The Journal of Arthroplasty xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
The Journal of Arthroplasty journal homepage: www.arthroplastyjournal.org
Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery Mark J. Gage, MD a, 1, Ran Schwarzkopf, MD, MSc b, 1, Michael Abrouk, BSc b, James D. Slover, MD, MSc a a b
Department of Orthopaedic Surgery, NYU Hospital for Joint Diseases, New York, New York Department Of Orthopaedic Surgery, University of California Irvine, Orange, California
a r t i c l e
i n f o
Article history: Received 14 January 2014 Accepted 6 April 2014 Available online xxxx Keywords: metabolic syndrome total joint arthroplasty complications obesity diabetes mellitus
a b s t r a c t This study investigated the impact of metabolic syndrome (MetS) on perioperative and postoperative complication rates: the results of a cohort of 168 total hip and knee arthroplasties, 63 of normal weight, 105 with obesity without risk factors for metabolic syndrome and 39 with obesity and other factors that classify them with metabolic syndrome. Patients with metabolic syndrome were more likely to have complications than those without metabolic syndrome (P = 0.0156). Perioperative and postoperative complication rates for the MetS and control groups were 35.9% and 16.3%, respectively. Elevated BMI was the element of MetS that had the largest impact on post-surgical complication rates, and this was statistically significant (P = 0.0028). The presence of MetS in patients undergoing total joint arthroplasty has a significant impact on surgical complication rates. This cannot be attributed to the BMI component alone, and may help guide efforts of patient optimization prior to total joint arthroplasty. © 2014 Elsevier Inc. All rights reserved.
Metabolic syndrome (MetS) is composed of a constellation of medical conditions arising from insulin resistance accompanying abnormal adipose deposition and function. It is defined as having a body mass index (BMI) ≥ 30 kg/m 2 as well as two of the following: hyperlipidemia, hypertriglyceridemia, hypertension, or diabetes. Risk factors for development of MetS have included aging, sedentary lifestyle, and genetic predisposition [1–3]. MetS puts one at elevated risk for cardiovascular complications related to coronary artery disease [1], as well as thromboembolic events by elevating the thrombogenicity of circulating blood [4]. The incidence of this syndrome is increasing at a dramatic rate, posing a major public health challenge [5]. Nearly 50 million Americans meet the criteria for MetS [6]. In previous surgical studies of comorbidity trends in patients undergoing total knee arthroplasty (TKA), there was a marked increase in patients meeting the MetS criteria [7]. With the increased need for total joint arthroplasty, along with the increasing prevalence of MetS, it is important to assess the effects this syndrome could have on postoperative outcomes [7–9]. The purpose of this study was to determine the affect metabolic syndrome may have on perioperative complication rates, surgical
The Conflict of Interest statement associated with this article can be found at http:// dx.doi.org/10.1016/j.arth.2014.04.009. Reprint requests: Ran Schwarzkopf, MD, MSc, 101 The City Drive South, Orange, CA 92868. 1 Both first authors contributed equally to the manuscript.
procedure time, length of hospital stay, and hospital readmission after total joint arthroplasty.
Materials and Methods Study Methods Patients were retrospectively identified as undergoing total hip or knee arthroplasty at a single academic institution between the periods of 2000 and 2007. Patients were selected to meet International Diabetes Foundation criteria for metabolic syndrome including BMI N30, and three of the following four conditions: elevated triglycerides, reduced HDL, hypertension, or diabetes. These identified patients were then compared with two other groups: those with a BMI N 30 without meeting the criteria for metabolic syndrome and a control group with a normal BMI and without any risk factors for metabolic syndrome during the same time period. Outcomes and complications during the hospital stay and for up to 1 year postoperatively were determined for the three patient groups. Postoperative complications recorded included deep vein thrombosis, pulmonary embolism, unexpected return to the operating room, decompensation requiring intensive care unit transfer, urinary tract infection, pneumonia, periprosthetic fracture, myocardial infarction, surgical site infection, revision for any reason, and dislocation. Operative data analyzed included tourniquet time, surgical time, and blood loss. Information regarding length of hospital stay, rehabilitation location, readmission rates as well as demographic
http://dx.doi.org/10.1016/j.arth.2014.04.009 0883-5403/© 2014 Elsevier Inc. All rights reserved.
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
2
M.J. Gage et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx
and patient information were collected for both the metabolic syndrome and control groups. Demographic variables such as age, gender and BMI were analyzed. The study was approved by the institutional review board.
