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. 2022 Aug 2;7(3):24730114221115677. doi: 10.1177/24730114221115677

Comparing the 30-Day Complications Between Smokers and Nonsmokers Undergoing Surgical Fixation of Ankle Fractures

Bernard H Sagherian 1,✉, Jawad J Hoballah 2, Hani Tamim 3
PMCID: PMC9358578  PMID: 35959141

Abstract

Background:

There have been conflicting reports regarding the effect of smoking on complications after surgical treatment of ankle fractures. This study aimed at identifying the complications for which smokers and subgroups of smokers are at a higher risk compared to nonsmokers when undergoing surgery for fixation of rotational ankle fractures.

Methods:

The American College of Surgeons National Surgical Quality Improvement Program data set from 2008 to 2019 was used to compare the 30-day wound, cardiac, renal, and infectious complications, related readmissions, and return to the operating room between the 2 cohorts.

Results:

Of 33 741 patients included, 25 642 (76.0%) were nonsmokers and 8099 (24.0%) were smokers. Multivariate analysis showed that smokers were at a higher risk for deep wound infection (OR 2.34, 95% CI 1.48-3.69, P < .001), wound dehiscence (OR 2.43, 95% CI 1.56-3.77, P < .001), related return to the operating room (OR 1.69, 95% CI 1.36-2.11, P < .001), and related readmissions (OR 1.67, 95% CI 1.32-2.09, P < .001). Smokers at an increased risk for deep infection included patients between 50 and 59 years (OR 5.75, 95% CI 1.78-18.5, P = .003), who were Black (OR 4.24, 95% CI 1.04-17.23, P = .044), who had body mass index (BMI) 35 to 39.9 (OR 3.73, 95% CI 1.46-9.50, P = .006), or operative times between 60 and 90 minutes (OR 3.64, 95% CI 1.79-7.39, P < .001). Smoker subgroups at a higher risk for wound dehiscence included patients between 50 and 59 years (OR 9.86, 95% CI 3.29-29.53, P < .001), with operative times between 90 and 120 minutes (OR 4.88, 95% CI 1.89-12.58, P < .001), with BMI 30 to 34.9 (OR 3.06, 95% CI 1.45-6.45, P = .003) and who underwent spinal/epidural anesthesia (OR 9.31, 95% CI 2.31-37.58, P = .002).

Conclusion:

Smokers were at an increased risk for deep wound infection, wound dehiscence, related reoperations, and related readmissions after ankle fracture surgery. Certain subgroups were at an even higher risk for these complications.

Level of Evidence:

Level III, retrospective cohort study.

Keywords: ankle fracture, complications, outcomes, risk factors, patient characteristics, smoking, smoker

Introduction

The overall incidence of ankle fractures ranges between 100 and 187 per 100 000 person-years.12,13,15,22 When unstable or displaced, they are treated surgically with open reduction and internal fixation (ORIF). To improve outcomes, several studies have previously addressed the complications after ankle fracture surgery and tried to identify risk factors for those adverse events.4,7,9,25,27,28,30,34,41 Diabetes14,16,23,25 -27,49 and obesity8,24,42 have been identified as risk factors for several complications in ORIF of ankle fractures. Although the prevalence of smoking was 14% in the United States in 2019 11 and around 20% globally, 36 there are still conflicting reports regarding the effect of smoking on outcomes after ankle fracture surgery. Although several studies have found smoking to be a risk factor for complications in ORIF of ankle fractures,5,21,28,29,32,37,39,40,50 some have failed to show an increased risk in smokers.4,30,33,35,43

Moreover, the studies that have identified smoking as a risk factor for certain complications have not analyzed specific subgroups of smokers who might be at an increased risk for those complications.32,34,38

The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) data set has been used in several studies to investigate outcomes following ankle fracture fixation. Although some have failed to show an increased risk of adverse events in smokers,4,9,30 others have grouped complications into major and minor adverse events and analyzed independent risk factors for those events combined,4,7,9 which limits the possibility of drawing sensible clinical inferences. Moreover, the studies that have found association between smoking and certain grouped complications have not attempted stratification of specific complications. 7 We therefore sought to use the ACS-NSQIP database to analyze specific complications for which smokers who undergo surgery for fixation of rotational ankle fractures are at an increased risk compared with nonsmokers, and to further stratify the cohorts into subgroups, based on age, gender, race, body mass index (BMI), operative times, anesthesia type, fracture type, and other comorbidities, to identify smokers who might be at an even higher risk of developing those complications.

Materials and Methods

Study Design

This was a retrospective cohort study using data from the ACS-NSQIP database that includes more than 150 variables collected on surgical patients from 719 centers across the United States and other countries. Although operative treatment techniques, postoperative protocols, and surgeon experience are not standardized, the ACS-NSQIP uses a prospective, peer-controlled, validated database to measure the 30-day risk-adjusted surgical outcomes. A site’s trained and certified Surgical Clinical Reviewer captures these data using a variety of methods including medical chart abstraction. 2 In accordance with our institutional guidelines, which follow the US Code of Federal Regulations for the Protection of Human Subjects, institutional review board approval was not needed for our analysis because data were deidentified and collected as part of a quality assurance activity.

