Simplified Cardiovascular Management (SimCard) Study in ... · CVD high- risk. Meeting any one of...
Transcript of Simplified Cardiovascular Management (SimCard) Study in ... · CVD high- risk. Meeting any one of...
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Dr. Maoyi Tian on behalf of SimCard working group
Simplified Cardiovascular Management (SimCard) Study in Tibet, China and Haryana, India
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• To develop,• Pilot-test and • Evaluate the feasibility and effectiveness of a
SIMPLIFIED, but GUIDELINE-BASED cardiovascular disease management program delivered by the COMMUNITY HEALTH WORKERS (CHWs) in resource-constrained settings in Tibet, China and Haryana, India
Aim
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Inclusion criteria
• Age ≥ 40
• Resident in the selected village
Screening
Method – subjects
Single-blinded cluster randomized controlled trial (47 clusters)
Exclusion criteria
• Bed-ridden • Unable to stay >8 months in a year
• Life-threatening disease • CVD related complications that can’t be managed
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Screening
Non CVDHigh-risk
CVD High-risk Baseline
Usual Care(24 clusters)
1-year Intervention(23 clusters)
Follow-up
Method – design
CVD high-riskMeeting any one of the following conditions:
• History of diabetes
• History of stroke
• History of coronary heart disease
• Both SBP ≥ 160mmHg at two different time points in the same day during the survey
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Salt Reduction
SmokingCessation
BP lowering
agentAspirin
2 Lifestyle Modifications
2 Drug Prescriptions
Electronic Decision Support System
(EDSS)
Method – intervention
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Method – outcome
• Primary outcome:The binary outcome of anti-hypertensive medication use of all high-risk
individuals. The significance test is for the net difference in the proportion of anti-hypertensive medication use between the groups.
• Secondary outcomes:• The binary outcome of aspirin use of all high-risk individuals;• The difference in pre-and-post mean SBP of high-risk individuals. • Others
• Outcome evaluation:• Baseline and post-intervention follow-up survey• Identical standardized instruments for both surveys
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Method – statistical analysis
• Power (>90%)• Primary outcome: assuming 20% in control group, detect a 10% difference ,
ICC=0.02• Secondary outcome: assuming SD of the change in SBP =15mmHg, detect a
3mmHg difference, ICC=0.02• Adequate power for sub-group analysis by country
• Method• Intent-to-treat using last observation carried forward• Analysis accounts for cluster effect and repeated measurements• Mixed models were used – logistic model (binary), linear model (continuous)
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Enrollment
Allocation
Follow-up
Analysis
Result – flow chart
52 villages (China: 30, India: 32)
5 villages were excluded
47 villages were recruited. 2,086 high-risks were identified (China: 1,036, India: 1,050) as high-risk.
Intervention Group1,095 high-risks from 23 villages
(China: 557, India: 538)
Control Group991 high-risks from 24 villages
(China: 479, India: 512)
962 high-risks from 23 villages (China: 478, India: 484)
866 high-risks from 24 villages (China: 431, India: 435)
IIT: 1,095 were analyzed. IIT: 991 were analyzed.
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Result – baseline characteristics
Characteristics (Mean, SD or %)Total
Intervention Control
Age (years) 59.7, 11.7 60.4, 11.8
Female (%) 65.4 66.8
Illiterate (%) 59.3 61.9
Body mass index (kg/m2) 23.6, 4.2 24.0, 4.4
Current smoker (%) 36.7 37.5
Coronary heart disease (%) 39.5 31.9
Stroke (%) 10.4 9.9
Diabetes (%) 13.4 9.8
Characteristics (Mean, SD or %)China
Intervention Control
Age (years) 59.5, 11.6 59.3, 11.3
