j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 8 ( 2 0 1 5 ) 4 5 0 e4 5 5
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.JournalofSurgicalResearch.com
Association for Academic Surgery
Does obesity affect outcomes of adult burn patients? Juliet J. Ray, MD, Shevonne S. Satahoo, MD, Jonathan P. Meizoso, MD, Casey J. Allen, MD, Laura F. Teisch, BS, Kenneth G. Proctor, PhD, Louis R. Pizano, MD, MBA, FACS, Nicholas Namias, MD, MBA, FACS, and Carl I. Schulman, MD, PhD, MSPH, FACS* Divisions of Trauma and Surgical Critical Care, DeWitt Daughtry Family Department of Surgery, University of Miami Miller School of Medicine, Miami, Florida
article info
abstract
Article history:
Background: Obesity negatively affects outcomes after trauma and surgery; results after
Received 8 December 2014
burns are more limited and controversial. The purpose of this study was to determine the
Received in revised form
effect of obesity on clinical and economic outcomes after thermal injury.
9 March 2015
Methods: The National Inpatient Sample was queried for adults from 2005e2009 with
Accepted 18 March 2015
International Classification of Diseases-9 codes for burn injury. Demographics and clinical
Available online 25 March 2015
outcomes of obese and nonobese cohorts were compared. Univariate and multivariate analysis using logistic regression models were performed. Data are expressed as median
Keywords:
(interquartile range) or mean standard deviation and compared at P < 0.05.
Obesity
Results: In 14,602 patients, 3.3% were obese (body mass index 30 kg/m2). The rate of
Overweight
obesity increased significantly by year (P < 0.001). Univariate analysis revealed significant
BMI
differences between obese and nonobese patients in incidence of wound infection (7.2%
Thermal injury
versus 5.0%), urinary tract infection (7.2% versus 4.6%), deep vein thrombosis in total body
TBSA
surface area (TBSA) 10% (3.1% versus 1.1%), pulmonary embolism in TBSA 10% (2.3%
Outcomes
versus 0.6%), length of stay [6 d (8) versus 5 d (9)], and hospital costs ($10,122.12 [$18,074.72]
DVT
versus $7892.07 [$17,191.96]) (all P < 0.05). Death occurred less frequently in the obese group
PE
(1.9% versus 4%, P ¼ 0.021). Significant predictors of grouped adverse events (urinary tract
Mortality
infection, wound infection, deep vein thrombosis, and pulmonary embolism) on multi-
Morbidity
variate analysis include obesity, TBSA 20%, age, and black race (all P 0.05). Conclusions: Obesity is an independent predictor of adverse events after burn injury; however, obesity is associated with decreased mortality. Our findings highlight the potential clinical and economic impact of the obesity epidemic on burn patients nationwide. ª 2015 Elsevier Inc. All rights reserved.
Portions of this work were presented at the Southern Regional Burn Conference, November 2014 and at the Academic Surgical Congress, February 2015. * Corresponding author. Divisions of Trauma and Surgical Critical Care, DeWitt Daughtry Family Department of Surgery, University of Miami Miller School of Medicine, Ryder Trauma Center, 1800 NW 10th Ave, Suite T 215 (D40), Miami, FL 33136. Tel.: þ1 305 585 1178; fax: þ1 305 326 7065. E-mail address: [email protected] (C.I. Schulman). 0022-4804/$ e see front matter ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jss.2015.03.049
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 8 ( 2 0 1 5 ) 4 5 0 e4 5 5
1.