Statistical Methods The study comprises three cohort groups to be compared. These groups include a baseline cohort that have no risk factors for MetS (63 patients), a cohort of the obese (BMI N 30) that do not meet criteria for MetS (105 patients), and a cohort among the obese that meet the criteria for MetS (39 patients). Patients under the age of 18 were excluded. For categorical variables, the percentage and sample size are provided. A chi-square test was used to compare categorical demographics between the two groups. Summary statistics for demographics are displayed in a tabular format along with the corresponding P-values. The proportion of patients who experience postoperative knee and/or hip surgical complications was compared between the two groups using Pearson's chi-squared test statistic. Surgical time was compared between the two groups using an analysis of covariance (ANCOVA). The ANCOVA is based on a general linear model which includes group membership and gender as a factors, and age as a covariate. Least squares (LS) estimates of the surgical time and their corresponding 95% confidence intervals were derived from the ANCOVA model. The P-value associated with the ANCOVA statistical test is presented. A table of the LS means with one standard error of the mean and sample size was created to provide visual assessment of the group differences. The length of hospital stay was analyzed in a manner analogous to the analysis of the surgical time. The analysis of readmission in terms of the proportion of patients who are readmitted to the hospital is similar to the analysis of the postoperative surgical complication outcome. Surgical adverse events are summarized using descriptive statistics (percentage and sample size). The percentage of surgical adverse events was tabulated by type of adverse event and group membership. Surgical adverse events are summarized using descriptive statistics (percentage and sample size). The percentage of surgical adverse events was tabulated by type of adverse event and group membership (Fig. 1). The impact of individual MetS components diabetes, dyslipidemia, hypertension, and BMI was examined with Pearson chi-square test. Corresponding 95% confidence intervals for complication rates were derived using Clopper–Pearson method.
Results There were 168 total patients assessed in the study. Sixty-three patients were of normal weight and did not have any of the criteria for MetS serving as a control group. The remaining 105 patients were classified as obese, and of the 105 obese patients, 39 of them met the criteria for metabolic syndrome. The patients without MetS were 29% male, and 71% female. The patients with MetS were 13% male, and 87% female. The mean age for patients without MetS was 59.8 years with a range of 18–87 years. The mean age for patients with MetS was 60.6 years with a range of 44–77 years. The mean BMI for patients without MetS was 37.3. The mean BMI for patients with MetS was 52.1 (Table 1). There were 14 (out of 39) and 21 (out of 129) patients in the MetS and control groups, respectively, that experienced surgical complication (in-hospital and/or within 1 year post-surgery). The surgical complication rates for the MetS and control groups were 35.9% (95% CI: 21.20%, 52.82%), and 16.3% (95% CI: 10.37%, 23.80%), respectively (P = 0.0156) (95% CI: − 37.64%, − 1.60%). Surgical in-hospital complication rates for the MetS and control groups were 20.51% and 7.75%, respectively, and this difference was statistically significant (P = 0.0497) (CI: 95%: − 27.91%, 2.39%) (Table 2). There was no significant difference in surgical time or length of stay between MetS and control groups. Subgroup analysis was performed comparing the following, BMI b 30 without MetS, BMI N 30 without MetS and BMI N 30 with MetS focusing on in-hospital complication rates. Regression analysis demonstrated complication rates of 1.6% for BMI b 30, 9.3% for BMI N 30 without MetS, and 15.4% for BMI N 30 with MetS. While these subgroups demonstrate a trend, the only statistically significant difference in complication rates occurred between the BMI b 30 group and the BMI N 30 with MetS group. The difference in complication rates between BMI b30 and BMI N 30 without MetS as well as the rates between BMI N 30 with and without MetS was not statistically significant (Table 3). BMI was found to have a significant increase in surgical time (P = 0.0102) based on the ANCOVA model, which included age, sex and BMI. The effect of diabetes, dyslipidemia and hypertension as individual risk factors, each increased surgical time, but none were statistically significant (diabetes P = 0.8702, dyslipidemia P = 0.4012, hypertension P = 0.8066) (Table 4). Elevated BMI was a significant risk factor for increasing length of stay (P = 0.0133) based on the ANCOVA model. However, similar to that seen in surgical time, the effect of diabetes status, dyslipidemia and
Table 1 Demographics of Our Patient Cohort Divided by Presence of BMI and MetS. Age (years) Group
n
Mean
BMI b 30 BMI ≥ 30, no MetS BMI ≥ 30 + MetS
63 66 39
62.2 57.4 60.6
BMI b 30 BMI ≥ 30, no MetS BMI ≥ 30 + MetS
63 66 39
43.0% 15.0% 13.0%
68.0 69.0 61.0 Gender
Male
Fig. 1. Metabolic syndrome components vs. total complication rates.
