Abstract

Background

Rectus abdominis plication increases intra-abdominal pressure and lower-extremity venous stasis, which may increase the incidence of venous thromboembolism (VTE) events.

Objectives

The aim of this study was to investigate the potential association between VTE and rectus abdominis muscle plication during surgery.

Methods

A retrospective review of all patients who underwent abdominal body contouring at the authors’ institution between 2010 and 2020 was completed. Cases were those with postoperative VTEs and were matched to controls (1:4) via potential confounders. Variables collected include demographic data, operative details, comorbidities, and postoperative complications. Statistical analysis was performed with parametric, nonparametric, and multivariable regression modeling.

Results

Overall, 1198 patients were included; 19 (1.59%) experienced a postoperative VTE and were matched to 76 controls. The overall cohort was 92.7% female with an average age of 44 years, an average Charlson Comorbidity Index of 1 point, and an average BMI of 30.1 kg/m2. History of cerebrovascular events (14.5% vs 36.8%, P = 0.026) differed significantly between cohorts, but no significant associations were noted in all other baseline demographics. Additionally, VTE cases were more likely to have received intraoperative blood transfusions (odds ratio = 8.4, P = 0.04). Bivariate analysis demonstrated cases were significantly more likely to experience concurrent complications, including delayed wound healing (0% vs 5.3%, P = 0.044), seroma formation (5.3% vs 21.1%, P = 0.027), and fat necrosis (0% vs 5.3%, P = 0.044). However, these findings were not significant in a multivariable regression model. Plication was not associated with VTE outcomes.

Conclusions

Rectus plication does not increase the risk of VTE. However, the odds of VTE are significantly increased in patients who received intraoperative blood products compared with those who did not.

Level of Evidence: 3

Abdominal contouring procedures, such as cosmetic abdominoplasty and panniculectomy, are routine operations for the removal of excess abdominal fat and skin and to strengthen the abdominal wall musculature.1 About 100,000 abdominoplasties were performed in the United States in 2020—a 56% increase since 2000—making it one of the most commonly performed plastic and reconstructive procedures.2 Unfortunately, abdominoplasties and panniculectomies are associated with higher complication rates than other surgeries, resulting in hematomas, infections, wound-healing problems, and, rarely, venous thromboembolism (VTE) events.3,4 Previous studies have shown that the risk of complications increases in patients who are smokers, have multiple medical comorbidities, and are undergoing multiple concurrent aesthetic procedures.4,5 VTEs, such as deep venous thrombosis (DVT) and pulmonary embolism (PE), are rare but potentially devastating complications of particular concern in this patient population. Although the risk of VTE ranges between 0.2% to 1.5% in abdominal body contouring procedures, the risk is markedly higher than that of other aesthetic procedures and VTEs remain a significant cause of morbidity and mortality.6-11

Considerable effort has been employed in reducing the incidence of VTE. Risk factors, prophylaxis regimens, and procedural recommendations for thromboembolic events have been well characterized in other areas of surgery with guidelines revised by the American College of Chest Physicians.12-14 However, these guidelines have yet to achieve consensus in plastic surgery because they contain minimal evidence from the plastic surgery literature and no plastic surgery procedures are included in the recommendations.15,16 In the arena of abdominal contouring specifically, there are few studies examining preoperative risk factors, and none to date have investigated the association between procedural techniques and VTE outcomes.10,17,18

Rectus abdominis plication, a commonly utilized method to reduce diastasis width and enhance abdominal contour, has been associated with increased intra-abdominal pressure (IAP) which may subsequently increase the risk of VTEs occurring.19 Previous investigations have demonstrated that increased IAP, via either plication or compression garments, may lead to lower-extremity venous stasis that persists for up to 48 hours after surgery.20,21 Momeni et al utilized real-time ultrasound to demonstrate the occurrence of common femoral stasis with tight abdominal wall fascial closures irrespective of intraoperative hydration.22,23 Some surgeons consider these findings potentially worrying as venous stasis is a key component of Virchow’s triad, a proposed mechanism of thrombosis formation.24,25 On the other hand, other surgeons believe this risk to be more of a theoretical one, pointing to the fact that patients with epidural anesthesia or paraplegia (both with vessel dilation and venous stasis) are not at an elevated risk of VTE. Despite these concerns, there is a lack of literature investigating direct associations between rectus abdominis plication and VTE. To our knowledge, only 1 case report has examined thrombosis formation after rectus plication with significant findings that point to increased venous stasis.21 We aim to bridge this gap in knowledge by characterizing the effect of rectus abdominis plication, as well as other risk factors, on VTEs in patients undergoing abdominal contouring procedures.

METHODS

Approval was obtained from the IRB at our institution, Montefiore Medical Center (Bronx, NY), an academic hospital and tertiary referral center, before performing a retrospective review of all patients who underwent cosmetic abdominoplasty or panniculectomy at our institution between January 2010 and March 2020. Patients were identified via Common Procedural Terminology codes (CPT codes 15847, 17999, and 15830) and confirmed with the surgeon’s operative notes. Exclusion criteria include patients under the age of 18 years, emergent surgeries, and those undergoing concurrent major procedures such as resections of intra-abdominal malignancies. Electronic medical records were reviewed by all investigators to ensure inclusion criteria were met and for collection of all patient data.

Demographic data, including age, sex, race/ethnicity, smoking status, BMI, history of prior bariatric procedures, and medical comorbidities, were collected. The Charlson Comorbidity Index (CCI) and Caprini Risk Score were calculated from comorbidities existing at the time of surgery. The CCI is a previously validated score that is associated with postoperative complications, mortality, and readmission in patients undergoing surgery in a variety of disciplines.26-29 The CCI predicts the 1-year mortality risk for patients with specific comorbid conditions. A total of 19 conditions are included in the CCI, including: age, cardiac risk, neurologic disease, respiratory disease, liver disease and renal disease, among others. Similarly, the Caprini Risk Score is a previously validated and widely used measure of VTE risk that takes into account both current comorbidities and previous health histories.30,31 Operative details such as plication of the rectus abdominus muscles during the operation, concurrent procedures (liposuction, mastopexy, breast reduction mammoplasty, brachioplasty, and hernia repair), use of a sequential compression device (SCD), American Society of Anesthesiologists (ASA) score, operative time, and type/duration of chemophylaxis were noted.

