Key result
Multimodal assessment is required to reliably predict neurological outcomes in post-cardiac arrest syndrome.
Why the study?
Predicting neurological outcomes in post-cardiac arrest syndrome is urgent due to high mortality and severe neurological disorders, but no single highly sensitive and specific criterion exists.
A multimodal approach combining clinical, laboratory, and instrumental data is necessary for the accurate prognostication of neurological outcomes following cardiac arrest.
Multimodal neuroprognostication may inform post-arrest decisions; leaves open prospective validation of optimal parameters.
Post-cardiac arrest syndrome is an extremely complex nosology, characterized by high mortality and the development of severe neurological disorders. Predicting the neurological outcome in this pathology is an urgent problem, since it allows determining the tactics of patient management and optimizing the scope of medical care, as well as preparing the patient's family members for expected results of treatment. Currently, clinical, laboratory and instrumental data are used as predictors of an unfavorable neurological outcome (e.g., pupillary responses, neuron-specific enolase levels, electroencephalography). There is no single criterion with high sensitivity and specificity for predicting neurological disorders; therefore, a multimodal approach is required. This article discusses several factors, the combination of which allows predicting the outcome of post-cardiac arrest syndrome with the greatest degree of reliability.
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Маркова et al. (2021) conducted a review in Post-cardiac arrest syndrome. Multimodal approach for predicting neurological outcomes was evaluated on Neurological outcome. A multimodal approach combining clinical, laboratory, and instrumental data is required to reliably predict neurological outcomes in patients with post-cardiac arrest syndrome.
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