Secondary Logo

Journal Logo

The Association of Body Mass Index to Postoperative Outcomes in Elderly Vascular Surgery Patients

A Reverse J-Curve Phenomenon

Nafiu, Olubukola O., MD, FRCA*; Kheterpal, Sachin, MD*; Moulding, Ruairi, MD, FRCA*; Picton, Paul, MD, FRCA*; Tremper, Kevin K., MD, FRCA*; Campbell, Darrell A. Jr., MD; Eliason, Jonathan L., MD; Stanley, James C., MD

doi: 10.1213/ANE.0b013e3181fcc51a
Cardiovascular Anesthesiology: Research Reports
Free
SDC

BACKGROUND: The purpose of this investigation was to determine whether there is a relation between body mass index (BMI) classes and early postoperative outcomes in elderly patients undergoing vascular surgery. We hypothesized that being overweight or obese increases the risks of surgery.

METHODS: Data from the American College of Surgeons' National Surgical Quality Improvement Program Participant Use Data File was used to identify the BMI (kg/m2) and 30-day outcomes of 25,337 patients aged ≥65 years undergoing vascular surgery from 2005 to 2007. Patients were stratified into 6 BMI classes: (1) underweight (BMI ≤18.5 kg/m2), (2) normal (BMI = 18.6–24.9 kg/m2), (3) overweight (BMI = 25–29.9 kg/m2), (4) obese class I (BMI = 30–34.9 kg/m2), (5) obese class II (BMI = 35–39.9 kg/m2), and (6) obese class III (BMI ≥40 kg/m2). Morbidity and mortality rates across all BMI classes were subjected to univariate and multiple logistic regression analyses.

RESULTS: Mortality rates varied among the BMI classes: 9.4% underweight, 4.0% normal, 3.0 overweight and obese I, 3.3% obese II, and 4.6% obese III (P < 0.001). Major postoperative morbidity paralleled the risk of death. Independent preoperative factors associated with mortality included diabetes mellitus, chronic obstructive pulmonary disease, active congestive heart failure, recent weight loss, disseminated cancer, and an inability to function independently. Each of these factors was statistically more important than the BMI alone in defining an increased risk of surgery.

CONCLUSION: Increased BMI alone was not a major factor predicting perioperative 30-day mortality in this cohort of elderly surgical patients; the effect was a nonlinear one with a reversed J-curve response documenting the poorest outcomes in underweight, normal, and a slight increase in excessively obese patients.

Published ahead of print December 2, 2010

From the Departments of *Anesthesiology and Surgery, University of Michigan, Ann Arbor, Michigan.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.anesthesia-analgesia.org).

The authors report no conflicts of interest.

Address correspondence and request for reprints to Olubukola O. Nafiu, MD, FRCA, University of Michigan Health System, 1500 East Medical Centre Dr., Room UH 1H247, Ann Arbor, MI 48109-0048. Address e-mail to onafiu@med.umich.edu.

Accepted August 25, 2010

Published ahead of print December 2, 2010

The elderly are one of the fastest growing segments of American society. Individuals 65 years of age and older represent approximately 15% of the United States (US) population and they are projected to represent 26% by 2025.1 An epidemiologic parallel to the aging of society is an increasing rate of obesity in the general population, particularly among the elderly.2,3 Current estimates suggest an overall obesity prevalence rate of approximately 15% to 20% among the elderly.2 The relevance of aging and obesity to the morbidity and mortality affecting vascular surgery patients remains undefined.

Obesity is closely linked with many chronic diseases including diabetes mellitus (DM), hypertension, and dyslipidemia that are associated with the progress of arteriosclerotic vascular disease.4,5 Although obesity is a known independent risk factor for all-cause mortality in adults5 and is often considered a contributor to poor surgical outcomes,6,7 its role in contributing to the death of the elderly remains controversial.8 Certain confounders such as the greater prevalence of chronic diseases and the shortened life expectancy in the elderly make the direct attribution of increased mortality to obesity in this older age group problematic.1,9

Earlier studies on the effect of body mass index (BMI) on surgical outcomes often have had contradictory conclusions, and many were from single institutions with small sample sizes or were retrospective in design.1014 Two recent reports assessing obesity in large numbers of patients using National Surgical Quality Improvement Program (NSQIP) data did not differentiate the effects of BMI on perioperative outcomes among older and younger adults,15,16 which is relevant because age is a known effect modifier in relating obesity to mortality. An effect modifier is a variable that changes the direction and/or strength of the relationship between an exposure and the outcome variable.17 For example, the relative risk of mortality with increasing BMI tends to decrease with age.17 Therefore, it becomes important to examine the elderly as a distinct group, especially in a setting where there is an appreciable postoperative risk of death. The operative hazards of vascular surgery provide an opportunity to assess the relevance of obesity in the aged.