Introduction
Obesity is a global epidemic that is projected to worsen over the next decade [1]. Affecting over one-third of the U.S. population, this represents a major public health threat with significant clinical and economic implications in medical and surgical populations [2e6]. Physiologic mechanisms, specifically inflammatory and immune mediator regulation, are altered by excess adipose tissue. These altered physiologic mechanisms lead to challenges in managing resuscitation requirements due to the cardiac ramifications of excess weight; respiratory support due to increased ventilation-perfusion mismatch; and thromboprophylaxis due to a potentially amplified prothrombotic state [7]. The impact of obesity in the burn population presents conflicting results [8e11]. Mortality in a cohort of obese patients from the National Burn Repository was 2.6 times higher than that in nonobese patients, and obese patients were 4.1 times more likely to have a length of stay (LOS) of 7 d [12]. A recent study showed extremely obese patients had LOS almost double that of nonobese patients and a mortality of 36.4% [13]. In contrast, by a study in pediatrics reported no difference in mortality between obese and nonobese patients (11% versus 8%) [10]. Ghanem et al. [9] evaluated 95 patients with burns >15% total body surface area (TBSA) and stratified obesity into “moderate,” “severe,” and “morbid” based on the World Health Organization classifications of body mass index (BMI). A BMI of 35, representing severe and morbid obesity, was a “tilt point” for higher than predicted mortality. Another study stratified adult patients by level of obesity and showed improved survival in the mild obesity group [14]. Obesity has also been associated with higher incidence of sepsis in adult, [11] but not pediatric burns [10]. A 20-y review of morbidly obese burn patients found a 43% incidence of fatal pulmonary embolism (PE) [8]. The purpose of this study was to determine the effect of obesity (BMI 30 kg/m2) on clinical and economic outcomes after thermal injury in a large national sample. The main objective was to identify whether obesity is an independent predictor of adverse events.
2.
Methods
2.1.
Data source and study population
This retrospective cohort study was exempt from the institutional review board approval as the data set is publically available and deidentified. The Nationwide Inpatient Sample (NIS), Healthcare Cost and Utilization Projects, and Agency for Healthcare Research and Quality database were chosen as the source population. The NIS is the largest publicly available all-payer inpatient heath care database in the United States, containing more than 7 million hospitalizations yearly [15]. This large representative sample allows for greater external validity and generalizability of results.
451
The NIS was queried for all adult patients (age 18 y) from 2005e2009 with International Classification of Diseases-9 (ICD-9) codes for burn injury (941e946.5, 948e949.5), excluding those with isolated injuries to the internal organs or eyes (n ¼ 33,638). This sample was further selected for those with an “emergency,” “urgent,” or “trauma center” admission yielding a total of 27,166 patients. Cases were excluded if no TBSA burn information was available (n ¼ 11,690) or if burn depth was not indicated (n ¼ 874), resulting in a final sample of 14,602 patients.
2.2.
Definition of variables
NIS variables were used to identify various patient characteristics including age, sex, race, LOS, discharge disposition, hospital costs, and income quartile. Disease severity was coded using the NIS category of All Patient Refined- Diagnosis Related Groups severity subclass. This classification takes into account the interaction between the principal diagnosis, presence of operating room and nonoperating room procedures, and secondary diagnoses in a process consisting of three phases [16]. The scoring system is as follows: 1 ¼ minor loss of function, 2 ¼ moderate loss of function, 3 ¼ major loss of function, and 4 ¼ extreme loss of function. Categories 3 þ 4 were grouped to form the classification of “high disease severity” in our study. Obesity was defined as patients with BMI 30 kg/m2 and identified both by ICD-9 codes for obesity and morbid obesity (278.00, 278.01; n ¼ 392) and by the specific code as an NIS variable (n ¼ 83) for a total of 475 obese patients in our sample. Burn depth was identified by ICD-9 codes, and patients were classified based on highest burn depth type regardless of TBSA of each burn degree.
2.3.
Assignment of comorbidity index
An adapted clinical comorbidity index was used based on methods previously outlined by Deyo et al. [17], which modified the original comorbidity index developed by Charlson et al. [18]. We searched each of the 15 diagnosis groups in the NIS for the 3e5 character ICD-9 codes identified by Deyo et al. along with the corresponding comorbidity measures already coded in the NIS. Each patient was then assigned two scores as follows: a weighted score (Charlson Comorbidity Index) based on the adapted score by Deyo et al. and an unweighted comorbidity index where 1 point was assigned to each of 17 possible comorbidities.
