Pub Date : 2025-12-11DOI: 10.1016/j.resuscitation.2025.110922
Mika’il Visanji , Omar Dewidar , Theresa Aves , Katherine S. Allan , Meijiao Guan , Brian Grunau , Christopher B. Fordyce , Jim Christenson , Jennie Helmer , Jacob Hutton , Paul Dorian , Steve Lin
Background
Cardiac arrest researchers frequently use administrative health databases to study out-of-hospital cardiac arrest (OHCA) incidence, but their sensitivity to identify OHCA is not well known.
Methods
We included Emergency Medical Services (EMS)-treated cases from the BC Cardiac Arrest Registry that survived to hospital admission between 2012 and 2016, and linked to their admission records in the hospital admissions database (Discharge Abstract Database). We calculated sensitivity as the proportion of cases with OHCA-related International Classification of Disease 10 (ICD-10) codes that were listed as a preadmission comorbidity or the primary reason for hospital stay (coded as arising preadmission). In cases without OHCA-related codes, we identified other recorded ICD-10 codes and diagnosis types.
Results
Of 6009 eligible OHCAs during the study period, 2032 (33.8 %) patients who survived to hospital admission were included. OHCA-related ICD-10 codes were recorded in 1357/2032 (66.8 %; 95 % CI 64.7, 68.8) of cases. Sensitivity did not differ across sex and age groups. Among cases without OHCA-related codes, acute myocardial infarction was the most frequently assigned pre-admission diagnosis (225/675; 33.3 %), coded as most responsible for hospital admission, and coronary artery disease-related ICD-10 codes were the most common pre-admission diagnoses (176/675, 26.1 %).
Conclusion
One third of patients in our patient population suffering from OHCA and admitted to hospital were not coded as having a cardiac arrest. Using administrative databases to identify OHCA patients results in underestimation of cardiac arrest incidence, highlighting the need for ongoing dedicated OHCA registries.
心脏骤停研究人员经常使用行政卫生数据库来研究院外心脏骤停（OHCA）的发生率，但其识别OHCA的敏感性尚不清楚。方法我们纳入了2012年至2016年期间在BC省心脏骤停登记处接受紧急医疗服务（EMS）治疗的住院病例，并将其入院记录与医院入院数据库（出院摘要数据库）相关联。我们将敏感性计算为与ohca相关的国际疾病分类10 （ICD-10）代码被列为入院前共病或住院的主要原因（编码为入院前发生）的病例的比例。在没有ohca相关代码的病例中，我们确定了其他记录的ICD-10代码和诊断类型。结果在研究期间的6009例符合条件的ohca中，2032例（33.8%）患者存活至住院。1357/2032例（66.8%;95% CI 64.7, 68.8）记录了与ohca相关的ICD-10代码。敏感性在性别和年龄组之间没有差异。在没有ohca相关代码的病例中，急性心肌梗死是最常见的入院前诊断（225/675,33.3%），被编码为最负责的入院原因，冠状动脉疾病相关的ICD-10代码是最常见的入院前诊断（176/675,26.1%）。结论本组患者中有三分之一的OHCA患者入院时未被编码为心脏骤停。使用行政数据库来识别OHCA患者会导致心脏骤停发生率的低估，这突出了持续的OHCA专门登记的必要性。
{"title":"Age and sex differences in the sensitivity of ICD-10 diagnostic codes for identifying patients with out-of-hospital cardiac arrest in the British Columbia cardiac arrest registry: a retrospective cohort study","authors":"Mika’il Visanji , Omar Dewidar , Theresa Aves , Katherine S. Allan , Meijiao Guan , Brian Grunau , Christopher B. Fordyce , Jim Christenson , Jennie Helmer , Jacob Hutton , Paul Dorian , Steve Lin","doi":"10.1016/j.resuscitation.2025.110922","DOIUrl":"10.1016/j.resuscitation.2025.110922","url":null,"abstract":"<div><h3>Background</h3><div>Cardiac arrest researchers frequently use administrative health databases to study out-of-hospital cardiac arrest (OHCA) incidence, but their sensitivity to identify OHCA is not well known.