PrevaLence of Albuminuria in Patients With CARdiovascular Disease and Type 2 Diabetes Mellitus in China: a National Cross-sectional Study
Conditions: Cardiovascular Disease, Type 2 Diabetes Mellitus
Sponsor: Beijing Anzhen Hospital

1st, Total 37
PrevaLence of Albuminuria in patients with CARdiovascular
Disease and
Type 2 Diabetes mellitus in China: a national cross-sectional
study PLACARD
Research Protocol
<< Version 3.1 , October 26, 2023 >>
main researcher:
Professor Ma Changsheng
Team leader unit:
Beijing Anzhen Hospital
Sponsor:
Heart Health Research Center
Financial
Sponsor:
Bayer HealthCare Co., Ltd.

2nd, Total 37
Principal Investigator Statement
I have read the following research protocol:
Research protocol title: Prevalence of Albuminuria in patients with
Cardiovascular Disease and Type 2 Diabetes mellitus in China: a national
cross-sectional
Version and date: Version 3.1, October 26, 2023
I have read the study protocol and all study documents and agree that they
contain all necessary details to conduct the study. I will follow the protocol and
complete the research within the allotted time. I will provide a copy of the study
protocol and all relevant information to all principals and sub-centre
investigators assisting with the conduct of the study. I will discuss the material
with them to ensure they fully understand the mission and conduct of the study.
Investigator's signature:
main researcher:
Professor Ma Changsheng
————————————————
date
signature

3rd, Total 37
Research Protocol Overview
Study title
Prevalence of Albuminuria in patients with Cardiovascular Disease and
Type 2 Diabetes mellitus in China: a national cross-sectional
Research
objectives
Primary Objective
To assess the prevalence of albuminuria in patients who are combined
with type 2 diabetes mellitus and different cardiovascular diseases in
inpatient and outpatient cardiology departments of secondary and tertiary
hospitals in China.
Secondary Objectives
(1) To evaluate the levels of microalbuminuria and macroalbuminuria of
patients with type 2 diabetes mellitus (T2DM) in inpatients and outpatients
cardiology departments;
(2) To evaluate the prevalence of microalbuminuria and macroalbuminuria
in patients with T2DM complicated with different cardiovascular diseases;
(3) To evaluate the related influence factors of albuminuria and the
treatment patterns of CKD patients and non-CKD patients in cardiology
departments;
(4) To evaluate the management of risk factors and complications in
cardiovascular departments of patients with T2DM complicated with
microalbuminuria and macroalbuminuria in different levels of hospitals.
Exploratory Objective

4th, Total 37
To evaluate the prevalence of retinopathy in T2DM patients with different
cardiovascular diseases attending inpatient and outpatient cardiology
departments in secondary and tertiary hospitals in China.
Research
design
Multicenter, cross-sectional study
Research
center
30 medical centers nationwide in China
Research
sample
3,000 cases
Study
timeline
Expected enrollment date of the first patient is December 2023
Last patient expected completion date is June 2024
Inclusion
criteria
1. Age ≥18 years old;
2. Diagnosed T2DM combined with ≥1 CVD (hypertension, coronary heart
disease, atrial fibrillation, heart failure);
3. During the data collection period, they went to the outpatient clinic of the
cardiology department of the research center, or received treatment in the
cardiology department;
4. Ability to self-sign informed consent (electronic /paper).
Exclusion
criteria
1. Pregnant or lactating women;
2. Dialysis patients;
3. Other diseases that lead to elevated albuminuria, such as severe
infection, confirmed primary glomerular disease, etc.;

5th, Total 37
4. Malignant tumors being treated (surgery, chemotherapy, radiotherapy
or targeted therapy);
5. Cachexia (CSS score ≥5 points);
6. Severe liver disease (Child- Pugh grade C) ;
7. Participated in an interventional clinical trial in the past three months.
Statistical
methods
The analysis will be performed using SAS 9.4 statistical software.
Descriptive statistics will be calculated and reported, including number of
observations, means, standard deviations, medians, interquartile ranges
for continuous variables, and frequencies and percentages for categorical
variables. Percentages will be calculated based on non-missing data
unless otherwise specified. The data will be checked for bias and outliers.
Conversion will be done as needed. Missing data will be assumed to be
missing at random or completely at random, and no imputation will be
applied except in special circumstances.
Data
collection
Case Report Form (CRF)

6th, Total 37
1 Introduction and Research Background
1.1 Cardiovascular disease, type 2 diabetes and chronic kidney disease
The association between Cardiovascular Disease (CVD) and Chronic Kidney Disease (CKD)
is well established. Traditional risk factors for CVD and CKD are similar, with type 2 diabetes
mellitus (T2DM) being the most prevalent risk factor. However, CKD is underdiagnosed and
undertreated in patients with CVD. Further understanding of the combination of CKD in CVD
patients is important to formulate prevention and treatment strategies for CVD patients and
high-risk groups, reduce adverse events in CVD patients, and prevent progression of CKD
to End Stage Renal Disease (ESRD).
CVD patients and CVD high-risk patients are high-risk groups for CKD. The Spanish
MULTIRISC study showed that about 37% of outpatients with CVD and CVD high-risk
patients had CKD1. T2DM accounts for 25%-30% of outpatients and inpatients in the
department of Cardiology, which is an important reason for the high incidence of CKD in the
CVD population.
Population aging has not only led to an increase in the prevalence of
T2DM but also the prevalence of the comorbid CKD. The greatest increase in the
prevalence of T2DM has occurred in low- and middle-income countries, where patients
with T2DM are also at higher risk of developing CKD. Although the incidence of CVD in
T2DM patients has decreased in recent years, T2DM-related renal impairment has not
decreased correspondingly. In China, 20%-40% of T2DM patients will progress to CKD,
which is the main factor of CKD and ESRD2. Globally, more than 50% of patients requiring
renal replacement therapy have concurrently T2DM3.
Impaired renal function increases the risk of CVD by 2 to 4 times4 and T2DM patients with

