Abstract
OBJECTIVES:
To evaluate the impact of hospital-level median door-to-extracorporeal cardiopulmonary resuscitation (ECPR) time on survival and neurologic outcomes in patients with out-of-hospital cardiac arrest (OHCA) requiring ECPR.
DESIGN:
Secondary analysis of the Japanese Association for Acute Medicine OHCA registry, a nationwide Japanese database of OHCA patients.
SETTING:
Fifty-three hospitals across Japan.
PATIENTS:
Adult patients who underwent ECPR between 2014 and 2021 were included. Hospitals were categorized into “rapid” or “delayed” groups based on their median door-to-ECPR times.
INTERVENTIONS:
None.
MEASUREMENTS AND MAIN RESULTS:
The primary outcome was 30-day survival. Secondary outcomes included 30-day and 90-day survival with favorable neurologic outcomes. Propensity score weighting was applied to adjust for confounders. In total, 2136 patients treated at 53 hospitals were included. Hospitals with shorter median door-to-ECPR times had higher 30-day survival rates (odds ratio [OR], 1.36; 95% CI, 1.21–1.53). Neurologic outcomes were better in the rapid hospital group at both 30 days (OR, 1.47; 95% CI, 1.24–1.73) and 90 days (OR, 1.47; 95% CI, 1.25–1.73) follow-ups.
CONCLUSIONS:
Hospital-level median door-to-ECPR time is a crucial predictor of survival and neurologic outcomes in OHCA patients requiring ECPR. Shorter door-to-ECPR times should be considered a key quality metric for ECPR processes.
Keywords: door-to-extracorporeal cardiopulmonary resuscitation time, extracorporeal cardiopulmonary resuscitation, neurological outcomes, out-of-hospital cardiac arrest, quality indicator, survival
KEY POINTS.
Question: Does hospital-level median door-to-extracorporeal cardiopulmonary resuscitation (ECPR) time impact survival and neurologic outcomes in out-of-hospital cardiac arrest (OHCA) patients requiring ECPR?
Findings: This secondary analysis of the Japanese Association for Acute Medicine OHCA registry, which included 2136 patients treated with ECPR across 53 hospitals, found that hospitals with shorter median door-to-ECPR times had significantly higher 30-day survival and improved neurologic outcomes at both 30 and 90 days.
Meaning: Shorter hospital-level door-to-ECPR times are associated with improved outcomes in OHCA patients and could serve as a quality indicator for ECPR processes across hospitals.
Extracorporeal cardiopulmonary resuscitation (ECPR) is a promising life-saving strategy for reducing mortality in patients with refractory cardiac arrest (CA) (1–3). However, to provide stable, high-quality ECPR to communities, further evidence is needed to improve the quality of ECPR processes. Improving the overall process, particularly the management before and after cannulation, is considered crucial for the success of ECPR. The guidelines published by the Extracorporeal Life Support Organization in 2021 emphasize the importance of the time required to establish extracorporeal membrane oxygenation (ECMO) support, recommending that appropriate ECMO flow should be established within 60 minutes of CA onset (4). However, this recommendation is based on limited evidence, highlighting the need for further research using robust data.
A key modifiable factor in ECPR success is door-to-ECPR time, which is defined as the time from the hospital arrival of patients to the initiation of ECPR. This metric may serve as a potential quality indicator that reflects differences in institutional processes and collaboration efficiency (5). While prior studies have shown that reducing delays in individual-level door-to-ECPR time is linked to better neurologic outcomes, with prognosis worsening with each 3-minute delay beyond 27–30 minutes (6), the role of door-to-ECPR time as a hospital-level performance metric remains unclear. Most previous studies have focused on individual institutions, limiting generalizability owing to regional and institutional variability (7, 8).
This study aimed to evaluate the impact of hospital-level door-to-ECPR time on the prognosis of patients with out-of-hospital cardiac arrest (OHCA) who underwent ECPR, providing insights that could help establish this metric as a quality indicator for ECPR processes across diverse healthcare settings.