Patient Selection

Data from 2008 through 2019 were queried to identify patients who underwent ankle fracture surgery using the Current Procedural Terminology codes 27766 (medial malleolus), 27769 (posterior malleolus), 27792 (lateral malleolus), 27814 (bimalleolar), 27822 (trimalleolar without posterior lip fixation), and 27823 (trimalleolar with posterior lip fixation). An initial 38 958 patients were identified. None had missing data of smoker status. NSQIP variables were used to exclude patients who had preoperative sepsis (n = 1147), open wound / wound infection prior to surgery (n = 981), or other concurrent/concomitant procedures (n = 3089).

Patient demographics, comorbidities, and selected laboratory values were obtained as baseline characteristics (Table 1). These included age, gender, race, American Society of Anesthesiology (ASA) classification, operative time, functional status, body mass index (BMI), diabetes mellitus, hypertension, steroid use, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), dyspnea, renal failure on dialysis, anesthesia type, bleeding disorders, international normalized ratio (INR), and hematocrit (Hct). The BMI classification was adapted from the World Health Organization global database. 47 Anemia was defined using the World Health Organization sex-based criteria. 48

Table 1.

Patient Characteristics.

Patient Characteristics (N = 33 741) Nonsmokers, Mean ± SD or n (%)
(n = 25 642; 76.0%)		 Smokers, n (%)
(n = 8099; 24.0%)		 P Value
Age, y 50.61 ± 18.46 43.63 ± 14.78 <.001
 ≤39 7890 (31.10) 3451 (42.60) <.001
 40-49 3643 (14.40) 1620 (20.00)
 50-59 4727 (18.60) 1727 (21.30)
 60-69 4793 (18.90) 994 (12.30)
 ≥70 4328 (17.10) 302 (3.70)
Gender
 Male 9873 (38.50) 4054 (50.10) <.001
 Female 15769 (61.50) 4045 (49.90)
Race/ethnicity
 White 16 435 (64.10) 4893 (60.40) <.001
 Black 2220 (8.70) 1150 (14.20)
 Asian 541 (2.10) 81 (1.00)
 Other 6430 (25.10) 1972 (24.40)
ASA class
 I-II 18 474 (72.20) 5892 (72.90) .209
 III-V 7116 (27.80) 2189 (27.10)
Mean total operation time, min 76.57 ± 42.35 76.14 ± 45.51 <.001
 <60 min 10 064 (39.26) 3335 (41.18) .005
 60-90 min 8111 (31.60) 2420 (29.90)
 90-120 min 4219 (16.50) 1300 (16.10)
 >120 min 3243 (12.60) 1043 (12.90)
Functional status prior to surgery
 Independent 24 497 (96.70) 7838 (98.10)
 Partially dependent/dependent 848 (3.30) 150 (1.90)
BMI a 30.92 ± 7.07 30.03 ± 6.89 <.001
 <18.5 109 (0.40) 51 (0.60) <.001
 18.5-24.9 4276 (16.70) 1744 (21.50)
 25-29.9 8155 (31.80) 2582 (31.90)
 30-34.9 7608 (29.70) 2210 (27.30)
 35-39.9 3096 (12.10) 905 (11.20)
 ≥40 2398 (9.40) 607 (7.50)
Diabetes on oral drugs or insulin
 No diabetes 22 523 (87.80) 7464 (92.20) <.001
 Diabetes on oral drugs 1330 (5.20) 280 (3.50)
 Diabetes on insulin 1789 (7.00) 355 (4.40)
Hypertension requiring medication 8355 (32.60) 1967 (24.30) <.001
Steroid use for chronic condition 451 (1.80) 94 (1.20) <.001
Severe COPD 557 (2.20) 406 (5.00) <.001
Dyspnea 626 (2.40) 273 (3.40) <.001
CHF (within 30 d) 133 (0.50) 24 (0.30) .010
Anesthesia technique – –
 General 22 503 (87.80) 7348 (90.80) <.001
 Spinal/epidural 2080 (8.10) 466 (5.80)
 Others 1048 (4.10) 282 (3.50)
Acute renal failure 46 (0.20) 6 (0.10) .040
Currently on dialysis 163 (0.60) 19 (0.20) <.001
Preoperative serum creatinine 0.96 ± .0.76 0.88 ± 0.54 <.001
 <1.2 mg/dL 13 656 (87.30) 4307 (92.10) <.001
 ≥1.2 mg/dL 1983 (12.70) 371 (7.90)
>10% loss body weight in last 6 mo 19 (0.10) 8 (0.10) .500
Bleeding disorders 786 (3.10) 173 (2.10) <.001
Preoperative INR 1.06 ± 0.26 1.04 ± 0.28 <.001
 ≤1.2 8011 (93.80) 2386 (95.80) <.001
 >1.2 528 (6.20) 105 (4.20)
Hematocrit, % b 38.89 ± 4.72 40.17 ± 4.68 <.001
 No anemia 11 489 (70.30) 3752 (76.60) <.001
 Mild anemia 3219 (19.70) 835 (17.10)
 Moderate-severe anemia 1631 (10.00) 309 (6.30)
Albumin 3.87 ± 0.53 3.91 ± 0.53 <.001
 ≥3.5 g/dL 5503 (80.00) 1737 (82.50) .009
 <3.5 g/dL 1380 (20.00) 368 (17.50)
CPT code
  CPT code 27766 1395 (5.40) 532 (6.60) <.001
  CPT code 27769 226 (0.90) 66 (0.80)
  CPT code 27792 8156 (31.80) 2694 (33.30)
  CPT code 27814 9381 (36.60) 2857 (35.30)
  CPT code 27822 4927 (19.20) 1524 (18.80)
  CPT code 27823 1557 (6.10) 426 (5.30)
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Abbreviations: ASA, American Society of Anesthesiology; BMI, body mass index; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; CPT, Current Procedural Terminology; INR, international normalized ratio.

