Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-25 @ 1:40 AM
Ignite Modification Date:
2025-12-25 @ 1:40 AM
NCT ID:
NCT04419194
Brief Summary:
To estimate the risks of daily hospital admissions for pulmonary embolism associated with short term exposure to climatic factors (temperature, precipitation, air pressure, sunshine duration, relative humidity, wind speed, and ambient fine particulate matter \[aerodynamic diameter ≤2.5 μm; PM2.5\]) in China.
Detailed Description:
Hospital admissions for pulmonary embolism were identified based on the primary diagnosis. The central adjudication committee at Peking Union Medical College Hospital (Beijing, China) reviewed all medical and death records and determined the final diagnosis. Two adjudication committee members verified events independently, and discrepancies were resolved by discussion involving additional committee members.For each admission, we extracted data on the date of admission, sex, age, and location of the patient from hospital information system.
All the data of daily meteorological variables for the same period, including temperature variables (°C) (the min, max and mean temperature), relative humidity (%), air pressure (hPa), precipitation (mm), wind speed (m/s) and sunshine duration (h), were collected from the China Meteorological Data Sharing Service System (http://www.escience.gov.cn/metdata/page/index.html). The data on PM2.5 levels in each city was collected from the National Air Pollution Monitoring System.
An overdispersed generalised additive model was used to estimate associations between climatic factors and pulmonary embolism admissions. A distributed lag non-linear model (DLNM) was employed to examine their lagged effects.
Study:
NCT04419194
Study Brief:
Protocol Section:
NCT04419194