English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background Despite perpetual improvement in post cardiac arrest (CA) care, a substantial number of patients with CA remain comatose after rewarming from targeted temperature management (TTM) and sedation discontinuation. Many patients in this situation eventually die, usually after withdrawal of life-sustaining treatment (WLST) due to a poor neurological prognosis [1, 2]. Neuroprognostication after cardiac arrest relies on a multimodal approach in which clinical examination, neurophysiological tools (electroencephalogram, somatosensory evoked potentials), biomarkers (neuron-specific enolase and S-100β) and brain imaging (computed tomography scan and magnetic resonance imaging) can be used in various combination for which the input mode is a confirmed postanoxic comatose state [3, 4]. However, these clinical and ancillary tests recommended in guidelines for neuroprognostication after CA were chiefly validated in retrospective studies of heterogeneous patient populations [5] potentially responsible for selection biases.

Neurological prognostication after cardiac arrest: how the “Best CPC” project would overcome selection biases