Wolf Creek XVIII Part 2: optimizing time intervals in cardiac arrest care

Abstract

Optimizing time intervals in cardiac arrest care was a featured topic at the 50th Anniversary Wolf Creek Conference (Wolf Creek XVIII) hosted by the Max Harry Weil Institute for Critical Care Research and Innovation in Ann Arbor, Michigan, USA on June 19–21, 2025. This narrative review summarizes the presentations and discussion of the topic by invited panelist and conference participants made up of international academic and industry scientists as well as thought leaders in the field of cardiac arrest resuscitation. The proceedings highlighted the limitations of binary proportion-based resuscitation metrics (e.g. “bystander CPR—yes/no”) in driving improvements in cardiac arrest outcomes and called for a paradigm shift—placing time intervals to key cardiac arrest interventions and responses to therapy at the center of benchmarking quality improvement and research. In addition to an overview of the current state and vision for the future state, we detail knowledge gaps and barriers to translation, and propose research priorities that include standardizing interval measurement, harmonizing reporting, and validating interval metrics for system performance and proximal outcomes. Making treatment and response intervals core metrics for systems-of-care, registries, and clinical trials could shift the field’s focus toward the goal of faster restoration of perfusion resulting in improved survival and better neurologic recovery.

Introduction

Sudden cardiac arrest is a major contributor to all cause mortality worldwide.¹ Despite decades of effort in public education, automated external defibrillator (AED) deployment, dispatcher training, system optimization, and new technologies, treatment outcomes remain unacceptable. The majority of cardiac arrest victims never have their heart restarted, most of those that do will die before leaving the hospital, and among survivors there is a significant burden of neurological disability.2, 3, 4, 5, 6

One well accepted premise in the pathophysiology of cardiac arrest, supported by both laboratory and clinical science, is that every minute without effective perfusion yields significant, nonlinear declines in the likelihood of survival and good neurological outcome. No other human illness is more time sensitive. Yet, despite this clarity, current practices in registry reporting, quality improvement, and even randomized trials often obscure this pathophysiology by emphasizing simple binary occurrences of process, treatment and outcome metrics.

Typical cardiac arrest reporting highlights the percentage of patients who receive bystander cardiopulmonary resuscitation (CPR), are treated with an AED prior to emergency medical services (EMS) arrival, and achieve return of spontaneous circulation (ROSC), —but the effectiveness of these interventions and impact of responses to therapy are highly dependent on how rapidly they occur. Consequently, two systems reporting identical binary percentages for these metrics may in fact deliver profoundly different actual clinical care. This has significant implications for how research is conducted, data is interpreted, and quality is measured.

This narrative review, drawing on the insights, analyses, and debates of the Wolf Creek XVIII conference, explores the critical role of time intervals in cardiac arrest care. We examine the scientific rationale for focusing on intervals, survey the current real-world patterns and reporting limitations, discuss the practical and knowledge barriers to interval-driven reform, and highlight key priorities to embed time-based metrics into the fabric of resuscitation research and quality improvement (Figure).

Figure.

Changing the focus of cardiac arrest resuscitation from binary proportional metrics to interval-based metrics could significantly improve outcomes.

Methods

Since its inception in 1975, the Wolf Creek Conference has a well-established tradition of providing a unique forum for robust intellectual exchange between thought leaders and scientists from academia and industry focused on advancing the science and practice of cardiac arrest resuscitation. The 50th Anniversary Wolf Creek XVIII Conference was hosted by the Max Harry Weil Institute for Critical Care Research and Innovation in Ann Arbor, Michigan, USA on June 19–21, 2025.⁷ Invited participants included international academic and industry scientists as well as thought leaders in the field of cardiac arrest resuscitation. All participants were required to complete conflict of interest disclosures.⁷

Optimizing time intervals in cardiac arrest care was one of six focused panel topics that was presented and discussed during the conference. This manuscript is a narrative review, synthesizing the expert presentations, moderator-guided discussions, and subsequent group debates. The session included panelists and participants with broad expertise—ranging from basic science through clinical trials, EMS medical direction, public health, technology, and health services research—who presented new data, engaged with published literature, and explored practical applications in live dialogue. The panel reviewed interval-focused registry and cohort data from multiple countries, described analytical methods for interval-outcome relationships (e.g., time to first compression, time to defibrillation, and time to ROSC), and highlighted recent innovations (such as extracorporeal cardiopulmonary resuscitation (ECPR) time windows).

