DOI: https://doi.org/10.21203/rs.3.rs-1446195/v1
Background: Although the prognosis of patients treated at specialized facilities has improved, the relationship between the number of patients treated at hospitals and prognosis is controversial and lacks constancy in those with out-of-hospital cardiac arrest (OHCA). This study aimed to clarify the effect of annual hospital admissions on the prognosis of adult patients with OHCA by analyzing a large cohort.
Methods: The effect of annual hospital admissions on patient prognosis was analyzed retrospectively using data from the Japanese Association for Acute Medicine OHCA registry, a nationwide multihospital prospective database. This study analyzed 3,632 of 35,754 patients hospitalized for cardiac OHCA at 86 hospitals. The hospitals were divided into tertiles based on the volume of annual admissions. The effect of hospital volume on prognosis was analyzed using logistic regression analysis with multiple imputation. Furthermore, three subgroup analyses were performed for patients with return of spontaneous circulation (ROSC) before arrival at the emergency department, patients admitted to critical care medical centers, and patients admitted to extracorporeal membrane oxygenation-capable hospitals.
Results: The 30-day survival rate after admission was not correlated with hospital volume in all cardiac OHCA patients and subgroups. However, the frequency of favorable neurological outcomes in cardiac OHCA patients with ROSC before arrival at the emergency department at high-volume centers was higher than those at medium- and low-volume centers.
Conclusion: Hospital volume did not significantly affect the prognosis of adult patients with cardiac OHCA. However, transport to a high-volume hospital may improve the neurological prognosis in cardiac OHCA patients with ROSC before arrival at the emergency department.
Out-of-hospital cardiac arrest (OHCA) occurs in 250,000 to 300,000 patients worldwide each year [1]. Advances have been made in the management of cardiac arrest, including modern cardiopulmonary resuscitation (CPR), extracorporeal CPR, emergency cardiovascular therapy, and targeted temperature management [2]; however, the in-hospital survival and neurologically intact survival rates remain disappointingly low in patients with a successful return of spontaneous circulation (ROSC) [3].
The outcomes for patients with OHCA have been shown to improve with the quality of round-the-clock post-resuscitation care [4, 5], while the frequency of post-resuscitation care in the emergency department also exerts a positive impact on patient outcomes [6, 7]. Therefore, recommendations suggesting criteria for cardiac-arrest hospitals have been published [8]. However, the relationship between hospital volume and prognosis in patients with OHCA is inconclusive, since some studies have demonstrated improved prognosis at high-volume hospitals [9–13], while others did not report any such improvement [14–16].
The relationship between the number of surgeries performed in hospitals and patient outcomes has been studied since the 1980s [17, 18]. In recent years, several studies have reported on the relationship between patient outcomes and medical services rendered by hospitals and physicians in various fields, not limited to surgery [19]. Specialized clinical departments such as stroke and coronary artery care units were established prior to the establishment of specialized treatment facilities for patients with cardiac arrest, and the effect of these facilities on prognosis improvement has been proven [20, 21].
In this study, we evaluated the impact of the volume of annual hospital admissions on the prognosis of patients with OHCA using a large cohort from a nationwide study.
This study conducted a post-hoc analysis of patients included in the Japanese Association for Acute Medicine OHCA (JAAM-OHCA) registry. This database is a nationwide multihospital prospective repository of hospital data collected according to the Utstein template, and in-hospital data, including treatments, arterial blood gas levels, and outcomes [22].
All Japanese emergency medical services (EMS) personnel can perform CPR in accordance with the Japanese resuscitation guidelines, which are based on the statement of the International Liaison Committee on Resuscitation. EMS personnel are legally prohibited from terminating resuscitation at the scene, and all patients with OHCA are transported to the hospital unless death is certain. The destination is usually not altered due to the cause of cardiac arrest. EMS usually transport patients with OHCA to the nearest emergency hospital, which is under the purview of the local medical control transports some cases, patients with ROSC may be transferred to a hospital that can provide more advanced care. In this registry, patient information is recorded when the hospital that first admitted the patient is a participating research hospital, and information on the prognosis is provided to the research facility by the transferring hospital. This registry includes all patients with OHCA, irrespective of internal or external causes. We used the JAAM-OHCA registry data for patients admitted between June 2014 and September 2017. Eighty-six hospitals and 35,754 patients were registered during this period.