</div></div><div><h3>Methods</h3><div>We included Emergency Medical Services (EMS)-treated cases from the BC Cardiac Arrest Registry that survived to hospital admission between 2012 and 2016, and linked to their admission records in the hospital admissions database (Discharge Abstract Database). We calculated sensitivity as the proportion of cases with OHCA-related International Classification of Disease 10 (ICD-10) codes that were listed as a preadmission comorbidity or the primary reason for hospital stay (coded as arising preadmission). In cases without OHCA-related codes, we identified other recorded ICD-10 codes and diagnosis types.</div></div><div><h3>Results</h3><div>Of 6009 eligible OHCAs during the study period, 2032 (33.8 %) patients who survived to hospital admission were included. OHCA-related ICD-10 codes were recorded in 1357/2032 (66.8 %; 95 % CI 64.7, 68.8) of cases. Sensitivity did not differ across sex and age groups. Among cases without OHCA-related codes, acute myocardial infarction was the most frequently assigned pre-admission diagnosis (225/675; 33.3 %), coded as most responsible for hospital admission, and coronary artery disease-related ICD-10 codes were the most common pre-admission diagnoses (176/675, 26.1 %).</div></div><div><h3>Conclusion</h3><div>One third of patients in our patient population suffering from OHCA and admitted to hospital were not coded as having a cardiac arrest. Using administrative databases to identify OHCA patients results in underestimation of cardiac arrest incidence, highlighting the need for ongoing dedicated OHCA registries.</div></div>","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"218 ","pages":"Article 110922"},"PeriodicalIF":4.6,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730713","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}
Anoxic brain injury following cardiac arrest is a leading cause of death in the United States. Withdrawal of life-sustaining therapy (WLST) is a common end-of-life decision in these patients, but its contributing factors and outcomes remain poorly understood. We developed machine learning models to enable large-scale, automated phenotyping to identify patients who died following WLST.
Methods
We used structured and unstructured EHR (Electronic Health Record) data from two major hospitals to train models that identify (1) patients with cardiac arrest and coma, and (2) patients who died after WLST. Performance was evaluated using the area under the receiver operating characteristic (AUROC) and precision-recall (AUPRC) curves, as well as other precision metrics.
Results
On holdout (internal) testing the models achieved AUROC/AUPRC values of 0.984/0.968 (cardiac arrest) and 0.992/0.991 (WLST). Cross-hospital evaluation showed strong performance for the cardiac arrest phenotype but variable generalizability for the WLST phenotype, with sensitivity depending on the training site. Population-level error rates were low (<0.5 %) for the cardiac arrest phenotype; estimates for WLST varied by hospital.
Conclusion
These models establish a reproducible framework for automated cohort identification. Nearly half of comatose post-arrest patients died following WLST, with 42 % of these deaths occurring within 72 h, highlighting the impact of early prognostication decisions. The models enable rapid cohort identification for research on neuroprognostication, including how WLST decisions may perpetuate self-fulfilling prophecies. Broader validation across health systems and larger cohorts will improve generalizability and inform evidence-based end-of-life decision-making.
Institutional review board approval: Mass General Brigham IRB BIDMC: 2022P000481; MGB: 2013P001024.
All procedures complied with institutional and national ethical standards; informed consent was waived for use of de-identified data.
