Cardiovascular Surgical Database in Mainland of China

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Transcript Cardiovascular Surgical Database in Mainland of China

Chinese Database for Cardiovascular Surgery
Questions and Thoughts
Shengshou Hu M.D.
President, Cardiovascular Institute & Fuwai Hospital
Director, National Center for Cardiovascular Disease
Prevention and Treatment
Background
STS Adult CV national database
The biggest cardiovascular surgical database
Since 1994
681 sites*
Cumulative number: >2,100,000*
*Data from STS Fall
2006 Report
Background
Adult Cardiac Surgical Database of EACTS
– 220,000 patients records*
– 12 countries*
– 99 hospitals*
*Data from EACTS first
adult cardiac surgical
database report 2003
Background
Background
Western’s Risk model can’t expect actual
mortality of Chinese patients
.07
.06
5.78%
.05
.04
3.30%
2.82%
Value mortality
.03
1.87%
.02
1.65%
.01
1
Parsonnet
Case Number
2
3
EuroSCORE Cleveland
4
OPR
5
Actual Mortality
Prediction value for operative mortality of four different coronary artery
bypass graft risk stratification models in Chinese patients
Zhonghua Xin Xue Guan Bing Za Zhi;2006;34:504-7
Different Risk factors for CABG
Fu Wai
STS
EuroSCORE
LVEF
+
+
+
Cr
+
+
+
Priority
+
+
+
Cardiac Shock
+
+
+
Age
-
+
+
Female
-
+
+
Previous CVP Procedure
-
+
+
LM
+
+
-
Arrythmia
+
+
-
MI
+
+
-
PI
+
-
-
Aortic Aneurysm Procedure
+
-
+
Tri-vessel Disease
-
+
-
Risk factors for CABG—Chinese experience (Submitted)
Background
Chinese patients with cardiovascular surgery
Compare with database of STS or EACTS
 Different characteristic of race
 Different practice guideline
Mortality of Isolated CABG in Fu Wai Hospital
Compare with STS Database
5%
 Indication and selection
 Different outcome
Mortality
 Peri-operative therapy
4%
3%
STS*
2%
1%
Fuwai Hospital
0%
1996 1997 1998 1999 2000 2001 2002 2003
Year
*Executive summary of STS national database www.sts.org
Questions for Database in China
Purpose of CV database
 Define Risk factors and outcome
 Application of practice guideline
 Quality control improvement for surgeons and
centers
 Clinical trial based on the register
 Research in targeted areas of cardiac surgery
Questions for Database in China
 Arouse enthusiasm of contributing centers
 Cooperative network
 No database in the most centers
 Software developing
 Dataset
 link to the world
 fit to clinical practice
 Collecting, monitoring and validating data
 The most important step
Questions for Database in China
Cooperative network
To arouse the enthusiasm of each potential
contributing center and surgeon
– Responsibility
– Resource share
• Risk factors evaluation
• Quality improvement
• Clinical analysis and Research
Questions for Database in China
Dataset
 Link with STS and Europe database
 Fit to Chinese cardiovascular surgical practice
 Union the definition of data
• Operative Data
• Patient Data
• Operative priority
• Demographics
• Procedure data
• Cardiac history
• Outcome Data
• Co-morbidities
• Complications
• Preoperative investigations
• Survival
• Preoperative support
Model of data collection in EACTS
Collecting, monitoring and validating data
Center
Center
Center
Dataset
Inspection
Double input
Database
Data center
Basic analysis
Risk model
Clinical research
Questions for Database in China
Database software developing
Local database
Submit data to data center regularly
Data share online
Our practice: Step by Step
First stage
Retrospectively CABG register
• CABG during 2004~2005
• Thirty-three hospital
Adult cardiac surgical register database
Second stage
National cardiac database
Retrospectively CABG register
(Oct 2006 ~ March 2007)
 33 centers in Mainland
 CABG in 2004~2005
 More than 10000 cases
 Set up CABG database
 Describe risk factors and
outcome of CABG
Adult cardiac surgery register
– Supported by Ministry of Science and Technology
– Call for national cooperation
 Define Risk factors and outcome
 Application of practice guideline
 Quality control improvement
 Clinical trial and research
National cardiac database
Supported by society or government
Nation wide participate
Special team for data collect and analysis