We reviewed all consecutive patients and identified those who had experienced a VTE event such as a DVT or a PE within 90 days of their operation. Event status was confirmed via duplex Doppler ultrasound, ventilation-perfusion scans, computed tomography pulmonary angiography scans, pulmonary angiograms, and/or MRI scans. Cases were matched to controls who did not experience a VTE in a 1:4 fashion while controlling for potential confounders.26,28,32 A 1:4 matching ratio was utilized to maximize statistical power in this rare disease scenario. Case-controls were matched on variables that differed significantly between case-control patients, including age, BMI, and preoperative comorbidities via the CCI.26,28,32 Due to the limitations of sample size, case-controls were matched on potentially confounding characteristics instead of utilizing a propensity-scored model. Other outcomes of interest include operative characteristics, length of stay, unplanned 30-day readmission/reoperation, and 30-day postoperative complications. Specific complications of interest include hematoma formation, intraoperative transfusions, surgical site infection, hernia/bulge, delayed wound healing, wound dehiscence, seroma, umbilical necrosis, and fat necrosis.

Statistical analysis was performed with Stata v. 17.0 (StataCorp, College Station, TX). Univariate analysis and descriptive statistics were utilized to characterize the study population and to compare baseline cohort characteristics. Findings are presented as mean values with standard deviations (SDs) for variables meeting parametric assumptions, and as median values with interquartile ranges (IQRs) for variables that were nonparametric. Matching was completed with the “calipmatch” package with age, BMI, and CCI caliper widths set as 10, 3, and 3, respectively.33 Bivariate analysis was performed with t-tests and chi-square analysis with Fisher’s exact test to identify associations between the case variable and other outcomes of interest, such as intraoperative transfusions, concurrent procedures, complications rates, length of stay, and duration of chemophylaxis. An unconditional logistic regression model was used to determine the odds of plication and other variables significant through bivariate analysis after adjusting for confounding variables such as varying baseline comorbidities via the CCI and varying intraoperative factors such as SCD usage. Conditional logistic regression modeling was employed to adjust for the impact of matching in the cohort with an adjusted odds ratio (OR) subsequently calculated for the case variable and other variables significant through bivariate analysis after adjusting for confounding variables such as varying baseline comorbidities via the CCI and varying intraoperative factors such as SCD usage. The CCI was included in the regression model instead of the Caprini Risk Score due to the wider breadth of medical conditions covered by it and because of the issue of multicollinearity between the indexes due to overlap of comorbid conditions encapsulated in each index measure. Conditional logistic regression is an extension of unconditional logistic regression modeling that allows one to take into account stratification and matching. In our model, utilizing a conditional logistic regression allowed for consideration of how the included participants were dispersed along the matching variables (age, BMI, CCI score) because any matching distorts how participants are naturally distributed among these variables in the unmatched cohort. We decided to include both the conditional and unconditional model in the results as debate remains regarding which is the superior model for matched data.34 Statistical significance was set a priori at P < 0.05.

RESULTS

A total of 1265 patients underwent either abdominoplasty or panniculectomy in the 10-year period. After excluding those who did not meet inclusion criteria, 1198 patients were enrolled in our study: 1107 women (92.7%) and 87 men (7.3%) with an overall mean [SD] age of 44 [11.2] years (range, 18-75 years). The median CCI for all patents was 1 (IQR = 0-3) and the median Caprini Risk Score was 4 (IQR = 4-6). The baseline characteristics and demographic data of all subjects enrolled in the study are presented in Table 1.

Table 1.

Characteristics of the Overall Study Population (N = 1198)

CharacteristicAll patients
Mean [SD]/Median (IQR)
Age (years)44 [11.2]
CCI1 (0-3)
Caprini Risk Score4 (4-6)
BMI (kg/m2)30.1 [5.2]
Operative time (minutes)285.2 [138.1]
n (%)
Plication
 No645 (54.1)
 Yes547 (45.9)
Sex
 Male87 (7.3)
 Female1107 (92.7)
Race
 Caucasian79 (6.6)
 Black203 (17)
 Asian5 (0.4)
 Hispanic424 (35.5)
 Other321 (26.9)
 Declined163 (13.6)
ASA score
 1138 (11.6)
 2892 (74.9)
 3157 (13.2)
 44 (0.3)
CharacteristicAll patients
Mean [SD]/Median (IQR)
Age (years)44 [11.2]
CCI1 (0-3)
Caprini Risk Score4 (4-6)
BMI (kg/m2)30.1 [5.2]
Operative time (minutes)285.2 [138.1]
n (%)
Plication
 No645 (54.1)
 Yes547 (45.9)
Sex
 Male87 (7.3)
 Female1107 (92.7)
Race
 Caucasian79 (6.6)
 Black203 (17)
 Asian5 (0.4)
 Hispanic424 (35.5)
 Other321 (26.9)
 Declined163 (13.6)
ASA score
 1138 (11.6)
 2892 (74.9)
 3157 (13.2)
 44 (0.3)

ASA, American Society of Anesthesiologists; CCI, Charlson Comorbidity Index; IQR, interquartile range; SD, standard deviation.

Table 1.

Characteristics of the Overall Study Population (N = 1198)

CharacteristicAll patients
Mean [SD]/Median (IQR)
Age (years)44 [11.2]
CCI1 (0-3)
Caprini Risk Score4 (4-6)
BMI (kg/m2)30.1 [5.2]
Operative time (minutes)285.2 [138.1]
n (%)
Plication
 No645 (54.1)
 Yes547 (45.9)
Sex
 Male87 (7.3)
 Female1107 (92.7)
Race
 Caucasian79 (6.6)
 Black203 (17)
 Asian5 (0.4)
 Hispanic424 (35.5)
 Other321 (26.9)
 Declined163 (13.6)
ASA score
 1138 (11.6)
 2892 (74.9)
 3157 (13.2)
 44 (0.3)
CharacteristicAll patients
Mean [SD]/Median (IQR)
Age (years)44 [11.2]
CCI1 (0-3)
Caprini Risk Score4 (4-6)
BMI (kg/m2)30.1 [5.2]
Operative time (minutes)285.2 [138.1]
n (%)
Plication
 No645 (54.1)
 Yes547 (45.9)
Sex
 Male87 (7.3)
 Female1107 (92.7)
Race
 Caucasian79 (6.6)
 Black203 (17)
 Asian5 (0.4)
 Hispanic424 (35.5)
 Other321 (26.9)
 Declined163 (13.6)
ASA score
 1138 (11.6)
 2892 (74.9)
 3157 (13.2)
 44 (0.3)

ASA, American Society of Anesthesiologists; CCI, Charlson Comorbidity Index; IQR, interquartile range; SD, standard deviation.