MATERIALS AND METHODS
Data Source and Participants
This study was a secondary analysis of the Japanese Association for Acute Medicine OHCA (JAAM-OHCA) registry, a prospective, multicenter, nationwide database developed by the steering committee of the JAAM. The detailed description of this registry has been previously published (9, 10). In brief, the registry integrates pre-hospital and in-hospital data and the outcomes of patients with OHCA who were transported to the emergency departments (EDs) of 93 institutions, including 69 university hospitals and/or tertiary critical care centers. The data were entered by clinicians or data administrators using an electronic data capture system with a standardized reporting form (9, 10). The JAAM-OHCA registry committee conducted data validation checks and provided anonymized datasets to the researchers. In this study, we included adult patients (18 yr old and older) who underwent ECPR between June 2014 and December 2021. The decision to initiate ECPR and its clinical indications were determined at the discretion of each participating hospital, as these were not standardized across the registry. The exclusion criteria were as follows: patients who had extracorporeal life support (ECLS) initiated after the return of spontaneous circulation (ROSC), patients for whom ECLS was s started more than 2 hours after hospital arrival, and those treated at hospitals that had managed fewer than ten patients required ECPR during the study period to ensure that minor variations in the number of patients required ECPR would not disproportionately impact hospital-level metrics. All procedures involving human participants were conducted in accordance with the “Ethical Guidelines for Life Science and Medical Research Involving Human Subjects” issued by the Japanese Ministries of Education, Culture, Sports, Science and Technology, and of Health, Labour and Welfare; these national guidelines are consistent with the ethical principles set forth in the 1975 Declaration of Helsinki and its later amendments. The protocol for this study was approved by the Ethics Committee of Kyoto University and the Ethics Review Committee of Nagoya University Graduate School of Medicine (2018-0083-2), as well as the ethics committees of each participating institution (Table S1, https://links.lww.com/CCM/H760). The requirement for written informed consent was waived for this study. This waiver was granted in accordance with ethical guidelines in Japan, as the registry contains only de-identified observational data and poses minimal risk. An opt-out approach was used in the primary registry.
Hospital-Level Door-to-ECPR Time Metrics
In this study, the hospital-level door-to-ECPR time metric was considered the exposure of interest. The door-to-ECPR time for each patient was calculated as the time from hospital arrival to the initiation of ECLS, specifically when the pump was started. The hospital-level door-to-ECPR time was defined as the median door-to-ECPR time for all patients required ECPR at each facility throughout the observation period. As there have been no prior studies characterizing hospital-level door-to-ECPR metrics, we empirically divided hospitals into two groups using the median hospital-level door-to-ECPR time as the cutoff: the rapid hospital group and the delayed hospital group.
Outcome Measures
The primary outcome measure was 30-day survival. Secondary outcomes included 30-day survival with favorable neurologic outcomes, defined as a Cerebral Performance Category (CPC) of 1 or 2, as well as 90-day survival and 90-day survival with favorable neurologic outcomes. Thirty‑ and 90‑day survival and CPC scores were recorded as part of routine clinical care: treating physicians or registry coordinators extracted the data from hospital charts for in‑patients and, for discharged patients, obtained the information during outpatient visits or through telephone interviews.
Statistical Analysis
The characteristics of the cohort hospitals and patient demographics were compared between the rapid hospital group and the delayed hospital group. Parametric data were expressed as means with sds, while nonparametric data were expressed as interquartile ranges. Unadjusted differences between the groups were assessed using standardized mean differences (SMDs). The relationship between the hospital-level door-to-ECPR time metric and patient volume was evaluated using Spearman rank correlation test. To assess the overall trend in door-to-ECPR time during the observation period, the patient-level door-to-ECPR times for each year’s cases were summarized using box plots. To examine the potential temporal variation in hospital-level door-to-ECPR time metrics and assess stability over time, we conducted additional analyses described in detail in the Supplementary Methods (https://links.lww.com/CCM/H760).
To estimate the effect of being treated at hospitals with faster vs. slower door-to-ECPR performance, we adjusted for patient-level confounding factors using propensity score analysis with the inverse probability weighting (IPW) method. Propensity scores were estimated using a logistic regression model, with hospital group assignment (rapid vs. delayed) as the outcome variable. Because our goal was to isolate in-hospital performance, the model included only patient-level variables determined before hospital arrival: age, sex, witnessed arrest, initial rhythm, bystander CPR, automated external defibrillator use, pre-hospital intubation, adrenaline administration, and call to ED interval (11–15). Because door-to-ECPR time itself is thought to be a hospital-level performance proxy, no additional hospital-level covariates (e.g., bed count, ECMO case volume, or infrastructure) were included in the model. After weighting, weighted logistic regression model was applied to estimate the association between hospital group and survival outcomes.
We calculated the SMDs to assess the balance of covariates between the groups after weighting. An SMD less than 0.25 indicated adequate balance (10, 16). Missing data were imputed using the missForest algorithm, a nonparametric method that uses random forests for imputation (10, 16). As an additional sensitivity analysis, we conducted a complete-case analysis to ensure the robustness of the results.
