Pub Date : 2026-01-07DOI: 10.1016/j.resuscitation.2026.110956
Jerry P. Nolan, Claudio Sandroni, Markus B. Skrifvars
{"title":"Reply to: Post-resuscitation care: myocardial dysfunction is the main cause of haemodynamic instability, not vasodilation","authors":"Jerry P. Nolan, Claudio Sandroni, Markus B. Skrifvars","doi":"10.1016/j.resuscitation.2026.110956","DOIUrl":"10.1016/j.resuscitation.2026.110956","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110956"},"PeriodicalIF":4.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145945697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1016/j.resuscitation.2026.110957
Maha Aly , Helen G. Liley
{"title":"The hidden complexity behind a ‘simple’ intervention in a multicentre trial: lessons from physiological-based umbilical cord clamping","authors":"Maha Aly , Helen G. Liley","doi":"10.1016/j.resuscitation.2026.110957","DOIUrl":"10.1016/j.resuscitation.2026.110957","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110957"},"PeriodicalIF":4.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145945725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1016/j.resuscitation.2026.110958
Johannes Wittig, Kasper Glerup Lauridsen
{"title":"Examining asynchronous intra-arrest ventilation through the prism of advanced airway devices – are all our tools equal?","authors":"Johannes Wittig, Kasper Glerup Lauridsen","doi":"10.1016/j.resuscitation.2026.110958","DOIUrl":"10.1016/j.resuscitation.2026.110958","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110958"},"PeriodicalIF":4.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145945559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Defibrillator deployment in France: time to put an end to the current anarchy. The ANAR-AED study","authors":"Bruno Thomas-Lamotte , Maël Blandin , Alexis Marouk , Nordine Benameur , Frédéric Lapostolle","doi":"10.1016/j.resuscitation.2026.110962","DOIUrl":"10.1016/j.resuscitation.2026.110962","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110962"},"PeriodicalIF":4.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145945554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1016/j.resuscitation.2026.110960
Demetris Yannopoulos , Deborah Jaeger , Rajat Kalra , Paul Rees , Charles Bruen , Alexandra Schick , Sergey Gurevich , Ganesh Raveendran , Adam Gottula , Jason Bartos
Extracorporeal cardiopulmonary resuscitation (ECPR) is the only therapy capable of rescuing patients from refractory cardiac arrest, but its effectiveness is critically dependent on time to reperfusion. The system proposed here, grounded in current physiologic and systems-level evidence, is designed to reliably achieve extracorporeal membrane oxygenation (ECMO) flow within approximately 45 min of collapse. This model emphasizes tightly organized, strike team–like ECPR units, parallel activation pathways, and predefined deployment and transport strategies independent of cannulation location. As ECPR systems evolve, integration of artificial intelligence–enabled dispatch and decision-support tools may further improve reliability, scalability, and equitable access to timely reperfusion.
{"title":"Survival on the clock: rethinking where and how we deliver ECPR","authors":"Demetris Yannopoulos , Deborah Jaeger , Rajat Kalra , Paul Rees , Charles Bruen , Alexandra Schick , Sergey Gurevich , Ganesh Raveendran , Adam Gottula , Jason Bartos","doi":"10.1016/j.resuscitation.2026.110960","DOIUrl":"10.1016/j.resuscitation.2026.110960","url":null,"abstract":"<div><div>Extracorporeal cardiopulmonary resuscitation (ECPR) is the only therapy capable of rescuing patients from refractory cardiac arrest, but its effectiveness is critically dependent on time to reperfusion. The system proposed here, grounded in current physiologic and systems-level evidence, is designed to reliably achieve extracorporeal membrane oxygenation (ECMO) flow within approximately 45 min of collapse. This model emphasizes tightly organized, strike team–like ECPR units, parallel activation pathways, and predefined deployment and transport strategies independent of cannulation location. As ECPR systems evolve, integration of artificial intelligence–enabled dispatch and decision-support tools may further improve reliability, scalability, and equitable access to timely reperfusion.</div></div>","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110960"},"PeriodicalIF":4.6,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145934570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Post-resuscitation care: myocardial dysfunction is the main cause of haemodynamic instability, not vasodilation","authors":"Bjørn Hoftun Farbu , Pål Klepstad , Halvor Langeland","doi":"10.1016/j.resuscitation.2025.110955","DOIUrl":"10.1016/j.resuscitation.2025.110955","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110955"},"PeriodicalIF":4.6,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145934600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-05DOI: 10.1016/j.resuscitation.2026.110961
Luiz E.V. Silva , Daniel Balcarcel , Tiffany S. Ko , Ryan W. Morgan , Robert A. Berg , Alexis Topjian , Fuchiang (Rich) Tsui , Matthew P. Kirschen
Aims
Heart rate variability (HRV), a non-invasive measure of autonomic function, may offer prognostic value after pediatric cardiac arrest. We used machine learning models to determine whether HRV features within the first 24 h after return of spontaneous circulation can predict outcomes in children following cardiac arrest, and whether adding clinical cardiac arrest characteristics improves model performance.