2.4.
Outcomes
Clinical outcomes were identified based on ICD-9 codes and included deep vein thrombosis (DVT), PE, urinary tract infection (UTI), wound infection (WI), and need for mechanical ventilation (Table 1). A composite category designated as grouped adverse events (GAE) was created to account for common morbidities affecting obese patients that we assessed using ICD-9 codes in our data set. The GAE consisted of UTI, WI, DVT, and PE. The NIS variable of death during hospitalization was used to determine mortality.
452
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 8 ( 2 0 1 5 ) 4 5 0 e4 5 5
Table 1 e ICD-9 codes for clinical outcomes.
Table 2 e Study sample by TBSA, degree burn, and race.
Clinical outcome
Demographic
DVT Acute venous embolism and thrombosis of deep vessels of lower extremity Acute venous embolism and thrombosis of other specified veins PE PE and infarction UTI Acute pyelonephritis Acute cystitis Infection and inflammatory reaction due to indwelling urinary catheter Wound infection Posttraumatic wound infection not elsewhere classified Infected postoperative seroma Need for mechanical ventilation Other continuous invasive mechanical ventilation
2.5.
ICD-9 codes
P value
No 453.4, 453.40e453.42
453.82, 453.84e453.86
415.1, 415.11, 415.13, 415.19 590.1, 590.10e590.11 595.0 996.64
958.3
TBSA 0%e9% 10%e19% 20%e29% 30%e39% 40%e100% Degree First Second Third Race White Black Hispanic
Yes
n
%
n
%
9514 2718 919 361 615
67.3 19.2 6.5 2.6 14.4
347 70 32 13 13
73.1 14.7 6.7 2.7 2.7
600 7466 6061
4.2 52.8 42.9
20 260 195
4.2 54.7 41.1
6370 1582 1040
70.8 17.6 11.6
248 61 34
72.3 17.8 9.9
0.214
0.712
0.64
998.51 96.7, 96.70e96.72
Statistical analysis
The two cohorts (obese versus nonobese) were compared in terms of demographics and outcomes. Statistical analyses were performed using SPSS version 21 (IBM Corporation; Armonk, NY). Data are reported as mean standard deviation or median (interquartile range). Significance was assessed at P < 0.05. Continuous variables were compared with Student t-test for parametric data and ManneWhitney U test for nonparametric data. Categorical data were compared with chisquared or Fisher exact test as appropriate. A binary logistic regression was performed with GAE as the dependent variable and age, black race, TBSA 20%, and obesity as covariates. This regression was repeated with the addition of the unweighted comorbidity index as a covariate to control for the disparity of comorbidities between cohorts.
3.
Obese
Results
In 14,602 patients, 3.3% were obese (n ¼ 475). The majority of the population had TBSA burns between 0 and 9% (n ¼ 9861; 67.3% of nonobese patients, 73.1% of obese patients). Seconddegree burns were most prevalent (n ¼ 7726), and most patients were classified as white (n ¼ 6618). There were no significant differences between the obese and nonobese patients in terms of these characteristics (Table 2). The rate of obesity increased significantly over the study period (2005: 1.7%, 2006: 2.0%, 2007: 2.8%, 2008: 4.6%, 2009: 5.2%, P < 0.001). On univariate analysis, significant differences were noted in the incidence of wound infection (7.2% versus 5.0%), UTI (7.2% versus 4.6%), DVT in TBSA burns 10% (3.1% versus 1.1%), PE in TBSA burns 10% (2.3% versus 0.6%), high disease severity (91.8% versus 73.5%), LOS (6 d [8] versus 5
d [9]), hospital costs ($10,122.12 [$18,074.72] versus $7892.07 [$17,191.96]), and discharge to home (57.7% versus 66.6%) (all P < 0.05). Interestingly, inpatient death occurred less frequently in the obese group (1.9% versus 4%, P ¼ 0.021). When excluding patients with small burns (TBSA
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.JournalofSurgicalResearch.com
Association for Academic Surgery
Does obesity affect outcomes of adult burn patients? Juliet J. Ray, MD, Shevonne S. Satahoo, MD, Jonathan P. Meizoso, MD, Casey J. Allen, MD, Laura F. Teisch, BS, Kenneth G. Proctor, PhD, Louis R. Pizano, MD, MBA, FACS, Nicholas Namias, MD, MBA, FACS, and Carl I. Schulman, MD, PhD, MSPH, FACS* Divisions of Trauma and Surgical Critical Care, DeWitt Daughtry Family Department of Surgery, University of Miami Miller School of Medicine, Miami, Florida
article info
abstract
Article history:
Background: Obesity negatively affects outcomes after trauma and surgery; results after
Received 8 December 2014
burns are more limited and controversial. The purpose of this study was to determine the
Received in revised form
effect of obesity on clinical and economic outcomes after thermal injury.