7th, Total 37
CKD live an average of 10-16 years shorter than others5. In CVD, urinary protein is strongly
associated with an increased risk of developing heart failure, especially in patients with
T2DM or CKD or both6. A recent large study integrated 4 community-based cohorts and
investigated the prognostic value of 12 biomarkers (including urinary protein excretion rate,
natriuretic peptide, and troponin) in 22,756 participants. With a median follow-up of 12
years, increased urinary protein excretion was found to be an independent predictor of
Heart Failure with reduced Ejection Fraction (HFrEF) and Heart Failure with preserved
Ejection Fraction (HFpEF) factors, and for each increase standard deviation in Urinary
Albumin/Creatinine Ratio (UACR), the risk of HFrEF increases by 21% and that of HFpEF
increases by 33%7. Increased proteinuria may reflect elevated levels of endothelial function
and inflammation, Which is consistent with the widespread microvascular dysfunction and
inflammation characterized by HFpEF8. Data from the SPRINT study showed that
proteinuria had an cumulative predictive value for heart failure risk on the basis of eGFR
(estimated glomerular filtration rate)9. Decreased renal function is also associated with an
increased risk of coronary heart disease. With the eGFR decreased to 60 - 75 mL/min/1.73
m2, the incidence of coronary heart disease increased linearly. When the eGFR decreased
to 15 mL/min/1.73 m2, the risk of dying from coronary heart disease increased threefold10.
In addition, albuminuria can also increase the mortality of non-ST-segment elevation
myocardial infarction (NSTEMI) patients11. Even in the absence of decreased eGFR,
patients with elevated UACR had significantly higher CKD and CVD risks12, while lower
urinary protein levels improved cardiovascular and renal outcomes in T2DM patients13.
Therefore , the 2021 European Society of Cardiology (ESC) cardiovascular prevention

8th, Total 37
guidelines recommend screening for the progression of atherosclerotic disease and renal
disease in all CKD patients with or without T2DM, including monitoring changes in urinary
protein14.
CKD prevention in T2DM patients is to identify high-risk groups and intervene in related risk
factors, such as strict control of blood pressure, rational control of blood sugar, adjustment
of unhealthy lifestyle, and adoption of kidney protective therapeutic measures15. To prevent
CVD events in CKD patients, treatment should be initiated in the early stages of CKD. The
presence of proteinuria is a predictor of CKD progression and is associated with increased
CVD risk, regardless of normal eGFR. According to the current recommendations of the
Kidney Disease: Improving Global Outcomes Working Group, the treatment of patients with
T2DM
should
include
lifestyle
modification
as
the
basic
treatment,
followed
by
renin-angiotensin
system(RAAS)
inhibitors,
Sodium-Glucose
Cotransporter
2
inhibitors(SGLT-2i), statins and metformin as first-line treatment. For patients at high risk
for CKD progression and CVD events, aldosterone receptor antagonists are recommended.
The reduction of urinary protein can be used as a sign of effective treatment.
A short-term
decrease in urinary protein of about 30% after initiation of RAAS inhibition is a better sign
for prognosis in patients with CVD and CKD14.
1.2 Evaluation of renal function
Based on eGFR and proteinuria levels, the KDIGO guidelines divide CKD into 5 eGFR levels
and 3 proteinuria stages (Figure 1) to judge the prognosis of patients. eGFR is one of the
reliable indicators to reflect renal function, but its clinical use has certain limitations. Firstly,
eGFR is calculated based on serum creatinine levels, which are affected by a variety of

9th, Total 37
factors, including muscle mass, extrarenal excretion, and dietary factors. Secondly, the
eGFR formula is established based on population data and is not applicable to all kidney
diseases. Furthermore, the presence of CKD as judged by eGFR alone means that 50% of
kidney function has been lost16.
CKD Category
Classification of Albuminuria
A1
A2
A3
Normal and
slightly elevated
Moderately
elevated
Severely
elevated
<30 mg/g
<3 mg/mmol
30-299mg/g
3-29 mg/mol
≥300mg/g
≥30mg/mmol
Classification of eGFR
(ml/min/1∙
73m2)
G1
Normal renal
function
≥90
G2
Mild decline
60-90
G3a
Mild to moderate
decline
45-59
G3b
Moderate to
severe decline
30-44
G4
Severe decline
15-29
G5
Renal failure
15
Figure 1. Classification and prognosis of chronic kidney disease (CKD) according to the
2012 KDIGO guidelines
UACR is a guideline recommended indicator for monitoring the risk of early kidney injury in
T2DM and kidney related diseases, which can reflect early kidney disease and kidney injury.
UACR measures the ratio of albumin to creatinine in a single urine sample and is a reliable
method for monitoring urinary protein excretion17. UACR between 30 and300mg/g is
defined as microalbuminuria, and UACR>300mg/g is defined massive proteinuria. UACR
can reliably reflect the 24-hour urinary protein volume, and is fast, simple, and accurate. It

