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PW222 A pragmatic tool to guide the intensity of chronic heart failure management: Green Amber Red Delineation of rIsk And Need in Chronic Heart Failure (GARDIAN-CHF)
POSTER ABSTRACTS
PW219 Prevalence Of Metabolic Syndrome And Association With Lifestyle Factors In India: A Nationwide Cross Sectional Study In Urban Subjects Prakash Deedwania*1, Rajeev Gupta2, Krishnakumar Sharma2, Vijay Achari3, Anil Bhansali4, Balkishan Gupta5, Anuj Maheshwari6, Tulika G. Mahanta7, Arvind Gupta8 1 University of California San Francisco, Fresno, United States, 2Fortis Escorts Hospital, Jaipur, 3 Patna Medical College, Patna, 4Postgraduate Institute of Medical Education and Research, Chandigarh, 5SP Medical College, Bikaner, 6BBD College of Dental Sciences, Lucknow, 7Assam Medical College, Dibrugarh, 8Jaipur Diabetes Research Centre, Jaipur, India Introduction: Metabolic syndrome is common but its lifestyle risk factors are poorly studied, especially in low and lower-middle income countries. Objectives: To determine association of socioeconomic and lifestyle factors with metabolic syndrome prevalence we performed a multisite cross-sectional study in India. Methods: The study was performed at eleven cities in India using cluster sampling. 6198 Subjects (men 3426, women 2772, response 62%, age 4810 years) were evaluated for sociodemographic, lifestyle, anthropometric and biochemical factors using uniform methodology. Prevalence of metabolic syndrome was determined using Asian-specific harmonized criteria. Significant socioeconomic and lifestyle associations were determined using linear trend analysis. Results: Age adjusted prevalence (%, 95% confidence intervals) of metabolic syndrome in men and women was 33.3 (31.7-34.9) and 40.4 (38.6-42.2) (harmonized Asian specific criteria), 23.9 (22.4-26.4) and 34.5 (32.0-36.1) (modified Adult Treatment Panel-3, ATP-3) and 17.2 (15.3-19.1) and 22.8 (20.1-24.2) (ATP-3). In men and women, respectively, high waist circumference was in 35.7 (34.1-37.3) and 57.5 (55.6-59.3), high blood pressure in 50.6 (48.9-52.3) and 46.3 (44.4-48.1), impaired fasting glucose or diabetes in 29.0 (27.530.5) and 28.0 (26.3-29.7), low HDL cholesterol in 34.1 (32.5-35.7) and 52.8 (50.9-54.7) and high triglycerides in 41.2 (39.5-42.8) and 31.5 (29.7-33.2) percent. Prevalence was significantly greater in subjects with lowest vs highest educational status (45 vs 26%), occupational status (46 vs 40%), dietary fat intake (52 vs 45%), sedentary lifestyle (47 vs 38%) and body mass index (66 vs 29%) categories (ptrend<0.05). Conclusion: There is high prevalence of metabolic syndrome among urban populations in India. Socioeconomic (high educational and socioeconomic status) and lifestyle (high fat diet, low physical activity, overweight and obesity) are important risk factors. Disclosure of Interest: None Declared PW220 The Prevalence of Metabolic syndrome in Coronary artery Disease patients compared to those without Coronary Artery Disease: Insights from South Indian population Stigimon Joseph*1 1 Cardiology, Little Flower Hospital And Research Center, Angamaly, Angamaly, Ernakulam, Kerala, India, India Introduction: There are few studies addressing the prevalence of Metabolic Syndrome among the South Indian population. There are limited data comparing the prevalence of Metabolic syndrome among Coronary Artery Disease (CAD) patients compared to healthy population. Objectives: To assess the prevalence of Metabolic Syndrome in Coronary Artery Disease patients and to compare with those without Coronary Artery Disease. Methods: Patients with CAD who were seen in the cardiology Out Patient Department formed the study group . CAD was defined as documented Acute Coronary Syndrome or positive TMT or disease documentation by Coronary Angiogram. During the same time period two population surveys were conducted which formed data for healthy general population. The two different population surveys were : a) Mostly manual laborers of the Panchayat ward where the hospital is situated (195 individuals participated). b) Sedentary population (office staff, teachers) (242 individuals participated). Results: A total of 1003 individuals were evaluated. 761 were included in the study. 405 patients have CAD as defined and they formed Group: A and 356 are healthy (group: B). Male to female ratio is almost equal (361 females and 400 males). The prevalence of Metabolic Syndrome is high and among South Indian population. Table 1. Prevalence of Metabolic Syndrome Definitions
Total(761)
Females(361)
Males(400)
IDF
298(39.1%)
169(46.8%)
129(33.8%)
ATP III
361(47.4%)
192(53.3%)
172(43.1%)
WHO
308(41.7%)
122(33.7%)
186(46.6%)
Prevalence is higher coronary artery disease patients.