The objective of this study was to determine whether there is a relation between 6 different BMI classes and 30-day morbidity and mortality of elderly patients undergoing vascular surgery. It was hypothesized that as the BMI increases, the risk of postoperative morbidity and mortality increases.

Back to Top | Article Outline

METHODS

Clinical information on 25,337 patients older than 65 years who underwent a vascular surgical procedure was obtained from the 2005 to 2007 Participant Use Data File of the American College of Surgeons' National Surgical Quality Improvement Program. Data in this file provided risk-adjusted surgical outcome information from 186 hospitals in the US collected by NSQIP-trained clinical nurse specialists who reviewed these data using a standardized format with strict definitions. Patients were followed through their hospital course and after discharge for 30 days postoperatively. The methodology for collecting these data prospectively, including its accuracy and reproducibility, has been detailed in previous publications.18,19

Study patients underwent a variety of vascular operations, identified by the same Current Procedure Terminology codes used in an earlier report.16 Cardiac, urologic, orthopedic, obstetric, gynecologic, bariatric, and general surgical patients were excluded from the study. Also excluded were patients without records of their height or weight. BMI data were available in all study patients, representing the patient's weight in kilograms divided by the square of the height in meters (BMI = kg/m2). Patients were classified as: (1) underweight (BMI ≤18.5 kg/m2), (2) normal (BMI = 18.6–24.9 kg/m2), (3) overweight (BMI = 25–29.9 kg/m2), (4) obese class I (BMI = 30–34.9 kg/m2), (5) obese class II (BMI = 35–39.9 kg/m2), and (6) obese class III (BMI ≥40 kg/m2), as specified by the National Institutes of Health.20 Other important information such as preoperative functional independence, presence of “do not resuscitate” (DNR) orders, and prevalence of common chronic diseases, including hypertension, DM, pulmonary disease, cardiac disease, stroke, renal disorders, cancer, etc., were also examined. Operation complexity was measured using the work relative value units (RVUs) and total operation and anesthesia times. Work RVUs is a scale (0–95) to quantify the amount of work involved in a specific surgery based on preprocedural, intraprocedural, and postprocedural time; technical skill; physical effort; mental effort and judgment; and stress due to potential risk. It is the work portion of the Resource-Based Relative Value System adopted by Medicare to quantify the amount of work involved in each medical procedure. A score of 0 represents least complex and 95 represents most complex.15 The definitions for the perioperative variables are detailed in Appendix 1 (see Supplemental Digital Content 1, http://links.lww.com/AA/A196) and Appendix 2 (see Supplemental Digital Content 2, http://links.lww.com/AA/A197).

The primary outcome studied was death within 30 days of the vascular procedures. Secondary outcomes measured included common postoperative site-specific complications including superficial and deep wound infections, wound disruptions, graft failures, organ space infections, or bleeding requiring transfusion, as well as systemic complications including pneumonia, pulmonary embolism, delayed ventilator wean, unplanned reintubation, myocardial infarction, cardiac arrest, septic shock, postoperative stroke, reoperation, urinary tract infection, sepsis, deep venous thrombosis, and postoperative renal insufficiency not requiring dialysis. We then computed a composite morbidity variable defined as the occurrence of one or more of these postoperative complications and compared the frequency among BMI groups.

Analysis of data was performed using SPSS version 16.0 (SPSS Inc., Chicago, IL). Basic descriptive statistics including means, standard deviations, and percentages were calculated for demographic and anthropometric data. All continuous variables were examined for skewness and kurtosis. Prevalence of overweight and obesity was described as simple proportions. Pearson's χ2 (for categorical) and 1-way analysis of variance (ANOVA) (for continuous) variables were used to assess baseline clinical and perioperative differences between BMI categories. Pairwise comparisons using the normal weight BMI group as reference were performed using the Bonferroni multiple comparison of means method.

