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
Study Type
OBSERVATIONAL
Enrollment
1,233,162
Chengdu Big Data Association
Chengdu, China
Number of Participants With Established Cardiovascular Disease, or Chronic Kidney Disease, or High Cardiovascular Risk
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.
Time frame: up to 5 years (2015 up to 2019)
Mean Age of Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
Mean Age of Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
Mean Age of Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
Number of Female and Male Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
Number of Female and Male Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
Number of Female and Male Inpatients and All Participants (In-and Outpatients) at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
Number of Inpatients and All Participants (In-and Outpatients) With Insurance Payment at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
Number of Inpatients and All Participants (In-and Outpatients) With Insurance Payment at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
Number of Inpatients and All Participants (In-and Outpatients) With Insurance Payment at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
Number of Inpatients and All Participants (In-and Outpatients) by Discharge Department at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
Number of Inpatients and All Participants (In-and Outpatients) by Discharge Department at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
Number of Inpatients and All Participants (In-and Outpatients) by Discharge Department at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
Number of Deaths in Inpatients and All Participants (In-and Outpatients) at Their Last Visit 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.
Time frame: On the last visit (1 day) in 2015 data was retrospectively assessed for the last 12 months in 2015.
Number of Deaths in Inpatients and All Participants (In-and Outpatients) at Their Last Visit 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.
Time frame: On the last visit (1 day) in 2017 data was retrospectively assessed for the last 12 months in 2017.
Number of Deaths in Inpatients and All Participants (In-and Outpatients) at Their Last Visit 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.
Time frame: On the last visit (1 day) in 2019 data was retrospectively assessed for the last 12 months in 2019.
The Value of Glycated Hemoglobin (HbA1c) in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
The Value of Glycated Hemoglobin (HbA1c) in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
The Value of Glycated Hemoglobin (HbA1c) in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
Concentration of Random Blood Glucose in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
Concentration of Random Blood Glucose in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
Concentration of Random Blood Glucose in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
Serum Creatine Concentration in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2015
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.
Time frame: Last visit in 2015, up to 1 day
Serum Creatine Concentration in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2017
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.
Time frame: Last visit in 2017, up to 1 day
Serum Creatine Concentration in Inpatients and in All Participants (in- and Outpatients) at Their Last Visit in 2019
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.
Time frame: Last visit in 2019, up to 1 day
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