<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04419194</url>
  </required_header>
  <id_info>
    <org_study_id>PUMCH-PE-Climatic factors</org_study_id>
    <nct_id>NCT04419194</nct_id>
  </id_info>
  <brief_title>Effect of Climatic Factors on the Seasonal Fluctuation of Pulmonary Embolism</brief_title>
  <official_title>Association Between Climatic Factors and Hospital Admissions for Pulmonary Embolism: Time Series Study in China Between Years 2014 to 2019.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Peking Union Medical College Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Peking Union Medical College Hospital</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      To estimate the risks of daily hospital admissions for pulmonary embolism associated with&#xD;
      short term exposure to climatic factors (temperature, precipitation, air pressure, sunshine&#xD;
      duration, relative humidity, wind speed, and ambient fine particulate matter [aerodynamic&#xD;
      diameter ≤2.5 μm; PM2.5]) in China.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Hospital admissions for pulmonary embolism were identified based on the primary diagnosis.&#xD;
      The central adjudication committee at Peking Union Medical College Hospital (Beijing, China)&#xD;
      reviewed all medical and death records and determined the final diagnosis. Two adjudication&#xD;
      committee members verified events independently, and discrepancies were resolved by&#xD;
      discussion involving additional committee members.For each admission, we extracted data on&#xD;
      the date of admission, sex, age, and location of the patient from hospital information&#xD;
      system.&#xD;
&#xD;
      All the data of daily meteorological variables for the same period, including temperature&#xD;
      variables (°C) (the min, max and mean temperature), relative humidity (%), air pressure&#xD;
      (hPa), precipitation (mm), wind speed (m/s) and sunshine duration (h), were collected from&#xD;
      the China Meteorological Data Sharing Service System&#xD;
      (http://www.escience.gov.cn/metdata/page/index.html). The data on PM2.5 levels in each city&#xD;
      was collected from the National Air Pollution Monitoring System.&#xD;
&#xD;
      An overdispersed generalised additive model was used to estimate associations between&#xD;
      climatic factors and pulmonary embolism admissions. A distributed lag non-linear model (DLNM)&#xD;
      was employed to examine their lagged effects.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">July 31, 2014</start_date>
  <completion_date type="Actual">July 31, 2019</completion_date>
  <primary_completion_date type="Actual">July 31, 2019</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Crossover</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Incidence of pulmonary embolism</measure>
    <time_frame>From July 31, 2014 to July 31, 2019</time_frame>
    <description>Daily counts of hospital admissions for primary diagnoses of pulmonary embolism among different demographic groups were used to estimate the associations between climatic factors and morbidity.</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">10000</enrollment>
  <condition>Pulmonary Embolism</condition>
  <arm_group>
    <arm_group_label>Observation</arm_group_label>
    <description>Observation</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        Patients diagnosed as pulmonary embolism who meet the inclusion criteria above.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Males and females.&#xD;
&#xD;
          -  With a primary diagnosis of pulmonary embolism based on clinical symptoms, with or&#xD;
             without radiologic features.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Lack of important data.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Shi Juhong, M.D</last_name>
    <role>Study Chair</role>
    <affiliation>Peking Union Medical College Hospital</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Peking Union Medical College Hospital</name>
      <address>
        <city>Beijing</city>
        <state>Beijing</state>
        <zip>100730</zip>
        <country>China</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>May 2020</verification_date>
  <study_first_submitted>June 4, 2020</study_first_submitted>
  <study_first_submitted_qc>June 4, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 5, 2020</study_first_posted>
  <last_update_submitted>June 4, 2020</last_update_submitted>
  <last_update_submitted_qc>June 4, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">June 5, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Pulmonary Embolism</keyword>
  <keyword>Climate</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Pulmonary Embolism</mesh_term>
    <mesh_term>Embolism</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04419194
org study id: PUMCH-PE-Climatic factors
nct id: NCT04419194
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
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.
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.
observational model: Case-Crossover
time perspective: Retrospective
measure: Incidence of pulmonary embolism
time frame: From July 31, 2014 to July 31, 2019
description: Daily counts of hospital admissions for primary diagnoses of pulmonary embolism among different demographic groups were used to estimate the associations between climatic factors and morbidity.
arm group label: Observation
description: Observation
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: Shi Juhong, M.D
role: Study Chair
affiliation: Peking Union Medical College Hospital
facility: 
country: China
responsible party type: Sponsor
mesh term: Pulmonary Embolism
mesh term: Embolism