9 March 2015
Methods: The National Inpatient Sample was queried for adults from 2005e2009 with
Accepted 18 March 2015
International Classification of Diseases-9 codes for burn injury. Demographics and clinical
Available online 25 March 2015
outcomes of obese and nonobese cohorts were compared. Univariate and multivariate analysis using logistic regression models were performed. Data are expressed as median
Keywords:
(interquartile range) or mean standard deviation and compared at P < 0.05.
Obesity
Results: In 14,602 patients, 3.3% were obese (body mass index 30 kg/m2). The rate of
Overweight
obesity increased significantly by year (P < 0.001). Univariate analysis revealed significant
BMI
differences between obese and nonobese patients in incidence of wound infection (7.2%
Thermal injury
versus 5.0%), urinary tract infection (7.2% versus 4.6%), deep vein thrombosis in total body
TBSA
surface area (TBSA) 10% (3.1% versus 1.1%), pulmonary embolism in TBSA 10% (2.3%
Outcomes
versus 0.6%), length of stay [6 d (8) versus 5 d (9)], and hospital costs ($10,122.12 [$18,074.72]
DVT
versus $7892.07 [$17,191.96]) (all P < 0.05). Death occurred less frequently in the obese group
PE
(1.9% versus 4%, P ¼ 0.021). Significant predictors of grouped adverse events (urinary tract
Mortality
infection, wound infection, deep vein thrombosis, and pulmonary embolism) on multi-
Morbidity
variate analysis include obesity, TBSA 20%, age, and black race (all P 0.05). Conclusions: Obesity is an independent predictor of adverse events after burn injury; however, obesity is associated with decreased mortality. Our findings highlight the potential clinical and economic impact of the obesity epidemic on burn patients nationwide. ª 2015 Elsevier Inc. All rights reserved.
Portions of this work were presented at the Southern Regional Burn Conference, November 2014 and at the Academic Surgical Congress, February 2015. * Corresponding author. Divisions of Trauma and Surgical Critical Care, DeWitt Daughtry Family Department of Surgery, University of Miami Miller School of Medicine, Ryder Trauma Center, 1800 NW 10th Ave, Suite T 215 (D40), Miami, FL 33136. Tel.: þ1 305 585 1178; fax: þ1 305 326 7065. E-mail address: [email protected] (C.I. Schulman). 0022-4804/$ e see front matter ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jss.2015.03.049
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 8 ( 2 0 1 5 ) 4 5 0 e4 5 5
1.
