hypothermia", N Engl J Med, 346, pp.557~563 (2002)
  5. Wijdicks EF, "Practice parameter: prediction of outcome in comatose survivors after cardiopulmonary resuscitation (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology", Neurology, 67, pp.203~210 (2006)
  6. Wijdicks EF, "MR imaging in comatose survivors of cardiac resuscitation", AJNR, 22, pp.1561~1565 (2001)
  7. Rossetti AO, "Prognosti-cation after cardiac arrest and hypothermia: a prospective study", Ann Neurol, 67, pp.301~307 (2010)
  8. Samaniego EA, "Sedation confounds outcome prediction in cardiac arrest survivors treated with hypothermia", Neurocrit Care, 15, pp.113~119 (2011)
  9. Koenig MA, "Clinical neurophysiologic monitoring and brain injury from cardiac arrest", Neurol Clin, 24, pp.89~106 (2006)
  10. Zandbergen EG, "SSEPs and prognosis in postanoxic coma: only short or also long latency responses?", Neurology, 67, pp.583~586 (2006)
  11. Fugate JE, "Predictors of neurologic outcome in hypothermia after cardiac arrest", Ann Neurol, 68, pp.907~914 (2010)
  12. Zandbergen EG, "Systematic review of prediction of poor outcome in anoxic-ischaemic coma with biochemical markers of brain damage", Intensive Care Med, 27, pp.1661~1667 (2001)
  13. Greer D, "Serial MRI changes in comatose cardiac arrest patients", Neurocrit Care, 14, pp.61~67 (2011)
  14. Topcuoglu MA, "Prognostic value of magnetic resonance imaging in post-resuscitation encephalopathy", Intern Med, 48, pp.1635~1645 (2009)
  15. Choi SP, "Diffusion-weighted magnetic resonance imaging for predicting the clinical outcome of comatose survivors after cardiac arrest: a cohort study", Crit Care, 14, pp.R17~ (2010)
  16. Wu O, "Comatose patients with cardiac arrest: predicting clinical outcome with diffusion-weighted MR imaging", Radiology, 252, pp.173~181 (2009)
  17. Greer D, "Clinical MRI interpretation for outcome prediction in cardiac arrest", Neurocrit Care, 17, pp.240~244 (2012)
  18. Rossetti AO, "Status epilepticus: an independent outcome predictor after cerebral anoxia", Neurology, 69, pp.255~260 (2007)
  19. Chen R, "Prediction of outcome in patients with anoxic coma: a clinical and electrophysiologic study", Crit Care Med, 24, pp.672~678 (1996)
  20. Young GB, "Continuous EEG monitoring in comatose intensive care patients: epileptiform activity in etiologically distinct groups", Neurocrit Care, 2, pp.5~10 (2005)
  21. Young GB, "EEG and clinical associations with mortality in comatose patients in a general intensive care unit", J Clin Neurophysiol, 16, pp.354~360 (1999)
  22. Kaplan PW, "Etiology, neurologic correlations, and prognosis in alpha coma", Clin Neurophysiol, 110, pp.205~213 (1999)
  23. Lee YC, "Accuracy of clinical signs, SEP, and EEG in predicting outcome of hypoxic coma: a meta-analysis", Neurology, 74, pp.572~580 (2010)
  24. Cunningham RT, "Serum neurone specific enolase (NSE) levels as an indicator of neuronal damage in patients with cerebral infarction", Eur J Clin Invest, 21, pp.497~500 (1991)
  25. Bottiger BW, "Astroglial protein S-100 is an early and sensitive marker of hypoxic brain damage and outcome after cardiac arrest in humans", Circulation, 103, pp.2694~2698 (2001)
  26. Shinozaki K, "S-100B and neuron-specific enolase as predictors of neurological outcome in patients after cardiac arrest and return of spontaneous circulation: a systematic review", Crit Care, 13, pp.R121~ (2009)
  27. Arbelaez A, "Diffusion-weighted MR imaging of global cerebral anoxia", AJNR, 20, pp.999~1007 (1999)
  28. Wijman CA, "Prognostic value of brain diffusion-weighted imaging after cardiac arrest", Ann Neurol, 65, pp.394~402 (2009)

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