The following cases were excluded from the analysis in this study were patients: (a) aged < 17 years, (b) with unknown initial rhythm, (c) who experienced ROSC upon contact with the EMS, (d) with an unknown prognosis 1 month after cardiac arrest, (e) with extrinsic cardiac arrest, (f) with cardiac arrest due to other medical causes, and (g) who died in the emergency department.
Patient-related outcomes assessed in this study included neurological outcome and survival 1 month after cardiac arrest. Neurological outcomes were evaluated using the cerebral performance category (CPC) scale [23]. Patients with a score of CPC 1 or CPC 2 were designated as having a favorable neurological outcome.
This retrospective analysis was conducted using a prospective registry (JAAM-OHCA registry).
Hospitals were divided into three equal groups according to the number of patients with cardiac OHCA (i.e., patient volume) received per year. In the present study, patient volume was equally divided by the number of hospitals, resulting in an unequal number of patients in each group. We selected the following potential patient-related factors that may affect the prognosis: sex, age, contact between doctor and patient before arrival at hospital, motor score on the Glasgow coma scale upon arrival at the emergency department (ED), defibrillation performed by EMS, use of airway devices by EMS, types of airway devices used by the EMS, primary electrocardiography rhythm at the scene, witness by bystander, CPR initiated by a bystander, defibrillation performed by a bystander, intravenous fluid administration by EMS, dosage of adrenaline administered until arrival at the ED, cause of cardiac OHCA, time from calling the EMS to arrival at the scene, time from calling the EMS to the first ROSC before arriving at the hospital, time from calling the EMS to the first ROSC after arriving at the hospital, time from arrival at the scene to arrival at the ED, and laboratory data on arrival at the ED (serum urea nitrogen, serum creatinine, serum total protein, serum albumin, pH, partial pressure of carbon dioxide, partial pressure of oxygen, HCO3, base excess, lactate, and glucose).
We also investigated the following three subgroups: patients who experienced ROSC before arrival at the ED, patients who were transported to critical-care medical centers, and patients who were transported to ECMO-capable hospitals. The same outcomes, potential patient factors, and hospital-volume categories were used as those for the main population (patients with OHCA).
We presented the patient and hospital characteristics of the three tertiles of hospital volume (low, middle and high). Continuous variables were presented as medians with interquartile ranges and categorical variables were presented as numbers and percentages. We employed multiple imputation by chained equations to address missing data, and 100 imputed datasets were created. We performed multivariable logistic regression analysis to examine the association between hospital volume and survival 1 month after cardiac arrest or rehabilitation 1 month after cardiac arrest, after adjusting for the above-mentioned patient factors. Robust standard errors were used to account for the clustering of patients within each hospital. Odds ratios and 95% confidence intervals (CIs) were calculated. All analyses were performed using R version 3.6.3. All reported p-values were two-tailed, and differences with p-values (p) < 0.05 were considered statistically significant.
Adult patients with OHCA (n = 28,784) were retrieved from those enrolled in the JAAM-OHCA registry (n = 34,754). Children under 17 years of age (n = 737), patients with missing data (n = 3,816), and patients who had already attained ROSC at the time of EMS contact (n = 1,417) were excluded. The current study also excluded patients with non-cardiac causes of OHCA (n = 13,601) and patients who died in the emergency room (n = 11,551), to ensure accurate assessment of the impact of the volume of annual hospital admissions on OHCA patients. Finally, the remaining 3,632 patients with cardiac OHCA were included in the analysis (Fig. 1).