RESULTS
Patient and Hospital Characteristics
Of the 81,234 patients registered in the JAAM-OHCA registry, 3,384 patients 18 years old or older received ECLS, of which 2,136 patients treated with ECPR at 53 facilities were included in the analysis (Fig. 1). The hospital-level door-to-ECPR time was 27 minutes (24–32 min), with 25 facilities classified as rapid hospitals (Table 1). These hospitals were mostly large, with 41 of the 53 (77.4%) having 500 or more beds. A total of 1432 patients (67%) received ECPR in rapid hospitals (Table 2). The details of the missing variables are provided in the Additional file (Table S2, https://links.lww.com/CCM/H760). Detailed characteristics of this witnessed subgroup are also shown in in the Additional file (Table S3, https://links.lww.com/CCM/H760). Overall, the patient-level door-to-ECPR time was 27 minutes (19–36 min), with no substantial year-to-year variation (SMD for each year from 2014 to 2021, using 2017 as the reference: 0.008, 0.150, 0.063; reference: 0.105, 0.074, 0.186, and –0.004) (Fig. S1, https://links.lww.com/CCM/H760). Additionally, there was a weak negative correlation between the average yearly number of patients who had ECLS for OHCA and the median door-to-ECPR time in each hospital (Fig. S2, https://links.lww.com/CCM/H760; Spearman rho = –0.34; p = 0.01). Year-to-year transitions in hospital classification based on door-to-ECPR time, using both binary (rapid vs. delayed) and quartile-based groupings, were generally stable over time, particularly when limited to hospitals with higher annual case volumes (Fig. S3, https://links.lww.com/CCM/H760). A linear trend analysis indicated a modest but significant decrease in hospital-level door-to-ECPR time over the study period (slope, –1.01 min/yr; 95% CI, –1.52 to –0.49; p = 0.002), suggesting potential performance improvement over time (Figs. S4 and S5, https://links.lww.com/CCM/H760).
Figure 1.
Flow diagram of the enrollment for this study. ECLS = extracorporeal life support, ECPR = extracorporeal cardiopulmonary resuscitation, ROSC = return of spontaneous circulation.
TABLE 1.
Characteristics of Cohort Hospitals
| Variable | Total Hospital (n = 53) | Rapid Hospitals (n = 28) | Delayed Hospitals (n = 25) | Standardized Mean Difference |
|---|---|---|---|---|
| Number of hospital bed | 604 (500–750) | 600 (444–743) | 612 (550–750) | –0.20 |
| Number of ICU bed | 10 (8–20) | 8 (8–18) | 12 (8–22) | –0.16 |
| Average yearly OHCA cases | 138 (94–193) | 155 (105–234) | 112 (82–167) | 0.53 |
| Pre-hospital physician resuscitation rate for OHCA (%) | 8 (2–18) | 5 (1–12) | 12 (3–22) | –0.39 |
| Number of ECPR cases included in this study | 31 (17–55) | 18 (13–36) | 43 (23–62) | 0.74 |
| Average extracorporeal life support cases per year | 6.3 (3.7–8.5) | 8.4 (5.3–11.0) | 3.2 (2.3–5.5) | 0.85 |
| Hospital-level median door-to-ECPR time (min) | 27 (24–32) | 24 (21–26) | 32 (30–36) | –2.6 |
ECPR = extracorporeal cardiopulmonary resuscitation, OHCA = out-of-hospital cardiac arrest.
TABLE 2.
