Clustering out-of-hospital cardiac arrest patients with non-shockable rhythm by machine learning latent class analysis.
Yohei OkadaSho KomukaiTetsuhisa KitamuraTakeyuki KiguchiTaro IrisawaTomoki YamadaKazuhisa YoshiyaChanghwi ParkTetsuro NishimuraTakuya IshibeYoshiki YagiMasafumi KishimotoToshiya InoueYasuyuki HayashiTaku SogabeTakaya MorookaHaruko SakamotoKeitaro SuzukiFumiko NakamuraTasuku MatsuyamaNorihiro NishiokaDaisuke KobayashiSatoshi MatsuiAtsushi HirayamaSatoshi YoshimuraShunsuke KimataTakeshi ShimazuShigeru OhtsuruTaku Iwaminull nullPublished in: Acute medicine & surgery (2022)
We identified four subphenotypes of OHCA patients with initial non-shockable rhythm. These patient subgroups presented with different characteristics associated with 30-day survival and neurological outcomes.