Seventy-six patients without VTEs were matched to 19 case patients. The matched cohorts were similar in their demographic characteristics with no statistically significant difference in their age (47.9 vs 47.4 years, P = 0.864), BMI (31.6 vs 32.1 kg/m2, P = 0.631), CCI (1 vs 1, P = 0.416), Caprini Risk Scores (4 vs 6, P = 0.135), duration of chemophylaxis (0 vs 0, P = 132), or operative time (280.8 vs 266.7 minutes, P = 0.684). There were no significant sex (P = 0.196) or race/ethnic (P = 0.131) differences between cohorts. Further analysis of patient demographics and previous medical history revealed no significant associations with VTE occurrence and previous history of smoking (2.6% vs 5.3%, P = 0.557), diabetes mellitus (22.4% vs 26.3%, P = 0.715), hypertension (36.8% vs 47.4%, P = 0.400), chronic obstruction pulmonary disease (2% vs 0%, P = 0.638), coronary artery disease (3.9% vs 5.3%, P = 0.597), chronic kidney disease (9.2% vs 5.3%, P = 0.597), steroid use (2.6% vs 0%, P = 0.638), immunosuppressant use (1.3% vs 0%, P = 0.800), radiation therapy (2.6% vs 5.3%, P = 0.492), chemotherapy (3.9% vs 10.5%, P = 0.260), and previous bariatric surgery (78.9% vs 68.2%, P = 0.151). Neither group included patients with concurrent hernia repair intraoperatively. Interestingly, a significant association was seen between VTE occurrence and a previous history of cerebrovascular accidents (14.5% vs 36.8%, P = 0.026) (Table 2).

Table 2.

Comparative Descriptive Demographics of Matched Cohorts

CharacteristicNo VTE (n = 76)VTE (n = 19)
Mean [SD]/median (IQR)Mean [SD]/median (IQR)P
Age (years)47.9 [11.3]47.4 [13]0.864
BMI (kg/m2)31.6 [4.8]32.1 [4.8]0.631
CCI1 (0-2)1 (0-3)0. 416
Caprini Risk Score4 (4-6)6 (4-9)0.135
Operative time (minutes)280.8 [127.8]266.7 [103.9]0.684
Duration of chemoprophylaxis (days)0 (0-1)0 (0-7)0.132
n (%)n (%)P
Plication0.990
 No44 (57.9)11 (57.9)
 Yes32 (42.1)8 (42.1)
Sex0.196
 Male5 (6.6)3 (15.8)
 Female71 (93.4)16 (84.2)
Race0.131
 Caucasian6 (7.9)4 (21.1)
 Black13 (17.1)5 (26.3)
 Asian1 (1.3)1 (5.3)
 Hispanic26 (34.2)4 (21.1)
 Other17 (22.4)5 (26.3)
 Declined13 (17.1)0 (0)
Smoking0.557
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Diabetes mellitus0.715
 No59 (77.6)14 (73.7)
 Yes17 (22.4)5 (26.3)
Hypertension0.400
 No48 (63.2)10 (52.6)
 Yes28 (36.8)9 (47.4)
COPD0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Coronary artery disease0.597
 No73 (96.1)18 (94.7)
 Yes3 (3.9)1 (5.3)
Cerebrovascular accident0.026
 No65 (85.5)12 (63.2)
 Yes11 (14.5)7 (36.8)
Chronic kidney disease0.497
 No69 (90.8)18 (94.7)
 Yes7 (9.2)1 (5.3)
Steroid use0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Immunosuppressant use0.800
 No75 (98.7)19 (100)
 Yes1 (1.3)0 (0)
Radiation therapy0.492
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Chemotherapy0.260
 No73 (96.1)17 (89.5)
 Yes3 (3.9)2 (10.5)
Previous bariatric surgery0.151
 No16 (21.1)7 (36.8)
 Yes60 (78.9)12 (63.2)
Hernia repair
 No76 (100)19 (100)
 Yes0 (0)0 (0)
SCD use0.035
 No9 (11.8)6 (31.6)
 Yes67 (88.2)13 (68.4)
Location0.179
 Outpatient45 (59.2)8 (42.1)
 Inpatient31 (40.8)11 (57.9)
Concurrent procedure0.512
 No26 (34.2)5 (26.3)
 Yes50 (65.8)14 (73.7)
CharacteristicNo VTE (n = 76)VTE (n = 19)
Mean [SD]/median (IQR)Mean [SD]/median (IQR)P
Age (years)47.9 [11.3]47.4 [13]0.864
BMI (kg/m2)31.6 [4.8]32.1 [4.8]0.631
CCI1 (0-2)1 (0-3)0. 416
Caprini Risk Score4 (4-6)6 (4-9)0.135
Operative time (minutes)280.8 [127.8]266.7 [103.9]0.684
Duration of chemoprophylaxis (days)0 (0-1)0 (0-7)0.132
n (%)n (%)P
Plication0.990
 No44 (57.9)11 (57.9)
 Yes32 (42.1)8 (42.1)
Sex0.196
 Male5 (6.6)3 (15.8)
 Female71 (93.4)16 (84.2)
Race0.131
 Caucasian6 (7.9)4 (21.1)
 Black13 (17.1)5 (26.3)
 Asian1 (1.3)1 (5.3)
 Hispanic26 (34.2)4 (21.1)
 Other17 (22.4)5 (26.3)
 Declined13 (17.1)0 (0)
Smoking0.557
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Diabetes mellitus0.715
 No59 (77.6)14 (73.7)
 Yes17 (22.4)5 (26.3)
Hypertension0.400
 No48 (63.2)10 (52.6)
 Yes28 (36.8)9 (47.4)
COPD0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Coronary artery disease0.597
 No73 (96.1)18 (94.7)
 Yes3 (3.9)1 (5.3)
Cerebrovascular accident0.026
 No65 (85.5)12 (63.2)
 Yes11 (14.5)7 (36.8)
Chronic kidney disease0.497
 No69 (90.8)18 (94.7)
 Yes7 (9.2)1 (5.3)
Steroid use0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Immunosuppressant use0.800
 No75 (98.7)19 (100)
 Yes1 (1.3)0 (0)
Radiation therapy0.492
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Chemotherapy0.260
 No73 (96.1)17 (89.5)
 Yes3 (3.9)2 (10.5)
Previous bariatric surgery0.151
 No16 (21.1)7 (36.8)
 Yes60 (78.9)12 (63.2)
Hernia repair
 No76 (100)19 (100)
 Yes0 (0)0 (0)
SCD use0.035
 No9 (11.8)6 (31.6)
 Yes67 (88.2)13 (68.4)
Location0.179
 Outpatient45 (59.2)8 (42.1)
 Inpatient31 (40.8)11 (57.9)
Concurrent procedure0.512
 No26 (34.2)5 (26.3)
 Yes50 (65.8)14 (73.7)

Calculated values are rounded to 1 decimal point. P values are reported for the comparison of patient demographics. CCI, Charlson Comorbidity Index; COPD, chronic obstructive pulmonary disease; IQR, interquartile range; SCD, sequential compression device; SD, standard deviation; VTE, venous thromboembolism.