Characteristics of Patients
| Variable | Total Cases (n = 2136) | Rapid Hospitals (n = 1432) | Delayed Hospitals (n = 704) | Standardized Mean Difference |
|---|---|---|---|---|
| Age (yr) | 60 (49–69) | 61 (49–70) | 59 (49–69) | 0.07 |
| Sex (female) | 373 (17%) | 272 (19%) | 101 (14%) | –0.12 |
| Witness status | 1689 (79%) | 1123 (78%) | 566 (80%) | –0.05 |
| Bystander cardiopulmonary resuscitation | 1040 (49%) | 691 (48%) | 349 (50%) | –0.03 |
| Initial shock rhythm | –0.12 | |||
| Ventricular fibrillation/ventricular tachycardia | 1411 (66%) | 941 (66%) | 470 (67%) | |
| Pulseless electrical activity | 359 (17%) | 243 (17%) | 116 (16%) | |
| Asystole | 211 (9.9%) | 135 (9.4%) | 76 (11%) | |
| Automated external defibrillator use | 161 (7.5%) | 112 (7.8%) | 49 (7.0%) | –0.06 |
| Intubation by paramedics | 190 (8.9%) | 137 (9.6%) | 53 (7.5%) | –0.11 |
| Administration of adrenaline | 1930 (90%) | 1283 (90%) | 647 (92%) | –0.08 |
| Time from call to emergency department (min) | 32 (26–39) | 31 (26–38) | 33 (27–42) | –0.22 |
| Door-to-extracorporeal cardiopulmonary resuscitation time (min) | 27 (19–36) | 23 (18–32) | 33 (24–43) | –0.60 |
| 30-d neurologic outcome | 237 (11%) | 175 (12%) | 62 (8.8%) | 0.11 |
| 90-d neurologic outcome | 172 (8.9%) | 123 (9.7%) | 49 (7.4%) | 0.08 |
| 30-d survival | 524 (25%) | 380 (27%) | 144 (20%) | 0.15 |
| 90-d survival | 294 (15%) | 205 (16%) | 89 (13%) | 0.07 |
Association Between Assignment to Rapid ECPR Initiation Hospitals and Outcomes
Using propensity score weighting, the overall patient characteristics were well balanced between the groups (Fig. S3, https://links.lww.com/CCM/H760). The 30-day survival rate in patients who received ECPR at rapid initiation hospitals was better than that of those treated at delayed initiation hospitals (odds ratio [OR], 1.40 [95% CI, 1.24–1.58]) (Fig. 2). Additionally, the OR for 30-day favorable neurologic outcomes was 1.43 (95% CI, 1.20–1.60). For 90-day outcomes, the OR for survival was 1.51 (95% CI, 1.33–1.71), and the OR for favorable neurologic outcomes at 90 days was 1.36 (95% CI, 1.15–1.61). Similar results were observed in sensitivity analyses, including a complete-case analysis (Table S4, https://links.lww.com/CCM/H760) and an analysis assuming that patients with favorable neurologic outcomes at day 30 remained alive and neurologically favorable at day 90 (Table S5, https://links.lww.com/CCM/H760).
Figure 2.
Adjusted odds ratios comparing rapid vs. delayed hospitals after propensity score adjustment. The forest plot shows the adjusted odds ratios for allocation to rapid hospitals for each outcome.
DISCUSSION
This study demonstrated that hospital-level door-to-ECPR time significantly predicts outcomes in patients with OHCA requiring ECPR. Patients treated at hospitals with shorter median door-to-ECPR times showed better survival at 30- and 90-day follow-ups and better neurologic outcomes. These findings indicate that hospitals with shorter door-to-ECPR times are likely to exhibit higher performance levels in ECPR initiation processes. Furthermore, this metric can be a quality indicator of hospital-level ECPR performance.
The median hospital-level door-to-ECPR time may reflect the previously reported association between a shorter low-flow duration and favorable outcomes for individual patients (5–7, 17) and the organizational efficiency and coordination of the hospital’s ECMO team during ECPR initiation. A shorter door-to-ECPR time likely reflects multiple factors, including seamless communication between pre-hospital care and the ECMO team, a well-established decision-making process for ECPR candidate selection, quick access to necessary resources such as priming the circuit, and proficiency in technical procedures like accurate cannulation and dilation (18, 19). In this study, we observed a weak correlation between a higher number of patients required ECPR and a shorter hospital-level door-to-ECPR duration. Greater experience contributes to reducing hospital-level door-to-ECPR time, which aligns well with face validity. Regardless of the case volume, implementing standardized protocols and conducting effective simulations might be the appropriate strategies to further reduce hospital-level door-to-ECPR time (20–22). Previous reports have indicated that achieving door-to-ECPR times of less than 30 minutes is challenging in clinical trial settings (23). Therefore, rather than merely setting simple time goals, it may be necessary to consider preparing simulations and protocols to shorten the time more effectively. The hospital-level door-to-ECPR time can be used to assess the effectiveness of simulations and protocols in this context.
The primary strength of this study lies in its use of a large, multicenter dataset from the JAAM-OHCA registry, which enhances the generalizability of the findings across diverse healthcare settings. This wide coverage allows for more robust conclusions that can be applied to various hospitals, from large academic centers to smaller community hospitals. Additionally, propensity score analysis with IPW provides a strong methodological approach to account for confounding factors, thereby strengthening the validity of the observed associations between median door-to-ECPR time and patient outcomes.