研究目的：心脏骤停后的缺氧脑损伤是美国死亡的主要原因。在这些患者中，停止维持生命治疗（WLST）是一种常见的临终决定，但其影响因素和结果仍然知之甚少。我们开发了机器学习模型，以实现大规模、自动化的表型分析，以识别WLST后死亡的患者。方法：我们使用来自两家大医院的结构化和非结构化EHR（电子健康记录）数据来训练模型，以识别(1)心脏骤停和昏迷患者，以及(2)WLST后死亡患者。使用接收器工作特性（AUROC）和精确召回率（AUPRC）曲线下的面积以及其他精度指标来评估性能。结果：经内部检验，模型的AUROC/AUPRC值分别为0.984/0.968（心脏骤停）和0.992/0.991 （WLST）。跨医院评估显示，心脏骤停表型具有很强的表现，但WLST表型具有可变的普遍性，其敏感性取决于训练地点。结论：这些模型为自动队列识别建立了一个可重复的框架。近一半的骤停后昏迷患者在WLST后死亡，其中42%的死亡发生在72小时内，突出了早期预后决定的影响。这些模型能够快速识别神经预测研究的队列，包括WLST决策如何使自我实现的预言永存。在卫生系统和更大的队列中进行更广泛的验证将提高普遍性，并为基于证据的临终决策提供信息。机构审查委员会批准：Mass General Brigham IRB BIDMC: 2022P000481；MGB: 2013 p001024。所有程序均符合机构和国家道德标准；对于使用去识别数据，我们放弃了知情同意。
{"title":"Large-scale automated phenotyping of cardiac arrest and withdrawal of life-sustaining therapy using electronic health record data","authors":"Catherine Clive , Arjun Singh , Bram Overmeer , Spencer Boris , Lydia Peterson , Jaden Searle , Greg Hooke , Niels Turley , Marta Fernandes , Aditya Gupta , Manohar Ghanta , Valdery Moura Junior , S. Mukeriji , Sahar Zafar , Edilberto Amorim , M. Brandon Westover , Haoqi Sun","doi":"10.1016/j.resuscitation.2025.110919","DOIUrl":"10.1016/j.resuscitation.2025.110919","url":null,"abstract":"<div><h3>Aims of the study</h3><div>Anoxic brain injury following cardiac arrest is a leading cause of death in the United States. Withdrawal of life-sustaining therapy (WLST) is a common end-of-life decision in these patients, but its contributing factors and outcomes remain poorly understood. We developed machine learning models to enable large-scale, automated phenotyping to identify patients who died following WLST.</div></div><div><h3>Methods</h3><div>We used structured and unstructured EHR (Electronic Health Record) data from two major hospitals to train models that identify (1) patients with cardiac arrest and coma, and (2) patients who died after WLST. Performance was evaluated using the area under the receiver operating characteristic (AUROC) and precision-recall (AUPRC) curves, as well as other precision metrics.</div></div><div><h3>Results</h3><div>On holdout (internal) testing the models achieved AUROC/AUPRC values of 0.984/0.968 (cardiac arrest) and 0.992/0.991 (WLST). Cross-hospital evaluation showed strong performance for the cardiac arrest phenotype but variable generalizability for the WLST phenotype, with sensitivity depending on the training site. Population-level error rates were low (<0.5 %) for the cardiac arrest phenotype; estimates for WLST varied by hospital.</div></div><div><h3>Conclusion</h3><div>These models establish a reproducible framework for automated cohort identification. Nearly half of comatose post-arrest patients died following WLST, with 42 % of these deaths occurring within 72 h, highlighting the impact of early prognostication decisions. The models enable rapid cohort identification for research on neuroprognostication, including how WLST decisions may perpetuate self-fulfilling prophecies. Broader validation across health systems and larger cohorts will improve generalizability and inform evidence-based end-of-life decision-making.</div><div><strong><em>Institutional review board approval:</em></strong> Mass General Brigham IRB BIDMC: 2022P000481; MGB: 2013P001024.</div><div>All procedures complied with institutional and national ethical standards; informed consent was waived for use of de-identified data.</div></div>","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"218 ","pages":"Article 110919"},"PeriodicalIF":4.6,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145725500","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 : 2025-12-08DOI: 10.1016/j.resuscitation.2025.110916
Munirah Alyaseen, Barnaby R. Scholefield
{"title":"Expanding qEEG feature analysis: A step towards better prognostication","authors":"Munirah Alyaseen, Barnaby R. Scholefield","doi":"10.1016/j.resuscitation.2025.110916","DOIUrl":"10.1016/j.resuscitation.2025.110916","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"218 ","pages":"Article 110916"},"PeriodicalIF":4.6,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145725515","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 : 2025-12-04DOI: 10.1016/j.resuscitation.2025.110918