a

BMI classification was adapted from the World Health organization (WHO) global database.

b

Anemia was defined using the WHO sex-based criteria.

Thirty-day mortality and morbidity, including cardiac, wound, respiratory, urinary tract, central nervous system, sepsis, venous thromboembolism, bleeding, mortality, related return to the operating room, and related readmission were recorded as adverse events. NSQIP classifies wound infection as deep when an infection appears to be related to the operation and involves the deep soft tissues of the incision.

Statistical Analysis

Statistical analyses were done using IBM SPSS Statistics software (version 28; Norman H. Nie, Dale H. Bent, C. Hadlai Hull; Armonk, NY). Categorical variables were presented as number and percentage and continuous ones as mean and SD. Continuous variables were compared using the independent t test and categorical variables using the χ2 test. Odds ratios (ORs) for complications were calculated, using logistic regression with 95% CIs. After an initial univariate analysis, relevant confounders for specific complications were controlled for, and a multivariate logistic regression analysis was performed to detect the independent effect of smoking on complications (Table 2). When smoking was found to be an independent risk factor for a specific complication, that adverse event was further analyzed by subgroup stratification to identify specific subgroup of patients who might be at an even higher risk for that specific complication. Total and postoperative length of stay were analyzed using linear regression and reported using β value with its 95% CI. The level of significance for P value was <.05.

Table 2.

Postoperative Outcomes.

Postoperative Complications Nonsmokers,
n (%) or Mean ± SD		 Smokers,
n (%) or Mean ± SD		 Unadjusted OR Adjusted OR
OR (95% CI) P Value OR (95% CI) P Value
Mortality 58 (0.20) 14 (0.20) 0.76 (0.43, 1.37) .366 1.30 (0.67, 2.54) .443
Bleeding 121 (0.50) 22 (0.30) 0.57 (0.37, 0.91) .017 1.03 (0.64, 1.68) .896
Return to operating room (related) 247 (1.00) 125 (1.50) 1.61 (1.30, 2.00) <.001 1.69 (1.36, 2.11) <.001
Thromboembolism a 143 (0.60) 34 (0.40) 0.75 (0.52, 1.09) .136 0.86 (0.58, 1.26) .433
 DVT 89 (0.30) 22 (0.30) 0.78 (0.49, 1.25) .302 0.87 (0.54, 1.41) .575
 Pulmonary embolism 66 (0.30) 13 (0.20) 0.62 (0.34, 1.13) .119 0.72 (0.39, 1.32) .290
Cardiac complications b 28 (0.10) 9 (0.10) 1.02 (0.48, 2.16) .964 1.15 (0.54, 2.49) .715
 Cardiac arrest 10 (0.00) 5 (0.10) 1.58 (0.54, 4.63) .402 2.27 (0.73, 7.01) .155
 MI 20 (0.10) 4 (0.00) 0.63 (0.22, 1.85) .404 0.68 (0.23, 2.00) .479
Pneumonia 70 (0.30) 12 (0.10) 0.54 (0.29, 1.00) .050 0.86 (0.44, 1.68) .656
Intubation c 32 (0.10) 13 (0.20) 1.29 (0.68, 2.45) .444 1.09 (0.55, 2.19) .801
Urinary tract infection 193 (0.80) 30 (0.40) 0.49 (0.33, 0.72) <.001 1.09 (0.73, 1.63) .683
Renal complications d 23 (0.10) 5 (0.10) 0.69 (0.26, 1.81) .449 1.26 (0.46, 3.42) .650
CVA 10 (0.00) 4 (0.00) 1.27 (0.40, 4.04) .690 3.37 (0.85, 13.39) .084
Sepsis 48 (0.20) 17 (0.20) 1.12 (0.65, 1.95) .685 1.49 (0.82, 2.72) .194
Superficial surgical site infection 188 (0.70) 67 (0.80) 1.13 (0.85, 1.49) .394 1.27 (0.94, 1.70) .116
Wound dehiscence 49 (0.20) 35 (0.40) 2.27 (1.47, 3.50) <.001 2.43 (1.56, 3.77) <.001
Deep wound infection 47 (0.20) 32 (0.40) 2.16 (1.38, 3.39) <.001 2.34 (1.48, 3.69) <.001
LOS (total stay) e 1.68 ± 3.66 1.33 ± 3.68 –0.35 (–0.44, –0.26) <.001 –0.01 (–0.10, –0.08) .830
LOS (postoperative stay) e 1.22 ± 2.98 0.94 ± 2.91 –0.29 (–0.36, –0.21) <.001 –0.01 (–0.09, –0.06) .687
Readmission (related) 287 (1.10) 119 (1.50) 1.32 (1.06, 1.63) .012 1.67 (1.32, 2.09) <.001
Related readmission reason P Value
 Superficial incisional SSI 18 (0.10) 19 (0.20) <.001
 Deep incisional SSI 26 (0.10) 17 (0.20) .017
 Wound disruption 12 (0.00) 9 (0.10) .043
 Pneumonia 13(0.10) 3 (0.00) .776
 Intubation c 0 (0.00) 1 (0.00) .240
 Urinary tract infection 14 (0.10) 3 (0.00) .777
 CVA 2 (0.00) 1 (0.00) .561
 Cardiac complications b 7 (0.00) 2 (0.00) 1.0
 Sepsis 13 (0.10) 2 (0.00) .545
 Pulmonary embolism 28 (0.10) 7 (0.10) .579
 Vein thrombosis requiring therapy 10 (0.00) 3 (0.00) 1.0
 Thromboembolism a 36 (0.10) 10 (0.10) .719
 Renal complications d 4 (0.00) 0 (0.00) .579
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Abbreviations: CVA, cerebrovascular accident; DVT, deep vein thromboembolism; LOS, length of stay; MI, myocardial infarction; OR, odds ratio; SSI, surgical site infection.