Despite the strengths of this study, it has several limitations. First, while the hospital-level door-to-ECPR time is associated with survival and neurologic outcomes, it captures only one segment of care and does not reflect post-cannulation complications, rehabilitation, or long-term follow-up—factors that critically influence patient recovery. The relationship between shorter door-to-ECPR times and such downstream outcomes remains unclear, and further research is warranted to explore these associations. Second, the registry lacks detailed hospital-level information (e.g., ECMO team training, staffing patterns, advanced technology availability, and standardized protocols), making it difficult to determine which specific institutional factors contribute to faster ECPR initiation. Because hospital-level performance likely reflects a complex combination of these unmeasured elements, future studies should incorporate more granular data to disentangle their effects and guide targeted quality improvement. Third, we excluded hospitals with fewer than ten patients who underwent ECPR, potentially introducing bias toward high-volume centers where systems may be more established. In lower-volume facilities, year-to-year variability in door-to-ECPR time may also be greater, limiting the stability of this metric as a performance indicator. Fourth, although we used IPW to balance baseline characteristics, residual confounding may still be present. Balance was assessed using a SMD threshold of less than 0.25, a commonly accepted criterion (16, 24). The call-to-ED interval remained slightly imbalanced (SMD ≈ 0.12), and important unmeasured confounders—such as patient comorbidities, regional EMS protocols, and variability in institutional indications for initiating ECPR—were not accounted for. These sources of heterogeneity may have introduced bias that could not be fully adjusted in the current analysis. Fifth, we categorized hospitals using the median door-to-ECPR time, although the relationship between time and outcomes may not be linear. Further reductions may not yield proportional benefits, and the optimal threshold for intervention remains uncertain. Finally, our findings cannot be generalized to regions where prehospital (on-scene) ECPR is widely implemented (25, 26). In such settings, prehospital care likely plays a dominant role in determining outcomes, and different metrics may be needed to evaluate system performance effectively.
CONCLUSIONS
In conclusion, the hospital-level median door-to-ECPR time is an crucial modifiable factor in the managing patients with OHCA requiring ECPR. Hospitals that achieve shorter door-to-ECPR times have been associated with improved survival and favorable neurologic outcomes. These findings highlight the need for targeted interventions to reduce delays in ECPR initiation, which can serve as a critical quality indicator of hospital-level ECPR performance. Future studies should address the identified limitations to further refine the use of median door-to-ECPR time as a performance metric and to identify effective strategies for optimizing this key process.
ACKNOWLEDGMENTS
We thank all those who contributed to the data collection of the Japanese Association for Acute Medicine Out-of-Hospital Cardiac Arrest registry.
Supplementary Material
Footnotes
Drs. Kasugai and Okada were involved in conceptualization. Drs. Kasugai and Mizutani were involved in statistical analysis. Drs. Honda, Kondo, Karamu, and Yamamoto were involved in supervision. Dr. Kasugai were involved in writing the original draft. All authors were involved in reviewing and editing the writing. All authors read and approved the final article.
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal).
This study was partially supported by the Future Society Innovation Project, sponsored by the Institutes of Innovation for Future Society, Nagoya University.
Dr. Kasugai received support for article research from the Institutes of Innovation for Future Society, Nagoya University. Dr. Okada received funding from the Zoll Foundation; they received support for article research from the National Institutes of Health. Dr. Kondo received funding from Abbott Japan LLC, AstraZeneca K.K., Boehringer Ingelheim, Ono Pharmaceutical, Kowa Company, Kyowa Kirin, and Novartis Pharma K.K. The remaining authors have disclosed that they do not have any potential conflicts of interest.
The protocol for this study was approved by the Ethics Committee of Kyoto University and the Ethics Review Committee of Nagoya University Graduate School of Medicine (2018-0083), as well as the ethics committees of each participating institution. Please see the Supplemental Digital Content (https://links.lww.com/CCM/H760) for more information. The requirement for written informed consent was waived for this study.
The dataset used in this article belongs to the Japanese Association for Acute Medicine (https://www.jaamohca-web.com).
Contributor Information
Yohei Okada, Email: okadayohei1127@yahoo.co.jp.
Junta Honda, Email: honda.junta.s0@f.mail.nagoya-u.ac.jp.
Toru Kondo, Email: kondo.toru.v2@f.mail.nagoya-u.ac.jp.
Shingo Kazama, Email: kazama.shingo.s8@f.mail.nagoya-u.ac.jp.
Takanori Yamamoto, Email: takanori72@gmail.com.
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