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 .
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.
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.