We do not provide a quantitative meta-analysis, given the narrative approach; instead, this review contextualizes the scientific evidence with both the nuanced discussions and actionable recommendations that emerged at the conference.

Current state

Traditional emphasis on binary proportion-based metrics

Since the publication of the original Utstein guidelines, the global resuscitation field has taken major strides in harmonizing data collection and reporting standards for both out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA).8, 9, 10, 11, 12 These standards have enabled meaningful benchmarking across communities, helped identify critical “links in the chain of survival,” and shaped both public health and health system policy. Chief among these have been binary proportion-based process measures: for OHCA, metrics such as percentage of cases receiving bystander CPR, percentage where a defibrillator is applied before EMS arrival, and percentage achieving ROSC are routinely measured quality indicators.

These measures have undoubtedly improved awareness and driven some degree of system optimization. For instance, the global push for dispatcher-assisted and layperson CPR training has increased bystander actions and modestly improved outcomes in many regions.¹³ Likewise, dissemination of public-access and first responder AEDs is associated with better outcomes in high-density urban areas.14, 15, 16, 17 However, even the best-performing communities face frustrating plateaus, and survival rates remain stubbornly heterogeneous.

The case for intervals

A growing body of observational, registry-based, and trial subanalysis reveals that survival and recovery of neurologic function is driven far more by “when” interventions are delivered than by “whether” they are delivered or “by whom”. From the patient’s perspective, what matters most is how long it takes to initiate chest compressions, rather than who does it. Even in cases where bystander CPR is performed, the interval from cardiac arrest to onset to initiating chest compressions could range from <1 min to just prior to EMS arrival, which could be >10 min. It follows that numerous observational studies have demonstrated a non-linear decline in the proportion of patients who survive with good neurologic function based on the estimated interval from cardiac arrest onset to the initiation of chest compressions.18, 19

A similar story can be told regarding the interval from cardiac arrest onset to other treatments such as defibrillation and adrenaline. Defibrillation within 2 min of cardiac arrest onset is a guideline recommendation for the treatment of in-hospital cardiac arrest, and delays beyond that interval are associated with lower rates of survival.²⁰ Data from the Netherlands presented at the conference indicated that an emergency call to first shock interval of 4–5 min was associated with 7 % unsuccessful defibrillations and a 73 % ROSC rate while an interval of 10–11 min was associated with 17 % unsuccessful defibrillations and a 51 % ROSC rate.²¹ A secondary analysis of the PARAMEDIC2 trial suggested that any potential benefit of 1.0 mg intravenous epinephrine on recovery of neurologic function is time dependent and it’s effect is likely undetectable when given more than 20 min after cardiac arrest onset.²² In terms of treatment results, the interval from cardiac arrest onset to ROSC is strongly associate with survival and recovery of neurologic function. For example, Goto et al. demonstrated that in a large registry study from Japan, every minute of delay to ROSC sharply reduced the rate of favorable neurological survival, with a near-exponential decay.²³ Similarly, Reynolds et al. found that favorable neurological outcomes after OHCA was rare if ROSC was not achieved within the first 8–10 min of resuscitation, and nearly absent after 35–40 min.²⁴

In cases where cardiac arrest does not respond to standard therapy, ECPR is emerging as a feasible and effective rescue strategy in optimized systems of care.²⁵ Survival with good neurologic outcome decreases as a function of time from CA onset to initiation of ECPR up to 45 min after which outcomes appear to plateau out to 90 min and beyond.²⁶ These observation results suggest a target of <45 min from CA onset to ECPR is likely to optimized CPR outcomes.