10th, Total 37
is an ideal clinical indicator for qualitative and quantitative diagnosis of albuminuria18. Thus,
given the high cost of CKD treatment and the low cost of detecting albuminuria, as well as
the need to identify previously unrecognized patients at high CVD risk, the 2021 ESC
Cardiovascular Prevention guidelines recommend that systematic evaluation of urinary
protein be considered in all men older than 40 and all women older than 50 (or
postmenopausal)14.
1.3 Improve the awareness rate of kidney disease in CVD patients
However, awareness of CKD has remained low19. An international cohort of 3 million
patients with diabetes or hypertension found that the overall UACR detection rate for
diabetes and hypertension was only 35.1% and 4.1% 20. A recent Swedish study found that
among more than 50,000 patients who met diagnostic criteria for CKD (i.e., at least two
eGFR < 60 mL/min/1.73m2 separated by more than 3 months), only 23% of patients had a
diagnosis of CKD in their electronic health records 21. The NHANES study found that the
awareness rate of CKD is much lower than that of hypertension and diabetes22. In a
NHANES study, the awareness rate of CKD patients with severe renal function decline was
41.8%, while the awareness rate of CKD patients with mild to moderate renal function
decline was only 7.8%23. In the KEEP study, the awareness rates of patients with the above
two conditions were 32.1% and 5.4%, respectively24. More importantly, patients with
eGFR>60 mL/min/1.73 m2 and elevated urinary protein account for more than 40% of CKD
patients, but urinary protein detection rates were low, and physicians and patients are more
aware of this type of CKD 25. This missed diagnosis may have adverse consequences for

11th, Total 37
patient care, as the use of nephrotoxic drugs is more common in undiagnosed CKD
patients26. Therefore, in the Healthy People 2030 plan in the United States, improving the
awareness rate of CKD continues to be listed as a priority national public health goal by the
health department27.
In China, the prevalence of albuminuria measurement in CVD patients is still unclear, and
there is limited data on the prevalence of albuminuria in patients with T2DM in the
Department of Cardiology. Further research is needed to increase relevant data to better
guide the diagnosis and treatment of CVD patients.
2. Research objectives
2.1 Primary objective
To assess the prevalence of albuminuria in patients who are combined with T2DM and
different cardiovascular diseases in inpatient and outpatient cardiology departments of
secondary and tertiary hospitals in China.
2.2 Secondary objectives
(1)To evaluate the levels of microalbuminuria and macroalbuminuria of patients with type 2
diabetes mellitus (T2DM) in inpatients and outpatients cardiology departments;
(2) To evaluate the prevalence of microalbuminuria and macroalbuminuria in patients with
T2DM complicated with different cardiovascular diseases;
(3) To evaluate the related influence factors of albuminuria and the treatment patterns of
CKD patients and non-CKD patients in cardiology departments;
(4) To evaluate the management of risk factors and complications in cardiovascular

12th, Total 37
departments
of
patients
with
T2DM
complicated
with
microalbuminuria
and
macroalbuminuria in different levels of hospitals.
2.3 Exploratory objective
To evaluate the prevalence of retinopathy in T2DM patients with different cardiovascular
diseases attending inpatient and outpatient cardiology departments in secondary and
tertiary hospitals in China.
3 Research design
3.1 Overall design
The PLACARD study was a cross-sectional observational study.
3.2 Center distribution
In the 6 major administrative regions of China (North China, East China, Northeast China,
Central South China, Southwest China, Northwest China), 30 regionally representative
medical centers with more than 50 daily outpatients in the Department of Cardiology were
selected, among which 3 tertiary hospitals and 2 secondary hospitals in each district.
According to the comprehensive situation of the hospital, a representative cardiology ward
will be selected in the inpatient department of each branch center, and several
representative outpatient doctors will be selected in the outpatient department.
3.3 Number of subjects
In this study, 50 patients with T2DM who meet the inclusion and exclusion criteria in the
outpatient department of cardiology and 50 inpatients will be continuously included in each
sub-center. A total of 100 patients will be included in each sub-center, totaling 3,000

13th, Total 37
patients. For details on sample size, see 6.6 Sample Size Estimation.
3.4 Estimated study duration
Each sub-center was activated and enrolled in sequence, with the enrollment period from
December 2023 to June 2024.
3.5 Patient Participation Time
Patient data will be collected after signing the informed consent, and the data of enrolled
patients will be included in the data analysis. No follow-up will be conducted in this study.
3.6 End of study
The study end date is the enrollment date of the 3,000th patient, which is expected to be
completed in June 2024.
3.7 Study Population
This study will adopt a stratified, multi-level, and multi-center strategy for continuous
screening to enroll patients who meet all inclusion criteria and none of the exclusion criteria.
During the enrollment period, the Clinical Coordinator will communicate with and invite all
potential patients attending the selected inpatient wards or the designated outpatient
physicians. Screening information, including patient name, gender, age, screening time,
successful enrollment, and reasons for enrollment failure, will be recorded using the patient
screening form (see Appendix 1). The patient screening form is kept by each sub-center,
which is the source document of this study and must not be transmitted to anywhere
outside the sub-center. Before conducting any study procedures or questionnaires, the
research team will obtain electronic or written informed consent from patients.
3.7.1 Inclusion criteria

