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Completed

NCT Number: NCT04903496

Clinical Characteristics and Disease Burden of Diabetic Patients Based on Tianjin Regional Database

The study aims to investigate the clinical characteristics, treatment, and economic burden of disease of Chinese diabetic/non-diabetic patients with/without established cardiovascular disease (CVD), chronic kidney disease (CKD), or at high cardiovascular risk, including:

* Primary objectives: describe the proportion of Chinese diabetic/non-diabetic patients with established cardiovascular disease, CKD, or at high cardiovascular risk including hypertension and hyperlipidemia * Secondary objectives: describe the demographic characteristics of the last visit for all patients, and the demographic characteristics of inpatients over time; investigate the clinical characteristic for all patients

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Key information

Conditions

Diabetes Diabetes Mellitus Endocrine System Diseases Glucose Metabolism Disorders Metabolic Diseases Nutritional and Metabolic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Chengdu Big Data Association

Chengdu, 610041, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients in the Tianjin regional database from 01/01/2015 to 31/12/2019
  • Group A: patients with diagnosis of diabetes, and with diagnosis of cardiovascular disease, heart failure, chronic kidney disease or at high cardiovascular risk
  • Group B: patients with diagnosis of diabetes, but not with diagnosis of cardiovascular disease, heart failure, chronic kidney disease or at high cardiovascular risk
  • Group C: patients with diagnosis of cardiovascular disease, heart failure, chronic kidney disease or at high cardiovascular risk, but not with diagnosis of diabetes
  • Group D: patients without diagnosis of cardiovascular disease, heart failure, chronic kidney disease or at high cardiovascular risk, and without diagnosis of diabetes. We will randomly select a group of non-diabetic patients without any of the above diseases by matching on age and gender

Definition of diabetes, cardiovascular disease, chronic kidney disease and high cardiovascular risk:

  • Diabetes: patients with at least 1 discharged diagnosis or 2 outpatient diagnosis of diabetes (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) (International classification of disease (ICD)-10 E10-E14);
  • Cardiovascular disease: patients with at least 1 discharged diagnosis or 2 outpatient diagnosis of ischemic heart diseases (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) (ICD-10 I20~I25); or patients with at least 1 discharged diagnosis or 2 outpatient diagnosis of cerebrovascular diseases (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) (ICD-10 I60~I69); or patients with at least 1 discharged diagnosis or 2 outpatient diagnosis of ischemic peripheral artery disease (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) (ICD-10 E10.501, E11.603, E14.501, E14.606, E14.503, I73.9, I99.03, I99.04);
  • Heart failure: patients with at least 1 discharged diagnosis or 2 outpatient diagnosis of heart failure (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) (ICD-10 I50);
  • Chronic kidney disease (CKD): inpatients with at least once 1 discharged diagnosis CKD (ICD-10 N18), or inpatients with the last estimated glomerular filtration rate (eGFR, calculated by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation) <60 mL/min/1.73 m2 or prescription of dialysis, but not with the diagnosis of acute kidney injury (ICD-10 N17); or outpatients with at least 2 diagnosis of CKD (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) or with two consecutive eGFR (calculated by CKD-EPI equation) <60 mL/min/1.73 m2 by 90 days or more;
  • High cardiovascular risk: patients with at least 1 discharged diagnosis or 2 outpatient diagnosis of hypertension (the first diagnosis will be the index diagnosis, and the time interval between diagnoses is not restricted) (ICD-10 I10~I15); or at least 1 discharged diagnosis or 2 outpatient diagnosis of hyperlipidemia (ICD-10 E78.001-E78.003, E78.101, E78.203, E78.301-E78.304, E78.306, E78.401, E78.501, E78.902);

Exclusion criteria

  • Patients with non-Chinese nationalities
  • Duplicated storage (records with same inpatient code)

Treatment and study plan

Primary outcomes

  1. Number of Participants With Established Cardiovascular Disease, or Chronic Kidney Disease, or High Cardiovascular Risk

    Time frame: up to 5 years (2015 up to 2019)

    Number of participants with established cardiovascular disease (CVD), chronic kidney disease (CKD), and/or high cardiovascular (CV) risk was calculated as (100%* Number of patients with labels of interested diseases from 2015 to the given year)/ (Number of diabetic or non-diabetic patients from 2015 to the given year).

    To compare diabetic with non-diabetic patients within a year and across years

    • the arms with diabetic in- and outpatients [Arm A and B together] were combined
    • the arms with non-diabetic in- and outpatients [Arm C and D together] were combined by year.