BMI ≥ 30 BMI ≥ 30, no MetS BMI ≥ 30 + MetS
63 66 39
Median
Std Dev
Min
Max
16.2 11.2 8.8
18.0 23.0 44.0
87.0 79.0 77.0
Female 67.0% 75.0% 77.0% BMI (kg/m2)
Mean
Std Dev
Min
Max
22.9 50.9 52.1
1.8 6.3 7.9
14.5 45.0 45.0
25.0 72.5 78.1
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
M.J. Gage et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx Table 2 Comparison of MetS and Each Risk Factor and Incidence of Complications. Risk Factor
All Complications
MetS No MetS P-value BMI No BMI P-value HT No HT P-value Dyslipidemia No dyslipidemia P-value Diabetes No diabetes P-value BMI + HT NO (BMI + HT) P-value BMI + Dyslipidemia No (BMI + Dyslipidemia) P-value BMI + Diabetes No (BMI + Diabetes) P-value Diabetes + HT No (Diabetes + HT) P-value α
35.90% 16.30% 0.0156α 28.60% 7.90% 0.0028 30.77% 19.23% 0.3768 31.80% 26.80% 0.8449 32.10% 18.60% 0.1740 30.76% 11.23% 0.0033 31.80% 18.60% 0.2508 33.30% 18.40% 0.1370 36.00% 18.30% 0.1740
In-hospital Complications 20.51% 7.75% 0.0497 16.20% 1.60% 0.0068 15.40% 16.70% 0.8230 18.30% 9.00% 0.4766 14.30% 10.00% 0.7379 16.70% 5.60% 0.0396 9.10% 11.00% 1.000 14.80% 9.90% 0.6801 16.00% 9.90% 0.5732
Bold = Statistical significance.
hypertension each demonstrated an increase in length of stay, but none were statistically significant (diabetes P = 0.5607, dyslipidemia P = 0.4577, hypertension P = 0.7993) (Table 4).
Discussion In 2000, approximately 47 million US residents had MetS with the prevalence continuing to rise [10]. Given the increasing number of patients undergoing joint arthroplasty each year, identifying the risk factors that may increase postoperative complication rates is important. In 3,830,420 patients undergoing TKA surgery from 1990 and 2004, the prevalence of obesity nearly doubled from 4% to 7.7%, diabetes increased from 9.9% to 14.7% and hypertension rose from 35% to 53.4% respectively [11]. Diabetes and obesity have each been noted to increase complication rates after joint arthroplasty [12–14]. Other studies have previously reported an increased prevalence of the comorbidities of MetS in patients undergoing TJA [7]. In addition, recent literature has begun to link MetS with elevated complication rates after arthroplasty [7,15], but it remains unclear if this is the result of the confounding co-morbidities associated with the syndrome or if this disease represents a separate, more concerning risk factor. A large part of the manifestations seen in metabolic syndrome stem from insulin resistance, which increases the risk of obesity and endothelial dysfunction [4]. This places patients at
Table 3 Subgroup Analysis Was Performed Comparing the Following, BMI b 30 Without MetS, BMI N 30 Without MetS and BMI N 30 With MetS Focusing on In-Hospital Complication Rates. Groups
BMI b 30
Rate 95% CI P-value
1.6% (1/63) (0.04%, 8.5%) 0.4350
BMI ≥ 30 and MetS = 0 9.3% (12/129) (4.9%, 15.7%) 0.0907
BMI ≥ 30 and MetS = 1 15.4% (6/39) (5.9%, 30.5%) 0.0229
3
Table 4 The Effect of MetS, Diabetes Status, Dyslipidemia, BMI, and Hypertension on Length of Stay and Surgical Time. Risk Factor MetS No MetS P-value BMI No BMI P-value HT No HT P-value Dyslipidemia No dyslipidemia P-value Diabetes No diabetes P-value
Length of Stay, Mean (SE) 5.3 (0.44) 4.6 (0.24) 0.2438 5.1 (0.32) 4.3 (0.31) 0.0133 5.9 (0.44) 4.6 (0.67) 0.7993 5.3 (0.66) 4.7 (0.44) 0.4577 5.0 (0.50) 4.7 (0.24) 0.5607
Surgical Time, Mean (SE) 168.4 (10.22) 149.8 (5.70) 0.1369 168.5 (6.96) 136.7 (7.33) 0.0102 164.8 (8.99) 159.9 (13.38) 0.8066 172.5 (13.34) 160.6 (9.05) 0.4012 155.3 (11.62) 153.1 (5.69) 0.8702
Statistical model uses a general linear model with risk and sex as factors and age as covariate. Least-squares means are represented.