a

Includes DVT and/or pulmonary embolism.

b

Includes cardiac arrest and/or MI.

c

Includes unplanned intubation and/or intubation >48 hours.

d

Includes acute renal failure and/or progressive renal insufficiency.

e

Linear regression reported as β and its 95% CI.

Results

A total of 33 741 patients were identified, of which 25 642 (76.0%) were nonsmokers and 8099 (24.0%) were smokers. Table 1 shows the baseline characteristics of each group. Demographic data showed that a higher proportion of smokers were younger in age (43.63 ± 14.78 years vs 50.61 ± 18.46 years, P < .001), male (50.10% vs 38.50%, P < .001), Black (14.20% vs 8.70%, P < .001), nonobese (21.50% vs 16.70%, P < .001), functionally independent (98.10% vs 96.70%, P < .001), nondiabetic (92.20% vs 87.80%, P < .001), nonanemic (76.60% vs 70.30%, P < .001) and underwent general anesthesia more frequently (90.80% vs 87.80, P < .001). Several characteristics were less prevalent in the smoker cohort; these included hypertension (24.30% vs 32.60%, P < .001), CHF (0.30% vs 0.50%, P < .001), bleeding disorders (2.10% vs 3.10%, P < .001), acute renal failure (0.10% vs 0.20%, P < .001), dialysis (0.20% vs 0.60%, P < .001), and steroid use (1.20% vs 1.80%, P < .001).

Regarding the 30-day outcomes, multivariate logistic regression analysis found smokers to be at a higher risk for developing wound dehiscence (OR 2.43, 95% CI 1.56-3.77, P < .001) and deep surgical site infection (OR 2.34, 95% CI 1.48-3.69, P < .001) compared to nonsmokers. Smokers were also at a higher risk for return to operating room related to the index procedure (OR 1.69, 95% CI 1.36-2.11, P < .001) and related readmissions (OR 1.67, 95% CI 1.32-2.09, P < .001). No statistically significant differences were found between the 2 groups in terms of mortality, cardiac complications, pneumonia, intubation, renal complication, cerebrovascular accidents, thromboembolism, bleeding, and total or postoperative length of stay (Table 2).

Upon stratification of different baseline characteristics in patients who developed deep wound infections (n = 79), several subgroups of smokers were at a risk higher than the baseline adjusted OR of 2.34 (95% CI 1.48-3.69, P < .001) for developing deep wound infection. These included patients who were between 40 and 49 years (OR 3.46, 95% CI 1.08-11.09, P = .037), between 50 and 59 years (OR 5.75, 95% CI 1.78-18.58, P = .003), those who were Black (OR 4.24, 95% CI 1.04-17.23, P = .044), had race other than White, Black, or Asian (OR 4.77, 95% CI 1.67-13.63, P = .004), had BMI between 30 and 34.9 (OR 2.83, 95% CI 1.29-6.21, P = .010) and 35 and 39.9 (OR 3.73, 95% CI 1.46-9.50, P = .006), had mild anemia (OR 3.80, 95% CI 1.33-10.85, P = .013) or operative times between 60 and 90 minutes (OR 3.64, 95% CI 1.79-7.39, P < .001). Stratification for wound dehiscence (n = 84) also showed certain subgroups of smokers to be at a risk greater than the baseline OR of 2.43 (95% CI 1.56-3.77, P < .001) compared with nonsmokers (Table 3). These included patients between 40 and 49 years (OR 4.49, 95% CI 1.27-15.87, P = .020), between 50 and 59 years (OR 9.86, 95% CI 3.29-29.53, P < .001), patients with operative times between 90 and 120 minutes (OR 4.88, 95% CI 1.89-12.58, P < .001), BMI between 30 and 34.9 (OR 3.06, 95% CI 1.45-6.45, P = .003), and those who underwent spinal or epidural anesthesia (OR 9.31, 95% CI 2.31-37.58, P = .002) or had mild anemia (OR 3.81, 95% CI 1.43-10.18, P = .008).

