Serum neuron-specific enolase as predictor of outcome in comatose cardiac-arrest survivors: a prospective cohort study
2011

Predicting Outcomes in Comatose Cardiac Arrest Survivors Using Serum Neuron-Specific Enolase

Sample size: 97 publication 10 minutes Evidence: high

Author Information

Author(s): Daubin Cédric, Quentin Charlotte, Allouche Stéphane, Etard Olivier, Gaillard Cathy, Seguin Amélie, Valette Xavier, Parienti Jean-Jacques, Prevost Fabrice, Ramakers Michel, Terzi Nicolas, Charbonneau Pierre, du Cheyron Damien

Primary Institution: CHU de Caen

Hypothesis

Can serum neuron-specific enolase (NSE) predict death or vegetative state in comatose cardiac-arrest survivors?

Conclusion

Higher levels of serum NSE in comatose patients after cardiac arrest are associated with poor outcomes, and a cut-off value of 97 ng/mL can predict such outcomes with high accuracy.

Supporting Evidence

  • 74% of patients had a poor outcome (CPC 4-5) at 3 months.
  • NSE levels at 24 h and 72 h were significantly higher in patients with poor outcomes.
  • A cut-off value of 97 ng/mL for NSE predicted poor outcomes with 100% specificity.
  • An approach combining NSE, SSEPs, and clinical-EEG tests identified 88% of patients with poor outcomes.

Takeaway

Doctors can check a blood test for a substance called NSE to see if someone who is unconscious after a heart problem might not get better. If the NSE level is really high, it means they might not wake up.

Methodology

A prospective observational cohort study was conducted in two hospitals, measuring serum NSE levels at 24 and 72 hours after cardiac arrest and assessing outcomes at 3 months.

Potential Biases

The study's design may introduce bias as clinicians were blinded to NSE results, but the lack of informed consent could affect the generalizability of the findings.

Limitations

The study had a relatively small sample size and potential biases due to the observational nature and the lack of informed consent.

Participant Demographics

The study included 97 patients, predominantly male (77%), with an average age of 57 years.

Statistical Information

P-Value

p<0.0001

Confidence Interval

[95% CI = 87-100]

Statistical Significance

p<0.0001

Digital Object Identifier (DOI)

10.1186/1471-2261-11-48

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