increased risk for thrombus-associated complications, which have been demonstrated in this study. This study investigates the affects of MetS on patients undergoing TJA surgery. MetS produced a higher rate of short-term complications. The impact of MetS on all surgical complication rates (in-hospital and/or within 1 year post-surgery) was significant, confirming the presence of MetS will have a negative impact on long-term outcomes as well. Given the requirement of obesity in the definition of MetS a subsequent subgroup analysis was performed to determine if BMI alone could be contributing to this elevated complication rate seen with our MetS cohort. When comparing patients with BMI b 30 with patients with BMI N 30 with and without MetS, only the patients with elevated BMI and MetS showed a statistically significant increase in complication rates, suggesting the other co-morbidities that make up the syndrome other than obesity do exert some increased risk for complications when found in obese patients. These results identify metabolic syndrome as a unique risk factor, separate from obesity that places arthroplasty patients at higher risk for postoperative complications. Our study is limited by a number of factors. The first limitation is the retrospective data set. The clinical information available within the data set is limited, and our statistical approach and methods by definition were limited to the resources of this database. Another limitation is that the definition of MetS is constantly evolving, and has grown to include new and different diagnostic criteria [1]. Our study has limited its definition of MetS to the current official definition according the International Diabetes Federation, which may or may not be different in the years to come and in concordance with the definition used in other studies [7,15–17]. The retrospective nature of our study limited the information gathered for each patient. We were unable to account for how well controlled each component of MetS was throughout the perioperative period, which could alter the complication rate [15]. A prospective study with a larger cohort would allow for control of these factors and to further stratify at-risk MetS patients. A future larger-powered study would allow for further analysis among the various components within metabolic syndrome (ie. dyslipidemia, diabetes, etc.) and further characterize how each component may be contributing to complication rates. The information presented in this study demonstrates that MetS represents a concerning risk factor that has a significant impact on the outcomes of patients undergoing total joint arthroplasty. This cannot be attributed to the BMI component alone, and may help guide efforts of patient optimization prior to total joint arthroplasty. Screening for this condition among the obese surgical candidates is advised to better assess preoperative risk.
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
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M.J. Gage et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx
This study can serve as valuable information in the preoperative counseling of metabolic syndrome patients and should prompt surgeons to proceed with caution when indicating these patients for arthroplasty.
References 1. Johnson LW, Weinstock RS. The metabolic syndrome: concepts and controversy. Mayo Clin Proc 2006;81(12):1615. 2. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15(7):539. 3. Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106(25):3143. 4. Alessi MC, Juhan-Vague I. Metabolic syndrome, haemostasis and thrombosis. Thromb Haemost 2008;99(6):995. 5. Ervin RB. Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003–2006. Natl Health Stat Report 2009(13):1. 6. Eckel RH, Daniels SR, Jacobs AK, et al. America's children: a critical time for prevention. Circulation 2005;111(15):1866. 7. Gonzalez Della Valle A, Chiu YL, Ma Y, et al. The metabolic syndrome in patients undergoing knee and hip arthroplasty: trends and in-hospital outcomes in the United States. J Arthroplasty 2012;27(10):1743 [e1741].