Table 2.

Comparative Descriptive Demographics of Matched Cohorts

CharacteristicNo VTE (n = 76)VTE (n = 19)
Mean [SD]/median (IQR)Mean [SD]/median (IQR)P
Age (years)47.9 [11.3]47.4 [13]0.864
BMI (kg/m2)31.6 [4.8]32.1 [4.8]0.631
CCI1 (0-2)1 (0-3)0. 416
Caprini Risk Score4 (4-6)6 (4-9)0.135
Operative time (minutes)280.8 [127.8]266.7 [103.9]0.684
Duration of chemoprophylaxis (days)0 (0-1)0 (0-7)0.132
n (%)n (%)P
Plication0.990
 No44 (57.9)11 (57.9)
 Yes32 (42.1)8 (42.1)
Sex0.196
 Male5 (6.6)3 (15.8)
 Female71 (93.4)16 (84.2)
Race0.131
 Caucasian6 (7.9)4 (21.1)
 Black13 (17.1)5 (26.3)
 Asian1 (1.3)1 (5.3)
 Hispanic26 (34.2)4 (21.1)
 Other17 (22.4)5 (26.3)
 Declined13 (17.1)0 (0)
Smoking0.557
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Diabetes mellitus0.715
 No59 (77.6)14 (73.7)
 Yes17 (22.4)5 (26.3)
Hypertension0.400
 No48 (63.2)10 (52.6)
 Yes28 (36.8)9 (47.4)
COPD0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Coronary artery disease0.597
 No73 (96.1)18 (94.7)
 Yes3 (3.9)1 (5.3)
Cerebrovascular accident0.026
 No65 (85.5)12 (63.2)
 Yes11 (14.5)7 (36.8)
Chronic kidney disease0.497
 No69 (90.8)18 (94.7)
 Yes7 (9.2)1 (5.3)
Steroid use0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Immunosuppressant use0.800
 No75 (98.7)19 (100)
 Yes1 (1.3)0 (0)
Radiation therapy0.492
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Chemotherapy0.260
 No73 (96.1)17 (89.5)
 Yes3 (3.9)2 (10.5)
Previous bariatric surgery0.151
 No16 (21.1)7 (36.8)
 Yes60 (78.9)12 (63.2)
Hernia repair
 No76 (100)19 (100)
 Yes0 (0)0 (0)
SCD use0.035
 No9 (11.8)6 (31.6)
 Yes67 (88.2)13 (68.4)
Location0.179
 Outpatient45 (59.2)8 (42.1)
 Inpatient31 (40.8)11 (57.9)
Concurrent procedure0.512
 No26 (34.2)5 (26.3)
 Yes50 (65.8)14 (73.7)
CharacteristicNo VTE (n = 76)VTE (n = 19)
Mean [SD]/median (IQR)Mean [SD]/median (IQR)P
Age (years)47.9 [11.3]47.4 [13]0.864
BMI (kg/m2)31.6 [4.8]32.1 [4.8]0.631
CCI1 (0-2)1 (0-3)0. 416
Caprini Risk Score4 (4-6)6 (4-9)0.135
Operative time (minutes)280.8 [127.8]266.7 [103.9]0.684
Duration of chemoprophylaxis (days)0 (0-1)0 (0-7)0.132
n (%)n (%)P
Plication0.990
 No44 (57.9)11 (57.9)
 Yes32 (42.1)8 (42.1)
Sex0.196
 Male5 (6.6)3 (15.8)
 Female71 (93.4)16 (84.2)
Race0.131
 Caucasian6 (7.9)4 (21.1)
 Black13 (17.1)5 (26.3)
 Asian1 (1.3)1 (5.3)
 Hispanic26 (34.2)4 (21.1)
 Other17 (22.4)5 (26.3)
 Declined13 (17.1)0 (0)
Smoking0.557
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Diabetes mellitus0.715
 No59 (77.6)14 (73.7)
 Yes17 (22.4)5 (26.3)
Hypertension0.400
 No48 (63.2)10 (52.6)
 Yes28 (36.8)9 (47.4)
COPD0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Coronary artery disease0.597
 No73 (96.1)18 (94.7)
 Yes3 (3.9)1 (5.3)
Cerebrovascular accident0.026
 No65 (85.5)12 (63.2)
 Yes11 (14.5)7 (36.8)
Chronic kidney disease0.497
 No69 (90.8)18 (94.7)
 Yes7 (9.2)1 (5.3)
Steroid use0.638
 No74 (97.4)19 (100)
 Yes2 (2.6)0 (0)
Immunosuppressant use0.800
 No75 (98.7)19 (100)
 Yes1 (1.3)0 (0)
Radiation therapy0.492
 No74 (97.4)18 (94.7)
 Yes2 (2.6)1 (5.3)
Chemotherapy0.260
 No73 (96.1)17 (89.5)
 Yes3 (3.9)2 (10.5)
Previous bariatric surgery0.151
 No16 (21.1)7 (36.8)
 Yes60 (78.9)12 (63.2)
Hernia repair
 No76 (100)19 (100)
 Yes0 (0)0 (0)
SCD use0.035
 No9 (11.8)6 (31.6)
 Yes67 (88.2)13 (68.4)
Location0.179
 Outpatient45 (59.2)8 (42.1)
 Inpatient31 (40.8)11 (57.9)
Concurrent procedure0.512
 No26 (34.2)5 (26.3)
 Yes50 (65.8)14 (73.7)

Calculated values are rounded to 1 decimal point. P values are reported for the comparison of patient demographics. CCI, Charlson Comorbidity Index; COPD, chronic obstructive pulmonary disease; IQR, interquartile range; SCD, sequential compression device; SD, standard deviation; VTE, venous thromboembolism.

Comparison of intraoperative characteristics demonstrated no significant associations between VTE occurrence and intraoperative plication (42.1% vs 42.1%, P = 0.990), location of surgery (40.8% vs 57.9% outpatient, P = 0.179), and presence of concurrent intraoperative procedures (65.8% vs 73.7%, P = 0.512). Importantly, there was a significant association between VTE occurrence and SCD use during surgery (88.2% vs 68.4%, P = 0.035). Postsurgical outcomes between cohorts were analyzed. No significant differences were observed in the majority of complications, including: hematoma formation (6.6% vs 10.5%, P = 0.556), unplanned return to the operating room (5.3% vs 10.5%, P = 0.399), scheduled revision surgery (1.3% vs 0%, P = 0.615), infection (3.9% vs 15.8%, P = 0.058), and wound dehiscence (7.9% vs 10.5%, P = 0.712). Bivariate analysis showed that patients with VTEs had a significantly higher incidence of readmission (6.6% vs 26.3%, P = 0.012), intraoperative blood transfusion (2.6% vs 15.8%, P = 0.022), delayed wound healing (0% vs 5.3%, P = 0.044), seroma formation (5.3% vs 21.1%, P = 0.027), and fat necrosis (0% vs 5.3%, P = 0.044) (Table 3).