Female (%) 72.0 70.8
Illiterate (%) 62.0 63.7
Body mass index (kg/m2) 23.0, 3.5 23.4, 3.8
Current smoker (%) 37.5 36.5
Coronary heart disease (%) 50.1 53.0
Stroke (%) 6.8 9.4
Diabetes (%) 2.9 1.9
Characteristics (Mean, SD or %)India
Intervention Control
Age (years) 59.9, 11.8 61.5, 12.1
Female (%) 58.6 63.1
Illiterate (%) 56.4 60.3
Body mass index (kg/m2) 24.1, 4.7 24.5, 4.8
Current smoker (%) 35.9 38.7
Coronary heart disease (%) 28.4 12.1
Stroke (%) 14.1 10.4
Diabetes (%) 24.3 17.2
Characteristics (Mean, SD or %)India
Intervention Control
Age (years) 59.9, 11.8 61.5, 12.1
Female (%) 58.6 63.1
Illiterate (%) 56.4 60.3
Body mass index (kg/m2) 24.1, 4.7 24.5, 4.8
Current smoker (%) 35.9 38.7
Coronary heart disease (%) 28.4 12.1
Stroke (%) 14.1 10.4
Diabetes (%) 24.3 17.2
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Result – secondary outcomes
Total Aspirin (%)
SBP (mmHg)
Current smoker (%)
Awareness of high salt harm (%)
InterventionPre 6.0 161.3, 29.6 36.7 46.9
Post 18.8 151.0, 27.0 37.7 59.6
ControlPre 4.7 161.4, 27.8 37.5 36.8
Post 2.8 153.2, 27.7 36.7 55.8
Net 11.7 -2.1 1.8 -6.3
P value <0.001 0.03 0.46 0.08
Total Aspirin (%)
SBP (mmHg)
Current smoker (%)
Awareness of high salt harm (%)
InterventionPre 6.0 161.3, 29.6 36.7 46.9
Post 18.8 151.0, 27.0 37.7 59.6
ControlPre 4.7 161.4, 27.8 37.5 36.8
Post 2.8 153.2, 27.7 36.7 55.8
Net 11.7 -2.1 1.8 -6.3
P value <0.001 0.03 0.46 0.08
China Aspirin (%)
SBP (mmHg)
Current smoker (%)
Awareness of high salt harm (%)
InterventionPre 7.0 166.2, 30.8 37.5 64.1
Post 23.7 155.3, 27.8 38.8 87.1
ControlPre 5.6 164.4, 28.8 36.2 52.9
Post 1.9 157.3, 29.2 36.1 76.2
Net 20.4 -3.8 1.4 -0.3
P value <0.001 0.006 0.65 0.19
China Aspirin (%)
SBP (mmHg)
Current smoker (%)
Awareness of high salt harm (%)
InterventionPre 7.0 166.2, 30.8 37.5 64.1
Post 23.7 155.3, 27.8 38.8 87.1
ControlPre 5.6 164.4, 28.8 36.2 52.9
Post 1.9 157.3, 29.2 36.1 76.2
Net 20.4 -3.8 1.4 -0.3
P value <0.001 0.006 0.65 0.19
India Aspirin (%)
SBP (mmHg)
Current smoker (%)
Awareness of high salt harm (%)
InterventionPre 5.0 156.2, 27.4 35.9 29.1
Post 13.8 146.6, 25.3 36.5 31.1
ControlPre 3.7 158.5, 26.5 38.7 21.4
Post 3.7 149.5, 25.7 37.2 36.7
Net 8.8 -0.5 2.1 -13.3
P value <0.001 0.71 0.22 <0.001
India Aspirin (%)
SBP (mmHg)
Current smoker (%)
Awareness of high salt harm (%)
InterventionPre 5.0 156.2, 27.4 35.9 29.1
Post 13.8 146.6, 25.3 36.5 31.1
ControlPre 3.7 158.5, 26.5 38.7 21.4
Post 3.7 149.5, 25.7 37.2 36.7
Net 8.8 -0.5 2.1 -13.3
P value <0.001 0.71 0.22 <0.001
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Result - summary
• Effectively changed CHWs and patients' behaviors in increasing
uptake of evidence-based medicine (anti-hypertensive medication
and aspirin)
• No significant changes in lifestyle factors
• Reduced systolic blood pressure by 2.1 mmHg
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Strength/Limitation
• Strength• Strong local government support• Adaptive intervention design in two countries• Active engagement of the CHWs• The use of EDSS
• Limitation• Generalizability• Unable to distinguish the effectiveness of different
intervention component
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Conclusion
Simplified evidence-based culturally-appropriate interventions
based on the high-risk approach could improve quality of primary
care and have the potential to reduce disease burden in resource-
constrained settings.
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• Collaborators
o Tibet University
o Public Health Foundation of India
o China Mobile Research Institute
o University of Oxford
• Funding source
National Heart, Lung, and Blood Institute (National Institutes of Health)
Acknowledgement
China site:Z Liu, D Dunzhu, X Zhao, H Chen, K ChoR Li, C Li, X Li, J Ji, E Delong, E PetersonY Wu, L Yan
India site:V Ajay, S Hameed, D JindalI Rawal, M Ali, R AmachandA Krishnan, N Tandon, D Prabhakaran