The hospitals were divided as follows on the basis of volume: low volume, 29 hospitals (patients, n = 250); medium volume, 28 hospitals (patients, n = 817); and high volume, 29 hospitals (patients, n = 2,565). The characteristics of the hospitals are presented in Table 1. The percentage of critical-care medical centers and number of doctors on the night/holiday shift were positively correlated with hospital volume (p < 0.001 and 0.018, respectively). Table 2 shows the characteristics of the patients included in the analysis based on hospital volume. Most characteristics related to the hospitals and patient transport did not differ significantly among the hospital-volume categories. However, the number of patients who contacted doctors before arriving at the hospital and the number of patients who required veno-arterial ECMO for CPR tended to increase with the increase in hospital volume.
| Low-Volume Hospital | Middle-Volume Hospital | High-Volume Hospital | |
|---|---|---|---|
| Institutions, n | 29 | 28 | 29 |
| Number of beds | 604.0 (460.0–800.0) | 624.0 (470.8–758.2) | 605.0 (520.0–768.0) |
| Number of ICU beds | 10.0 (6.0–14.0) | 9.5 (6.0–18.5) | 12.0 (8.0–20.0) |
| Critical care medical center | 16 (55.2%) | 21 (75.0%) | 29 (100.0%) |
| Number of all OHCA patients delivered in the last 1 year | 70.0 (31.0–106.0) | 123.5 (95.0–150.0) | 230.0 (158.0–320.0) |
| Number of hospitalized cardiac OHCA patients per year | 5.5 (3.4–6.8) | 13.8 (12.0–16.8) | 32.1 (24.6–39.4) |
| Number of doctors in the treatment of cardiac arrest cases at emergency department | |||
| Day shift | |||
| One doctor, n (%) | 2 (6.9%) | 0 (0.0%) | 1 (3.4%) |
| Two doctors, n (%) | 6 (20.7%) | 2 (7.1%) | 2 (6.9%) |
| ≥ 3 doctors, n (%) | 21 (72.4%) | 26 (92.9%) | 26 (89.7%) |
| Night/holiday shift | |||
| One doctor, n (%) | 6 (20.7%) | 2 (7.1%) | 1 (3.4%) |
| Two doctors, n (%) | 13 (44.8%) | 8 (28.5%) | 6 (20.7%) |
| ≥ 3 doctors, n (%) | 10 (34.5%) | 20 (71.4%) | 22 (75.9%) |
| Number of nurses in the treatment of cardiac arrest cases at emergency department | |||
| Day shift | |||
| One nurse, n (%) | 2 (6.9%) | 2 (7.1%) | 6 (20.7%) |
| Two nurses, n (%) | 11 (37.9%) | 11 (39.3%) | 12 (41.4%) |
| ≥ 3 nurses, n (%) | 16 (55.2%) | 15 (53.8%) | 11 (37.9%) |
| Night/holiday shift | |||
| One nurse, n (%) | 10 (34.5%) | 6 (21.4%) | 8 (27.6%) |
| Two nurses, n (%) | 10 (34.5%) | 13 (46.4%) | 15 (51.7%) |
| ≥ 3 nurses, n (%) | 9 (31.0%) | 9 (32.2%) | 6 (20.7%) |
| Availability of medical specialists in hospital | |||
| Emergency Physician, n (%) | 27 (93.1%) | 27 (96.4%) | 29 (100.0%) |
| Intensivist, n (%) | 23 (79.3%) | 20 (71.4%) | 26 (89.7%) |
| Anesthesiologist, n (%) | 25 (86.2%) | 25 (89.3%) | 21 (72.4%) |
| Cardiologist, n (%) | 25 (86.2%) | 27 (96.4%) | 27 (93.1%) |
| ECMO-capable hospitals, n (%) | 26 (89.7%) | 27 (96.4%) | 29 (100.0%) |
| Data are presented as the median (25th -75th percentile), percentage, or numbers. | |||
| ECMO: extra corporeal membrane oxygenation, ICU: intensive care unit, OHCA: out-of-hospital cardiac arrest. | |||