Table 3.

Perioperative Surgical Outcomes in Matched Case vs Controls

OutcomeNo VTE (n = 76)VTE (n = 19)
n (%)n (%)P
Rectus plication32 (42.1)8 (42.1)>0.99
Hematoma5 (6.6)2 (10.5)0.556
Unplanned return to operating room4 (5.3)2 (10.5)0.399
Scheduled revision surgery1 (1.3)0 (0)0.615
Readmission5 (6.6)5 (26.3)0.012
Blood transfusion2 (2.6)3 (15.8)0.022
Infection3 (3.9)3 (15.8)0.058
Delayed wound healing0 (0)1 (5.3)0.044
Dehiscence6 (7.9)2 (10.5)0.712
Seroma4 (5.3)4 (21.1)0.027
Fat necrosis0 (0)1 (5.3)0.044
OutcomeNo VTE (n = 76)VTE (n = 19)
n (%)n (%)P
Rectus plication32 (42.1)8 (42.1)>0.99
Hematoma5 (6.6)2 (10.5)0.556
Unplanned return to operating room4 (5.3)2 (10.5)0.399
Scheduled revision surgery1 (1.3)0 (0)0.615
Readmission5 (6.6)5 (26.3)0.012
Blood transfusion2 (2.6)3 (15.8)0.022
Infection3 (3.9)3 (15.8)0.058
Delayed wound healing0 (0)1 (5.3)0.044
Dehiscence6 (7.9)2 (10.5)0.712
Seroma4 (5.3)4 (21.1)0.027
Fat necrosis0 (0)1 (5.3)0.044

Calculated values are rounded to 1 decimal point. P values are reported for the comparison of patient compilations. VTE, venous thromboembolism

Table 3.

Perioperative Surgical Outcomes in Matched Case vs Controls

OutcomeNo VTE (n = 76)VTE (n = 19)
n (%)n (%)P
Rectus plication32 (42.1)8 (42.1)>0.99
Hematoma5 (6.6)2 (10.5)0.556
Unplanned return to operating room4 (5.3)2 (10.5)0.399
Scheduled revision surgery1 (1.3)0 (0)0.615
Readmission5 (6.6)5 (26.3)0.012
Blood transfusion2 (2.6)3 (15.8)0.022
Infection3 (3.9)3 (15.8)0.058
Delayed wound healing0 (0)1 (5.3)0.044
Dehiscence6 (7.9)2 (10.5)0.712
Seroma4 (5.3)4 (21.1)0.027
Fat necrosis0 (0)1 (5.3)0.044
OutcomeNo VTE (n = 76)VTE (n = 19)
n (%)n (%)P
Rectus plication32 (42.1)8 (42.1)>0.99
Hematoma5 (6.6)2 (10.5)0.556
Unplanned return to operating room4 (5.3)2 (10.5)0.399
Scheduled revision surgery1 (1.3)0 (0)0.615
Readmission5 (6.6)5 (26.3)0.012
Blood transfusion2 (2.6)3 (15.8)0.022
Infection3 (3.9)3 (15.8)0.058
Delayed wound healing0 (0)1 (5.3)0.044
Dehiscence6 (7.9)2 (10.5)0.712
Seroma4 (5.3)4 (21.1)0.027
Fat necrosis0 (0)1 (5.3)0.044

Calculated values are rounded to 1 decimal point. P values are reported for the comparison of patient compilations. VTE, venous thromboembolism

Multivariable regression modeling was used to further delineate the associations between VTE occurrence and perioperative complications while adjusting for potential confounders. The unconditional model noted significantly higher odds of readmission (OR = 5.3, 95% CI = 1.2-23.5, P = 0.03), and intraoperative blood transfusion (OR = 8.4, 95% CI = 1.1-62.4, P = 0.04) in VTE-positive patients. However, the increased odds of blood transfusions did not reach a priori statistical significance when analyzed via the conditional regression model (P = 0.061). A significant association between readmission and VTE status was noted in the conditional model as well, with odds of readmission in VTE patients being 15.5 times that of non-VTE patients (95% CI = 1.5-158.9, P = 0.021). No significant differences were noted in either unconditional or conditional analysis between groups regarding hematoma formation, unplanned return to the operating room, infection, wound dehiscence, seroma formation, and fat necrosis. Plication was not significantly associated with VTE status on bivariate analysis or multivariable regression modeling (Table 4).

Table 4.

Comparison of Perioperative Risk Profiles in Matched Case vs Controls

OutcomeUnconditional modelConditional Model
OR95% CIPOR95% CIP
Rectus plication1.70.5-5.60.3991.10.3-3.70.869
Hematoma1.70.2-14.30.61.20.1-19.90.887
Unplanned return to operating room1.80.3-12.40.62.30.2-26.60.508
Readmission5.31.2-23.50.0315.51.5-158.90.021
Blood transfusion8.41.1-62.40.0441.20.8-2024.70.061
Infection10.1-12.311.10.02-42.50.958
Dehiscence1.10.2-8.10.92.80.2-36.80.431
Seroma3.90.8-19.70.14.80.8-29.10.084
Fat necrosis10.1-13.910.90.1-15.50.963
OutcomeUnconditional modelConditional Model
OR95% CIPOR95% CIP
Rectus plication1.70.5-5.60.3991.10.3-3.70.869
Hematoma1.70.2-14.30.61.20.1-19.90.887
Unplanned return to operating room1.80.3-12.40.62.30.2-26.60.508
Readmission5.31.2-23.50.0315.51.5-158.90.021
Blood transfusion8.41.1-62.40.0441.20.8-2024.70.061
Infection10.1-12.311.10.02-42.50.958
Dehiscence1.10.2-8.10.92.80.2-36.80.431
Seroma3.90.8-19.70.14.80.8-29.10.084
Fat necrosis10.1-13.910.90.1-15.50.963

Calculated values are rounded to 1 decimal point. P values are reported for the comparison of complications. OR, odds ratio.

Table 4.