Before performing multiple logistic regression analyses, we examined the univariate predictors for multi-colinearity by first creating a correlation matrix and scanning for highly correlated variables (≥0.7). None of the variables had sufficiently high correlation indicating a low likelihood of significant colinearity. Multivariate analysis was performed using forward stepwise logistic regression to calculate the adjusted odds ratios for 30-day morbidity and all-cause mortality in the BMI categories with the normal group acting as reference. Variables were entered into the model on the basis of statistical significance and clinical relevance. A model fit was measured with the Hosmer-Lemeshow goodness-of-fit test.21 All reported P values were 2 sided and a P value of 0.05 was considered to be significant.

Back to Top | Article Outline

RESULTS

Demographic and medical information for the 25,337 patients studied are listed in Table 1. Certain characteristics of this group were notable. Obese class I, II, and III patients were significantly younger than normal weight or underweight patients (P < 0.001). Elderly female patients were significantly more likely to belong to the underweight class or obese class III, whereas male patients were more likely to be either overweight or in obese class I or II. Overweight and mildly obese class I elderly patients were more likely to be functionally independent. Underweight patients were significantly less likely to be functionally independent and more likely to have DNR orders.

Table 1

Table 1

The chronic diseases hypertension, DM, and congestive heart failure increased steadily across the BMI classes (ANOVA, P < 0.01). The highest frequency of a recent myocardial infarction or angina was in obese classes II and III. Underweight patients were more likely to have had a stroke, obstructive emphysema, disseminated cancer, recent weight loss, low serum albumin, or ascites.

Perioperative events, including mean preincision time, total anesthesia and operative times, and the primary procedure work RVUs were significantly different among the BMI classes (Table 2). In this regard, obese patients had significantly longer operative times than underweight and normal weight patients, despite their undergoing less-complex procedures (Bonferroni's pairwise comparisons, P = 0.02). Underweight patients underwent the most complex procedures and had the highest proportion of preoperative contaminated wounds. That group also had the highest transfusion rate, possibly a reflection of surgical complexity. The absolute number of red blood cell units transfused intraoperatively did not correlate with BMI class (data not shown), but was correlated with the complexity of the surgical procedure (r = 0.4; P < 0.001).

Table 2

Table 2

Of the 25,337 patients, there were 1009 deaths giving a mortality rate of 4% in this cohort of vascular surgery patients. Similarly, the composite postoperative morbidity rate was 28.5%. Analysis of the postoperative mortality and morbidity revealed important differences (Table 3). One-way ANOVA indicated a statistically significant difference for mortality among the BMI classes (F = 23.6, df = 5; P < 0.001). Overall crude mortality rate demonstrated a reverse-J distribution pattern (Fig. 1) with the highest mortality being 9.4% in the underweight group, decreasing to a nadir in the overweight and obese class I patients, with an increase in obese class II and III patients. The composite morbidity rate followed a pattern similar to the mortality curve (Fig. 1). Postoperative complications occurred most frequently in the underweight class with the frequency decreasing progressively to the obese class I group and then increasing in the higher BMI classes II and III. The hospital length of stay varied significantly by BMI classes (F = 21.9, df = 5; P < 0.001) and was similar to the variation in mortality rates.

Table 3

Table 3

Figure 1

Figure 1

The incidence of postoperative superficial and deep wound surgical site infections increased significantly across the BMI classes with the lowest frequency in underweight and the highest incidence in the obese class III patients. The incidences of postoperative respiratory complications, urinary tract infection, graft or prosthetic failure, and need for reoperation varied significantly by BMI class with the highest frequency of these complications occurring in the underweight group (P < 0.001).

Multivariate logistic regression defined a number of factors associated with 30-day mortality (Table 4). Adjusted mortality rate described a geometric pattern similar to that observed on univariate analysis (Fig. 2). The Hosmer-Lemeshow goodness-of-fit test for this model was not statistically significant indicating a good predictive model (χ2 = 8.2, df = 8; P = 0.42). A diagnosis of diabetes, chronic obstructive emphysema, or preoperative dyspnea was significantly associated with a 23%, 36%, and 52% higher risk of mortality, respectively. As might have been anticipated, patients with DNR orders had the highest risk for mortality. Interestingly, age and work RVUs had only a slight effect on the odds of mortality when controlled for other factors.

Table 4

Table 4

Figure 2

Figure 2

Back to Top | Article Outline

DISCUSSION

This investigation indicates that among elderly vascular surgery patients BMI class was a significant predictor of 30-day mortality, but the effect was nonlinear with a reversed J-curve response documenting the poorest outcomes in underweight, normal, and excessively obese patients. The distribution of composite postoperative morbidity followed a pattern similar to the mortality curve.

