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Underweight, Markers of Cachexia, and Mortality in Acute Myocardial Infarction: A Prospective Cohort Study of Elderly Medicare Beneficiaries.

Bucholz EM, Krumholz HA, Krumholz HM - PLoS Med. (2016)

Bottom Line: Underweight patients are at higher risk of death after acute myocardial infarction (AMI) than normal weight patients; however, it is unclear whether this relationship is explained by confounding due to cachexia or other factors associated with low body mass index (BMI).The adverse effects of low BMI were greatest in patients with very low BMIs.Strategies to promote weight gain in underweight patients after AMI are worthy of testing.

View Article: PubMed Central - PubMed

Affiliation: Department of Pediatrics, Boston Children's Hospital and Boston Medical Center, Boston, Massachusetts, United States of America.

ABSTRACT

Background: Underweight patients are at higher risk of death after acute myocardial infarction (AMI) than normal weight patients; however, it is unclear whether this relationship is explained by confounding due to cachexia or other factors associated with low body mass index (BMI). This study aimed to answer two questions: (1) does comprehensive risk adjustment for comorbid illness and frailty measures explain the higher mortality after AMI in underweight patients, and (2) is the relationship between underweight and mortality also observed in patients with AMI who are otherwise without significant chronic illness and are presumably free of cachexia?

Methods and findings: We analyzed data from the Cooperative Cardiovascular Project, a cohort-based study of Medicare beneficiaries hospitalized for AMI between January 1994 and February 1996 with 17 y of follow-up and detailed clinical information to compare short- and long-term mortality in underweight and normal weight patients (n = 57,574). We used Cox proportional hazards regression to investigate the association of low BMI with 30-d, 1-y, 5-y, and 17-y mortality after AMI while adjusting for patient comorbidities, frailty measures, and laboratory markers of nutritional status. We also repeated the analyses in a subset of patients without significant comorbidity or frailty. Of the 57,574 patients with AMI included in this cohort, 5,678 (9.8%) were underweight and 51,896 (90.2%) were normal weight at baseline. Underweight patients were older, on average, than normal weight patients and had a higher prevalence of most comorbidities and measures of frailty. Crude mortality was significantly higher for underweight patients than normal weight patients at 30 d (25.2% versus 16.4%, p < 0.001), 1 y (51.3% versus 33.8%, p < 0.001), 5 y (79.2% versus 59.4%, p < 0.001), and 17 y (98.3% versus 94.0%, p < 0.001). After adjustment, underweight patients had a 13% higher risk of 30-d death and a 26% higher risk of 17-y death than normal weight patients (30-d hazard ratio [HR] 1.13, 95% CI 1.07-1.20; 17-y HR 1.26, 95% CI 1.23-1.30). Survival curves for underweight and normal weight patients separated early and remained separate over 17 y, suggesting that underweight patients remained at a significant survival disadvantage over time. Similar findings were observed among the subset of patients without comorbidity at baseline. Underweight patients without comorbidity had a 30-d adjusted mortality similar to that of normal weight patients but a 21% higher risk of death over the long term (30-d HR 1.08, 95% CI 0.93-1.26; 17-y HR 1.21, 95% CI 1.14-1.29). The adverse effects of low BMI were greatest in patients with very low BMIs. The major limitation of this study was the use of surrogate markers of frailty and comorbid conditions to identify patients at highest risk for cachexia rather than clear diagnostic criteria for cachexia.

Conclusions: Underweight BMI is an important risk factor for mortality after AMI, independent of confounding by comorbidities, frailty measures, and laboratory markers of nutritional status. Strategies to promote weight gain in underweight patients after AMI are worthy of testing.