14th, Total 37
1. Age ≥18 years old;
2. Diagnosed T2DM combined with ≥1 CVD (hypertension, coronary heart disease, atrial
fibrillation, heart failure);
3. During the data collection period, they went to the outpatient clinic of the cardiology
department of the research center, or received treatment in the cardiology department;
4. Ability to self-sign informed consent (electronic /paper).
3.7.2 Exclusion criteria
1. Pregnant or lactating women;
2. Dialysis patients;
3. There are other diseases that lead to elevated proteinuria, such as severe infection,
confirmed primary glomerular disease, etc.;
4. Malignant tumors being treated (surgery, chemotherapy, radiotherapy or targeted
therapy);
5. Cachexia (CSS score ≥5 points) ;
6. Severe liver disease (Child- Pugh grade C) ;
7. Participated in an interventional clinical trial in the past three months.
4 Research plan
4.1 Study data collection plan
The PLACARD study will be a cross-sectional observational study that collect patient
information only once after screening and retrace the case system after the first visit,
without any follow-up. It is expected that each center will complete the screening and

15th, Total 37
enrollment of patients within one month.
During the information collection period the investigator will:
1. Sign the informed consent form: Before signing the informed consent form, the
participants should be fully informed of the research purpose and how the data will be used,
and the researcher should also sign the informed consent form. The investigator and the
patient each keep an original signed informed consent form;
2. Patient screening form: After signing the informed consent form, it will be confirmed
whether the patient meets all the inclusion criteria and not all exclusion criteria, and the
screening information will be recorded in the patient screening form. In order to ensure the
continuity of screening, the screening information of potential patients who failed to enroll
will also be recorded in the patient screening form;
3. After the patients are enrolled, the researchers should complete the following tasks and
collect relevant data:
• Demographic information: gender, date of birth, education, type of medical insurance;
• Patient history: T2DM, hypertension, hyperlipidemia, coronary heart disease, atrial
fibrillation, heart failure, stroke (ischemic and hemorrhagic), transient ischemic attack
(TIA), cataracts, and macular degeneration;
• History of surgical intervention: coronary intervention, coronary artery bypass grafting
and coronary angiographic stenosis;
• Questionnaire: Edinburgh Intermittent Claudication Questionnaire (ECQ ) ;
• Physical examination: blood pressure, heart rate, height and weight;
• Clinical assessment information: blood glucose (including HbA1c , fasting blood glucose,

16th, Total 37
two-hour postprandial blood glucose),
renal function (including
serum creatinine
glomerular filtration rate, UACR), blood lipids (including total cholesterol, LDL cholesterol,
HDL Cholesterol, triglycerides), funduscopy, and the detection frequency of the above
inspections in the past year (mainly based on patient self-report);
• Whether the doctor prescribes urine routine examination for inpatients, and whether the
doctor issues a new doctor's order after the outpatients report back the renal function
examination;
•
Combined
drug
information:
this
prescription
drug
and
commonly
used
drugs
(outpatients) and medications during hospitalization (inpatients);
• Information about patient behavior: smoking history and drinking history;
• UACR value detected on the day of enrollment;
• The result of funduscopy gained on the day of enrollment.
4.2 Definition of diseases involved in the research
1) Hypertension is defined as: When blood pressure was measured on different days
without antihypertensive drugs, patients had systolic blood pressure ≥140mmHg and/or
diastolic blood pressure ≥90mmHg; Or patients with a history of hypertension who are
currently taking antihypertensive medications and whose blood pressure is less than
140/90 MMHG are also diagnosed with hypertension. (For patients with newly diagnosed
hypertension, it is recommended to return to the clinic and register after diagnosis. If
there is no follow-up after the initial visit, registration will not be granted).
2) Diabetes is defined as: There are diabetes symptoms such as polydipsia, polyuria,
polyphagia, and weight loss plus random blood glucose ≥11.1mmol/L.. Fasting blood

17th, Total 37
glucose is ≥7.0mmol/L; blood glucose is ≥11.1mmol/L in 2 hours oral glucose
tolerance test. Patient with a history of diabetes and is currently using hypoglycemic
drugs should be considered diabetes even their blood sugar is normal.
3) Hyperlipidemia is defined as: In the absence of lipid-lowering drugs, for fasting
measurement of blood lipids, total cholesterol is ≥6.2mmol/L or low-density lipoprotein
is ≥4.1mmol/L or triglyceride is ≥2.3mmol/L. Patient with a history of hyperlipidemia
and is currently using lipid lowering drugs should be considered hyperlipidemia even their
blood lipid is at a normal level
4) Coronary heart disease is defined as: Any history of myocardial infarction, coronary
artery bypass grafting, coronary intervention, or coronary artery stenosis >50%, or typical
angina symptoms, and evidence of myocardial ischemia on electrocardiogram or
echocardiography segmental wall motion abnormalities.
5) Heart failure is defined as: typical symptoms and signs of heart failure such as nocturnal
paroxysmal dyspnea, reduced exercise tolerance, bilateral ankle joint edema, and left
ventricular ejection fraction <40%; or there are typical symptoms and signs of heart
failure,
left
ventricular
ejection
fraction
≥40%,
elevated
BNP,
left
ventricular
hypertrophy/left atrial enlargement or abnormal ventricular diastolic function; or a history
of heart failure in the past, currently taking heart failure-related drugs, although there are
no symptoms and signs of heart failure and laboratory findings, still diagnosed as heart
failure.
6) Atrial fibrillation is defined as: single-lead electrocardiogram ( ≥30 s) or 12-lead
electrocardiogram (≥10s) shows that P wave disappears and is replaced by fibrillation