8. Memtsoudis SG, Besculides MC, Reid S, et al. Trends in bilateral total knee arthroplasties: 153,259 discharges between 1990 and 2004. Clin Orthop Relat Res 2009;467(6):1568. 9. Iorio R, Robb WJ, Healy WL, et al. Orthopaedic surgeon workforce and volume assessment for total hip and knee replacement in the United States: preparing for an epidemic. J Bone Joint Surg Am 2008;90(7):1598. 10. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA 2002;287(3):356. 11. Memtsoudis SG, Della Valle AG, Besculides MC, et al. Risk factors for perioperative mortality after lower extremity arthroplasty: a population-based study of 6,901,324 patient discharges. J Arthroplasty 2010;25(1):19. 12. Marchant Jr MH, Viens NA, Cook C, et al. The impact of glycemic control and diabetes mellitus on perioperative outcomes after total joint arthroplasty. J Bone Joint Surg Am 2009;91(7):1621. 13. Changulani M, Kalairajah Y, Peel T, et al. The relationship between obesity and the age at which hip and knee replacement is undertaken. J Bone Joint Surg (Br) 2008;90(3):360. 14. Schwarzkopf R, Thompson SL, Adwar SJ, et al. Postoperative complication rates in the “super-obese” hip and knee arthroplasty population. J Arthroplasty 2012;27(3):397. 15. Zmistowski B, Dizdarevic I, Jacovides CL, et al. Patients with uncontrolled components of metabolic syndrome have increased risk of complications following total joint arthroplasty. J Arthroplasty 2013;28(6):904. 16. Liu SS, Della Valle AG, Besculides MC, et al. Trends in mortality, complications, and demographics for primary hip arthroplasty in the United States. Int Orthop 2009;33(3):643. 17. Gandhi R, Razak F, Davey JR, et al. Metabolic syndrome and the functional outcomes of hip and knee arthroplasty. J Rheumatol 2010;37(9):1917.
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
Contents lists available at ScienceDirect
The Journal of Arthroplasty journal homepage: www.arthroplastyjournal.org
Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery Mark J. Gage, MD a, 1, Ran Schwarzkopf, MD, MSc b, 1, Michael Abrouk, BSc b, James D. Slover, MD, MSc a a b
Department of Orthopaedic Surgery, NYU Hospital for Joint Diseases, New York, New York Department Of Orthopaedic Surgery, University of California Irvine, Orange, California
a r t i c l e
i n f o
Article history: Received 14 January 2014 Accepted 6 April 2014 Available online xxxx Keywords: metabolic syndrome total joint arthroplasty complications obesity diabetes mellitus
a b s t r a c t This study investigated the impact of metabolic syndrome (MetS) on perioperative and postoperative complication rates: the results of a cohort of 168 total hip and knee arthroplasties, 63 of normal weight, 105 with obesity without risk factors for metabolic syndrome and 39 with obesity and other factors that classify them with metabolic syndrome. Patients with metabolic syndrome were more likely to have complications than those without metabolic syndrome (P = 0.0156). Perioperative and postoperative complication rates for the MetS and control groups were 35.9% and 16.3%, respectively. Elevated BMI was the element of MetS that had the largest impact on post-surgical complication rates, and this was statistically significant (P = 0.0028). The presence of MetS in patients undergoing total joint arthroplasty has a significant impact on surgical complication rates. This cannot be attributed to the BMI component alone, and may help guide efforts of patient optimization prior to total joint arthroplasty. © 2014 Elsevier Inc. All rights reserved.
Metabolic syndrome (MetS) is composed of a constellation of medical conditions arising from insulin resistance accompanying abnormal adipose deposition and function. It is defined as having a body mass index (BMI) ≥ 30 kg/m 2 as well as two of the following: hyperlipidemia, hypertriglyceridemia, hypertension, or diabetes. Risk factors for development of MetS have included aging, sedentary lifestyle, and genetic predisposition [1–3]. MetS puts one at elevated risk for cardiovascular complications related to coronary artery disease [1], as well as thromboembolic events by elevating the thrombogenicity of circulating blood [4]. The incidence of this syndrome is increasing at a dramatic rate, posing a major public health challenge [5]. Nearly 50 million Americans meet the criteria for MetS [6]. In previous surgical studies of comorbidity trends in patients undergoing total knee arthroplasty (TKA), there was a marked increase in patients meeting the MetS criteria [7]. With the increased need for total joint arthroplasty, along with the increasing prevalence of MetS, it is important to assess the effects this syndrome could have on postoperative outcomes [7–9]. The purpose of this study was to determine the affect metabolic syndrome may have on perioperative complication rates, surgical
The Conflict of Interest statement associated with this article can be found at http:// dx.doi.org/10.1016/j.arth.2014.04.009. Reprint requests: Ran Schwarzkopf, MD, MSc, 101 The City Drive South, Orange, CA 92868. 1 Both first authors contributed equally to the manuscript.
procedure time, length of hospital stay, and hospital readmission after total joint arthroplasty.