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Related in: MedlinePlus

Adjusted Cox proportional hazards regression restricted cubic splinemodels for all patients and for the subset of patients without significantcomorbidity or frailty.(A) and (B) show 1-y adjusted mortality for all patients and for the subsetof patients without significant comorbidity or frailty, respectively. (C)and (D) show 17-y adjusted mortality for all patients and for patientswithout significant comorbidity or frailty. The reference category ispatients with a BMI of 20 kg/m2. In each panel, the black linedenotes the estimated HR, and gray shading indicates the 95% confidencelimits. Unadjusted 1- and 17-y curves for all patients and for the subset ofpatients without significant comorbidity or frailty are shown in S1 Fig.Analyses were adjusted for patient demographics (age, sex, race),cardiovascular risk factors (diabetes, hypertension, smoking, prior CAD),comorbidities (CHF, COPD, CVA/stroke, cirrhosis/liver disease, CKD, HIV orimmunocompromised state, cancer, Alzheimer disease/dementia, terminalillness), markers of nutritional status (anemia, hypoalbuminemia), measuresof frailty (admission from an SNF, mobility on admission, urinary continenceon admission), clinical presentation (Killip classification, systolic bloodpressure, heart rate, ST-elevation AMI, anterior infarction, cardiac arreston admission, renal insufficiency), and treatment (PCI or CABG within thefirst 30 d of admission, fibrinolytic therapy, aspirin on admission, andbeta-blockers on admission).
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pmed.1001998.g002: Adjusted Cox proportional hazards regression restricted cubic splinemodels for all patients and for the subset of patients without significantcomorbidity or frailty.(A) and (B) show 1-y adjusted mortality for all patients and for the subsetof patients without significant comorbidity or frailty, respectively. (C)and (D) show 17-y adjusted mortality for all patients and for patientswithout significant comorbidity or frailty. The reference category ispatients with a BMI of 20 kg/m2. In each panel, the black linedenotes the estimated HR, and gray shading indicates the 95% confidencelimits. Unadjusted 1- and 17-y curves for all patients and for the subset ofpatients without significant comorbidity or frailty are shown in S1 Fig.Analyses were adjusted for patient demographics (age, sex, race),cardiovascular risk factors (diabetes, hypertension, smoking, prior CAD),comorbidities (CHF, COPD, CVA/stroke, cirrhosis/liver disease, CKD, HIV orimmunocompromised state, cancer, Alzheimer disease/dementia, terminalillness), markers of nutritional status (anemia, hypoalbuminemia), measuresof frailty (admission from an SNF, mobility on admission, urinary continenceon admission), clinical presentation (Killip classification, systolic bloodpressure, heart rate, ST-elevation AMI, anterior infarction, cardiac arreston admission, renal insufficiency), and treatment (PCI or CABG within thefirst 30 d of admission, fibrinolytic therapy, aspirin on admission, andbeta-blockers on admission).

Mentions: When BMI was examined as a continuous variable, there was an inverse relationshipbetween BMI and the hazards of death at both 1 and 17 y. The highest risk of deathwas observed in those with very low BMI (<17 kg/m2), and the lowestrisk in those with BMIs in the upper range of normal (>24 kg/m2). Thisrelationship persisted after adjustment (Figs 2 and S1).


Underweight, Markers of Cachexia, and Mortality in Acute Myocardial Infarction: A Prospective Cohort Study of Elderly Medicare Beneficiaries.

Bucholz EM, Krumholz HA, Krumholz HM - PLoS Med. (2016)

Adjusted Cox proportional hazards regression restricted cubic splinemodels for all patients and for the subset of patients without significantcomorbidity or frailty.(A) and (B) show 1-y adjusted mortality for all patients and for the subsetof patients without significant comorbidity or frailty, respectively. (C)and (D) show 17-y adjusted mortality for all patients and for patientswithout significant comorbidity or frailty. The reference category ispatients with a BMI of 20 kg/m2. In each panel, the black linedenotes the estimated HR, and gray shading indicates the 95% confidencelimits. Unadjusted 1- and 17-y curves for all patients and for the subset ofpatients without significant comorbidity or frailty are shown in S1 Fig.Analyses were adjusted for patient demographics (age, sex, race),cardiovascular risk factors (diabetes, hypertension, smoking, prior CAD),comorbidities (CHF, COPD, CVA/stroke, cirrhosis/liver disease, CKD, HIV orimmunocompromised state, cancer, Alzheimer disease/dementia, terminalillness), markers of nutritional status (anemia, hypoalbuminemia), measuresof frailty (admission from an SNF, mobility on admission, urinary continenceon admission), clinical presentation (Killip classification, systolic bloodpressure, heart rate, ST-elevation AMI, anterior infarction, cardiac arreston admission, renal insufficiency), and treatment (PCI or CABG within thefirst 30 d of admission, fibrinolytic therapy, aspirin on admission, andbeta-blockers on admission).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4836735&req=5