Table 3.

Stratification of Patients With Deep Wound Infection and Wound Dehiscence.

Deep Infection
(n = 79)		 Wound Dehiscence
(n = 84)
Nonsmokers,
n (%)		 Smokers,
n (%)		 Adjusted OR (95% CI) P Value Nonsmokers,
n (%)		 Smokers,
n (%)		 Adjusted OR (95% CI) P Value
Overall 47 (0.20) 32 (0.40) 2.34 (1.48-3.69) <.001 49 (0.20) 35 (0.40) 2.43 (1.56-3.77) <.001
Age, y
 ≤39 11 (0.14) 8 (0.23) 1.78 (0.71-4.45) .221 4 (0.05) 7 (0.20) 4.14 (1.24-14.37) .025
 40-49 5 (0.14) 7 (0.43) 3.46 (1.08-11.09) .037 4 (0.11) 7 (0.43) 4.49 (1.27-15.87) .020
 50-59 4 (0.08) 10 (0.58) 5.75 (1.78-18.58) .003 4 (0.08) 18 (1.04) 9.86 (3.29-29.53) <.001
 60-69 11 (0.23) 5 (0.50) 2.01 (0.68-5.91) .207 15 (0.31) 3 (0.30) 0.56 (1.16-1.99) .371
 ≥70 15 (0.35) 2 (0.66) 1.95 (0.44-8.60) .377 19 (0.44) 0 (0.00) N/A N/A
Gender
 Female 31 (0.20) 16 (0.40) 2.29 (1.24-4.22) .008 34 (0.22) 17 (0.42) 2.15 (1.19-3.89) .012
 Male 16 (0.16) 16 (0.39) 2.42 (1.21-4.84) .013 15 (0.15) 18 (0.44) 3.33 (1.61-6.92) .001
Race/ethnicity
 White 34 (0.21) 18 (0.37) 1.85 (1.04-3.29) .037 37 (0.23) 20 (0.41) 1.95 (1.13-3.39) .017
 Black 3 (0.14) 6 (0.52) 4.24 (1.04-17.23) .044 4 (0.18) 5 (0.43) 2.26 (2.58-8.80) .239
 Asian 2 (0.37) 0 (0.00) N/A N/A 1 (0.18) 0 (0.00) N/A N/A
 Other 8 (0.12) 8 (0.41) 4.77 (1.67-13.63) .004 7 (0.11) 10 (0.51) 5.64 (2.72-15.81) .001
ASA class
 I, II 22 (0.12) 17 (0.29) 2.73 (1.44-5.16) .002 13 (0.07) 17 (0.29) 4.52 (2.18-9.39) <.001
 III-V 25 (0.35) 15 (0.69) 2.11 (1.10-4.05) .024 36 (0.51) 18 (0.82) 1.73 (8.98-3.09) .060
Operative time
 <60 min 13 (0.13) 8 (0.24) 1.99 (0.82-4.85) .130 13 (0.13) 10 (0.30) 2.47 (1.77-5.74) .034
 60-90 min 17 (0.21) 16 (0.66) 3.64 (1.79-7.39) <.001 15 (0.18) 9 (0.37) 2.40 (1.63-5.61) .042
 90-120 min 11 (0.26) 5 (0.38) 2.39 (0.76-7.51) .135 11 (0.26) 10 (0.77) 4.88 (1.89-12.58) .001
 >120 min 6 (0.19) 3 (0.29) 1.69 (0.42-6.88) .461 10 (0.31) 6 (0.58) 2.05 (5.73-5.79) .173
BMI
 18.5-24.9 7 (0.16) 3 (0.17) 1.14 (0.28-4.56) .858 10 (0.23) 5 (0.29) 1.33 (2.44-4.01) .610
 25-29.9 11 (0.13) 8 (0.31) 2.48 (0.99-6.21) .052 14 (0.17) 11 (0.43) 2.57 (1.15-5.76) .022
 30-34.9 15 (0.20) 11 (0.50) 2.83 (1.29-6.21) .010 16 (0.21) 13 (0.59) 3.06 (1.45-6.45) .003
 35-39.9 10 (0.32) 9 (0.99) 3.73 (1.46-9.50) .006 5 (0.16) 5 (0.55) 3.32 (6.96-11.53) .058
 ≥40 3 (0.13) 1 (0.16) 1.32 (0.14-12.73) .809 4 (0.17) 0 (0.00) N/A N/A
Diabetes
 Diabetes on insulin 10 (0.75) 2 (0.71) 0.75 (0.16-3.55) .715 8 (0.60) 5 (1.79) 0.83 (1.10-6.93) .864
 Diabetes on oral drugs 7 (0.39) 2 (0.56) 1.43 (0.30-6.91) .657 6 (0.34) 1 (0.28) 0.71 (7.09-6.00) .759
Anesthesia technique
 General 42 (0.19) 30 (0.41) 2.36 (1.47-3.80) <.001 42 (0.19) 29 (0.39) 2.49 (1.51-4.11) <.001
 Spinal/epidural 3 (0.14) 2 (0.43) 3.09 (0.51-18.68) .220 4 (0.19) 6 (1.29) 9.31 (2.31-37.58) .002
Hematocrit (%)
 Mild anemia 8 (0.25) 7 (0.84) 3.80 (1.33-10.85) .013 9 (0.28) 8 (0.96) 3.81 (1.43-10.18) .008
 Moderate-severe anemia 9 (0.55) 2 (0.65) 1.17 (0.25-5.46) .838 11 (0.67) 5 (1.62) 2.81 (8.94-8.42) .064
CPT code
  CPT code 27766 2 (0.14) 3 (0.56) 3.92 (0.65-23.51) .135 1 (0.07) 0 (0.00) N/A N/A
  CPT code 27769 1 (0.44) 0 (0.00) N/A N/A (0.00) (0.00) N/A N/A
  CPT code 27792 11 (0.13) 7 (0.26) 2.15 (0.83-5.57) .117 10 (0.12) 10 (0.37) 2.98 (1.23-7.19) .015
  CPT code 27814 20 (0.21) 14 (0.49) 2.61 (1.30-5.24) .007 21 (0.22) 12 (0.42) 1.92 (6.93-3.99) .078
  CPT code 27822 10 (0.20) 7 (0.46) 2.65 (0.99-7.13) .053 13 (0.26) 11 (0.72) 3.28 (1.42-7.59) .005
  CPT code 27823 3 (0.19) 1 (0.23) 1.20 (0.13-11.59) .873 4 (0.26) 2 (0.47) 2.03 (0.37-11.24) .417
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Abbreviations: ASA, American Society of Anesthesiology; BMI, body mass index; CPT, Current Procedural Terminology; N/A, not applicable; OR, odds ratio.