    Patients with risk factors were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

Secondary outcomes

  1. Mean Age of Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    The mean age was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  2. Mean Age of Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    The mean age was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  3. Mean Age of Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    The mean age was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  4. Number of Female and Male Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    The number of female and male was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  5. Number of Female and Male Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    The number of female and male was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  6. Number of Female and Male Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    The number of female and male was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  7. Number of Inpatients and All Participants (In-and Outpatients) With Insurance Payment at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    The number of participants with insurance payment was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  8. Number of Inpatients and All Participants (In-and Outpatients) With Insurance Payment at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    The number of participants with insurance payment was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  9. Number of Inpatients and All Participants (In-and Outpatients) With Insurance Payment at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    The number of participants with insurance payment was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  10. Number of Inpatients and All Participants (In-and Outpatients) by Discharge Department at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    The number of participants in a particular discharge department was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses and records in multiple discharge departments simultaneously. Thus, one participant could potentially occur more than once per arm.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  11. Number of Inpatients and All Participants (In-and Outpatients) by Discharge Department at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    The number of participants in a particular discharge department was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses and records in multiple discharge departments simultaneously. Thus, one participant could potentially occur more than once per arm. Thus, one participant could potentially occur more than once per arm.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  12. Number of Inpatients and All Participants (In-and Outpatients) by Discharge Department at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    The number of participants in a particular discharge department was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses and records in multiple discharge departments simultaneously. Thus, one participant could potentially occur more than once per arm.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  13. Number of Deaths in Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2015

    Time frame: On the last visit (1 day) in 2015 data was retrospectively assessed for the last 12 months in 2015.

    The number of participants who were diagnosed as dead in 2015 was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  14. Number of Deaths in Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2017

    Time frame: On the last visit (1 day) in 2017 data was retrospectively assessed for the last 12 months in 2017.

    The number of participants who were diagnosed as dead in 2017 was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  15. Number of Deaths in Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2019

    Time frame: On the last visit (1 day) in 2019 data was retrospectively assessed for the last 12 months in 2019.

    The number of participants who were diagnosed as dead in 2019 was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  16. The Value of Glycated Hemoglobin (HbA1c) in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    The value of glycated hemoglobin (HbA1c) was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  17. The Value of Glycated Hemoglobin (HbA1c) in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    The value of glycated hemoglobin (HbA1c) was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  18. The Value of Glycated Hemoglobin (HbA1c) in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    The value of glycated hemoglobin (HbA1c) was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  19. Concentration of Random Blood Glucose in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    The concentration (Millimole per liter (mmol/L)) of random blood glucose was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  20. Concentration of Random Blood Glucose in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    The concentration (Millimole per liter (mmol/L)) of random blood glucose was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  21. Concentration of Random Blood Glucose in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    The concentration (Millimole per liter (mmol/L)) of random blood glucose was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  22. Serum Creatine Concentration in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2015

    Time frame: Last visit in 2015, up to 1 day

    Serum creatine concentration (μmol/L) was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2015. The Arms A, B, C, D - inpatients only were mutually exclusive in 2015.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  23. Serum Creatine Concentration in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2017

    Time frame: Last visit in 2017, up to 1 day

    Serum creatine concentration (μmol/L) was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2017. The Arms A, B, C, D - inpatients only were mutually exclusive in 2017.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

  24. Serum Creatine Concentration in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2019

    Time frame: Last visit in 2019, up to 1 day

    Serum creatine concentration (μmol/L) was calculated for inpatients grouped by their diagnoses category [Arm A, B, C, D - inpatients only] and for all participants [All in- and outpatients] at their last visit in 2019. The Arms A, B, C, D - inpatients only were mutually exclusive in 2019.

    Patients with risk factors (RF) were patients with diagnosis of CVD, HF, CKD or at high CV risk. Each participant could potentially have multiple diagnoses simultaneously.

    The data presented for this outcome is an retrospective analysis of electronic healthcare records of the Tianjin regional data base. Participants with diagnoses of interest were identified by International Classification of Disease (ICD) code.

Sponsors and collaborators

Lead sponsor

Boehringer Ingelheim

Industry

Collaborators

  • Chengdu Big Data Association

Registry information

Official study title

Characteristics, Treatment, and Economic Burden of Disease of Chinese Diabetic/Non-diabetic Patients With/Without Established Cardiovascular Disease, Chronic Kidney Disease, or at High Cardiovascular Risk

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
May 26, 2021
Registry last updated
Nov 12, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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