18th, Total 37
wave (f wave) with irregular size, shape and duration, the RR interval is absolutely
irregular; or there is a history of atrial fibrillation in the past, and the drug related to atrial
fibrillation is currently being taken. Although the electrocardiogram does not show the
performance of atrial fibrillation, it is still diagnosed as atrial fibrillation.
7) Severe infection is defined as: life-threatening infection, including systemic inflammatory
response syndrome, sepsis, septic shock or systemic multiple organ dysfunction
syndrome.
8) Primary glomerular disease is defined as: a disease of unknown etiology, often involving
bilateral glomeruli, with hematuria, proteinuria, edema, hypertension, renal dysfunction,
etc. as the main clinical manifestations, including acute glomerulonephritis, rapidly
progressive glomerulonephritis, chronic glomerulonephritis, asymptomatic hematuria
and/or proteinuria, and nephrotic syndrome.
9) CSS score of cachexia is defined as: patients with CSS ≥5 points are considered to be
in the state of cachexia, refered to the "2020 Guidelines for the Clinical Diagnosis and
Treatment of Cancer Cachexia", adopted the CSS Cachexia Staging Scale .
4.3 Research procedure
The patient recruitment consisted of two parts, 50 patients
from outpatients attending the
Department of Cardiology and 50 from in patients receiving treatment in the Department of
Cardiology.
• In the outpatient department, a selected, representative cardiologist should be followed
and eligible patients among the physician's visits would be continuously screened. It is
necessary to communicate with the person in charge of the Department of Cardiology

19th, Total 37
before the start of the branch center to determine the following outpatient doctors, and
plan and determine the enrollment process with the outpatient doctors in advance. On
the screening day, record and follow the T2DM patients encountered by the doctor
during the consultation process, communicate with the patient for informed consent,
screen according to the inclusion criteria, and generate a study number for those who
meet the enrollment criteria (see flow chart 1).
• In the ward selected by the inpatient department of the Department of Cardiology, the
clinical coordinator conducts a preliminary examination of all inpatients in the ward
through the hospital medical record system, records the patient with T2DM, and
communicates with the patient for informed consent, according to the inclusion and
exclusion criteria, screening is carried out, and those who meet the inclusion conditions
are enrolled and a research number is generated (see flow chart 2).
A face-to-face questionnaire should be conducted on the enrolled patients and baseline
information
such
as,
medical
history,
clinical
assessment
information,
medication
information, and living habits should be collected; and physical examination, UACR tests
and funduscopy were performed on the patients. For outpatients, it is also necessary to
query all the medical records of the enrolled patients on the day after the day of enrollment
to supplement any missing information.
To evaluate the doctor's attention to chronic kidney disease, this study mainly reviewed the
doctor's order to observe whether the doctor prescribes the UACR checklist for patients
with T2DM to monitor the renal function of the patients. If the doctor has issued a UACR test
for the patient, record the inspection value; if the doctor has not prescribed the test, use the

20th, Total 37
UACR measurement equipment provided in this study to obtain the results. When all the
research-related information of the enrolled patients is collected, and the UACR results are
obtained and fed back to the doctors, the data collection process is deemed to be over. In
addition, after the doctor obtains the results of the UACR examination, whether to revise the
doctor's order based on the detected nephropathy is also one of the ways to measure the
doctor's awareness of the identification and management of the nephropathy of diabetic
patients in the cardiology department.
Flowchart 1, Outpatient enrollment process

21st, Total 37
Flowchart 2, Inpatient enrollment process
5 Research evaluation
5.1 Clinical evaluation
During the study period, the clinical data and demographic data of the enrolled patients will
be measured and recorded, including gender, age, height, weight, as well as disease
history, drug history, smoking status, and drinking status. The physical examination will also
collect basic physiological data such as blood pressure and heart rate to assess the
patient's basic physical characteristics.
5.2 Medical record inquiry
The indicators examined will be retraced by querying the HIS electronic medical record
system. The medical records will be queried for the most recent transcripts of relevant tests
such as blood glucose, lipids, blood tests and renal function of the enrolled patients in the
last three months, to check for logical matches of disease or medication history, and
combined with the patient's self-reported record of the frequency with which he/she has

22nd, Total 37
monitored and managed the indicators in the past year.
5.3 Laboratory inspection
During the study period, dry urine cups will be taken and fresh randomized mid stage urine
samples will be collected from patients in the study group. Portable urine testing
instruments (such as the Mission ACON U120 Ultra/EMPSUN Enpusen urine testing
machine and 14 test strips, which are purchased by the sponsor and provided to each
center, are used to measure the patient's microalbumin and urine creatinine data by using
dry chemical methods, namely test strips, see appendix 2). And the UACR value will be
calculated by using the formula UACR(mg/g)=urine microalbumin(mg/L)*1000/(urine
creatinine(mmol/L) * 0.113).
During the study period, portable fundus cameras (which are purchased by the sponsor
and provided to each center, with equipment examples shown in appendix 3) will be used
to take fundus photos of enrolled patients, and the results obtained immediately will be fed
back to the doctors and patients.
5.4 Physician behavior and kidney disease management
After collecting the urine sample and calculating the UACR value, the patient will feed back
the test results to his/her doctor. This study will record the doctor's current diagnosis, and
use the method of reviewing medical records to evaluate whether he/she provides a new
diagnosis and prescription for the patient's renal function.
6 Statistical Considerations
6.1 General considerations