Subgroups of patients with increased risk of related readmissions (n = 406) included those between 40 and 49 years (OR 2.66, 95% CI 1.54-4.58, P < .001) and 50 and 59 years (OR 1.78, 95% CI 1.09-2.91, P = .021), who were Black (OR 2.18, 95% CI 1.11-4.27, P = .0230), had BMI between 30 and 34.9 (OR 1.91, 95% CI 1.28-2.85, P < .001), had mild anemia (OR 2.14, 95% CI 1.28-3.56, P = .004) or operative times between 60 and 90 minutes (OR 2.48, 95% CI 1.65-3.73, P < .001). Characteristics that increased the risk of return to operating room (n = 372) included male gender (OR 2.32, 95% CI 1.64-3.27, P < .001), age 40-49 years (OR 2.19, 95% CI 1.25-3.85, P = .007) or >70 years (OR 2.08, 95% CI 1.02-4.25, P = .043), BMI 25 to 29.9 (OR 2.10, 95% CI 1.41-3.15, P < .001), Black ethnicity (OR 2.60, 95% CI 1.26-5.34, P = .010), operative times 60-90 minutes (OR 2.56, 95% CI 1.75-3.73, P < .001), anemia (OR 3.45, 95% CI 1.92-6.19, P < .001), and neuraxial anesthesia (OR 3.16, 95% CI 1.54-6.48, P < .002).

Discussion

The aim of our study was to evaluate the differences in complications between smokers and nonsmokers undergoing ORIF for ankle fractures and to further analyze whether there are certain subgroups of smokers who are at even higher risks for those complications. Smokers were found to have a higher risk of deep wound infection, wound dehiscence, related return to the operating room and related readmissions. Certain characteristics conferred a higher increase in the risk for these complications.

Our study has the largest number of patients analyzing the impact of smoking in ankle fracture fixation, with a total of 33 741 patients. Prior studies were limited to single institution case series30,32,34 where the limited number of patients might not allow an in-depth analysis of risk factors. SooHoo et al 41 have used California’s discharge database and analyzed 57 183 patients who had undergone ORIF for ankle fractures. Smoking was not analyzed in this large population study as the variable was not available. 41

The findings in our study are in contradistinction to other NSQIP studies that have not found any association between smoking and postoperative complications.4,9 These studies have grouped adverse events into aggregates, like severe adverse events, and major or minor local and systemic complications.4,7,9 This grouping of complications makes clinical interpretation of the results difficult as mentioned by Basques et al. 4 Our study aimed to analyze the effect of smoking on individual outcomes that can help surgeons incorporate rigorous measures to avert those complications. Miller et al 30 did not find smoking to be a risk factor for wound complications in a cohort of 478 patients undergoing ankle fracture surgery. They attributed this to extensive counseling of smokers and potentially less cigarette smoking during the healing period. 30 Nåsell et al 31 have found that a 6-week smoking-cessation program started immediately after emergency fracture surgery significantly reduced the postoperative complication rate (P = .048).