Real-world patterns and the knowledge “blind spot”

Wolf Creek panelists presented analytic examples from Europe, Singapore, North America, and Australasia, each displaying the same underlying biology: estimated intervals from cardiac arrest to treatment and treatment response are strongly associated with outcomes. This suggests that system-of-care optimization focused on shortening time-to-compression, time-to-defibrillation, time-to-drug therapy and time-to-ROSC has the potential to measurably improve quality of care and outcomes in ways that cannot be achieve with a persistent focus on binary proportions alone. For example, survival with good neurologic outcome is >50 % higher when bystander CPR is initiated within 1 min of cardiac arrest (or before EMS call) compared to 4–5 min, which is the median for dispatcher assisted CPR.18, 19 Survival with good neurologic function is twice as likely when ROSC is achieved within 6–8 min of OHCA compared to 12–14 min.23, 24 A similar relationship has been reported for IHCA with good neurologic outcomes of 10 %, 5 %, and 2.5 % when ROSC is achieved 5, 10, and 20 min after cardiac arrest onset.²⁷ In one OHCA ECPR cohort, survival with good neurologic function is twice as likely when ECPR was initiated 25–30 min after cardiac arrest compared to 45–50 min.²⁶

The challenge, as panelists and participants emphasized, is that current science and practice remain anchored in binary proportion-based reporting and that the resources and technology required to measure, standardize, and share interval metrics at scale have lagged. This “blind spot” limits both understanding and progress.

Potential future state

Interval-driven quality as a new paradigm

A fundamental shift to interval-based assessment would re-anchor resuscitation quality around the true drivers of outcome: minimizing the duration of no-flow and low-flow states by enabling the earliest possible interventions. In this paradigm:

• –Instead of reporting “percentage of cases with bystander CPR,” systems would benchmark “median time from collapse to first chest compression,” and use this to track impact of lay responder education and deployment programs as well as the quality telecommunicator CPR. As the moment of collapse is usually not time stamped, the moment of the call to the dispatch center can be taken as a reliable proxy.
• –Rather than “AED applied—yes/no,” registries would capture “collapse-to-defibrillation interval,” and use this to quantify the impact of various AED deployment and delivery strategies. All AEDs and EMS monitors store time stamped information on connection and defibrillation, but few devices allow easy access to that information.
• –ROSC would not be a simple binary, but a time-stamped outcome (collapse-to-ROSC or call-to-ROSC), enabling a patient-centered assessment of overall system performance that can be used to identify weak links in the chain of survival and tracking impact of specific interventions (e.g., dispatcher training, responder deployment, and public access AED placement).
• –ECPR systems of care would be designed to achieve ECPR flow within 45 min of cardiac arrest onset, and the proportion of patients treated within that interval would be used as a system-of-care quality metric.

Technology and future system design

The envisioned “interval-optimized” system would leverage several technological and procedural advances:

• 1.Digital, Synchronized Timestamping: Modern dispatch, AEDs, and monitors increasingly include real-time network connectivity and standardized clocking (“network time protocol”), reducing drift and facilitating universal cutpoint definition. Automation could replace manual log review, reducing burden and error.
• 2.Mobile Health and Real-Time Alerts: Smartphone apps, wearable devices, and video or audio surveillance systems could automatically recognize and timestamp collapse (possibly via accelerometry, heart rhythm detection, or acoustic sensing), summoning help and recording the precise onset for all witnessed and unwitnessed events.
• 3.Integrated Feedback and Quality Dashboards: EMS and hospitals would use interval-based dashboards for continuous quality improvement, with feedback for individual providers, system leaders, and policymakers.
• 4.Rapid Escalation Pathways and ECPR: Rapid stratification could identify candidates for escalation (e.g., rapid transport for ECPR), with workflow optimized to achieve targeted collapse-to-circuit time and maximize neurologically viable salvage.

Biologic time and patient-centered decision-making

Interval-based metrics could be further refined by incorporation of “biologic time,” i.e., individualized physiologic and biochemical indicators of perfusion adequacy and tissue viability. Instead of defining futility strictly via clock time, advanced monitoring (e.g., quantitative VF waveform analysis, cerebral oximetry, or even point of care molecular biomarkers) could help tailor persistence, escalation, or termination decisions to real patient potential, reminiscent of acute stroke’s movement from “time from onset” to “tissue-based” windows.