Materials and Methods Study Methods Patients were retrospectively identified as undergoing total hip or knee arthroplasty at a single academic institution between the periods of 2000 and 2007. Patients were selected to meet International Diabetes Foundation criteria for metabolic syndrome including BMI N30, and three of the following four conditions: elevated triglycerides, reduced HDL, hypertension, or diabetes. These identified patients were then compared with two other groups: those with a BMI N 30 without meeting the criteria for metabolic syndrome and a control group with a normal BMI and without any risk factors for metabolic syndrome during the same time period. Outcomes and complications during the hospital stay and for up to 1 year postoperatively were determined for the three patient groups. Postoperative complications recorded included deep vein thrombosis, pulmonary embolism, unexpected return to the operating room, decompensation requiring intensive care unit transfer, urinary tract infection, pneumonia, periprosthetic fracture, myocardial infarction, surgical site infection, revision for any reason, and dislocation. Operative data analyzed included tourniquet time, surgical time, and blood loss. Information regarding length of hospital stay, rehabilitation location, readmission rates as well as demographic
http://dx.doi.org/10.1016/j.arth.2014.04.009 0883-5403/© 2014 Elsevier Inc. All rights reserved.
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
2
M.J. Gage et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx
and patient information were collected for both the metabolic syndrome and control groups. Demographic variables such as age, gender and BMI were analyzed. The study was approved by the institutional review board.
Statistical Methods The study comprises three cohort groups to be compared. These groups include a baseline cohort that have no risk factors for MetS (63 patients), a cohort of the obese (BMI N 30) that do not meet criteria for MetS (105 patients), and a cohort among the obese that meet the criteria for MetS (39 patients). Patients under the age of 18 were excluded. For categorical variables, the percentage and sample size are provided. A chi-square test was used to compare categorical demographics between the two groups. Summary statistics for demographics are displayed in a tabular format along with the corresponding P-values. The proportion of patients who experience postoperative knee and/or hip surgical complications was compared between the two groups using Pearson's chi-squared test statistic. Surgical time was compared between the two groups using an analysis of covariance (ANCOVA). The ANCOVA is based on a general linear model which includes group membership and gender as a factors, and age as a covariate. Least squares (LS) estimates of the surgical time and their corresponding 95% confidence intervals were derived from the ANCOVA model. The P-value associated with the ANCOVA statistical test is presented. A table of the LS means with one standard error of the mean and sample size was created to provide visual assessment of the group differences. The length of hospital stay was analyzed in a manner analogous to the analysis of the surgical time. The analysis of readmission in terms of the proportion of patients who are readmitted to the hospital is similar to the analysis of the postoperative surgical complication outcome. Surgical adverse events are summarized using descriptive statistics (percentage and sample size). The percentage of surgical adverse events was tabulated by type of adverse event and group membership. Surgical adverse events are summarized using descriptive statistics (percentage and sample size). The percentage of surgical adverse events was tabulated by type of adverse event and group membership (Fig. 1). The impact of individual MetS components diabetes, dyslipidemia, hypertension, and BMI was examined with Pearson chi-square test. Corresponding 95% confidence intervals for complication rates were derived using Clopper–Pearson method.