Introduction
Obesity is a global epidemic that is projected to worsen over the next decade [1]. Affecting over one-third of the U.S. population, this represents a major public health threat with significant clinical and economic implications in medical and surgical populations [2e6]. Physiologic mechanisms, specifically inflammatory and immune mediator regulation, are altered by excess adipose tissue. These altered physiologic mechanisms lead to challenges in managing resuscitation requirements due to the cardiac ramifications of excess weight; respiratory support due to increased ventilation-perfusion mismatch; and thromboprophylaxis due to a potentially amplified prothrombotic state [7]. The impact of obesity in the burn population presents conflicting results [8e11]. Mortality in a cohort of obese patients from the National Burn Repository was 2.6 times higher than that in nonobese patients, and obese patients were 4.1 times more likely to have a length of stay (LOS) of 7 d [12]. A recent study showed extremely obese patients had LOS almost double that of nonobese patients and a mortality of 36.4% [13]. In contrast, by a study in pediatrics reported no difference in mortality between obese and nonobese patients (11% versus 8%) [10]. Ghanem et al. [9] evaluated 95 patients with burns >15% total body surface area (TBSA) and stratified obesity into “moderate,” “severe,” and “morbid” based on the World Health Organization classifications of body mass index (BMI). A BMI of 35, representing severe and morbid obesity, was a “tilt point” for higher than predicted mortality. Another study stratified adult patients by level of obesity and showed improved survival in the mild obesity group [14]. Obesity has also been associated with higher incidence of sepsis in adult, [11] but not pediatric burns [10]. A 20-y review of morbidly obese burn patients found a 43% incidence of fatal pulmonary embolism (PE) [8]. The purpose of this study was to determine the effect of obesity (BMI 30 kg/m2) on clinical and economic outcomes after thermal injury in a large national sample. The main objective was to identify whether obesity is an independent predictor of adverse events.
2.
Methods
2.1.
Data source and study population
This retrospective cohort study was exempt from the institutional review board approval as the data set is publically available and deidentified. The Nationwide Inpatient Sample (NIS), Healthcare Cost and Utilization Projects, and Agency for Healthcare Research and Quality database were chosen as the source population. The NIS is the largest publicly available all-payer inpatient heath care database in the United States, containing more than 7 million hospitalizations yearly [15]. This large representative sample allows for greater external validity and generalizability of results.
451
The NIS was queried for all adult patients (age 18 y) from 2005e2009 with International Classification of Diseases-9 (ICD-9) codes for burn injury (941e946.5, 948e949.5), excluding those with isolated injuries to the internal organs or eyes (n ¼ 33,638). This sample was further selected for those with an “emergency,” “urgent,” or “trauma center” admission yielding a total of 27,166 patients. Cases were excluded if no TBSA burn information was available (n ¼ 11,690) or if burn depth was not indicated (n ¼ 874), resulting in a final sample of 14,602 patients.
2.2.
Definition of variables
NIS variables were used to identify various patient characteristics including age, sex, race, LOS, discharge disposition, hospital costs, and income quartile. Disease severity was coded using the NIS category of All Patient Refined- Diagnosis Related Groups severity subclass. This classification takes into account the interaction between the principal diagnosis, presence of operating room and nonoperating room procedures, and secondary diagnoses in a process consisting of three phases [16]. The scoring system is as follows: 1 ¼ minor loss of function, 2 ¼ moderate loss of function, 3 ¼ major loss of function, and 4 ¼ extreme loss of function. Categories 3 þ 4 were grouped to form the classification of “high disease severity” in our study. Obesity was defined as patients with BMI 30 kg/m2 and identified both by ICD-9 codes for obesity and morbid obesity (278.00, 278.01; n ¼ 392) and by the specific code as an NIS variable (n ¼ 83) for a total of 475 obese patients in our sample. Burn depth was identified by ICD-9 codes, and patients were classified based on highest burn depth type regardless of TBSA of each burn degree.
2.3.
Assignment of comorbidity index
An adapted clinical comorbidity index was used based on methods previously outlined by Deyo et al. [17], which modified the original comorbidity index developed by Charlson et al. [18]. We searched each of the 15 diagnosis groups in the NIS for the 3e5 character ICD-9 codes identified by Deyo et al. along with the corresponding comorbidity measures already coded in the NIS. Each patient was then assigned two scores as follows: a weighted score (Charlson Comorbidity Index) based on the adapted score by Deyo et al. and an unweighted comorbidity index where 1 point was assigned to each of 17 possible comorbidities.