Table 2. Prevalence of Metabolic Syndrome CAD x no CAD groups
Conclusion: 1. The overall prevalence of Metabolic Syndrome in South Indian population is high (39%). 2. Coronary Artery Disease patients have higher prevalence compared to healthy population. 3. A significant proportion of our population have BMI <18, still they have predilection for Metabolic syndrome which needs further evaluation. Disclosure of Interest: None Declared PW222 A pragmatic tool to guide the intensity of chronic heart failure management: Green Amber Red Delineation of rIsk And Need in Chronic Heart Failure (GARDIAN-CHF) Simon Stewart*1, Yih-Kai Chan1, James McVeigh2, Melinda Carrington1, and on behalf of the WHICH? Study Investigators 1 Preventative Health, Baker IDI Heart and Diabetes Institute, Melbourne, 2Prince of Wales Hospital, Randwick, Sydney, Australia Introduction: There is scope to improve the cost-effective application of chronic heart failure (CHF) management programs. Objectives: To examine the potential cost-benefits of applying an innovative traffic light system, the Green Amber Red Delineation of rIsk And Need (GARDIAN), to guide the intensity of post-discharge management of CHF. Methods: We used outcome data from the multicentre, randomized controlled Which Intervention is most cost-effective and Consumer friendly in reducing Hospital stay (WHICH?) Trial comprising typically older patients hospitalised with CHF. Using the distribution (quartiles) of days alive and out-of-hospital up to 18 months post index hospitalisation we: 1) confirmed a gradient of event-free survival, 2) identified characteristics that predicted eventfree survival (p<0.05 for observed gradients) and 3) aggregated predictive variables into 3 key GARDIAN domains (clinical stability, gold-standard management and holistic profile). Results: Differential group event-free outcomes were – Group A (n¼56, 548+ days eventfree, mean 1.8 days hospital stay and 0% mortality), Group B (n¼83, 530-547 days, 7.7 days, 0%), Group C (n¼71, 393-529 days, 28.2 days, 11.3%) and Group D (n¼70, 0 – 392 days, 24.1 days, 87.2%). Clear gradients across the 4 groups were found according to age, self-care ability, cognitive impairment, language status, prior CHF admission, acute pulmonary oedema, index stay, stay in intensive care, eGFR, anaemia, treatment with an ACEi or beta-blocker and early post-discharge clinical instability (mostly congestion). Compared with statistical modelling, pragmatic aggregation of these variables according to pre-specified GARDIAN coding (Green/low risk with only one domain deficit, Amber/ medium risk with two domain deficits and automatic Red/high risk red status if postdischarge clinical instability present) was most accurate in aligning with the groups; further enhanced when any intensive care stay indicated clinical instability (automatic Red status). Applying GARDIAN coding, for every 100 CHF patients, 9%, 64% and 27%, respectively would be designated Green, Amber and Red and follow-up titrated accordingly. Predicted false negatives (requiring redesignation as Red on readmission) in Green would be 22% (2 patients) and false positives in Red would be 11%. Conclusion: The GARDIAN-CHF tool represents a promising, pragmatic tool to guide the intensity of CHF-MPs when limited resources restrict their application. Disclosure of Interest: None Declared PW224 Hard Aquifer Drinking Water Linked To High Ct Coronary Angiogram Calcium Scores John F. England*1, Marcin Roman2, Lloyd Davis3 1 Cardiology, Blue Mountains District Anzac Memorial Hospital, Katoomba NSW, 2Radiology, PRP, DUBBO NSW, 3Cardiology, Westmead Hospital, WESTMEAD NSW, Australia Introduction: In rural Australia (compared to seaboard coastal population) health demographics reports of an increased incidence of coronary artery disease, ruptured calcific coronary arteries at angioplasty (haemopericardium) and thyroid disease prompted public health officials in the town of Mudgee (300km west of Sydney) to install a water softening plant two years ago. Drinking water from the Burrundulla aquifer was associated with salt corrosion of metal plumbing fittings and hot water heating tanks. Objectives: 100 consecutive CT coronary angiograms (CTCA) in the postal code area of Mudgee (hard water) were compared to 100 consecutive CTCAs in postal code area of the NSW coastal town of Gosford (soft water) and matched for age distribution and sex - 75% male, aged 70 years Methods: CTCA data compared the upper quartiles of each area and contrasted with CTCAs from 100 older consecutive patients in the city of Sydney from the same radiological practice. Results:
Different Groups.