| Low-Volume Hospital | Middle-Volume Hospital | High-Volume Hospital | |
|---|---|---|---|
| Institutions, n | 29 | 28 | 29 |
| Patients, n | 250 | 817 | 2,565 |
| Male, n (%) | 170 (68.0%) | 575 (70.4%) | 1,852 (72.2%) |
| Age, year | 70.0 (60.0–82.0) | 71.0 (60.0–82.0) | 69.0 (58.0–79.0) |
| Cause of cardiac OHCA, n (%) | |||
| Acute coronary syndrome | 77 (30.8%) | 269 (32.9%) | 805 (31.4%) |
| Other cardiac 1 | 75 (30.0%) | 226 (27.7%) | 620 (24.2%) |
| Presumed cardiac | 98 (39.2%) | 322 (39.4%) | 1,140 (44.4%) |
| Witness by bystander, n (%) | 171 (68.4%) | 564 (69.0%) | 1,754 (68.4%) |
| CPR initiated by bystander, n (%) | 130 (52.0%) | 358 (43.8%) | 1,233 (48.1%) |
| Defibrillation by bystander, n (%) | 5 (2.0%) | 48 (5.9%) | 160 (6.2%) |
| Primary ECG rhythm at the scene, n (%) | |||
| Ventricular fibrillation | 89 (35.6%) | 325 (39.8%) | 1,113 (43.4%) |
| Pulseless ventricular tachycardia | 1 (0.4%) | 10 (1.2%) | 16 (0.6%) |
| Pulseless electrical activity | 71 (28.4%) | 223 (27.3%) | 701 (27.3%) |
| Asystole | 89 (35.6%) | 259 (31.7%) | 735 (28.7%) |
| Treatments by EMS | |||
| Defibrillation, n (%) | 58 (23.2%) | 196 (24.0%) | 722 (28.1%) |
| Use of airway devices, n (%) | |||
| Bag valve mask | 179 (71.6%) | 485 (59.4%) | 1,041 (40.6%) |
| Laryngeal mask airway | 5 (2.0%) | 21 (2.6%) | 171 (6.7%) |
| Esophageal obturator airway | 53 (21.2%) | 267 (32.7%) | 940 (36.6%) |
| Tracheal intubation | 13 (5.2%) | 44 (5.4%) | 413 (16.1%) |
| Intravenous fluid administration, n (%) | 78 (31.6%) | 329 (40.3%) | 1120 (43.7%) |
| Treatments by doctor before arrival at ED, n (%) | 23 (9.2%) | 91 (11.1%) | 566 (22.1%) |
| Adrenaline dosage until arrival at ED (mg) | 2.0 (1.0–4.0) | 3.0 (2.0–5.0) | 2.0 (1.0–4.0) |
| Time (min.) | |||
| From calling EMS to arrival at the scene (min) | 9.0 (7.0–11.0) | 8.0 (7.0–10.0) | 8.0 (6.0–10.0) |
| From arrival at the scene to arrival at the ED (min) | 22.0 (17.0–29.0) | 22.0 (17.0–29.0) | 24.0 (18.0–31.0) |
| ECG rhythm on arrival at ED, n (%) | |||
| Ventricular fibrillation | 28 (11.2%) | 101 (12.4%) | 469 (18.3%) |
| Pulseless ventricular tachycardia | 5 (2.0%) | 8 (1.0%) | 15 (0.6%) |
| Pulseless electrical activity | 65 (26.0%) | 220 (26.9%) | 645 (25.1%) |
| Asystole | 87 (34.8%) | 249 (30.5%) | 714 (27.8%) |
| Return of spontaneous circulation | 65 (26.0%) | 239 (29.3%) | 722 (28.1%) |
| CPR by V-A ECMO, n (%) | 37 (14.8%) | 144 (17.6%) | 667 (26.0%) |
| Time from arrival at ED to start of VA-ECMO (min) | 35.5 (26.8–63.0) | 40.5 (29.0–65.0) | 29.0 (20.0–41.0) |
| Laboratory data on arrival at the ED | |||
| Serum Urea nitrogen (mg/dl) | 19.1 (14.1–30.8) | 19.0 (14.9–27.0) | 18.9 (14.0–26.6) |
| Serum Creatinine (mg/dl) | 1.15 (0.95–1.60) | 1.13 (0.90–1.43) | 1.11 (0.90–1.50) |
| Serum total protein (g/dl) | 6.2 (5.7–6.8) | 6.1 (5.5–6.7) | 6.1 (5.4–6.6) |
| Serum albumin (g/dl) | 3.4 (3.0–3.8) | 3.4 (2.9–3.8) | 3.3 (2.8–3.7) |
| pH | 7.06 (6.92–7.25) | 7.10 (6.93–7.25) | 7.06 (6.90–7.25) |
| PaCO2 (mmHg) | 52.3 (38.6–77.4) | 52.5 (39.5–73.5) | 51.80 (37.3–77.5) |
