21
Emily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson The Obesity Paradox: The Importance for Long-term Outcomes in Non-ST-Elevation Myocardial Infarction – The CRUSADE Experience

E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

  • Upload
    ion

  • View
    54

  • Download
    0

Embed Size (px)

DESCRIPTION

The Obesity Paradox: T he Importance for Long-term Outcomes in Non-ST-Elevation Myocardial Infarction – The CRUSADE Experience. E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson. Disclosures. None. Obesity in the United States. - PowerPoint PPT Presentation

Citation preview

Page 1: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Emily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

The Obesity Paradox: The Importance for Long-term Outcomes in Non-ST-Elevation Myocardial Infarction – The CRUSADE Experience

Page 2: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Disclosures

None

Page 3: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Obesity in the United States

CDC. Behavioral Risk Factor Surveillance System: 2010 survey data. Atlanta, GA: US Department of Health and Human Services, CDC; 2011.

Page 4: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

0.5

BMI and Incident MIIn Individuals without Prior

MI

RR

(95%

CI)

18.5-24.9

<18.5 25.0-29.9

>=30

BMI

Eur Heart J. 2013 ;34(5):345-53.

21-23.5

BMI and Mortality Among STEMI Patients

18.5-21

<18.5

HR

(95%

CI)

4.0

1.0

0.25

BMI

26.5-28

23.5-25

25-26.5

28-30.0

>30.0

Int Jour of Obes. 2002; 26, 1046-1053. 

The Paradox

2.0

Page 5: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

The Obesity Paradox

First used to describe counterintuitive survival advantages in 19991

Reported for diabetes2, heart failure3, chronic kidney disease4, and CAD5

What is still unclear: Whether the paradox exists among older,

NSTEMI patients Persistence of effects over long periods of

followup Differential mortality associations by metabolic

status1Kidney Int. 1999;55(4):1560-1567.2JAMA. 2012;308(6):581-590.3Am J Cardiol. 2003;91(7):891-8944Am J Clin Nutr. 2005;81(3):543-5545Am J Med. Oct 2007;120(10):863-870

Page 6: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Objectives

To determine the association between body mass index (BMI) and risk of all-cause mortality over three years in a population of elderly NSTEMI patients

To determine whether BMI associations differ by “metabolically healthy” status

Page 7: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Methods

Data Sources CRUSADE linked to CMS data (2001-2006) National NSTEMI Quality Improvement Initiative Exclusions

»Patients transferred out (N=4474)»Patients missing information on height and/or weight

(N=2300)»Non-index admissions for patients with multiple

records (N=1329)»Died during hospitalization (N=2623)

Final Sample: N=34,465

Page 8: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Body Mass Index (BMI)

Calculated from weight and height on admission

WHO categories(kg/m2)6

<18.5 Underweight 18.5-24.9 Normal Weight 25-29.9 Overweight 30-34.9 Obese class I 35-39.9 Obese class II >=40 Obese class III

6World Health Organ Tech Rep Ser. 2000;894:i-xii, 1-253.

Page 9: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Objective II

Metabolically Unhealthy7

• Two or more of the following: 1. High blood pressure (>130/85 mmHG) or

hypertension2. Diabetes mellitus 3. High triglycerides (>150 mg/dl)4. Low HDL (<40 mg/DL in men, <50 mg/DL in women)

Metabolically healthy or “benign” obese• Preserved insulin sensitivity• Lower visceral fat accumulation

7Eur Heart J. 2013;34(5):389-397

Page 10: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Statistical Analysis Cox proportional hazards modeling with

censoring on death All-cause mortality over 3-years CRUSADE long-term mortality model8

AgeGender RaceFamily Hx of CADSmoking status

Prior MIPrior CABGPrior PCIPrior CHFPrior strokeHeart rate

HF at presentationECG findingsInitial HCT Initial troponin

8Am Heart J. 2011;162(5):875-883.

Page 11: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

28%Obese

Obesity in CRUSADE

4%

32%

36%

18%

6%

4%

UnderweightNormal WeightOverweightObese Class IObese Class IIObese Class III

Page 12: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Patient Characteristics (%)

  Obesity Class*

 UnderWeight

(N=1236)

NormalWeight

(N=11186)

Over-Weight

(N=12506)

Obese I(N=6089)

Obese II(N=2226)

Obese III(N=1222)

Demographics            Age in years (median) 82.0 80.0 77.0 75.0 73.0 72.0

Male Sex 30.7 49.3 59.4 54.7 46.1 35.5White Race 83.8 86.7 86.7 86.5 86.3 84.4

Medical history            Hypertension 71.1 73.5 76.2 81.2 84.6 86.2

Diabetes 16.9 25.4 34.3 44.8 55.7 61.1Dyslipidemia 33.9 46.5 54.6 59.3 60.7 58.9

Current/Recent Smoker 19.7 14.3 12.5 10.6 10.1 9.9All-Cause Mortality

Unadjusted 3-year Mortality 62.4 45.6 31.8 28.0 29.5 32.8

Page 13: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Cumulative Incidence - Mortality

Page 14: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

ResultsAll-Cause Mortality

Page 15: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Metabolically Unhealthy

Overall <18.5 18.5-24.9 25-29.9 30-34.9 35-35.9 >=400

102030405060708090

100

71.2%

47.8%

61.7%71.9%

81.2%85.7% 85.5%

% Metabolically Unhealthy

%

BMI Category (kg/m2)

Page 16: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Sensitivity AnalysisAll-Cause Mortality Metabolically Healthy Patients

Page 17: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Sensitivity Analysis

All-Cause Mortality Metabolically Unhealthy Patients

Page 18: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Potential Explanations

Selection bias: “healthiest” patients survive long enough to develop MI

Obese patients with more severe events may have greater metabolic reserve and increased resistance to catabolic burden

Cachexia abnormal cytokine & neurohormonal levels, mortality

BMI categories may have heterogeneous groups

Page 19: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Limitations

No followup after 3 years “Metabolically Healthy” classification

couldn’t be made in 1/3 of patients because HDL & triglycerides were not measured

No information on cause of death, which may be important to obesity paradox

Page 20: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Conclusions & Future Directions

The obesity paradox persists over the long term for NSTEMI

Similar associations between BMI and all-cause mortality for metabolically healthy patients

Further studies on metabolism and BMI are needed

Page 21: E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson

Thank You!