Database
We analyzed data from the Shizuoka Kokuho Database in this study [15,16,17,18]. This database is owned by the Federation of National Health Insurance Organizations and consists of administrative claims data from Shizuoka Prefecture, Japan. Shizuoka Prefecture had a population of approximately 3.6 million in 2020.
There are three main types of health insurance plans in Japan: Employee’s Health Insurance (EHI), National Health Insurance (NHI), and Late Elder’s Health Insurance (LEHI); EHI and NHI are for those under the age of 75. NHI is for people who are mainly self-employed citizens, part-time workers, or unemployed. Employees of large or small companies are not enrolled in the NHI plan. All individuals over the age of 75 are enrolled in the LEHI plan. The Shizuoka Kokuho Database consists of NHI and LEHI data and covers approximately 2.2 million people in Shizuoka Prefecture [18].
In this study, we analyzed data from April 2012 to September 2018. The data included registrant information (including age, sex, observation period, reason for withdrawal, and death dates), insurance claim data (including prescribed medicines, procedures, and 10th Revision of the International Classification of Diseases (ICD-10) codes), and the long-term care insurance data (including support and care level as well as information about care services provided for insured individuals). These claims data were updated on a monthly basis. The ICD-10 diagnostic codes were updated for the duration of treatment for a specific disease. All prescribed medicines are coded in Japanese original codes, and each code is linked to an Anatomical Therapeutic Chemical Classification System (ATC) code. These data were tied to individuals by anonymized individual identifiers for research purposes.
This study was approved by the institutional review board of Shizuoka General Hospital (Shizuoka, Japan; SGHIRB#2020021), and informed consent was waived because the data were anonymized.
Study population
We included those with cardiac arrests without return of spontaneous circulation (ROSC) on arrival at the hospital and assumed that all cardiac arrest patients who arrived at the hospital without ROSC received closed chest compressions after arrival at the hospital. To identify people with cardiopulmonary arrests without ROSC on arrival at the hospital, we first included those who had a record of closed chest compressions in the admission month. We excluded those who were less than 20 years old with cardiac arrests due to causes other than choking. The cause of cardiac arrest was determined to be choking by the presence of the ICD-10 codes for choking (codes: T172, T173, T174, T175, T178, T179, T71). We excluded those receiving ventilation assistance or who received enteral nutrition in the month prior to cardiac arrest because they were not living independently and may have had serious dysphagia before the event. We excluded those with an upper airway tumor because their upper airway may have been restricted by the tumor and the tumor may have affected their long-term prognosis. We excluded those who lacked claims data during the 6 months before the event because we could not evaluate information about comorbidities and medications before the event.
Outcomes
We defined the primary endpoint as death, and survival rates were analyzed at 3 and 12 months. In this database, deaths were recorded separately from insurance withdrawal. We defined the secondary endpoint as independence on tube feeding or total parenteral nutrition (TPN) at 3 and 12 months.
Definitions and data collection
Other variables included age, sex, comorbidities (dementia, stroke, Sjogren’s syndrome), medications (antipsychotics, dopamine agonists, sedative agents, anticholinergic agents), and living conditions before the event (ADL, nursing home residency, history of aspiration pneumonia, dysphagia rehabilitation). In addition, we considered targeted temperature management, tracheostomy, gastrostomy, and dysphagia rehabilitation as procedures after choking-induced cardiac arrest. From the ICD-10 diagnostic codes registered within 12 months prior to choking, we identified comorbidities (stroke, Sjogren’s syndrome, aspiration pneumonia). From the ATC codes, we identified medicines (donepezil, antipsychotics, dopamine agonists, sedative agents, anticholinergic agents) prescribed prior to choking. We defined dementia as the use of donepezil. From the long-term care insurance data, we identified the level of care needed and nursing home admission. In Japan, level of care is categorized into seven levels: two levels of support, with relative independence; and five levels of nursing care [19, 20]. We defined independence in ADL as level 2 or lower care and dependence as level 3 or higher care. From the records of procedures after choking in the insurance claims database, we identified dysphagia rehabilitation, targeted temperature management, tracheostomy, and gastrostomy.
Statistical analysis
We summarized data as the mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables and frequency and percentage for categorical variables. Comparisons were made using the Mann-Whitney U test for continuous variables and the χ2 test or Fisher’s exact test for categorical variables.
Kaplan-Meier survival analysis was used to assess long-term survival. Survival time was compared among age groups (20–64 years, 65–74 years, 75–84 years, 85 years and older). It was also compared between the ventilator- and nonventilator-dependent groups at 3 months.
Statistical analyses were performed using Stata (version: 16.1; StataCorp, 2020, College Station) and R (version: 4.0.1; R Foundation for Statistical Computing), and a two-sided significance level < 0.05 was considered statistically significant.