Methods
Retrospective study of children who received post-arrest care in the PICU at the Children’s Hospital of Philadelphia from 2020 to 2023. Thirty-six HRV features were extracted from ECG recordings and Extreme Gradient Boosting (XGB) models were trained to predict unfavorable neurological outcome, defined as Pediatric Cerebral Performance Category 4–6 and an increase >1 from baseline. Models were evaluated by cross-validation across the entire 24-h period and within sequential 6-h epochs. Additional models included clinical arrest characteristics. Performance was assessed by area under the receiver operating characteristic curve (AUROC).
Results
Of the 75 patients who met inclusion criteria (median age 6.8 [IQR 10.4] years), 51% had an unfavorable outcome. Model considering HRV features and age achieved an AUROC of 0.80 (95% CI: 0.68–0.88). Top HRV predictors included standard deviation (SDNN), power at very low and low frequency bands, entropy, and fractal scaling. Performance was similar across the 6-h epochs (p’s > 0.1). Adding cardiac arrest characteristics did not improve model performance (AUROC 0.83 [0.73–0.92], p > 0.41).
Conclusion
Using machine learning, HRV features within 24 h after pediatric cardiac arrest predict unfavorable outcome with AUROC 0.8. Adding clinical variables did not improve model performance.
{"title":"Prediction of neurological outcome after pediatric cardiac arrest using heart rate variability and machine learning","authors":"Luiz E.V. Silva , Daniel Balcarcel , Tiffany S. Ko , Ryan W. Morgan , Robert A. Berg , Alexis Topjian , Fuchiang (Rich) Tsui , Matthew P. Kirschen","doi":"10.1016/j.resuscitation.2026.110961","DOIUrl":"10.1016/j.resuscitation.2026.110961","url":null,"abstract":"<div><h3>Aims</h3><div>Heart rate variability (HRV), a non-invasive measure of autonomic function, may offer prognostic value after pediatric cardiac arrest. We used machine learning models to determine whether HRV features within the first 24 h after return of spontaneous circulation can predict outcomes in children following cardiac arrest, and whether adding clinical cardiac arrest characteristics improves model performance.</div></div><div><h3>Methods</h3><div>Retrospective study of children who received post-arrest care in the PICU at the Children’s Hospital of Philadelphia from 2020 to 2023. Thirty-six HRV features were extracted from ECG recordings and Extreme Gradient Boosting (XGB) models were trained to predict unfavorable neurological outcome, defined as Pediatric Cerebral Performance Category 4–6 and an increase >1 from baseline. Models were evaluated by cross-validation across the entire 24-h period and within sequential 6-h epochs. Additional models included clinical arrest characteristics. Performance was assessed by area under the receiver operating characteristic curve (AUROC).</div></div><div><h3>Results</h3><div>Of the 75 patients who met inclusion criteria (median age 6.8 [IQR 10.4] years), 51% had an unfavorable outcome. Model considering HRV features and age achieved an AUROC of 0.80 (95% CI: 0.68–0.88). Top HRV predictors included standard deviation (SDNN), power at very low and low frequency bands, entropy, and fractal scaling. Performance was similar across the 6-h epochs (<em>p</em>’s > 0.1). Adding cardiac arrest characteristics did not improve model performance (AUROC 0.83 [0.73–0.92], <em>p</em> > 0.41).</div></div><div><h3>Conclusion</h3><div>Using machine learning, HRV features within 24 h after pediatric cardiac arrest predict unfavorable outcome with AUROC 0.8. Adding clinical variables did not improve model performance.</div></div>","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110961"},"PeriodicalIF":4.6,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Another unknown in the adrenaline equation: impact of administration interval on cardiac arrest outcomes. The ADRE-TIME-LINE study","authors":"Maël Blandin, Alexis Marouk, Anne-Laure Feral-Pierssens, Frédéric Lapostolle","doi":"10.1016/j.resuscitation.2025.110954","DOIUrl":"10.1016/j.resuscitation.2025.110954","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"219 ","pages":"Article 110954"},"PeriodicalIF":4.6,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145897419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.resuscitation.2025.110947
Therese Djärv
{"title":"Reply to “Choking ’Witnessed but Untreated’ Since 1880: Are We Still Missing It?”","authors":"Therese Djärv","doi":"10.1016/j.resuscitation.2025.110947","DOIUrl":"https://doi.org/10.1016/j.resuscitation.2025.110947","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"4 1","pages":""},"PeriodicalIF":6.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145895428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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