IDF
ATP III
WHO
Hard water Mudgee
Calcium Score ¼ 1120.8 (SD 992)
Group.A (With CAD)
170 (41.6%) p**
209 (51.8%) p**
202(50%) p**
Soft rainwater Gosford
Calcium Score ¼ 767.6 (SD 522)
Dam water Sydney (older reference group)
Calcium Score ¼ 897.4 (SD 812)
Group.B(without CAD)
128(34.3%)
147(41.4%)
103(26.1%)
4.9% of Coronary artery disease patients and 8.1% of healthy individuals have BMI<18. It is interesting to note that 25% of them have ¼> 2 risk factors for Metabolic syndrome though they cannot be classified as having Metabolic syndrome with present diagnostic criteria. This observation “ the clustering of metabolic risk factors in lean individuals” needs further evaluation.
e302
The hydrated lime water softening unit reduced the calcium carbonate levels from 410mg/L to 115mg/L and pH from 8.4 to 7.8. Sydney and coastal NSW drinking waters are soft and reach WHO Guidelines for total hardness less than 50mg/L. Representative cases over a 2 year period, different operators in different hospitals:
GHEART Vol 9/1S/2014
j
March, 2014
j
POSTER/2014 WCC Posters
PW219 Prevalence Of Metabolic Syndrome And Association With Lifestyle Factors In India: A Nationwide Cross Sectional Study In Urban Subjects Prakash Deedwania*1, Rajeev Gupta2, Krishnakumar Sharma2, Vijay Achari3, Anil Bhansali4, Balkishan Gupta5, Anuj Maheshwari6, Tulika G. Mahanta7, Arvind Gupta8 1 University of California San Francisco, Fresno, United States, 2Fortis Escorts Hospital, Jaipur, 3 Patna Medical College, Patna, 4Postgraduate Institute of Medical Education and Research, Chandigarh, 5SP Medical College, Bikaner, 6BBD College of Dental Sciences, Lucknow, 7Assam Medical College, Dibrugarh, 8Jaipur Diabetes Research Centre, Jaipur, India Introduction: Metabolic syndrome is common but its lifestyle risk factors are poorly studied, especially in low and lower-middle income countries. Objectives: To determine association of socioeconomic and lifestyle factors with metabolic syndrome prevalence we performed a multisite cross-sectional study in India. Methods: The study was performed at eleven cities in India using cluster sampling. 6198 Subjects (men 3426, women 2772, response 62%, age 4810 years) were evaluated for sociodemographic, lifestyle, anthropometric and biochemical factors using uniform methodology. Prevalence of metabolic syndrome was determined using Asian-specific harmonized criteria. Significant socioeconomic and lifestyle associations were determined using linear trend analysis. Results: Age adjusted prevalence (%, 95% confidence intervals) of metabolic syndrome in men and women was 33.3 (31.7-34.9) and 40.4 (38.6-42.2) (harmonized Asian specific criteria), 23.9 (22.4-26.4) and 34.5 (32.0-36.1) (modified Adult Treatment Panel-3, ATP-3) and 17.2 (15.3-19.1) and 22.8 (20.1-24.2) (ATP-3). In men and women, respectively, high waist circumference was in 35.7 (34.1-37.3) and 57.5 (55.6-59.3), high blood pressure in 50.6 (48.9-52.3) and 46.3 (44.4-48.1), impaired fasting glucose or diabetes in 29.0 (27.530.5) and 28.0 (26.3-29.7), low HDL cholesterol in 34.1 (32.5-35.7) and 52.8 (50.9-54.7) and high triglycerides in 41.2 (39.5-42.8) and 31.5 (29.7-33.2) percent. Prevalence was significantly greater in subjects with lowest vs highest educational status (45 vs 26%), occupational status (46 vs 40%), dietary fat intake (52 vs 45%), sedentary lifestyle (47 vs 38%) and body mass index (66 vs 29%) categories (ptrend<0.05). Conclusion: There is high prevalence of metabolic syndrome among urban populations in India. Socioeconomic (high educational and socioeconomic status) and lifestyle (high fat diet, low physical activity, overweight and obesity) are important risk factors. Disclosure of Interest: None Declared PW220 The Prevalence of Metabolic syndrome in