Comparison of Perioperative Risk Profiles in Matched Case vs Controls

OutcomeUnconditional modelConditional Model
OR95% CIPOR95% CIP
Rectus plication1.70.5-5.60.3991.10.3-3.70.869
Hematoma1.70.2-14.30.61.20.1-19.90.887
Unplanned return to operating room1.80.3-12.40.62.30.2-26.60.508
Readmission5.31.2-23.50.0315.51.5-158.90.021
Blood transfusion8.41.1-62.40.0441.20.8-2024.70.061
Infection10.1-12.311.10.02-42.50.958
Dehiscence1.10.2-8.10.92.80.2-36.80.431
Seroma3.90.8-19.70.14.80.8-29.10.084
Fat necrosis10.1-13.910.90.1-15.50.963
OutcomeUnconditional modelConditional Model
OR95% CIPOR95% CIP
Rectus plication1.70.5-5.60.3991.10.3-3.70.869
Hematoma1.70.2-14.30.61.20.1-19.90.887
Unplanned return to operating room1.80.3-12.40.62.30.2-26.60.508
Readmission5.31.2-23.50.0315.51.5-158.90.021
Blood transfusion8.41.1-62.40.0441.20.8-2024.70.061
Infection10.1-12.311.10.02-42.50.958
Dehiscence1.10.2-8.10.92.80.2-36.80.431
Seroma3.90.8-19.70.14.80.8-29.10.084
Fat necrosis10.1-13.910.90.1-15.50.963

Calculated values are rounded to 1 decimal point. P values are reported for the comparison of complications. OR, odds ratio.

DISCUSSION

VTE events such as DVT and PE are an unfortunate but well-documented complication of abdominal contouring procedures such as abdominoplasty and panniculectomy6-10. Although the risk is about 1%, VTEs represent a considerate cause of morbidity and mortality given the rapidly increasing prevalence and already common presence of these procedures.2 There is sparse literature examining VTEs in abdominal contouring procedures and the role that rectus plication may play in increased VTE risk via increased IAP. Several authors have suggested that no increase in the IAP is associated with plication of the rectus abdominus muscle during abdominoplasty.35,36 Other authors disagree with this point, and some believe that external compression postoperatively, such as with the use of compression garments, may actually increase the IAP more than muscle plication. To our knowledge, this study is the largest examination of VTE and its associated factors in abdominal contouring procedures in a cohort generalizable to the cosmetic abdominoplasty and panniculectomy patient population at large.3

The incidence of VTEs noted our study population was 1.59%, aligning with general trends and rates noted in the existing literature.6-10 Similar to previous studies, pre-existing comorbidities and higher baseline risk were more prevalent in patients undergoing panniculectomies than in those undergoing abdominoplasties.3 These potential confounders were addressed via post-hoc matching of cases to controls, controlling for age, BMI, and comorbidity indices to generate comparison groups with similar baseline risk profiles. Post-match descriptive statistics demonstrated no significant differences between cohorts with the exception of previous cerebrovascular accidents—a known risk of VTEs which was adjusted for in subsequent analysis.37 It seems likely that the clotting mechanism responsible for cerebrovascular accidents in some patients might also put them at risk for VTEs, which was supported by the results of the analysis.

SCDs, a commonly used tool for prevention of DVTs in surgery, were less likely to be utilized in the VTE cohort. This finding is expected and supports the validity of our study. In their widely cited meta-analysis, Urbankova et al found significant reductions in the number of DVTs in patients who utilized intermittent pneumatic compression devices compared with those who did not.38-40 Current guidelines for SCD usage are derived mostly from examination of SCDs plus anticoagulation vs anticoagulation alone in surgical patients.41-43 These results further emphasize the importance of SCD usage, a relatively easy and low-risk treatment that is a validated method for decreasing the risk of VTE in surgical patients.

This study did not find significant associations between rectus abdominis plication and VTEs despite proof of increased venous stasis.22,23 As rectus abdominis plication is commonly performed in abdominal contouring procedures, it is imperative to establish the technique’s safety profile. Because increased IAP may lead to lower-extremity venous stasis that persists for up to 48 hours after surgery, rectus plication remains a possible contributor in the multifactorial nature of VTE genesis.19-21,24 However, our results indicate that although a possible factor, plication alone is not a significant cause of VTEs in abdominal contouring patients. Unsurprisingly, 30-day readmission rates and duration of anticoagulation were significantly higher in the VTE group. Given the serious nature of these complications, patients often require extensive work-up, treatment, and monitoring that require careful inpatient medical care.44 Unsurprisingly, the majority of admissions occurred after the VTE was noted for diagnosis and anticoagulation management, which likely contributed to this association.

Interestingly, unconditional analysis showed that patients who received intraoperative transfusions had an 8.4-fold increase in the odds of having a VTE compared to those who did not receive transfusions. Although generally considered safe and elective procedures, the risk of bleeding remains of special concern and patients who experience severe intraoperative blood loss may require transfusions. Blood products are lifesaving therapeutics with potential adverse effects including, but not limited to, febrile transfusion reactions, hemolytic transfusion reactions, transfusion-related acute lung injury, and transfusion-associated circulatory overload.44-46 There are numerous proinflammatory factors and labile blood components that contribute to these overt syndromes and create an environment of heightened inflammation. These proinflammatory factors include cellular blood components, infectious pathogens, undesirable antibodies, as well as foreign leukocytes with high burdens of proinflammatory cytokines and chemokines.47 Elevated inflammation has been linked as both a cause and consequence of VTEs and may be a main perpetrator of the pathology. Unlike other mechanisms of thrombosis involving vascular endothelial injury and subsequent exposure of procoagulant materials, vascular inflammation may initiate thrombosis of an intact vessel.48-50 Additionally, blood products may cause hematologic abnormalities such as thrombocytopenia and coagulation factor derangements that may cause imbalances leading to thrombus formation and subsequent DVT/PE.47 Given the potential link between intraoperative transfusions and postoperative VTEs, surgeons may consider incorporating anti-inflammatory or thromboprophylaxis strategies into the perioperative care of patients who require blood products.

There are several limitations to our study beyond its retrospective design. Due to the investigation being carried out at a single institution and the low incidence of VTEs, our case size was limited despite an impressive overall sample size. Thus, we may not have had sufficient power to detect associations between VTE occurrence and plication status as well as other related complications. Statistical power was improved via 1:4 case-control matching. Despite the significant association between intraoperative blood transfusion and VTE occurrence in the unconditional analysis, the P-value via the conditional analysis was slightly above the threshold for significance. We believe that this is likely the result of a lack of statistical power due to the rarity of the complication compounded with the decreased power inherent in conditional matched regressions. Additionally, detailed reasons for transfusions or the specific types of blood products used were not documented and could not be accounted for during analysis. Typically, when patients required multiple units of packed red cells, they required additional blood products such as plasma or platelets, which likely contributed to the statistically significant increase in blood products seen in the VTE group. The severity of VTEs could not be further explored or stratified for analysis due to sample size limitations. Future multicenter studies with larger cohorts should be pursued to enhance statistical power and allow for more nuanced analysis of related complications and the interplay between intraoperative transfusions and VTEs.