Although the rates of deep wound infection and wound dehiscence were low, 0.2% in nonsmokers and 0.4% in smokers, multivariate analysis showed a 2-fold increased risk for developing these complications in smokers, with OR 2.34 (P < .001) and 2.43 (P < .001), respectively. A significant finding in our study was the higher risk of wound complication in certain subgroups. Smokers of Black origin were at a much higher risk for deep wound infections with an OR of 4.24 (P = .044). A recent NSQIP study analyzing patients undergoing orthopaedic trauma surgery has found higher frequencies of deep wound infection (0.5% vs 0.3%, P = .002) among Black patients, although with decreased mortality and postoperative transfusion. 44 Prior studies evaluating complications after ankle fracture surgery have not examined the effect of ethnicity on adverse outcomes.4,7,9,28,30,32,34,41

Smokers in certain age groups were at a higher risk of developing deep wound infections and wound dehiscence than the baseline OR of 2.34 and 2.43 for those complications respectively. Patients between 40 and 49 years had an OR of 3.46 (P = .037) for deep infection and 4.49 (P = .020) for wound dehiscence. The increased risk was even more prominent in the 50-59 years age group with an OR of 5.75 (P = .003) for deep infection and 9.86 (P < .001) for dehiscence. Cornelius et al 11 have reported the highest rate of smoking in adults aged 45-64 years (17.0%) vs 8.2% for 65 years and older. This might also be true for the smoking habits and number of cigarettes consumed per day, with patients in the older age group smoking less. The NSQIP does not record the heaviness of smoking or smokeless tobacco. Although several studies have not found age to be a risk factor for wound complications in ankle fracture surgery,7,30,38 others have found older patients to be at an increased risk of infectious complications.4,41 More pronounced effect of risk factors on certain age groups is not uncommon. Gil et al 17 have found the negative effect of obesity on perioperative complications and hospital costs of open ankle fractures to be primarily manifested in patients with obesity who are younger than 60 years.

Stratification by operative time also showed differences in the risk of wound complications above the baseline for deep wound infection and for wound dehiscence. Smokers with operative times between 60 and 90 minutes had an OR of 3.64 (P < .001) for deep compared to the baseline OR of 2.34. Similarly, smokers with operative times between 90 and 120 minutes had a 2-fold increased risk of wound dehiscence (OR 4.88, P < .001) compared to the baseline risk of 2.43. Ovaska et al 34 have found increased risk of wound infections (OR 2.07, P < .001) in patients with operative times more than 90 minutes. The effect of operative time has been studied in several elective orthopaedic procedures like total hip and knee arthroplasty.10,45 However, in ankle fracture surgery, operative time might be dictated by the complexity of the fracture, which the ACS-NSQIP does not report; thus, its independent effect on outcomes is difficult to assess.

The same trend of increased risk for wound infection and dehiscence above the baseline was seen in smokers with BMI between 30 and 34.9 (obese) and 35 and 39.9 (severely obese). This finding is expectable given the high risk obesity has on postoperative wound and other complications. 33 Several studies have found that obesity does not increase the rate of complications after ankle fracture fixation8,42; however, obese patients tend to have higher number of medical comorbidities and sustain more complex fracture types than nonobese patients.24,42

A significant finding in our study was the highly increased risk of wound dehiscence in the subgroup of smokers undergoing spinal/epidural anesthesia (OR 9.31, P < .002). None of the prior studies have assessed the impact of anesthesia type on complications after ORIF of ankle fractures.4,7,9,28,38,41 This finding can be due to selection bias, where the sicker patients with more comorbidities were given neuraxial anesthesia.

Mild anemia too conferred an increased risk for deep wound infection and wound dehiscence above the baseline. Although the negative effects of anemia on postoperative outcomes have been studied in hip and knee arthroplasty18,46 and hip fracture surgery,19,20 only 1 study has found anemia to be a risk factor for “any adverse event” in ankle fracture surgery. 9

Stratification by fracture type showed that trimalleolar fractures posed a 3-fold increased risk of wound dehiscence in smokers compared with nonsmokers treated for the same fracture type (OR 3.28, P = .005). Sato et al 38 have found both smoking and trimalleolar fractures to be independent risk factors for infection after surgical fixation of ankle fractures.

Our study is the first to address related return to the operating room and related readmissions. Basques et al 4 found only ASA more than 3 to be a risk factor for any readmission after ORIF of ankle fractures. Although smokers in our study were the healthier cohort, they had a higher risk for reoperations and readmission related to the index surgery. A recent study comparing union rates in midfoot and hindfoot arthrodesis has also found smokers to be younger in age and with less comorbidities, although with increased rates of nonunion and infection. 1 Our stratification analyses identified subgroups of smokers at even a higher risk for related readmissions and related reoperations (Table 4). This is important for patient counseling and for hospitals as this might incur additional costs that might not be covered if a bundled payment gets implemented for ankle fracture surgery. 3 This is in addition to the indirect costs that can occur because of time away from work or loss of productivity due to the readmissions. Belatti and Phisitkul 6 have shown that in 2011, treatments for ankle fractures and dislocation had contributed the most (31.0% of $11 billion) to the overall economic burden of foot and ankle surgery in the Medicare population, with more than 80% of the cost from indirect costs, like temporary work loss. 6

Table 4.

