ArticleEClinicalMedicine2022
Development and validation of an interpretable prehospital return of spontaneous circulation (P-ROSC) score for patients with out-of-hospital cardiac arrest using machine learning: A retrospective study.
Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Influencing factors analysis and prediction model development for ROSC in adult non-traumatic OHCA: a retrospective study based on pre-hospital emergency settings.Annals of medicine · 2026Article
- Spatial heterogeneity in risk-adjusted return of spontaneous circulation after out-of-hospital cardiac arrest: the urbanization-adjusted RACA model.BMC emergency medicine · 2026Article
- External validation of the Prehospital Return of Spontaneous Circulation (P-ROSC) score for predicting prehospital return of spontaneous circulation among patients with out-of-hospital cardiac arrest.Resuscitation plus · 2026Article
- [Regression analysis to calculate the time point of ROSC-A feasibility study].Die Anaesthesiologie · 2026Article
- Survival outcomes following prehospital intubation in nontraumatic out of hospital cardiac arrest in Bangkok Thailand.Scientific reports · 2026Observational
- Artificial intelligence in medicine: a position paper by the Italian Society of Internal Medicine.Internal and emergency medicine · 2026Article
- Use of artificial intelligence in the out-of-hospital care settings: a scoping review.BMJ digital health & AI · 2026Article
- Leveraging AI and transfer learning to enhance out-of-hospital cardiac arrest outcome prediction in diverse setting.NPJ digital medicine · 2025Article
- Association between endotracheal intubation and outcomes of nonshockable out-of-hospital cardiac arrest in Japan.BMC emergency medicine · 2025Article
- Comparison of return of spontaneous circulation prediction scores in patients with cardiac arrest during ambulance transport.BMC emergency medicine · 2025Article
- Utilization of non-invasive ventilation before prehospital emergency anesthesia in trauma - a cohort analysis with machine learning.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025Article
- Which Matters More for Out-of-Hospital Cardiac Arrest Survival: Witnessed Arrest or Bystander Cardiopulmonary Resuscitation?Journal of the American Heart Association · 2025Article
- P-ROSC, UB-ROSC, and RACA Scores in Predicting the Return of Spontaneous Circulation in Out-of-hospital Cardiac Arrest: A Retrospective Cohort.Archives of academic emergency medicine · 2025Article
- LC risk score - development and evaluation of a scale for assessing the risk of developing long COVID.Archives of medical science : AMS · 2025Article
- External Validation and Comparison of Statistical and Machine Learning-Based Models in Predicting Outcomes Following Out-of-Hospital Cardiac Arrest: A Multicenter Retrospective Analysis.Journal of the American Heart Association · 2024Article
- The short- and mid-term mortality trends in out-of-hospital cardiac arrest survivors: insights from a 5-year multicenter retrospective study in Taiwan.Resuscitation plus · 2024Article
- The Current Discussion Regarding End-of-Life Care for Patients with Out-of-Hospital Cardiac Arrest with Initial Non-Shockable Rhythm: A Narrative Review.Medicina (Kaunas, Lithuania) · 2024Review
- Artificial intelligence to support out-of-hospital cardiac arrest care: A scoping review.Resuscitation plus · 2023Article
- Machine learning pre-hospital real-time cardiac arrest outcome prediction (PReCAP) using time-adaptive cohort model based on the Pan-Asian Resuscitation Outcome Study.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Return of spontaneous circulation (ROSC) before arrival at the emergency department is an early indicator of successful resuscitation in out-of-hospital cardiac arrest (OHCA). Several ROSC prediction scores have been developed with European cohorts, with unclear applicability in Asian settings. We aimed to develop an interpretable prehospital ROSC (P-ROSC) score for ROSC prediction based on patients with OHCA in Asia. Methods: This retrospective study examined patients who suffered from OHCA between Jan 1, 2009 and Jun 17, 2018 using data recorded in the Pan-Asian Resuscitation Outcomes Study (PAROS) registry. AutoScore, an interpretable machine learning framework, was used to develop P-ROSC. On the same cohort, the P-ROSC was compared with two clinical scores, the RACA and the UB-ROSC. The predictive power was evaluated using the area under the curve (AUC) in the receiver operating characteristic analysis. Findings: 170,678 cases were included, of which 14,104 (8.26%) attained prehospital ROSC. The P-ROSC score identified a new variable, prehospital drug administration, which was not included in the RACA score or the UB-ROSC score. Using only five variables, the P-ROSC score achieved an AUC of 0.806 (95% confidence interval [CI] 0.799-0.814), outperforming both RACA and UB-ROSC with AUCs of 0.773 (95% CI 0.765-0.782) and 0.728 (95% CI 0.718-0.738), respectively. Interpretation: The P-ROSC score is a practical and easily interpreted tool for predicting the probability of prehospital ROSC. Funding: This research received funding from SingHealth Duke-NUS ACP Programme Funding (15/FY2020/P2/06-A79).
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