CONCLUSIONS

Our findings establish the safety profile of rectus abdominis plication, a commonly used technique in abdominal contouring procedures, after adjusting for potentially confounding factors via case-control match and regression analysis. However, the odds of VTEs are significantly increased in patients who received intraoperative blood products compared with those who did not. Physicians may consider the addition of anti-inflammatory and/or thromboprophylaxis strategies in patients receiving transfusions to decrease the risk of VTEs.

Disclosures

The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.

Funding

The authors received no financial support for the research, authorship, and publication of this article.

REFERENCES

1.

Regan
JP
,
Casaubon
CJ
.
Abdominoplasty
.
StatPearls
;
2021
.

2.

American Society of Plastic Surgeons
.
Plastic Surgery Statistics Report, 2020
. American Society of Plastic Surgeons;
2021
.

3.

Lesko
RP
,
Cheah
MA
,
Sarmiento
S
,
Cooney
CM
,
Cooney
DS
.
Postoperative complications of panniculectomy and abdominoplasty: a retrospective review
.
Ann Plast Surg.
2020
;
85
(
3
):
285
289
.

4.

Winocour
J
,
Gupta
V
,
Ramirez
JR
,
Shack
RB
,
Grotting
JC
,
Higdon
KK
.
Abdominoplasty: risk factors, complication rates, and safety of combined procedures
.
Plast Reconstr Surg.
2015
;
136
(
5
):
597e
606e
.

5.

Momeni
A
,
Heier
M
,
Bannasch
H
,
Stark
GB
.
Complications in abdominoplasty: a risk factor analysis
.
J Plast Reconstr Aesthet Surg.
2009
;
62
(
10
):
1250
1254
.

6.

Keiter
JE
,
Johns
D
,
Rockwell
WB
.
Importance of postoperative hydration and lower extremity elevation in preventing deep venous thrombosis in full abdominoplasty: a report on 450 consecutive cases over a 37-year period
.
Aesthet Surg J.
2015
;
35
(
7
):
839
841
.

7.

Neaman
KC
,
Hansen
JE
.
Analysis of complications from abdominoplasty: a review of 206 cases at a university hospital
.
Ann Plast Surg.
2007
;
58
(
3
):
292
298
.

8.

Sforza
M
,
Husein
R
,
Saghir
R
, et al.
Deep vein thrombosis (DVT) and abdominoplasty: a holistic 8-point protocol-based approach to prevent DVT
.
Aesthet Surg J.
2021
;
41
(
10
):
Np1310
np1320
.

9.

Somogyi
RB
,
Ahmad
J
,
Shih
JG
,
Lista
F
.
Venous thromboembolism in abdominoplasty: a comprehensive approach to lower procedural risk
.
Aesthet Surg J.
2012
;
32
(
3
):
322
329
.

10.

Keyes
GR
,
Singer
R
,
Iverson
RE
,
Nahai
F
.
Incidence and predictors of venous thromboembolism in abdominoplasty
.
Aesthet Surg J.
2018
;
38
(
2
):
162
173
.

11.

Gupta
V
,
Yeslev
M
,
Winocour
J
, et al.
Aesthetic breast surgery and concomitant procedures: incidence and risk factors for major complications in 73,608 cases
.
Aesthet Surg J.
2017
;
37
(
5
):
515
527
.

12.

Kearon
C
,
Akl
EA
,
Ornelas
J
, et al.
Antithrombotic therapy for VTE disease: CHEST guideline and expert panel report
.
Chest.
2016
;
149
(
2
):
315
352
.

13.

Heijboer
RRO
,
Lubberts
B
,
Guss
D
,
Johnson
AH
,
DiGiovanni
CW
.
Incidence and risk factors associated with venous thromboembolism after orthopaedic below-knee surgery
.
J Am Acad Orthop Surg.
2019
;
27
(
10
):
e482
e490
.

14.

Samama
CM
,
Laporte
S
,
Rosencher
N
, et al.
Rivaroxaban or enoxaparin in nonmajor orthopedic surgery
.
N Engl J Med.
2020
;
382
(
20
):
1916
1925
.

15.

Davison
SP
,
Venturi
ML
,
Attinger
CE
,
Baker
SB
,
Spear
SL
.
Prevention of venous thromboembolism in the plastic surgery patient
.
Plast Reconstr Surg.
2004
;
114
(
3
):
43e
51e
.

16.

Young
VL
,
Watson
ME
.
The need for venous thromboembolism (VTE) prophylaxis in plastic surgery
.
Aesthet Surg J
2006
;
26
(
2
):
157
175
.

17.

Mittal
P
,
Heuft
T
,
Richter
DF
,
Wiedner
M
.
Venous thromboembolism (VTE) prophylaxis after abdominoplasty and liposuction: a review of the literature
.
Aesthetic Plast Surg.
2020
;
44
(
2
):
473
482
.

18.

Perzia
BM
,
Marquez
J
,
Mellia
JA
, et al.
Venous thromboembolism and bleeding events with chemoprophylaxis in abdominoplasty: a systematic review and pooled analysis of 1596 patients
.
Aesthet Surg J.
2021
;
41
(
11
):
1279
1289
.

19.

Clayman
MA
,
Clayman
ES
,
Seagle
BM
,
Sadove
R
.
The pathophysiology of venous thromboembolism: implications with compression garments
.
Ann Plast Surg.
2009
;
62
(
5
):
468
472
.

20.

Huang
GJ
,
Bajaj
AK
,
Gupta
S
,
Petersen
F
,
Miles
DAG
.
Increased intraabdominal pressure in abdominoplasty: delineation of risk factors
.
Plast Reconstr Surg.
2007
;
119
(
4
):
1319
1325
.

21.

Pannucci
CJ
,
Alderman
AK
,
Brown
SL
,
Wakefield
TW
,
Wilkins
EG
.
The effect of abdominal wall plication on intra-abdominal pressure and lower extremity venous flow: a case report
.
J Plast Reconstr Aesthet Surg.
2012
;
65
(
3
):
392
394
.

22.

Momeni
A
,
Sorice
SC
,
Li
AY
,
Nguyen
DH
,
Pannucci
C
.
Breast reconstruction with free abdominal flaps is associated with persistent lower extremity venous stasis
.
Plast Reconstr Surg.
2019
;
143
(
6
):
1144e
1150e
.

23.