Charlotte Eickelmann, Anna Josefine Beiske, Martin Deicke, Julia Johanna Grannemann, Annika Hoyer, Lydia Johnson Kolaparambil Varghese, Bernd Strickmann, Mathini Vaseekaran, Gerrit Jansen
INTRODUCTIONThis study examines the influence of supraglottic airway (SGA) devices versus tracheal intubation (TI) on key ventilation parameters during intra-arrest-ventilation using volume-controlled-ventilation (VCV) in adult out-of-hospital cardiac arrest (OHCA).METHODSThis cohort study is based on real-world data obtained from the emergency medical service of the Gütersloh district, Germany. Ventilation data were extracted in March 2024 from emergency ventilators and combined with patient-level information from the German Resuscitation Registry. Adult OHCA cases receiving intra-arrest-ventilation 01/2019-08/2023 with VCV via either SGA or TI were included. Collected parameters included the airway device used, set tidal volume (VTset), measured expiratory tidal volume (VTe), and leakage volume (VLeak). The primary outcome was the difference between VTset-VTe. Patients were grouped according to the airway management strategy used (SGA vs. TI). Potential differences in outcomes between these groups were assessed using linear mixed regression models.RESULTSVCV was performed in n=27 individuals (682 minutes) using SGA in n=13 (330 minutes) vs. TI in n=14 (352 minutes). The mean total VTset was 562.8±58.0ml (TI=573.9±62.5ml; SGA=550.9±50.1ml). The mean VTe totaled 270.7±205.5ml (TI=348.1±215.6ml; SGA=188.2±156.6ml). The mean VLeak was 23.3±27.4% (TI=5.5±7.0%; SGA=42.3±28.4%). Compared to SGA, TI was associated with smaller VTset-VTe (regression coefficient: -128.3ml; 95%-CI: [-252.3ml; -4.3ml]; p=0.0427) as well as for a lower VLeak (regression coefficient: -32.3%; 95%-CI: [-46.1%; -18.4%]; p<0.0001) for TI.CONCLUSIONIn OHCA cases receiving mechanical intra-arrest-ventilation with VCV, TI was associated with higher delivered VTe, less deviation from VTset, and significantly lower VLeak compared to SGA.
{"title":"Tacheal intubation vs. supraglottic airway devices during mechanical intra-arrest-ventilation with volume-controlled-ventilation in out-of-hospital cardiac arrest: a cohort study","authors":"Charlotte Eickelmann, Anna Josefine Beiske, Martin Deicke, Julia Johanna Grannemann, Annika Hoyer, Lydia Johnson Kolaparambil Varghese, Bernd Strickmann, Mathini Vaseekaran, Gerrit Jansen","doi":"10.1016/j.resuscitation.2025.110918","DOIUrl":"https://doi.org/10.1016/j.resuscitation.2025.110918","url":null,"abstract":"INTRODUCTIONThis study examines the influence of supraglottic airway (SGA) devices versus tracheal intubation (TI) on key ventilation parameters during intra-arrest-ventilation using volume-controlled-ventilation (VCV) in adult out-of-hospital cardiac arrest (OHCA).METHODSThis cohort study is based on real-world data obtained from the emergency medical service of the Gütersloh district, Germany. Ventilation data were extracted in March 2024 from emergency ventilators and combined with patient-level information from the German Resuscitation Registry. Adult OHCA cases receiving intra-arrest-ventilation 01/2019-08/2023 with VCV via either SGA or TI were included. Collected parameters included the airway device used, set tidal volume (VTset), measured expiratory tidal volume (VTe), and leakage volume (VLeak). The primary outcome was the difference between VTset-VTe. Patients were grouped according to the airway management strategy used (SGA vs. TI). Potential differences in outcomes between these groups were assessed using linear mixed regression models.RESULTSVCV was performed in n=27 individuals (682 minutes) using SGA in n=13 (330 minutes) vs. TI in n=14 (352 minutes). The mean total VTset was 562.8±58.0ml (TI=573.9±62.5ml; SGA=550.9±50.1ml). The mean VTe totaled 270.7±205.5ml (TI=348.1±215.6ml; SGA=188.2±156.6ml). The mean VLeak was 23.3±27.4% (TI=5.5±7.0%; SGA=42.3±28.4%). Compared to SGA, TI was