In-hospital cardiac arrest carries a grave prognosis, with survival to discharge in the range of 15-20%. Key factors determining outcome include the presenting cardiac rhythm, aetiology, and early initiation of resuscitation. Some cardiac rhythms benefit from defibrillation (shockable rhythms). During resuscitation patients may switch between shockable and non-shockable rhythms, and may show signs of spontaneous circulation temporarily. Depending on rhythm and according to guidelines, patients receive direct current (DC) shocks (defibrillator) and/or i.v. adrenaline, atropine and amiodarone, which may affect state-transitions. We wish to make statistical analysis (time-series analysis, Markov modelling) of these state-transitions and variations in hemodynamic variables during resuscitation, related to CPR interventions and the cause of arrest. The cause of arrest will be determined based on chart records, interview with staff and autopsy if appropriate. One hypothesis is that differences in the patterns of state-transitions may reflect underlying aetiology, which may guide in future decision-making during resuscitation.