2.4.
Outcomes
Clinical outcomes were identified based on ICD-9 codes and included deep vein thrombosis (DVT), PE, urinary tract infection (UTI), wound infection (WI), and need for mechanical ventilation (Table 1). A composite category designated as grouped adverse events (GAE) was created to account for common morbidities affecting obese patients that we assessed using ICD-9 codes in our data set. The GAE consisted of UTI, WI, DVT, and PE. The NIS variable of death during hospitalization was used to determine mortality.
452
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 8 ( 2 0 1 5 ) 4 5 0 e4 5 5
Table 1 e ICD-9 codes for clinical outcomes.
Table 2 e Study sample by TBSA, degree burn, and race.
Clinical outcome
Demographic
DVT Acute venous embolism and thrombosis of deep vessels of lower extremity Acute venous embolism and thrombosis of other specified veins PE PE and infarction UTI Acute pyelonephritis Acute cystitis Infection and inflammatory reaction due to indwelling urinary catheter Wound infection Posttraumatic wound infection not elsewhere classified Infected postoperative seroma Need for mechanical ventilation Other continuous invasive mechanical ventilation
2.5.
ICD-9 codes
P value
No 453.4, 453.40e453.42
453.82, 453.84e453.86
415.1, 415.11, 415.13, 415.19 590.1, 590.10e590.11 595.0 996.64
958.3
TBSA 0%e9% 10%e19% 20%e29% 30%e39% 40%e100% Degree First Second Third Race White Black Hispanic
Yes
n
%
n
%
9514 2718 919 361 615
67.3 19.2 6.5 2.6 14.4
347 70 32 13 13
73.1 14.7 6.7 2.7 2.7
600 7466 6061
4.2 52.8 42.9
20 260 195
4.2 54.7 41.1
6370 1582 1040
70.8 17.6 11.6
248 61 34
72.3 17.8 9.9
0.214
0.712
0.64
998.51 96.7, 96.70e96.72
Statistical analysis
The two cohorts (obese versus nonobese) were compared in terms of demographics and outcomes. Statistical analyses were performed using SPSS version 21 (IBM Corporation; Armonk, NY). Data are reported as mean standard deviation or median (interquartile range). Significance was assessed at P < 0.05. Continuous variables were compared with Student t-test for parametric data and ManneWhitney U test for nonparametric data. Categorical data were compared with chisquared or Fisher exact test as appropriate. A binary logistic regression was performed with GAE as the dependent variable and age, black race, TBSA 20%, and obesity as covariates. This regression was repeated with the addition of the unweighted comorbidity index as a covariate to control for the disparity of comorbidities between cohorts.
3.
Obese
Results
In 14,602 patients, 3.3% were obese (n ¼ 475). The majority of the population had TBSA burns between 0 and 9% (n ¼ 9861; 67.3% of nonobese patients, 73.1% of obese patients). Seconddegree burns were most prevalent (n ¼ 7726), and most patients were classified as white (n ¼ 6618). There were no significant differences between the obese and nonobese patients in terms of these characteristics (Table 2). The rate of obesity increased significantly over the study period (2005: 1.7%, 2006: 2.0%, 2007: 2.8%, 2008: 4.6%, 2009: 5.2%, P < 0.001). On univariate analysis, significant differences were noted in the incidence of wound infection (7.2% versus 5.0%), UTI (7.2% versus 4.6%), DVT in TBSA burns 10% (3.1% versus 1.1%), PE in TBSA burns 10% (2.3% versus 0.6%), high disease severity (91.8% versus 73.5%), LOS (6 d [8] versus 5
d [9]), hospital costs ($10,122.12 [$18,074.72] versus $7892.07 [$17,191.96]), and discharge to home (57.7% versus 66.6%) (all P < 0.05). Interestingly, inpatient death occurred less frequently in the obese group (1.9% versus 4%, P ¼ 0.021). When excluding patients with small burns (TBSA