The interval composite score

Central to this future state is the adoption of validated, risk-adjusted, and easily interpretable composite scores—such as a “ROSC Interval Score”—that account for both time-to- time-to-ROSC and ROSC rates across patient types and settings (OHCA/IHCA), supporting apples-to-apples benchmarking, continuous quality improvement (CQI), pay-for-performance, and research.

Knowledge gaps

Measurement and interval attribution

Arrest recognition frequently varies or is delayed; the true “collapse” time is rarely witnessed or recorded, leading to heavy reliance on surrogates (e.g., 911-call-to-intervention) which themselves may obscure “no-flow” vs. “low-flow” intervals. Diagnostic uncertainty arises especially in unwitnessed events, pediatric populations, and non-cardiac aetiologias. No universally accepted method exists for time-zero attribution, complicating comparison and undermining standardized reporting.

Data completeness, quality, and representativeness

Many registries permit, but do not require, key interval data; those that do often face incomplete, inconsistent, or error-prone timestamping, especially where EMS records, dispatcher logs, and device downloads must be manually reconciled. This introduces selection and reporting bias, as well as regional disparities (urban/rural gap in device-connectivity, registry adoption, and data validation). These gaps are particularly salient in global benchmarking initiatives, where variations in definitions may further confound comparisons.

Unmeasured confounding and resuscitation time bias

Research into the temporal association of interventions with outcomes is often confounded by “resuscitation time bias,” wherein longer resuscitations reflect more refractory or severe cases.²⁸ Carefully-designed randomized and analytic studies are required to differentiate causal benefit from spurious associations, especially in drug trials and device analyses.

Absence of validated composite metrics

While the concept of an interval-based composite score is compelling, no such metric is yet universally accepted or validated across registry, clinical trial, and reporting environments. The methodological challenges of incorporating multiple time intervals, accounting for both time to treatment response and absence of treatment response (i.e. ROSC), integrating patient and event characteristics, and modeling non-linear relationships remain substantial.

Integration of physiology and biologic markers

No routine protocol exists to integrate physiologic data—such as P_ETCO₂, rSO₂, diastolic blood pressure, or point-of-care biomarkers—into interval-based quality measures, limiting the shift from strict chronologic time to patient-centered “biological time” assessment.

Barriers to translation

Data capture, technology, and integration

Accurate recording of intervention and outcome times requires interoperability across dispatch, EMS, device, and hospital systems, including robust, synchronized clocks and digital documentation. In many settings, data must still be abstracted manually, which is both labor-intensive and error prone. The lack of standardized approaches to device time correction (e.g., AEDs) further complicates matters. The device-specific software that is needed for good interpretation of data has a wide variability of quality and needs improvement.

While some current and many next-generation AEDs and monitors can communicate wirelessly and upload time-stamped data, such equipment is not globally deployed; rural and resource-limited systems may lag in both technology and personnel. Even in advanced systems, extracting and auditing data at scale remains a significant challenge, requiring sustained investment and system coordination.

Registry and reporting infrastructure

International and national cardiac arrest registries (e.g., CARES in the United States, PAROS in Asia, EuReCa in Europe) facilitate research and quality improvement, but most still relegate interval data to optional or supplemental fields, rather than core requirements. The recent update of the Utstein OHCA registry template considers time intervals to dispatch and to first defibrillation as core data.¹² Moreover, public reporting, guideline update cycles, and pay-for-performance measurements are not yet structured to prioritize interval-based metrics, limiting both accountability and external pressure for change.

Financial and resource investment

Developing next-level interval measurement capability requires not only hardware (devices, network infrastructure), but also personnel (data abstractors, quality officers, informaticians) and training at multiple system levels. For many systems—particularly those operating at the threshold of sustainability or dependent on episodic grant funding—this poses a major hurdle.