Coronary artery Disease patients compared to those without Coronary Artery Disease: Insights from South Indian population Stigimon Joseph*1 1 Cardiology, Little Flower Hospital And Research Center, Angamaly, Angamaly, Ernakulam, Kerala, India, India Introduction: There are few studies addressing the prevalence of Metabolic Syndrome among the South Indian population. There are limited data comparing the prevalence of Metabolic syndrome among Coronary Artery Disease (CAD) patients compared to healthy population. Objectives: To assess the prevalence of Metabolic Syndrome in Coronary Artery Disease patients and to compare with those without Coronary Artery Disease. Methods: Patients with CAD who were seen in the cardiology Out Patient Department formed the study group . CAD was defined as documented Acute Coronary Syndrome or positive TMT or disease documentation by Coronary Angiogram. During the same time period two population surveys were conducted which formed data for healthy general population. The two different population surveys were : a) Mostly manual laborers of the Panchayat ward where the hospital is situated (195 individuals participated). b) Sedentary population (office staff, teachers) (242 individuals participated). Results: A total of 1003 individuals were evaluated. 761 were included in the study. 405 patients have CAD as defined and they formed Group: A and 356 are healthy (group: B). Male to female ratio is almost equal (361 females and 400 males). The prevalence of Metabolic Syndrome is high and among South Indian population. Table 1. Prevalence of Metabolic Syndrome Definitions
Total(761)
Females(361)
Males(400)
IDF
298(39.1%)
169(46.8%)
129(33.8%)
ATP III
361(47.4%)
192(53.3%)
172(43.1%)
WHO
308(41.7%)
122(33.7%)
186(46.6%)
Prevalence is higher coronary artery disease patients.
Table 2. Prevalence of Metabolic Syndrome CAD x no CAD groups
Conclusion: 1. The overall prevalence of Metabolic Syndrome in South Indian population is high (39%). 2. Coronary Artery Disease patients have higher prevalence compared to healthy population. 3. A significant proportion of our population have BMI <18, still they have predilection for Metabolic syndrome which needs further evaluation. Disclosure of Interest: None Declared PW222 A pragmatic tool to guide the intensity of chronic heart failure management: Green Amber Red Delineation of rIsk And Need in Chronic Heart Failure (GARDIAN-CHF) Simon Stewart*1, Yih-Kai Chan1, James McVeigh2, Melinda Carrington1, and on behalf of the WHICH? Study Investigators 1 Preventative Health, Baker IDI Heart and Diabetes Institute, Melbourne, 2Prince of Wales Hospital, Randwick, Sydney, Australia Introduction: There is scope to improve the cost-effective application of chronic heart failure (CHF) management programs. Objectives: To examine the potential cost-benefits of applying an innovative traffic light system, the Green Amber Red Delineation of rIsk And Need (GARDIAN), to guide the intensity of post-discharge management of CHF. Methods: We used outcome data from the multicentre, randomized controlled Which Intervention is most cost-effective and Consumer friendly in reducing Hospital stay (WHICH?) Trial comprising typically older patients hospitalised with CHF. Using the distribution (quartiles) of days alive and out-of-hospital up to 18 months post index hospitalisation we: 1) confirmed a gradient of event-free survival, 2) identified characteristics that predicted eventfree survival (p<0.05 for observed gradients) and 3) aggregated predictive variables into 3 key GARDIAN domains (clinical stability, gold-standard management and holistic profile). Results: Differential group event-free outcomes were – Group A (n¼56, 548+ days eventfree, mean 1.8 days hospital stay and 0% mortality), Group