23rd, Total 37
This study will be performed using SAS 9.4 statistical software. Descriptive statistics are
calculated and reported, including number of observations, means, standard deviations,
medians,
and
interquartile
ranges
for
continuous
variables,
and
frequencies
and
percentages
for
categorical
variables.
Percentages
will
be
calculated
based
on
non-missing data unless otherwise specified. The data will be checked for bias and outliers.
Conversion will be done as needed. Missing data will be assumed to be missing at random
or completely at random, and no imputation will be applied except in special circumstances.
6.2 Definition of analysis set
The full analysis set will include all enrolled participants with UACR data.
6.3 Outcome Analysis
6.3.1 Main endpoint
The primary endpoint of this study will be the prevalence of albuminuria (UACR ≥30 mg/g)
in patients with type 2 diabetes presented to the Department of Cardiology , and the
prevalence of albuminuria and other demographic characteristics will be assessed by
descriptive
abstracts.
In
summary,
the
relationship
between
the
stage
of
renal
impairment/disease (A1-A3 or GFR classification) and relevant covariates was analyzed by
logistic regression model. Crude ORs and multivariate-adjusted ORs will be reported,
including covariates including:
Age group (18-39 years old, 40-59 years old, 60-69 years old, ≥70 years old ); gender;
BMI group (18.5, 23.9, 27.9, 28 ), blood pressure, blood lipid (LDL, HDL, TG), living habits
(smoking, drinking); sub-research centers, nephrotoxic drugs being used, disease history.
Prevalence will be analyzed grouped by stratification factors, gender and age, geographic

24th, Total 37
region (East, South, Central, North, Northwest and Southwest), etc.
6.4.2 Secondary endpoints
(1)
Albuminuria
level
in
patients
with
T2DM
in
the
Department
of
Cardiology
(microalbuminuria means UACR value >30 and <300 mg/g; macroalbuminuria means
UACR value ≥300 mg/g);
(2) The prevalence and level of albuminuria in different types of cardiovascular diseases in
the Department of Cardiovascular Medicine ( microalbuminuria refers to UACR values >30
and <300 mg/g ; macroalbuminuria refers to UACR values ≥300 mg/g );
(3) Different treatment patterns for patients with CKD and patients without CKD;
(4) Assessing the current status of disease-related risk factor management in patients with
T2DM attending cardiovascular medicine departments at different levels of hospitals;
(5) Evaluating the management of complications in patients with T2DM in different levels of
hospitals.
6.4.3 Exploratory endpoint
The prevalence of retinopathy in patients with T2DM and the level of retinopathy in patients
with T2DM in the Department of Cardiology.
6.5 Bias and confounding factors management
6.5.1 Bias
The research hospital of this study selects representative medical centers of different
grades distributed in six geographical regions of China. The research population chooses a
continuous population of diabetic patients in the Department of Cardiology, including
outpatients and inpatients, to reflect the real situation of cardiovascular patients with type 2

25th, Total 37
diabetes, which reduces the selection bias to a certain extent. The data collection of this
study adopts the combination of participants' self-report and retrospective of the case
system to ensure the accuracy of the collected survey data and reduce the information bias
to a certain extent.
6.5.2 Confounding
The data analysis of this study will stratify the center, gender, age, concomitant medication
and other factors, and control and correct the influence of potential confounding factors on
the results through multivariate regression analysis. Model assumptions will be checked
and, if necessary, appropriate transformations or nonparametric analysis methods will be
used.
6.6 Sample size estimation
According to studies published in 200728 and 200529, among hypertensive patients with
T2DM, the detection rate of albuminuria in 2,473 patients in mainland China was 59.9%,
and the detection rate of albuminuria in 5,549 patients in 6 countries in Asia was 58.6%.
There were no pre-defined statistical hypothesis tests and power analyzes for this study.
Based on the enrollment of 30 participating units in two different levels (18 in the tertiary
level and 12 in the secondary level), assuming a prevalence rate of 50% and a target
sample size of 3,000 patients. Therefore, at least 100 cases were selected for each
participating unit, which can provide an accuracy of 3.6%, and the 95% CI is 48.2%, 51.8%.
Total number
of analysis
Prevalenc
e
Number of
related
9 5% confidence
interval
9 5% confidence interval
width (%)

26th, Total 37
sets
events
1,000
50 %
500
46.9% , 53.2%
6.3%
1,500
50 %
750
47.4% , 5 2.6%
5.2 %
2,000
50 %
1,000
47.8% , 5 2.2%
4.4%
3,000
50 %
1,500
48.2% , 5 1.8%
3.6 %
5,000
50 %
2,500
48.6 %, 51.4%
2.8%
9,000
50 %
4,500
49.0 % , 51.0 %
2.0 %
7 Research and Data Management
7.1 Data collection and management
7.1.1 Confidentiality
The research documents will be properly kept, and the paper originals will be kept by the
local research center according to regulations. Electronic files and data will be stored in a
non-URL-accessible area, and it is only accessible through the website, and only
authorized researchers who have completed training in data handling will have access to
the data. Access to the database is controlled by setting the user ID and password system.
All passwords stored in the system will be encrypted using SSL .
7.1.2 Anonymization, de-identification and destruction
Each enrolled patient will be assigned a unique identification code. Any medical records or
data sets transmitted to the sponsor will only represent the patient with this code, with any
personally identifiable information anonymized. All laboratory reports uploaded to the
database according to the regulations must be deprived of privacy before uploading, and

