title: Dynamic prediction of patient outcomes during ongoing cardiopulmonary resuscitation.
abstract: The probability of the return of spontaneous circulation (ROSC) and subsequent favourable outcomes changes dynamically during advanced cardiac life support (ACLS). We sought to model these changes using time-to-event analysis in out-of-hospital cardiac arrest (OHCA) patients.
  
  
  
  Adult (≥18 years old), non-traumatic OHCA patients without prehospital ROSC were included. Utstein variables and initial arterial blood gas measurements were used as predictors. The incidence rate of ROSC during the first 30min of ACLS in the emergency department (ED) was modelled using spline-based parametric survival analysis. Conditional probabilities of subsequent outcomes after ROSC (1-week and 1-month survival and 6-month neurologic recovery) were modelled using multivariable logistic regression. The ROSC and conditional probability models were then combined to estimate the likelihood of achieving ROSC and subsequent outcomes by providing k additional minutes of effort.
  
  
  
  A total of 727 patients were analyzed. The incidence rate of ROSC increased rapidly until the 10th minute of ED ACLS, and it subsequently decreased. The conditional probabilities of subsequent outcomes after ROSC were also dependent on the duration of resuscitation with odds ratios for 1-week and 1-month survival and neurologic recovery of 0.93 (95% CI: 0.90-0.96, p<0.001), 0.93 (0.88-0.97, p=0.001) and 0.93 (0.87-0.99, p=0.031) per 1-min increase, respectively. Calibration testing of the combined models showed good correlation between mean predicted probability and actual prevalence.
  
  
  
  The probability of ROSC and favourable subsequent outcomes changed according to a multiphasic pattern over the first 30min of ACLS, and modelling of the dynamic changes was feasible.
authors.affiliation: Department of Emergency Medicine, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea. Electronic address: dremkks@snubh.org.
authors.forename: Joonghee
authors.initials: J
authors.lastname: Kim
authors.affiliation: Department of Emergency Medicine, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea.
authors.forename: Kyuseok
authors.initials: K
authors.lastname: Kim
authors.affiliation: Department of Emergency Medicine, University of Pittsburgh, Iroquois Building, Suite 400 A, 3600 Forbes Avenue, Pittsburgh, PA 15261, United States.
authors.forename: Clifton W
authors.initials: CW
authors.lastname: Callaway
authors.affiliation: Medical Device Research and Development Center, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea.
authors.forename: Kibbeum
authors.initials: K
authors.lastname: Doh
authors.affiliation: Department of Emergency Medicine, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea.
authors.forename: Jungho
authors.initials: J
authors.lastname: Choi
authors.affiliation: Department of Emergency Medicine, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea.
authors.forename: Jongdae
authors.initials: J
authors.lastname: Park
authors.affiliation: Department of Emergency Medicine, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea.
authors.forename: You Hwan
authors.initials: YH
authors.lastname: Jo
authors.affiliation: Department of Emergency Medicine, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea.
authors.forename: Jae Hyuk
authors.initials: JH
authors.lastname: Lee
mesh_terms: D000368:Aged; D016887:Cardiopulmonary Resuscitation; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D058687:Out-of-Hospital Cardiac Arrest / Q000401:mortality / Q000628:therapy; D012044:Regression Analysis; D016896:Treatment Outcome
keywords: Advanced cardiac life support; Cardiopulmonary resuscitation; Cerebral ischaemia; Prognosis