Epidemiological Study of Out-of-hospital Cardiac Arrest in Guangzhou
1 other identifier
observational
44,375
1 country
1
Brief Summary
Aim This was a population-based retrospective cohort study of OHCA. This study intends to retrospectively analyze the data of pre-hospital emergency system in Guangzhou for 10 years, explore the incidence trend of OHCA in Guangzhou for 10 years; Through further analysis, we try to explore the time distribution characteristics of OHCA in order to understand the epidemiological characteristics and rules of OHCA in super large cities in southern China. Methods The pre-hospital traffic data in the main urban area of Guangzhou Emergency Medical Command Center database from 2011 to 2020 were collected. The cases diagnosed as "cardiac arrest" and "sudden death" were screened, and the cases with non-cardiac causes in the diagnosis were deleted. The crude incidence rate and age-standardized incidence rate of OHCA were calculated. Joinpoint software was used to calculate the changing nodes in the OHCA incidence trend, and the AnnualPercent Change (APC) and Average AnnualPercent Change (Average AnnualPercent Change, APC) of OHCA incidence were calculated. AAPC). The OHCA data were grouped according to the six main urban areas, and the crude incidence rate, ASIR and changing trend of the six main urban areas were calculated. The data of OHCA were grouped by age, and the crude incidence rate, ASIR and changing trend of each age group were calculated. The data information was divided into groups according to 24 hours a day, 7 days a week, and four seasons. The number of OHCA cases in different time periods was statistically described. The data were imported into SPSS 26.0 for analysis, and Mann-Kendall test was used to evaluate the statistical significance of the time trend. Time rhythm variability was tested for mean distribution using chi-square goodness of fit test.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jan 2021
Longer than P75 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
January 1, 2021
CompletedFirst Submitted
Initial submission to the registry
June 3, 2024
CompletedFirst Posted
Study publicly available on registry
June 7, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2025
CompletedJune 7, 2024
December 1, 2023
5 years
June 3, 2024
June 3, 2024
Conditions
Outcome Measures
Primary Outcomes (4)
Crude incidence rate
The frequency of new cases of a disease in a given population over a given period of time.
2011-01-01 to 2020-12-31
Age standardized incidence rate
Incidence rates after removing the influence of age, and incidence rates normalised by age. The rationale is that age is an important influence on cancer incidence, with higher incidence rates occurring at older ages, so that if the age structure of the population in two regions is very different, it is not possible to determine whether the high incidence of a disease in a particular region is due to a different age composition or to other influences if incidence rate comparisons are applied.
2011-01-01 to 2020-12-31
Average annual percentage change
Calculated using the weighted average of the APC, it is an overall measure of trend.
2011-01-01 to 2020-12-31
Annual percentage change
Indicates the change from one year to the next within a segment at a constant percentage on a log-linear model for evaluating trends within segments.
2011-01-01 to 2020-12-31
Study Arms (8)
0-19 years age group
20-29 years age group
30-39 years age group
40 to 49 age group
50 to 59 age group
60 to 69 age group
70 to 79 age group
80+age group
Age group greater than or equal to 80 years
Interventions
Selection of cases with a secondary diagnosis containing the diagnostic keywords "cardiac arrest" and "sudden death"."cardiac arrest" and "sudden death".The incidence rate is then calculated
Eligibility Criteria
Cases in the database with a secondary diagnosis containing the diagnostic keywords "cardiac arrest" and "sudden death".Data were collected from the GZ-EMS Command Centre's dispatch system database of pre-hospital data for the central urban districts of City.
You may qualify if:
- Cases in the database with a secondary diagnosis containing the diagnostic keywords "cardiac arrest" and "sudden death"
You may not qualify if:
- cases where the diagnosis of "cardiac arrest" and "sudden death" includes a diagnosis of a non-cardiac cause such as asphyxiation, suicide, drowning, advanced cancer, trauma, shock, poisoning, cerebral vascular accident, etc;
- cases with duplicate records of sex, age, time of call, pick-up address and initial diagnosis
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Yu Tao
Guangdong, Guangdong, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- STUDY DIRECTOR
Tao Yu
Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, China
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
June 3, 2024
First Posted
June 7, 2024
Study Start
January 1, 2021
Primary Completion
December 31, 2025
Study Completion
December 31, 2025
Last Updated
June 7, 2024
Record last verified: 2023-12
Data Sharing
- IPD Sharing
- Will not share