pmed.1001998.g002: Adjusted Cox proportional hazards regression restricted cubic splinemodels for all patients and for the subset of patients without significantcomorbidity or frailty.(A) and (B) show 1-y adjusted mortality for all patients and for the subsetof patients without significant comorbidity or frailty, respectively. (C)and (D) show 17-y adjusted mortality for all patients and for patientswithout significant comorbidity or frailty. The reference category ispatients with a BMI of 20 kg/m2. In each panel, the black linedenotes the estimated HR, and gray shading indicates the 95% confidencelimits. Unadjusted 1- and 17-y curves for all patients and for the subset ofpatients without significant comorbidity or frailty are shown in S1 Fig.Analyses were adjusted for patient demographics (age, sex, race),cardiovascular risk factors (diabetes, hypertension, smoking, prior CAD),comorbidities (CHF, COPD, CVA/stroke, cirrhosis/liver disease, CKD, HIV orimmunocompromised state, cancer, Alzheimer disease/dementia, terminalillness), markers of nutritional status (anemia, hypoalbuminemia), measuresof frailty (admission from an SNF, mobility on admission, urinary continenceon admission), clinical presentation (Killip classification, systolic bloodpressure, heart rate, ST-elevation AMI, anterior infarction, cardiac arreston admission, renal insufficiency), and treatment (PCI or CABG within thefirst 30 d of admission, fibrinolytic therapy, aspirin on admission, andbeta-blockers on admission).
Mentions: When BMI was examined as a continuous variable, there was an inverse relationshipbetween BMI and the hazards of death at both 1 and 17 y. The highest risk of deathwas observed in those with very low BMI (<17 kg/m2), and the lowestrisk in those with BMIs in the upper range of normal (>24 kg/m2). Thisrelationship persisted after adjustment (Figs 2 and S1).

Bottom Line: Underweight patients are at higher risk of death after acute myocardial infarction (AMI) than normal weight patients; however, it is unclear whether this relationship is explained by confounding due to cachexia or other factors associated with low body mass index (BMI).The adverse effects of low BMI were greatest in patients with very low BMIs.Strategies to promote weight gain in underweight patients after AMI are worthy of testing.

View Article: PubMed Central - PubMed

Affiliation: Department of Pediatrics, Boston Children's Hospital and Boston Medical Center, Boston, Massachusetts, United States of America.

ABSTRACT

Background: Underweight patients are at higher risk of death after acute myocardial infarction (AMI) than normal weight patients; however, it is unclear whether this relationship is explained by confounding due to cachexia or other factors associated with low body mass index (BMI). This study aimed to answer two questions: (1) does comprehensive risk adjustment for comorbid illness and frailty measures explain the higher mortality after AMI in underweight patients, and (2) is the relationship between underweight and mortality also observed in patients with AMI who are otherwise without significant chronic illness and are presumably free of cachexia?

Methods and findings: We analyzed data from the Cooperative Cardiovascular Project, a cohort-based study of Medicare beneficiaries hospitalized for AMI between January 1994 and February 1996 with 17 y of follow-up and detailed clinical information to compare short- and long-term mortality in underweight and normal weight patients (n = 57,574). We used Cox proportional hazards regression to investigate the association of low BMI with 30-d, 1-y, 5-y, and 17-y mortality after AMI while adjusting for patient comorbidities, frailty measures, and laboratory markers of nutritional status. We also repeated the analyses in a subset of patients without significant comorbidity or frailty. Of the 57,574 patients with AMI included in this cohort, 5,678 (9.8%) were underweight and 51,896 (90.2%) were normal weight at baseline. Underweight patients were older, on average, than normal weight patients and had a higher prevalence of most comorbidities and measures of frailty. Crude mortality was significantly higher for underweight patients than normal weight patients at 30 d (25.2% versus 16.4%, p < 0.001), 1 y (51.3% versus 33.8%, p < 0.001), 5 y (79.2% versus 59.4%, p < 0.001), and 17 y (98.3% versus 94.0%, p < 0.001). After adjustment, underweight patients had a 13% higher risk of 30-d death and a 26% higher risk of 17-y death than normal weight patients (30-d hazard ratio [HR] 1.13, 95% CI 1.07-1.20; 17-y HR 1.26, 95% CI 1.23-1.30). Survival curves for underweight and normal weight patients separated early and remained separate over 17 y, suggesting that underweight patients remained at a significant survival disadvantage over time. Similar findings were observed among the subset of patients without comorbidity at baseline. Underweight patients without comorbidity had a 30-d adjusted mortality similar to that of normal weight patients but a 21% higher risk of death over the long term (30-d HR 1.08, 95% CI 0.93-1.26; 17-y HR 1.21, 95% CI 1.14-1.29). The adverse effects of low BMI were greatest in patients with very low BMIs. The major limitation of this study was the use of surrogate markers of frailty and comorbid conditions to identify patients at highest risk for cachexia rather than clear diagnostic criteria for cachexia.

Conclusions: Underweight BMI is an important risk factor for mortality after AMI, independent of confounding by comorbidities, frailty measures, and laboratory markers of nutritional status. Strategies to promote weight gain in underweight patients after AMI are worthy of testing.

Show MeSH
Related in: MedlinePlus