Results There were 168 total patients assessed in the study. Sixty-three patients were of normal weight and did not have any of the criteria for MetS serving as a control group. The remaining 105 patients were classified as obese, and of the 105 obese patients, 39 of them met the criteria for metabolic syndrome. The patients without MetS were 29% male, and 71% female. The patients with MetS were 13% male, and 87% female. The mean age for patients without MetS was 59.8 years with a range of 18–87 years. The mean age for patients with MetS was 60.6 years with a range of 44–77 years. The mean BMI for patients without MetS was 37.3. The mean BMI for patients with MetS was 52.1 (Table 1). There were 14 (out of 39) and 21 (out of 129) patients in the MetS and control groups, respectively, that experienced surgical complication (in-hospital and/or within 1 year post-surgery). The surgical complication rates for the MetS and control groups were 35.9% (95% CI: 21.20%, 52.82%), and 16.3% (95% CI: 10.37%, 23.80%), respectively (P = 0.0156) (95% CI: − 37.64%, − 1.60%). Surgical in-hospital complication rates for the MetS and control groups were 20.51% and 7.75%, respectively, and this difference was statistically significant (P = 0.0497) (CI: 95%: − 27.91%, 2.39%) (Table 2). There was no significant difference in surgical time or length of stay between MetS and control groups. Subgroup analysis was performed comparing the following, BMI b 30 without MetS, BMI N 30 without MetS and BMI N 30 with MetS focusing on in-hospital complication rates. Regression analysis demonstrated complication rates of 1.6% for BMI b 30, 9.3% for BMI N 30 without MetS, and 15.4% for BMI N 30 with MetS. While these subgroups demonstrate a trend, the only statistically significant difference in complication rates occurred between the BMI b 30 group and the BMI N 30 with MetS group. The difference in complication rates between BMI b30 and BMI N 30 without MetS as well as the rates between BMI N 30 with and without MetS was not statistically significant (Table 3). BMI was found to have a significant increase in surgical time (P = 0.0102) based on the ANCOVA model, which included age, sex and BMI. The effect of diabetes, dyslipidemia and hypertension as individual risk factors, each increased surgical time, but none were statistically significant (diabetes P = 0.8702, dyslipidemia P = 0.4012, hypertension P = 0.8066) (Table 4). Elevated BMI was a significant risk factor for increasing length of stay (P = 0.0133) based on the ANCOVA model. However, similar to that seen in surgical time, the effect of diabetes status, dyslipidemia and
Table 1 Demographics of Our Patient Cohort Divided by Presence of BMI and MetS. Age (years) Group
n
Mean
BMI b 30 BMI ≥ 30, no MetS BMI ≥ 30 + MetS
63 66 39
62.2 57.4 60.6
BMI b 30 BMI ≥ 30, no MetS BMI ≥ 30 + MetS
63 66 39
43.0% 15.0% 13.0%
68.0 69.0 61.0 Gender
Male
Fig. 1. Metabolic syndrome components vs. total complication rates.
BMI ≥ 30 BMI ≥ 30, no MetS BMI ≥ 30 + MetS
63 66 39
Median
Std Dev
Min
Max
16.2 11.2 8.8
18.0 23.0 44.0
87.0 79.0 77.0
Female 67.0% 75.0% 77.0% BMI (kg/m2)
Mean
Std Dev
Min
Max
22.9 50.9 52.1
1.8 6.3 7.9
14.5 45.0 45.0
25.0 72.5 78.1
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
M.J. Gage et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx Table 2 Comparison of MetS and Each Risk Factor and Incidence of Complications. Risk Factor
All Complications
MetS No MetS P-value BMI No BMI P-value HT No HT P-value Dyslipidemia No dyslipidemia P-value Diabetes No diabetes P-value BMI + HT NO (BMI + HT) P-value BMI + Dyslipidemia No (BMI + Dyslipidemia) P-value BMI + Diabetes No (BMI + Diabetes) P-value Diabetes + HT No (Diabetes + HT) P-value α
35.90% 16.30% 0.0156α 28.60% 7.90% 0.0028 30.77% 19.23% 0.3768 31.80% 26.80% 0.8449 32.10% 18.60% 0.1740 30.76% 11.23% 0.0033 31.80% 18.60% 0.2508 33.30% 18.40% 0.1370 36.00% 18.30% 0.1740
In-hospital Complications 20.51% 7.75% 0.0497 16.20% 1.60% 0.0068 15.40% 16.70% 0.8230 18.30% 9.00% 0.4766 14.30% 10.00% 0.7379 16.70% 5.60% 0.0396 9.10% 11.00% 1.000 14.80% 9.90% 0.6801 16.00% 9.90% 0.5732
Bold = Statistical significance.
hypertension each demonstrated an increase in length of stay, but none were statistically significant (diabetes P = 0.5607, dyslipidemia P = 0.4577, hypertension P = 0.7993) (Table 4).