27th, Total 37
identifiable personal information can be covered before uploading to ensure patient privacy.
Biological samples generated during the research will be destroyed immediately after
analysis.
7.1.3 Source data
The source data will include original medical records, patient screening forms, instrument
inspection reports, questionnaires and case report forms for filling in the data collection site,
and all other documents used to record patients' diagnoses and treatment in the hospital.
The research center should provide past medical records, including patient medical history,
surgical history, and access to various examinations and diagnoses.
7.2 data management
Recording and reporting study data is via paper or electronic case report form (CRF). The
researcher needs to sign the paper CRF. Researchers must be responsible for preserving
and providing accurate source data. Researchers must allow research-related monitoring,
auditing, ethical review, and regulatory agency inspections, and provide source data or
documents for their inquiries. The sponsor or designee is responsible for data management
of this study, including data quality checks. Unless local regulations or institutional policy
require a longer retention period, investigators must ensure that records and documents
related to this study (including signed informed consent forms) are retained for 10 years
after completion of the study. No records shall be destroyed during the retention period
without the written approval of the sponsor. No records shall be transferred to another
location or to a third party without written notice to the sponsor.
7.3 Quality control

28th, Total 37
The researcher must electronically signed CRF before submission. Any obvious errors or
omissions in the data or forms that need to be clarified require further inquiries and
verification directly with the medical center from which the data originated. Additionally, key
data may be double-keyed for additional quality control. During the study period (screening,
initiation, enrollment, and end), the sponsor will send monitors to conduct at least one
monitoring at each participating research center. The sponsor will organize audits as
needed.
8 Regulatory, Ethics and Research Oversight
8.1 Safety and Adverse Events
Although the likelihood of safety issues or adverse events arising from the implementation
of this study is small, unexpected conditions (including serious adverse events and adverse
events) that may be directly related to the study will be continuously monitored and
reported as required. AEs that meet timely reporting requirements will be summarized in a
narrative or other form and submitted to the IRB at follow-up review (if there is a follow-up
review), or will be recorded and followed up on the patient case report form but not
submitted to the IRB (if no follow-up review is required).
8.2 Ethical review and protocol changes
IRB/IEC review and approval were required before initiation. During the research period, if
there is any modification to the research documents such as the research protocol and
informed consent form, it needs to be reviewed, approved or filed again by the IRB/IEC
(according to the specific requirements of the IRB /IEC). During the research period, a

29th, Total 37
written summary of the research progress shall be provided to the IRB/IEC as required, and
the IRB/IEC and other applicable regulations shall be complied with.
The researcher/institution agrees to allow the auditor or monitor to have direct access to all
relevant documents, and to arrange time to cooperate with the auditor/monitor to discuss
issues and any issues found. Audits and monitoring can be done at any time during or after
the study.
8.3 Informed consent procedure
Since no intervention is involved, potential participants will be informed quickly through
electronic or paper informed consent, and researchers at each center must explain the
following in detail to patients:
• Voluntary participation and the right to withdraw from the study at any time at any stage,
without discrimination or retaliation, without affecting the patient's medical care and rights.
• Participation in research and personal data are confidential.
• According to the Declaration of Helsinki, patients should be informed of the nature,
purpose, possible expected benefits and risks of the research. Ensure that patients have
enough time to consider whether they are willing to participate, and sign the informed
consent.
• One original copy of the signed informed consent form was handed over to the patient,
and the other original copy was properly kept in the local center.
8.4 Data protection
Investigators must inform participants about how their personal study-related data or
medical records will be used, and they must explain to them the extent of disclosure and

30th, Total 37
that their medical records may be reviewed by authorized personnel designated by the
sponsor or by IRB/IEC and regulatory authorities.
8.5 Study Discontinuation
Participants may request to withdraw informed consent and withdraw from the study at any
time. The study did not involve an intervention, and adverse events will not be discontinued
or the center closed, but adverse events will be recorded in the study file. The sponsor,
investigator, or regulatory agency may decide to suspend the study, or part of it, for safety
or administrative reasons after reaching an agreement.

31st, Total 37
Appendix 1
Patient Screening Form
Screening
Date
Serial
Number
Medical
Record
Number
Name
Age
Gender
Enrollment
Success
Reasons
for
Enrollment Failure
ID
Male
Female
Yes
No
Patient Refused
Enrollment
Patient Does Not
Meet Inclusion
Criteria