B (n¼83, 530-547 days, 7.7 days, 0%), Group C (n¼71, 393-529 days, 28.2 days, 11.3%) and Group D (n¼70, 0 – 392 days, 24.1 days, 87.2%). Clear gradients across the 4 groups were found according to age, self-care ability, cognitive impairment, language status, prior CHF admission, acute pulmonary oedema, index stay, stay in intensive care, eGFR, anaemia, treatment with an ACEi or beta-blocker and early post-discharge clinical instability (mostly congestion). Compared with statistical modelling, pragmatic aggregation of these variables according to pre-specified GARDIAN coding (Green/low risk with only one domain deficit, Amber/ medium risk with two domain deficits and automatic Red/high risk red status if postdischarge clinical instability present) was most accurate in aligning with the groups; further enhanced when any intensive care stay indicated clinical instability (automatic Red status). Applying GARDIAN coding, for every 100 CHF patients, 9%, 64% and 27%, respectively would be designated Green, Amber and Red and follow-up titrated accordingly. Predicted false negatives (requiring redesignation as Red on readmission) in Green would be 22% (2 patients) and false positives in Red would be 11%. Conclusion: The GARDIAN-CHF tool represents a promising, pragmatic tool to guide the intensity of CHF-MPs when limited resources restrict their application. Disclosure of Interest: None Declared PW224 Hard Aquifer Drinking Water Linked To High Ct Coronary Angiogram Calcium Scores John F. England*1, Marcin Roman2, Lloyd Davis3 1 Cardiology, Blue Mountains District Anzac Memorial Hospital, Katoomba NSW, 2Radiology, PRP, DUBBO NSW, 3Cardiology, Westmead Hospital, WESTMEAD NSW, Australia Introduction: In rural Australia (compared to seaboard coastal population) health demographics reports of an increased incidence of coronary artery disease, ruptured calcific coronary arteries at angioplasty (haemopericardium) and thyroid disease prompted public health officials in the town of Mudgee (300km west of Sydney) to install a water softening plant two years ago. Drinking water from the Burrundulla aquifer was associated with salt corrosion of metal plumbing fittings and hot water heating tanks. Objectives: 100 consecutive CT coronary angiograms (CTCA) in the postal code area of Mudgee (hard water) were compared to 100 consecutive CTCAs in postal code area of the NSW coastal town of Gosford (soft water) and matched for age distribution and sex - 75% male, aged 70 years Methods: CTCA data compared the upper quartiles of each area and contrasted with CTCAs from 100 older consecutive patients in the city of Sydney from the same radiological practice. Results:
Different Groups.
IDF
ATP III
WHO
Hard water Mudgee
Calcium Score ¼ 1120.8 (SD 992)
Group.A (With CAD)
170 (41.6%) p**
209 (51.8%) p**
202(50%) p**
Soft rainwater Gosford
Calcium Score ¼ 767.6 (SD 522)
Dam water Sydney (older reference group)
Calcium Score ¼ 897.4 (SD 812)
Group.B(without CAD)
128(34.3%)
147(41.4%)
103(26.1%)
4.9% of Coronary artery disease patients and 8.1% of healthy individuals have BMI<18. It is interesting to note that 25% of them have ¼> 2 risk factors for Metabolic syndrome though they cannot be classified as having Metabolic syndrome with present diagnostic criteria. This observation “ the clustering of metabolic risk factors in lean individuals” needs further evaluation.
e302
The hydrated lime water softening unit reduced the calcium carbonate levels from 410mg/L to 115mg/L and pH from 8.4 to 7.8. Sydney and coastal NSW drinking waters are soft and reach WHO Guidelines for total hardness less than 50mg/L. Representative cases over a 2 year period, different operators in different hospitals:
GHEART Vol 9/1S/2014
j
March, 2014
j
POSTER/2014 WCC Posters