associated with smaller VTset-VTe (regression coefficient: -128.3ml; 95%-CI: [-252.3ml; -4.3ml]; p=0.0427) as well as for a lower VLeak (regression coefficient: -32.3%; 95%-CI: [-46.1%; -18.4%]; p<0.0001) for TI.CONCLUSIONIn OHCA cases receiving mechanical intra-arrest-ventilation with VCV, TI was associated with higher delivered VTe, less deviation from VTset, and significantly lower VLeak compared to SGA.","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"31 1","pages":"110918"},"PeriodicalIF":6.5,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689540","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 : 2025-12-03DOI: 10.1016/j.resuscitation.2025.110911
Lis Frykler Abazi, Sune Forsberg, Felix Böhm, Martin Jonsson, Mattias Ringh, Gabriel Riva, Ludvig Elfwén, Per Nordberg, Akil Awad, Charlotte Miedel, Anette Nord, Andreas Claesson, Nils Witt, Jacob Hollenberg
{"title":"Coronary angiography findings in relation to defibrillation refractoriness in out-of-hospital cardiac arrest - a nationwide study over 10 years","authors":"Lis Frykler Abazi, Sune Forsberg, Felix Böhm, Martin Jonsson, Mattias Ringh, Gabriel Riva, Ludvig Elfwén, Per Nordberg, Akil Awad, Charlotte Miedel, Anette Nord, Andreas Claesson, Nils Witt, Jacob Hollenberg","doi":"10.1016/j.resuscitation.2025.110911","DOIUrl":"https://doi.org/10.1016/j.resuscitation.2025.110911","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"27 1","pages":""},"PeriodicalIF":6.5,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657363","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 : 2025-12-03DOI: 10.1016/j.resuscitation.2025.110915
Zachary M. Shinar, Brian Burns
{"title":"ECPR in the futile traumatic patient: breaking paradigms or fanciful optimism?","authors":"Zachary M. Shinar, Brian Burns","doi":"10.1016/j.resuscitation.2025.110915","DOIUrl":"10.1016/j.resuscitation.2025.110915","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"218 ","pages":"Article 110915"},"PeriodicalIF":4.6,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657365","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 : 2025-12-03DOI: 10.1016/j.resuscitation.2025.110914
Per Olav Berve , Simon Orlob
{"title":"Intra-arrest ventilation: we can only improve what we measure – But what are our devices really calculating?","authors":"Per Olav Berve , Simon Orlob","doi":"10.1016/j.resuscitation.2025.110914","DOIUrl":"10.1016/j.resuscitation.2025.110914","url":null,"abstract":"","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"218 ","pages":"Article 110914"},"PeriodicalIF":4.6,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657362","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 : 2025-12-01DOI: 10.1016/j.resuscitation.2025.110851
David G. Dillon , Katherine S. Allan , Juan Carlos C. Montoy , Mika’il Visanji , Robert M. Rodriguez , Steve Lin , Ralph C. Wang
Background
Up to fifteen percent of out-of-hospital cardiac arrests (OHCAs) are precipitated by occult drug overdose – cases without history or evidence of drug use that are often attributed to a non-overdose cause. The NAloxone Cardiac ARrest Decision Instrument (NACARDI) was derived to help emergency medical service (EMS) providers rapidly identify patients at higher risk of occult opioid-associated (OA)-OHCAs during resuscitation. In this analysis we externally validate NACARDI in an independent cohort of OHCA patients.
Methods
We conducted a retrospective validation using data from EMS-attended OHCA patients and coroner records in Ontario, Canada between 2020–2021. Inclusion criteria were age ≥18 years and OHCA death with a coroner record. Exclusion criteria were EMS-suspected drug overdose or known cause of the OHCA. NACARDI consists of two criteria: patient age and unwitnessed cardiac arrest. Two cut-offs for patient age were assessed for this validation: <50 years (NACARDI-50) and <60 years (NACARDI-60). The primary outcome was coroner adjudicated cause of death. We calculated screening characteristics and receiver operating characteristic (ROC) curves using standard formulae.