Momeni
A
,
Tecce
MG
,
Lanni
MA
, et al.
Increased lower extremity venous stasis may contribute to deep venous thrombosis formation after microsurgical breast reconstruction—an ultrasonographic study
.
J Reconstr Microsurg.
2017
;
33
(
3
):
173
178
.

24.

Kushner
A
,
West
WP
,
Pillarisetty
LS
.
Virchow triad.
In:
StatPearls
.
StatPearls
;
2022
.

25.

Mackman
N
.
New insights into the mechanisms of venous thrombosis
.
J Clin Invest.
2012
;
122
(
7
):
2331
2336
.

26.

Charlson
ME
,
Pompei
P
,
Ales
KL
,
MacKenzie
CR
.
A new method of classifying prognostic comorbidity in longitudinal studies: development and validation
.
J Chronic Dis
1987
;
40
(
5
):
373
383
.

27.

Huang
Y
,
Zhang
Y
,
Li
J
,
Liu
G
.
Charlson Comorbidity Index for evaluatiοn οf the outcomes of elderly patients undergoing laparoscopic surgery for colon cancer
.
J BUON.
2017
;
22
(
3
):
686
691
.

28.

Quan
H
,
Li
B
,
Couris
CM
, et al.
Updating and validating the Charlson Comorbidity Index and score for risk adjustment in hospital discharge abstracts using data from 6 countries
.
Am J Epidemiol.
2011
;
173
(
6
):
676
682
.

29.

Sato
S
,
Nakamura
M
,
Shimizu
Y
, et al.
Impact of postoperative complications on outcomes of second surgery for second primary lung cancer
.
Surg Today.
2020
;
50
(
11
):
1452
1460
.

30.

Golemi
I
,
Salazar Adum
JP
,
Tafur
A
,
Caprini
J
.
Venous thromboembolism prophylaxis using the Caprini score
.
Dis Mon.
2019
;
65
(
8
):
249
298
.

31.

Zhou
H
,
Hu
Y
,
Li
X
, et al.
Assessment of the risk of venous thromboembolism in medical inpatients using the Padua prediction score and Caprini risk assessment model
.
J Atheroscler Thromb.
2018
;
25
(
11
):
1091
1104
.

32.

Radovanovic
D
,
Seifert
B
,
Urban
P
, et al.
Validity of Charlson Comorbidity Index in patients hospitalised with acute coronary syndrome. Insights from the nationwide AMIS Plus registry 2002-2012
.
Heart
2014
;
100
(
4
):
288
294
.

33.

CALIPMATCH: Stata module for caliper matching without replacement [computer program]
. College Station, TX: StataCorp;
2017
.

34.

Kuo
CL
,
Duan
Y
,
Grady
J
.
Unconditional or conditional logistic regression model for age-matched case-control data?
Front Public Health.
2018
;
6
:
57
.

35.

Rodrigues
MA
,
Nahas
FX
,
Gomes
HC
,
Ferreira
LM
.
Ventilatory function and intra-abdominal pressure in patients who underwent abdominoplasty with plication of the external oblique aponeurosis
.
Aesthetic Plast Surg.
2013
;
37
(
5
):
993
999
.

36.

Rodrigues
MA
,
Nahas
FX
,
Reis
RP
,
Ferreira
LM
.
Does diastasis width influence the variation of the intra-abdominal pressure after correction of rectus diastasis?
Aesthet Surg J.
2015
;
35
(
5
):
583
588
.

37.

Kappelle
LJ
.
Preventing deep vein thrombosis after stroke: strategies and recommendations
.
Curr Treat Options Neurol
2011
;
13
(
6
):
629
635
.

38.

Swanson
E
.
Do sequential compression devices really reduce the risk of venous thromboembolism in plastic surgery patients?
Plast Reconstr Surg.
2015
;
136
(
4
):
577e
578e
.

39.

Swanson
E
.
The effect of sequential compression devices on fibrinolysis in plastic surgery outpatients: a randomized trial
.
Plast Reconstr Surg.
2020
;
145
(
2
):
392
401
.

40.

Urbankova
J
,
Quiroz
R
,
Kucher
N
,
Goldhaber
SZ
.
Intermittent pneumatic compression and deep vein thrombosis prevention. A meta-analysis in postoperative patients
.
Thromb Haemost.
2005
;
94
(
6
):
1181
1185
.

41.

Eisele
R
,
Kinzl
L
,
Koelsch
T
.
Rapid-inflation intermittent pneumatic compression for prevention of deep venous thrombosis
.
J Bone Joint Surg Am.
2007
;
89
(
5
):
1050
1056
.

42.

Kahn
SR
,
Lim
W
,
Dunn
AS
, et al.
Prevention of VTE in nonsurgical patients: antithrombotic therapy and prevention of thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines
.
Chest.
2012
;
141
(
2 Suppl
):
e195S
e226S
.

43.

Kakkos
SK
,
Caprini
JA
,
Geroulakos
G
,
Nicolaides
AN
,
Stansby
GP
,
Reddy
DJ
.
Combined intermittent pneumatic leg compression and pharmacological prophylaxis for prevention of venous thromboembolism in high-risk patients
.
Cochrane Database Syst Rev.
2008
;
4
:
Cd005258
. doi:

44.

Gutt
CN
,
Oniu
T
,
Wolkener
F
,
Mehrabi
A
,
Mistry
S
,
Büchler
MW
.
Prophylaxis and treatment of deep vein thrombosis in general surgery
.
Am J Surg.
2005
;
189
(
1
):
14
22
.

45.

Delaney
M
,
Wendel
S
,
Bercovitz
RS
, et al.
Transfusion reactions: prevention, diagnosis, and treatment
.
Lancet.
2016
;
388
(
10061
):
2825
2836
.

46.

Garraud
O
,
Tariket
S
,
Sut
C
, et al.
Transfusion as an inflammation hit: knowns and unknowns
.
Front Immunol.
2016
;
7
:
534
.

47.

Avall
A
,
Hyllner
M
,
Bengtson
JP
,
Carlsson
L
,
Bengtsson
A
.
Postoperative inflammatory response after autologous and allogeneic blood transfusion
.
Anesthesiology
1997
;
87
(
3
):
511
516
.

48.

Branchford
BR
,
Carpenter
SL
.
The role of inflammation in venous thromboembolism
.
Front Pediatr.
2018
;
6
:
142
.

49.

Colling
ME
,
Tourdot
BE
,
Kanthi
Y
.
Inflammation, infection and venous thromboembolism
.
Circ Res.
2021
;
128
(
12
):
2017
2036
.

50.

Mukhopadhyay
S
,
Johnson
TA
,
Duru
N
, et al.
Fibrinolysis and inflammation in venous thrombus resolution
.
Front Immunol.
2019
;
10
:
1348
.

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