| PaO2 (mmHg) | 144.0 (82.9–288.7) | 137.5 (81.4–280.0) | 169.0 (82.6–340.0) |
| HCO3 (mEq/l) | 16.2 (12.8–19.7) | 16.2 (12.1–19.8) | 15.4 (11.9–18.8) |
| Base excess (mEq/l) | -13.1 (-17.9–-7.3) | -13.0 (-18.7–-7.0) | -14.4 (-20.2–-8.6) |
| Lactate (mg/dl) | 100.8 (72.0–129.6) | 90.8 (59.2–122.1) | 95.0 (65.7–128.7) |
| Glucose (mg/dl) | 244.0 (172.25–305.25) | 260.5 (198.00–330.50) | 263.0 (199.0–330.0) |
| Patient with ROSC prior to arrival at ED, n (%) | 65 (26.0%) | 239 (29.3%) | 722 (28.1%) |
| Time from calling EMS to the first ROSC before arriving at the ED (min) 2 | 22.0 (15.0–27.0) | 18.0 (13.0–25.0) | 19.0 (13.0–26.0) |
| Time from calling EMS to the first ROSC after arriving at the ED (min) 3 | 44.0 (34.0–56.5) | 42.5 (34.0–57.0) | 44.0 (34.0–57.0) |
| Time from ED arrival to ROSC after admission (min) 3 | 13.0 (8.0–20.0) | 13.0 (8.0–22.0) | 13.0 (8.0–24.0) |
| Motor score of GCS in ED | 1.0 (1.0–1.0) | 1.0 (1.0–1.0) | 1.0(1.0–1.0) |
| Therapeutic hypothermia, n (%) | 74 (29.6%) | 256 (31.3%) | 955 (37.2%) |
| Outcomes one month after cardiac arrest | |||
| Survive, n (%) | 81 (32.4%) | 269 (32.9%) | 883 (34.4%) |
| Favorable neurological outcome, n (%) | 46 (18.4%) | 167 (20.4%) | 543 (21.2%) |
| Data are presented as the median (25th -75th percentile), percentage, or numbers. | |||
| 1 “Other cardiac” causes include heart failure, valvular disease, cardiomyopathy, and cardiac diseases other than identified acute coronary syndrome. | |||
| 2 Data limited to cases with ROSC prior to ED arrival. | |||
| 3 Data limited to cases with cardiac arrest on arrival at the ED. | |||
| CPR: cardiopulmonary resuscitation, ECG: electrocardiogram, ED: emergency department, EMS: emergency medical services, GCS: Glasgow coma scale, OHCA: out-of-hospital cardiac arrest, ROSC: return of spontaneous circulation VA-ECMO: veno-arterial extra corporeal membrane oxygenation. | |||
Figure 2 shows the odds ratios of the impact of hospital volume on the patient survival rate 30 days after admission. There was no consistent trend in the survival outcomes. Figure 3 shows the odds ratios of the impact of hospital volume on favorable neurological outcomes 30 days after admission. Compared to the previous results, the prognosis tended to improve with the increase in hospital volume. An analysis focused on patients that achieved ROSC before arrival at the ED revealed that admission to a high-volume center significantly improved the neurological prognosis (odds ratio: 1.955, p = 0.04). The characteristics of OHCA patients in each subgroup are shown in Additional files 1–3.
This study retrospectively analyzed the effect of institutional volume on patient prognosis using data from more than 30,000 individuals registered with the nationwide OHCA registry. Although there was no significant difference, the neurological outcome tended to improve with the increase in the annual number of cardiac OHCA patients, which was remarkable in cardiac OHCA patients who experienced ROSC before arrival to the ED.