System complexity, cultural factors, and variation

Interval-based reporting introduces new complexity for providers, leaders, and policymakers: shifting from “did we do it?” to “how quickly did we do it?” requires retraining, change management, and alignment with professional incentives and culture. Systems with less experience in data-driven CQI, or lacking in leadership stability and buy-in, may struggle to implement interval measurement, benchmark peer performance, or drive improvement.

Differences in geography, demographics, and resuscitation system design (e.g., stay-and-play vs. scoop-and-run transport models; physician-led vs. paramedic-led teams) may complicate comparisons, necessitating both contextual adaptation and flexible implementation.

Equity and access

Emphasizing interval achievement could have unintended consequences: low-resource communities (e.g., with longer EMS travel times or fewer AEDs) may be “penalized” despite optimal use of assets; well-resourced communities may appear artificially superior. Conversely, implementation of interval measurement could motivate investment in currently underserved regions, if coupled with targeted support and quality improvement partnerships.

Data interpretation, communication, and ethics

Interval-based metrics pose unique challenges in communication: how should “late” interventions be contextualized, and what constitutes “acceptable delay”? Further, outcomes may be perceived differently by stakeholders (public, providers, policymakers), necessitating careful framing to ensure metrics drive improvement rather than punitive action or nihilism.

Practical, ethical, and medicolegal issues surrounding use of biological/physiologic time (e.g., Do Not Attempt Resuscitation cutoffs, triage for advanced therapies) will also require consensus-building and transparent decision-making.

Priorities for research and implementation

Accelerating the shift toward interval-focused resuscitation science and practice demands a multi-pronged research and system change agenda. Key priorities emerging from both panel discussion and synthesis of the literature include:

• 1.
  Interval data standardization and integration

  • –
    Mandate interval collection: Make core time intervals— “collapse/call-to-CPR,” “collapse/call-to-defibrillation,” and “collapse/call-to-ROSC,”—mandatory in local, regional, and national registry datasets, harmonizing definitions and enabling apples-to-apples comparison.
  • –
    Standardize devices and documentation: Collaborate with manufacturers to ensure all new AEDs, monitors, and dispatch systems provide accurate, network-synced, and accessible timestamps; incentivize software integration that automates upload and cross-matching across data sources.
  • –
    Transparency and data sharing: Encourage open-access interval reporting, with stratification by key characteristics (age, initial rhythm, geography, etc.), to strengthen global benchmarking and research.
• 2.
  Composite metric development and validation

  • –
    Design, validate, and disseminate composite scores: Assemble working groups to design and validate multi-interval, risk-adjusted quality indices (e.g., a “ROSC Interval Score”) that can be embedded into registries, research protocols, and electronic quality dashboards.
  • –
    Iterative refinement: Use simulation, real-world registry data, and trial datasets to refine metrics for interpretability, predictive value, and benchmarking utility.
• 3.
  Clinical research focused on intervals

  • –
    Comparative effectiveness trials: Structure prospective clinical trials with rigorous interval stratification—both as inclusion/exclusion and analytic variables—enabling direct assessment of intervention timing effects on neurologically intact survival.
  • –
    Clinical decision algorithms: Develop and test algorithms for dynamic decision-making (e.g., when to escalate to mechanical CPR, ECPR) based on pre-specified interval or physiologic criteria.
  • –
    Resuscitation time bias: Advance analytic methods to control and correct for resuscitation time bias in observational and registry studies, strengthening causal inference.
• 4.
  Biologic time and physiologic integration

  • –
    Physiologic markers: Explore, validate, and contextualize physiologic parameters (such as P_ETCO₂, cerebral oximetry, lactate, continuous blood pressure, and novel biomarkers) to supplement interval data, aiming for blended “chrono-biologic” assessment of resuscitation potential.
  • –
    Personalized termination algorithms: Investigate outcome impact and resource use of termination-of-resuscitation rules that incorporate both interval and physiologic parameters.
• 5.
  Quality improvement, education, and feedback