Results
Of 2904 OHCA cases without an obvious cause, 791 had coroner evaluations and 121 (15.3 %) were adjudicated as occult OA-OHCA. NACARDI-60 had: sensitivity 82.6 % (95 %CI 74.9–88.4 %), specificity 77.1 % (95 %CI 73.8–80.1 %), negative predictive value 96.1 % (95 %CI 94.1–97.4 %), and positive predictive value 39.4 % (95 %CI 33.6–45.5 %). NACARDI-50 had: sensitivity 63.6 % (95 %CI 54.4–72.2 %), specificity 89.3 % (95 %CI 86.7–91.5 %), negative predictive value 93.2 % (95 %CI 90.9–95.0 %), and positive predictive value 51.7 % (95 %CI 43.4–59.9 %). ROC curves for both NACARDI-50 and NACARDI-60 demonstrated excellent discrimination for occult OA-OHCA.
Conclusion
In this external validation cohort, NACARDI had a sensitivity and specificity sufficiently high to aid in the real-time identification of occult OA-OHCA in the field. NACARDI has the potential to guide targeted interventions for OA-OHCA.
{"title":"Validation of the naloxone cardiac arrest decision instrument for identifying opioid-associated cardiac arrests","authors":"David G. Dillon , Katherine S. Allan , Juan Carlos C. Montoy , Mika’il Visanji , Robert M. Rodriguez , Steve Lin , Ralph C. Wang","doi":"10.1016/j.resuscitation.2025.110851","DOIUrl":"10.1016/j.resuscitation.2025.110851","url":null,"abstract":"<div><h3>Background</h3><div>Up to fifteen percent of out-of-hospital cardiac arrests (OHCAs) are precipitated by occult drug overdose – cases without history or evidence of drug use that are often attributed to a non-overdose cause. The NAloxone Cardiac ARrest Decision Instrument (NACARDI) was derived to help emergency medical service (EMS) providers rapidly identify patients at higher risk of occult opioid-associated (OA)-OHCAs during resuscitation. In this analysis we externally validate NACARDI in an independent cohort of OHCA patients.</div></div><div><h3>Methods</h3><div>We conducted a retrospective validation using data from EMS-attended OHCA patients and coroner records in Ontario, Canada between 2020–2021. Inclusion criteria were age ≥18 years and OHCA death with a coroner record. Exclusion criteria were EMS-suspected drug overdose or known cause of the OHCA. NACARDI consists of two criteria: patient age and unwitnessed cardiac arrest. Two cut-offs for patient age were assessed for this validation: <50 years (NACARDI-50) and <60 years (NACARDI-60). The primary outcome was coroner adjudicated cause of death. We calculated screening characteristics and receiver operating characteristic (ROC) curves using standard formulae.</div></div><div><h3>Results</h3><div>Of 2904 OHCA cases without an obvious cause, 791 had coroner evaluations and 121 (15.3 %) were adjudicated as occult OA-OHCA. NACARDI-60 had: sensitivity 82.6 % (95 %CI 74.9–88.4 %), specificity 77.1 % (95 %CI 73.8–80.1 %), negative predictive value 96.1 % (95 %CI 94.1–97.4 %), and positive predictive value 39.4 % (95 %CI 33.6–45.5 %). NACARDI-50 had: sensitivity 63.6 % (95 %CI 54.4–72.2 %), specificity 89.3 % (95 %CI 86.7–91.5 %), negative predictive value 93.2 % (95 %CI 90.9–95.0 %), and positive predictive value 51.7 % (95 %CI 43.4–59.9 %). ROC curves for both NACARDI-50 and NACARDI-60 demonstrated excellent discrimination for occult OA-OHCA.</div></div><div><h3>Conclusion</h3><div>In this external validation cohort, NACARDI had a sensitivity and specificity sufficiently high to aid in the real-time identification of occult OA-OHCA in the field. NACARDI has the potential to guide targeted interventions for OA-OHCA.</div></div>","PeriodicalId":21052,"journal":{"name":"Resuscitation","volume":"217 ","pages":"Article 110851"},"PeriodicalIF":4.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145252094","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 : 2025-12-01DOI: 10.1016/j.resuscitation.2025.110900
Tatsuya Norii , Michael A. Smyth , Monica E. Kleinman , Sander van Goor , Janet E. Bray
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