Previous studies that examined institutional volume and patient prognosis failed to reach a consensus on various aspects of this association [9–16]. The relatively small sample size and inclusion of few hospitals constituted limitations of these studies, while the current study, which incorporated patients from a large registry, may be equipped to overcome this problem.
The divergent conclusions in previous studies may be attributed to differences in the target patient populations: some studies that reported no association between hospital volume and patient prognosis included patients with non-cardiac OHCA [14, 15]. In contrast, the cohort of studies that reported improvement in patient outcomes at high-volume hospitals was restricted to patients with cardiac OHCA [11–13]. Patients whose transport time was 10 min or less [11] and those with a shockable rhythm [12] were reported to have a better prognosis. Therefore, previous studies suggested that patients who are likely to survive and have a favorable neurological outcome are more likely to benefit from hospital volume. In the present study, we found a significant prognostic effect of hospital volume when limited to patients with ROSC before arrival at the ED. This result is consistent with that of several previous studies.
Meanwhile, another large-scale study of patients with cardiac OHCA (whose sample size was comparable to the current study) reported that no correlation existed between hospital volume and prognosis [16]. There are several possible reasons for the lack of a significant correlation between the size of the hospital and patient prognosis. Hospital factors such as location (urban/rural), teaching status, and 24-h cardiac interventional services have been reported to be correlated with prognosis [10, 13]. Similar studies have reported that physical volume, and nurses and rehabilitation therapists affect patient prognosis [24–28], although these studies did not investigate patients with cardiac arrest.
This study did have some limitations. Although the sample size of this study was large, there was a bias in the number of patients in the groups, which was unavoidable owning to categorization, and may have affected the results. This study was limited to registry-participating hospitals, which resulted in a facility selection bias. This is because hospitals that participate in registries are more likely to be highly active. Moreover, there may be differences in the registration methods and omissions in registration depending on the hospital, which may affect the results. Limited information was available on the differences between hospitals and their respective characteristics. Hospitals characteristics besides the number of OHCA patients accepted may have affected the results, because we did not utilize factors related to hospitals as covariates in the logistic regression analysis.
The current study showed that the annual number of cardiac OHCA patients admitted to a hospital may have a positive impact on favorable neurological prognosis, although other hospital characteristics were not considered. Further research is needed to identify the hospital characteristics with the optimal effect on OHCA patients.
The annual number of cardiac OHCA patients received by the hospital did not significantly affect the prognosis of adult cardiogenic OHCA patients in most cases, although it was beneficial in cardiac arrest patients who achieved ROSC before arrival at the hospital’s ED. Thus, transport to a high-volume hospital may improve prognosis.
CPC: cerebral performance category
CPR: cardiopulmonary resuscitation
ECG: electrocardiogram
ECMO: extra corporeal membrane oxygenation.
ED: emergency department
EMS: emergency medical services
GCS: Glasgow coma scale
ICU: intensive care unit
JAAM-OHCA: Japanese Association for Acute Medicine out-of-hospital cardiac arrest
OHCA: out-of-hospital cardiac arrest
ROSC: return of spontaneous circulation
VA-ECMO: veno-arterial extra corporeal membrane oxygenation
Ethics approval and consent to participate: The registry for this study was an epidemiological study with no treatment intervention, and informed consent was waived. This decision was approved by The respective Ethics Committees of Kyoto University and Hokkaido University .The experimental protocols were approved by The respective Ethics Committees of Kyoto University and Hokkaido University (approval number: 0130060). All experiments were performed in accordance with relevant guidelines and regulations.
Consent for publication: Not applicable.
Availability of data and materials: The datasets generated and/or analysed during the current study are not publicly available due to the large amount of data but are available from the corresponding author on reasonable request.
Competing interests: The authors declare that they have no competing interests.
Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Authors' contributions: TT and MH contributed to study conception and manuscript preparation. KO and KM contributed to analysis of the data. MH contributed to manuscript preparation and revision for intellectual content. All authors read and approved the final manuscript version prior to submission.
Acknowledgements: We would like to thank Editage (https://online.editage.jp/) for English language editing.