Obesity is a major public health issue in the US,1,2 and the 64% incidence of overweight and obese individuals in the present study of elderly vascular surgical patients was not unexpected. The US Department of Health and Human Services has recognized being overweight and obese as 1 of the 10 leading markers of poor health,22 and nearly a decade ago published a goal to reduce obesity rates in adults to 15% by 2010.23 This goal will not be met given the fact that approximately 66% of the country's adults are already either overweight or obese.24 Nevertheless, the projected health care cost of this epidemic25,26 demands that a focused effort to reduce obesity be pursued.

This study underscores the known relation of hypertension and diabetes to vascular disease with an increasing BMI.27,28 Contrary to earlier reports about obese vascular surgical patients,16 the current study demonstrated a strong association between high BMI and the prevalence of cardiac diseases, including heart failure, recent angina, and myocardial infarction. Obesity is a risk factor for heart failure and myocardial dysfunction independent of its role in hypertension, diabetes, and coronary heart disease.29 Because heart failure underlies a number of adverse cardiac events30,31 after surgery, it may account for a segment of the mortality in obese patients undergoing vascular operations.

Considerable interest surrounds the geometric nature of how BMI class is related to mortality. Epidemiologic studies have variously described J-shaped, U-shaped, monotonic, and linear relationships32,33; 2 recent surgical studies exhibited a reverse J-shaped relationship.15,16 This phenomenon is accompanied with an “obesity paradox” in which overweight and moderate obesity were associated with a lower, not higher, mortality.32 This finding was also evident among adults with heart failure and hypertension.34,35 The present study demonstrated a reverse J-shaped distribution in all-cause mortality with univariate and multivariate analyses (Figs. 1 and 2). It is possible that the relationship between obesity and mortality is substantially different between subjects in longitudinal studies and hospitalized patients.

Mechanisms underlying the obesity paradox remain speculative.34,36 Many have posited that adiposity may confer protection against various inflammatory mediators in heart failure patients by the production of “buffering” lipoproteins.3739 Similar protection against the inflammatory response accompanying surgical trauma may be operational in obese class I and II patients, but is likely to be limited in the severely obese class III group. The relationship between BMI group and mortality in the present study is consistent with an earlier report in older hospitalized patients.40 These investigators, similar to us, demonstrated an increased death rate in the lowest BMI groups with only a slight increase in the highest BMI categories. It is conceivable that in elderly surgical patients, high BMI alone does not have a major prognostic implication for perioperative mortality. This in no way diminishes the observed negative impact of high BMI on longevity and quality of life in longitudinal studies of adult nonhospitalized patients.4,5,8

The DNR status in this study deserves note. It was included in a logistic regression model, unlike previous studies in vascular surgery patients.16 Patients in the current study with DNR orders had 3 times the odds of 30-day mortality compared with those without DNR orders, even after adjusting for variables such as age and disease severity.41 Clearly, those factors underlying a DNR order are important predictors of 30-day mortality in elderly vascular surgery patients. Similarly, the present study confirms the importance of preoperative functional status to postoperative outcome.42 Elderly patients who were functionally dependent before their operation had 3 times increased odds of mortality in the current study. Loss of functional independence is a good surrogate for overall physiologic reserve in the elderly as well as a predisposing factor for positive energy balance and obesity.43 Additionally, functionally dependent elderly patients are more likely to be frail and have sarcopenia (loss of muscle bulk), and these 2 conditions are associated with increased mortality.44 Because the current study is observational in nature, it cannot provide firm evidence for the contribution of sarcopenia and frailty to the observed outcome.

There are certain limitations in the current investigation that should be considered in interpreting the study data. Because one cannot exclude the possibility of unmeasured or unknown confounders influencing the associations observed in this study, the apparent effect of BMI on mortality in the elderly vascular surgery patient may not be a reflection of a direct causal relationship. In fact, indirect factors may be quite important. For example, an alternative reason for the obesity paradox may be that overweight patients develop symptomatic vascular disease earlier than lean patients, and are therefore operated on when their anatomic disease is less advanced. A similar observation in patients with heart failure39 suggests that their disease becomes symptomatic at an earlier stage compared with that affecting non-obese patients. Thus, obesity may simply unmask less-severe vascular disease at the time of its clinical presentation. It is also possible that obese patients may be more aggressively monitored and cared for in the perioperative period because of the general perception that they are at a higher risk for anesthetic and surgical complications. Another possible limitation is the disproportionate distribution of patients according to BMI class. However, our finding reflects the prevailing demographics of the elderly in the US.3 It is also conceivable that the sickest underweight or severely obese patients never made it to surgery. However, there is no way to determine this from a cross-sectional study.