  • –
    Dashboard-driven CQI: Develop user-friendly, real-time feedback tools that display key interval metrics at the local, agency, and system levels, paired with benchmarking and best practice sharing.
  • –
    Provider and public education: Re-orient training for dispatchers, lay rescuers, and clinicians to emphasize not only the *doing* but the *speed* of key actions—potentially gamifying or incentivizing rapid response.
  • –
    Simulation and systems testing: Employ high-fidelity simulation, tabletop exercises, and in-situ drills to identify bottlenecks, test interval-improving interventions, and ensure transferability to the field.
• 6.
  Policy, advocacy, and resource allocation

  • –
    Guideline integration: Collaborate with leaders in resuscitation science (e.g., ILCOR, AHA, ERC) to reference interval-based metrics as core quality indicators in consensus guidelines and performance standards.
  • –
    Equitable access and funding: Advocate for targeted investment in AED deployment, first-response infrastructure, and digital data systems in under-resourced areas, aiming for universal achievement of interval-based performance targets.
  • –
    Legislative action: Support public policy requiring integration of interval metrics into accountable care systems, using interval reporting to galvanize advocacy.

Conclusions

The science and clinical experience are unambiguous: in cardiac arrest, every minute counts—each delay in compression, defibrillation, or ROSC irreparably erodes neurologic survival and perpetuates inequity. Yet, the predominant tools of quality and research—binary proportion-based measures—obscure the true drivers of meaningful outcome and system performance. As vividly articulated at Wolf Creek XVIII, the time has come to reorient the field around time intervals as primary, actionable anchors of care quality, innovation, and outcome.

Realizing this vision will not be simple. It demands new investments in technology, data systems, and workforce; cultural shifts in training, communication, and leadership; and scientifically grounded work to fill persistent gaps in evidence, measurement, and application. Yet the potential rewards—a doubling of survival, maximized benefit from both established and novel therapies, and actionable targets for every resuscitation system—are both feasible and transformative.

By moving toward a future where “how quickly” replaces “whether” as the core question, cardiac arrest research and clinical care can finally unlock the step-changes in survival and recovery that patients, families, and communities deserve.

AI disclosure

Claude 4.0 Sonnet (Anthropic) was used to summarize the transcript of the session recording and generate an initial draft of the narrative review.

CRediT authorship contribution statement

Theresa M. Olasveengen: Writing – review & editing, Project administration, Methodology, Conceptualization. Haruka Takahashi: Writing – review & editing, Methodology, Data curation, Conceptualization. Rudolph W. Koster: Writing – review & editing, Methodology, Formal analysis, Conceptualization. Gavin D. Perkins: Writing – review & editing, Methodology, Conceptualization. Robert W. Neumar: Writing – review & editing, Writing – original draft, Project administration, Conceptualization.

Funding

Funding for the conference was provided by the Max Harry Weil Institute for Critical Care Research and Innovation and corporate sponsors including ZOLL Medical, Stryker, Corpuls, Resuscitec, Phillips, Shiller Medical, the American Heart Association, add the American Red Cross.

Declaration of competing interest

The author is an Editorial Board Member/Editor-in-Chief/Associate Editor/Guest Editor for Resuscitation Plus and was not involved in the editorial review or the decision to publish this article.

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: TMO: Board member, Laerdal Foundation (NGO). HR: Research Funding, Zoll Foundation. RWK: Paid consultant for Stryker Emergency Care. GDP declares research funding from the National Institute for Health Research. The views expressed are those of the author(s) and not necessarily those of the NIHR, the NHS, or the UK Department of Health and Social Care. GDP serves as Editor-in-Chief for Resuscitation Plus. To ensure the integrity of the peer-review process, Professor Perkins had no involvement in the peer review or editorial decision-making for this article. Editorial responsibility for this manuscript was delegated to an independent editor. RWN: Immediate Past Co-Chair, International Liaison Committee on Resuscitation, President and Board Chair, SaveMiHeart; Research Funding, NIH, AHA and Laerdal Foundation; Research equipment, BrainCool and Corpuls. RWN serves as Guest Editor for the Wolf Creek XVIII 2025 Special Edition of Resuscitation Plus. To ensure the integrity of the peer-review process, Professor Neumar had no involvement in the peer review or editorial decision-making for this article. Editorial responsibility for this manuscript was delegated to an independent editor.