32nd, Total 37
Appendix 2
Comparison chart of UACR tester and 14 test papers

33rd, Total 37
Appendix 3
Portable fundus camera

34th, Total 37
References
1. Aleix Cases Amenós, JRG-J., Pedro Conthe Guti é rrez , Prevalence of chronic
kidney disease in patients with or at a high risk of cardiovascular disease. Rev Esp
Cardiol 2010, 63 (2), 225-228.
2. Galindo, RJ, et al., Clinical characteristics and outcomes of patients with
end-stage renal disease hospitalized with diabetes ketoacidosis. BMJ Open
Diabetes Res Care 2020, 8 (1).
3. Ortiz, A .; Informacion Enfermedades Renales Geneticas , EKPFFN d. A. pl LC l. E.
d. RFRIA d. TR d. IR, RICORS2040: the need for collaborative research in chronic
kidney disease. Clin Kidney J 2022, 15 (3), 372-387.
4. Gansevoort, RT, et al., Chronic kidney disease and cardiovascular risk:
epidemiology, mechanisms, and prevention. Lancet 2013, 382 (9889), 339-52.
5. Wen, CP, et al., Diabetes with early kidney involvement may shorten life
expectancy by 16 years. Kidney Int 2017, 92 (2), 388-396.
6. McMurray, JJV, Urinalysis: A Window to the Heart. JACC Heart Fail 2019, 7 (5),
402-403.
7. de Boer, RA, et al., Association of Cardiovascular Biomarkers With Incident Heart
Failure With Preserved and Reduced Ejection Fraction. JAMA Cardiol 2018, 3 (3),
215-224.
8. Gladden, JD, et al., Heart Failure with Preserved Ejection Fraction. Annual Review
of Medicine 2018, 69 (1), 65-79.
9. Vaduganathan, M., et al., Prevention of heart failure events with intensive versus
standard blood pressure lowering across the spectrum of kidney function and

35th, Total 37
albuminuria: a SPRINT substudy . European Journal of Heart Failure 2020, 23 (3), 3
84- 392.
10.
Manjunath, G., et al., Level of kidney function as a risk factor for
atherosclerotic cardiovascular outcomes in the community. Journal of the American
College of Cardiology 2003, 41 (1), 47-55.
11.
Akerblom, A., et al., Albuminuria and cardiovascular events in patients with
acute coronary syndromes: Results from the TRACER trial. Am Heart J 2016, 178,
1-8.
12.
Coresh, J., et al., Change in albuminuria and subsequent risk of end-stage
kidney disease: an individual participant-level consortium meta-analysis of
observational studies. Lancet Diabetes Endocrinol 2019, 7 (2), 115-127 .
13.
Persson, F., et al., Changes in Albuminuria Predict Cardiovascular and Renal
Outcomes in Type 2 Diabetes: A Post Hoc Analysis of the LEADER Trial. Diabetes
Care 2021, 44 (4), 1020-1026.
14.
Visseren , FLJ, et al., 2021 ESC Guidelines on cardiovascular disease
prevention in clinical practice. Eur Heart J 2021, 42 (34), 3227-3337.
15.
Jha, V., et al., Chronic kidney disease : global dimension and perspectives.
Lancet 2013, 382 (9888), 260-72.
16.
Sanchez-Nino, MD, et al., Clinical proteomics in kidney disease as an
exponential technology: heading towards the disruptive phase. Clin Kidney J 2017,
10 (2), 188-191.
17.
Johnson, DW, et al., Chronic kidney disease and measurement of

36th, Total 37
albuminuria or proteinuria: a position statement. Med J Aust 2012, 197 (4), 224-5.
18.
Tao, J., et al., Elevated urine albumin-to-creatinine ratio increases the risk
of new-onset heart failure in patients with type 2 diabetes. Cardiovasc Diabetol
2023, 22 (1), 70.
19.
Chu, CD, et al., Patient Awareness of CKD: A Systematic Review and
Meta-analysis of Patient-Oriented Questions and Study Setting. Kidney Med 2021,
3 (4), 576-585 e1.
20.
Shin, JI, et al., Albuminuria Testing in Hypertension and Diabetes: An
Individual-Participant Data Meta-Analysis in a Global Consortium. Hypertension
2021, 78 (4), 1042-1052.
21.
Carriazo , S., et al., More on the invisibility of chronic kidney disease... and
counting. Clin Kidney J 2022, 15 (3), 388-392.
22.
Chu, CD, et al., CKD Awareness Among US Adults by Future Risk of Kidney
Failure. Am J Kidney Dis 2020, 76 (2), 174-183.
23.
Plantinga, LC, et al., Patient awareness of chronic kidney disease: trends
and predictors. Arch Intern Med 2008, 168 (20), 2268-75.
24.
Saab, G., et al., CKD awareness in the United States: the Kidney Early
Evaluation Program (KEEP). Am J Kidney Dis 2008, 52 (2), 382-3.
25.
Lee, J., et al., Albuminuria Testing by Race and Ethnicity among Patients
with Hypertension with and without Diabetes. Am J Nephrol 2019, 50 (1), 48-54.
26.
Bosi, A., et al., Use of nephrotoxic medications in adults with chronic kidney
disease in Swedish and US routine care. Clinical Kidney Journal 2022, 15 (3),

37th, Total 37
442-451.
27.
Services, USD o. H. a. H. Increase the proportion of adults with chronic
kidney disease who know they have it — CKD‑02 Periodical Increase the
proportion of adults with chronic kidney disease who know they have it — CKD‑
02 [Online], 2023, p. Pages.
https://health.gov/healthypeople/objectives-and-data/browse-objectives/chronic-
kidney-disease/increase-proportion-adults-chronic-kidney-disease-who-
know-they-have-it-ckd-02 (accessed Date Accessed).
28. Mainland China Microalbuminuria Prevalence Study Group, DU, J., Pan, CY A
survey of microalbuminuria prevalence in hypertensive type 2 diabetic patients in
mainland China. Chinese Journal of Internal Medicine 2007, 46(3), 184-188.
29. Wu, AYT, Kong, NCT, de Leon, FA et al. An alarmingly high prevalence of
diabetic nephropathy in Asian type 2 diabetic patients: the MicroAlbuminuria
Prevalence (MAP) Study . Diabetologia 2005, 48, 17–26.