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

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)

Population: In- and outpatients in 2015, 2017, and 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, groups were combined as per protocol to 'Diabetic Patients \[Arm A and B\]' and 'Non-Diabetic Patients \[Arm C and D\]'. Arms were not mutually exclusive. Only patients with available data were included in this analysis.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.

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.

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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.

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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.

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. Inpatients results \[Arm A, B, C, D\] are reported separately per arm, in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data were included in this analysis. Patients could have records in multiple departments or could not be classified to any given department.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. Inpatients results \[Arm A, B, C, D\] are reported separately per arm, in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data were included in this analysis. Patients could have records in multiple departments or could not be classified to any given department.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. Inpatients results \[Arm A, B, C, D\] are reported separately per arm, in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data were included in this analysis. Patients could have records in multiple departments or could not be classified to any given department.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2015 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2015. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2017 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2017. Only patients with available data for this outcome were included in this analysis.

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

Population: In- and outpatients in 2019 with and without diabetes and with and without diagnosis of risk factors CVD, HF, CKD, and high CV risk. For this outcome, inpatients results \[Arm A, B, C, D\] are reported separately per arm and in- and outpatients results \[All in-and outpatients\] are reported over all in- and outpatients and over all arms in 2019. Only patients with available data for this outcome were included in this analysis.