Discussion In 2000, approximately 47 million US residents had MetS with the prevalence continuing to rise [10]. Given the increasing number of patients undergoing joint arthroplasty each year, identifying the risk factors that may increase postoperative complication rates is important. In 3,830,420 patients undergoing TKA surgery from 1990 and 2004, the prevalence of obesity nearly doubled from 4% to 7.7%, diabetes increased from 9.9% to 14.7% and hypertension rose from 35% to 53.4% respectively [11]. Diabetes and obesity have each been noted to increase complication rates after joint arthroplasty [12–14]. Other studies have previously reported an increased prevalence of the comorbidities of MetS in patients undergoing TJA [7]. In addition, recent literature has begun to link MetS with elevated complication rates after arthroplasty [7,15], but it remains unclear if this is the result of the confounding co-morbidities associated with the syndrome or if this disease represents a separate, more concerning risk factor. A large part of the manifestations seen in metabolic syndrome stem from insulin resistance, which increases the risk of obesity and endothelial dysfunction [4]. This places patients at
Table 3 Subgroup Analysis Was Performed Comparing the Following, BMI b 30 Without MetS, BMI N 30 Without MetS and BMI N 30 With MetS Focusing on In-Hospital Complication Rates. Groups
BMI b 30
Rate 95% CI P-value
1.6% (1/63) (0.04%, 8.5%) 0.4350
BMI ≥ 30 and MetS = 0 9.3% (12/129) (4.9%, 15.7%) 0.0907
BMI ≥ 30 and MetS = 1 15.4% (6/39) (5.9%, 30.5%) 0.0229
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Table 4 The Effect of MetS, Diabetes Status, Dyslipidemia, BMI, and Hypertension on Length of Stay and Surgical Time. Risk Factor MetS No MetS P-value BMI No BMI P-value HT No HT P-value Dyslipidemia No dyslipidemia P-value Diabetes No diabetes P-value
Length of Stay, Mean (SE) 5.3 (0.44) 4.6 (0.24) 0.2438 5.1 (0.32) 4.3 (0.31) 0.0133 5.9 (0.44) 4.6 (0.67) 0.7993 5.3 (0.66) 4.7 (0.44) 0.4577 5.0 (0.50) 4.7 (0.24) 0.5607
Surgical Time, Mean (SE) 168.4 (10.22) 149.8 (5.70) 0.1369 168.5 (6.96) 136.7 (7.33) 0.0102 164.8 (8.99) 159.9 (13.38) 0.8066 172.5 (13.34) 160.6 (9.05) 0.4012 155.3 (11.62) 153.1 (5.69) 0.8702
Statistical model uses a general linear model with risk and sex as factors and age as covariate. Least-squares means are represented.
increased risk for thrombus-associated complications, which have been demonstrated in this study. This study investigates the affects of MetS on patients undergoing TJA surgery. MetS produced a higher rate of short-term complications. The impact of MetS on all surgical complication rates (in-hospital and/or within 1 year post-surgery) was significant, confirming the presence of MetS will have a negative impact on long-term outcomes as well. Given the requirement of obesity in the definition of MetS a subsequent subgroup analysis was performed to determine if BMI alone could be contributing to this elevated complication rate seen with our MetS cohort. When comparing patients with BMI b 30 with patients with BMI N 30 with and without MetS, only the patients with elevated BMI and MetS showed a statistically significant increase in complication rates, suggesting the other co-morbidities that make up the syndrome other than obesity do exert some increased risk for complications when found in obese patients. These results identify metabolic syndrome as a unique risk factor, separate from obesity that places arthroplasty patients at higher risk for postoperative complications. Our study is limited by a number of factors. The first limitation is the retrospective data set. The clinical information available within the data set is limited, and our statistical approach and methods by definition were limited to the resources of this database. Another limitation is that the definition of MetS is constantly evolving, and has grown to include new and different diagnostic criteria [1]. Our study has limited its definition of MetS to the current official definition according the International Diabetes Federation, which may or may not be different in the years to come and in concordance with the definition used in other studies [7,15–17]. The retrospective nature of our study limited the information gathered for each patient. We were unable to account for how well controlled each component of MetS was throughout the perioperative period, which could alter the complication rate [15]. A prospective study with a larger cohort would allow for control of these factors and to further stratify at-risk MetS patients. A future larger-powered study would allow for further analysis among the various components within metabolic syndrome (ie. dyslipidemia, diabetes, etc.) and further characterize how each component may be contributing to complication rates. The information presented in this study demonstrates that MetS represents a concerning risk factor that has a significant impact on the outcomes of patients undergoing total joint arthroplasty. This cannot be attributed to the BMI component alone, and may help guide efforts of patient optimization prior to total joint arthroplasty. Screening for this condition among the obese surgical candidates is advised to better assess preoperative risk.
Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
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M.J. Gage et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx
This study can serve as valuable information in the preoperative counseling of metabolic syndrome patients and should prompt surgeons to proceed with caution when indicating these patients for arthroplasty.
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Please cite this article as: Gage MJ, et al, Impact of Metabolic Syndrome on Perioperative Complication Rates After Total Joint Arthroplasty Surgery, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.04.009