In conclusion, this large cross-sectional study of elderly vascular surgery patients revealed an effect of BMI on morbidity and mortality that was nonlinear, in that morbidity and mortality were highest in the underweight and morbidly obese class III patients and lowest in overweight and obese class I and II individuals. In fact, patients having normal weight exhibited a greater mortality when undergoing vascular surgical procedures than did those who were overweight or in obese class I and II categories. This obesity paradox should be recognized when undertaking anesthetic management and surgical interventions for vascular disease. Additionally, BMI may be an important consideration in interpreting risk-adjusted surgical outcomes, which may be particularly important in pay-for-performance paradigms in elderly vascular surgery patients.

Back to Top | Article Outline

REFERENCES

1. Elia M. Obesity in the elderly. Obes Res 2001;9:244S–8S
2. Arterburn DE, Crane PK, Sullivan SD. The coming epidemic of obesity in elderly Americans. J Am Geriatr Soc 2004;52:1907–12
3. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA 2006;295:1549–55
4. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA 1999;282:1523–9
5. Pi-Sunyer FX. Medical hazards of obesity. Ann Intern Med 1993;119:655–60
6. Lee CT, Dunn RL, Chen BT, Joshi DP, Sheffield J, Montie JE. Impact of body mass index on radical cystectomy. J Urol 2004;172:1281–5
7. Fasol R, Schindler M, Schumacher B, Schlaudraff K, Hannes W, Seitelberger R, Schlosser V. The influence of obesity on perioperative morbidity: retrospective study of 502 aorto-coronary bypass operations. Thorac Cardiovasc Surg 1992;40:126–9
8. Zamboni M, Mazzali G, Zoico E, Harris TB, Meigs JB, Di Francesco V, Fantin F, Bissoli L, Bosello O. Health consequences of obesity in the elderly: a review of four unresolved questions. Int J Obes (Lond) 2005;29:1011–29
9. Tayback M, Kamanyika S, Chee E. Body weight as a risk factor in the elderly. Arch Intern Med 1990;150:1065–72
10. Chapman GW Jr, Mailhes JB, Thompson HE. Morbidity in obese and non-obese patients following gynecologic surgery for cancer. J Natl Med Assoc 1988;80:417–20
11. Holley JL, Shapiro R, Lopatin WB, Tzakis AG, Hakala TR, Starzl TE. Obesity as a risk factor following cadaveric renal transplantation. Transplantation 1990;49:387–9
12. Prem KA, Mensheha N, McKelvey JL. Operative treatment of adenocarcinoma of the endometrium in obese women. Am J Obstet Gynecol 1965;92:16–22
13. Stern SH, Insall JN. Total knee arthroplasty in obese patients. J Bone Joint Surg Am 1990;72:1400–4
14. Vinton AL, Traverso LW, Jolly PC. Wound complications after modified radical mastectomy compared with tylectomy with axillary lymph node dissection. Am J Surg 1991;161:584–8
15. Mullen JT, Moorman DW, Davenport DL. The obesity paradox: body mass index and outcomes in patients undergoing non-bariatric general surgery. Ann Surg 2009;250:166–72
16. Davenport DL, Xenos ES, Hosokawa P, Radford J, Henderson WG, Endean ED. The influence of body mass index obesity status on vascular surgery 30-day morbidity and mortality. J Vasc Surg 2009;49:140–7
17. Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath CW Jr. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med 1999;341:1097–105
18. Daley J, Khuri SF, Henderson W, Hur K, Gibbs JO, Barbour G, Demakis J, Irvin G III, Stremple JF, Grover F, McDonald G, Passaro E Jr, Fabri PJ, Spencer J, Hammermeister K, Aust JB, Oprian C. Risk adjustment of the postoperative morbidity rate for the comparative assessment of the quality of surgical care: results of the National Veterans Affairs Surgical Risk Study. J Am Coll Surg 1997;185:328–40
19. Khuri SF, Henderson WG, Daley J, Jonasson O, Jones RS, Campbell DA Jr, Fink AS, Mentzer RM Jr, Steeger JE. The patient safety in surgery study: background, study design, and patient populations. J Am Coll Surg 2007;204:1089–102
20. Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Am J Clin Nutr 1998;68:899–917
21. Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate Data Analysis. 5th ed. London: Prentice Hall International, 1998
22. US Department of Health and Human Services. Healthy People 2010. 2nd ed. Washington, DC: US Department of Health and Human Services, 2000
23. The Surgeon General's Call to Action to Prevent and Decrease Overweight and Obesity. Rockville, MD: Public Health Service, Office of the Surgeon General, 2001
24. Wang Y, Beydoun MA, Liang L, Caballero B, Kumanyika SK. Will all Americans become overweight or obese? Estimating the progression and cost of the US obesity epidemic. Obesity (Silver Spring) 2008;16:2323–30
25. Hawn MT, Bian J, Leeth RR, Ritchie G, Allen N, Bland KI, Vickers SM. Impact of obesity on resource utilization for general surgical procedures. Ann Surg 2005;241:821–6
26. Rossner S. Obesity in the elderly a future matter of concern? Obes Rev 2001;2:183–8
27. Brown CD, Higgins M, Donato KA. Body mass index and the prevalence of hypertension and dyslipidemia. Obes Res 2000;8:605–19
28. Gelber RP, Gaziano JM, Manson JE, Buring JE, Sesso HD. A prospective study of body mass index and the risk of developing hypertension in men. Am J Hypertens 2007;20:370–7
29. Gelber RP, Gaziano JM, Orav EJ, Manson JE, Buring JE, Kurth T. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol 2008;52:605–15
30. Davenport DL, Ferraris VA, Hosokawa P, Henderson WG, Khuri SF, Mentzer RM Jr. Multivariable predictors of postoperative cardiac adverse events after general and vascular surgery: results from the patient safety in surgery study. J Am Coll Surg 2007;204:1199–210
31. Lee TH, Marcantonio ER, Mangione CM, Thomas EJ, Polanczyk CA, Cook EF, Sugarbaker DJ, Donaldson MC, Poss R, Ho KK, Ludwig LE, Pedan A, Goldman L. Derivation and prospective validation of a simple index for prediction of cardiac risk of major non-cardiac surgery. Circulation 1999;100:1043–9
32. Manson JE, Bassuk SS, Hu FB, Stampfer MJ, Colditz GA, Willett WC. Estimating the number of deaths due to obesity: can the divergent findings be reconciled? J Womens Health 2007;16:168–76
33. Ajani UA, Lotufo PA, Gaziano JM, Lee IM, Spelsberg A, Buring JE, Willett WC, Manson JE. Body mass index and mortality among US male physicians. Ann Epidemiol 2004;14:731–9
34. Kalantar-Zadeh K, Horwich TB, Oreopoulos A, Kovesdy CP, Younessi H, Anker SD, Morley JE. Risk factor paradox in wasting diseases. Curr Opin Clin Nutr Metab Care 2007;10:433–42
35. Horwich TB, Fonarow GC, Hamilton MA, MacLellan WR, Woo MA, Tillisch JH. The relationship between obesity and mortality in patients with heart failure. J Am Coll Cardiol 2001;38:789–95
36. Horwich TB, Fonarow GC. Reverse epidemiology beyond dialysis patients: chronic heart failure, geriatrics, rheumatoid arthritis, COPD, and AIDS. Semin Dial 2007;20:549–53
37. Rauchhaus M, Coats AJ, Anker SD. The endotoxin-lipoprotein hypothesis. Lancet 2000;356:930–3
38. Szmitko PE, Teoh H, Stewart DJ, Verma S. Adiponectin and cardiovascular disease: state of the art? Am J Physiol Heart Circ Physiol 2007;292:H1655–63
39. Lavie CJ, Osman AF, Milani RV, Mehra MR. Body composition and prognosis in chronic systolic heart failure: the obesity paradox. Am J Cardiol 2003;91:891–4
40. Landi F, Onder G, Gambassi G, Pedone C, Carbonin P, Bernabei R. Body mass index and mortality among hospitalized patients. Arch Intern Med 2000;160:2641–4
41. Shepardson LB, Youngner SJ, Speroff T, Rosenthal GE. Increased risk of death in patients with do-not-resuscitate orders. Med Care 1999;37:727–37
42. Vanitallie TB. Frailty in the elderly: contributions of sarcopenia and visceral protein depletion. Metabolism 2003;52:22–6
43. Roubenoff R. Sarcopenic obesity: does muscle loss cause fat gain? Ann NY Acad Sci 2000;904:553–7
44. Morley JE. Anorexia, body composition, and ageing. Curr Opin Clin Nutr Metab Care 2001;4:9–13

Supplemental Digital Content

Back to Top | Article Outline
© 2011 International Anesthesia Research Society