Stratification of Patients With Readmission and Reoperation.

Readmission
(n = 406)		 Return to Operating Room
(n = 372)
Nonsmokers, n (%) Smokers, n (%) Adjusted OR (95% CI) P Value Nonsmokers, n (%) Smokers, n (%) Adjusted OR (95% CI) P Value
Overall 287 (1.10) 119 (1.50) 1.67 (1.32-2.09) <.001 247 (1.00) 125 (1.50) 1.69 (1.36-2.11) <.001
Age, y
 ≤39 42 (0.50) 29 (0.80) 1.57 (0.97-2.53) .066 55 (0.70) 42 (1.22) 1.67 (1.12-2.51) .013
 40-49 24 (0.70) 30 (1.90) 2.66 (1.54-4.58) <.001 26 (0.71) 24 (1.48) 2.19 (1.25-3.85) .007
 50-59 39 (0.80) 29 (1.70) 1.78 (1.09-2.91) .021 38 (0.80) 30 (1.74) 1.76 (1.07-2.90) .026
 60-69 66 (1.40) 22 (2.20) 1.45 (0.89-2.37) .138 60 (1.25) 20 (2.01) 1.38 (0.82-2.32) .226
 ≥70 109 (2.50) 8 (2.60) 0.99 (0.48-2.06) .986 61 (1.41) 9 (2.98) 2.08 (1.02-4.25) .043
Gender
 Female 188 (1.19) 69 (1.71) 1.77 (1.31-2.38) <.001 163 (1.03) 61 (1.51) 1.50 (1.11-2.03) .008
 Male 99 (1.00) 50 (1.23) 1.53 (1.07-2.19) .020 84 (0.85) 64 (1.58) 2.32 (1.64-3.27) <.001
Race/ethnicity
 White 214 (1.30) 70 (1.43) 1.48 (1.11-1.98) .008 183 (1.11) 75 (1.53) 1.43 (1.09-1.89) .010
 Black 18 (0.81) 19 (1.65) 2.18 (1.11-4.27) .023 13 (0.59) 18 (1.57) 2.60 (1.26-5.34) .010
 Asian 5 (0.92) 0 (0.00) N/A N/A 3 (0.55) 0 (0.00) N/A N/A
 Other 50 (0.78) 30 (1.52) 2.06 (1.30-3.27) .002 48 (0.75) 32 (1.62) 2.37 (1.50-3.76) <.001
ASA class
 I, II 117 (0.63) 64 (1.09) 2.01 (1.47-2.77) <.001 117 (0.63) 70 (1.19) 1.92 (1.43-2.59) <.001
 III, V 169 (2.37) 55 (2.51) 1.38 (0.99-1.92) .060 129 (1.81) 55 (2.51) 1.46 (1.06-2.03) .021
Operative time
 <60 min 94 (0.93) 36 (1.08) 1.24 (0.84-1.84) .281 82 (0.81) 44 (1.32) 1.68 (1.16-2.45) .007
 60-90 min 84 (1.04) 41 (1.69) 2.48 (1.65-3.73) <.001 71 (0.88) 47 (1.94) 2.56 (1.75-3.73) <.001
 90-120 min 62 (1.47) 23 (1.77) 1.50 (0.90-2.52) .123 53 (1.26) 14 (1.08) 0.89 (0.49-1.62) .701
 >120 min 47 (1.45) 19 (1.82) 1.27 (0.74-2.17) .392 41 (1.26) 20 (1.92) 1.52 (0.89-2.62) .128
BMI
 18.5-24.9 44 (1.03) 15 (0.86) 1.11 (0.59-2.08) .753 33 (0.77) 16 (0.92) 1.22 (0.67-2.24) .519
 25-29.9 63 (0.77) 38 (1.47) 3.40 (2.26-5.10) <.001 60 (0.74) 41 (1.59) 2.10 (1.41-3.15) <.001
 30-34.9 94 (1.24) 41 (1.86) 1.91 (1.28-2.85) .001 81 (1.06) 38 (1.72) 1.75 (1.18-2.60) .005
 35-39.9 54 (1.74) 12 (1.33) 0.98 (0.51-1.88) .957 42 (1.36) 20 (2.21) 1.66 (0.97-2.86) .066
 ≥40 32 (1.33) 12 (1.98) 2.07 (1.03-4.18) .042 30 (1.25) 9 (1.48) 1.25 (0.59-2.65) .569
Diabetes
 Diabetes on insulin 51 (3.83) 14 (5.00) 1.37 (0.75-2.54) .309 38 (2.86) 10 (3.57) 1.20 (0.59-2.44) .621
 Diabetes on oral drugs 25 (1.40) 8 (2.25) 1.60 (0.71-3.60) .255 21 (1.17) 9 (2.54) 2.39 (1.07-5.33) .033
Anesthesia technique
 General 240 (1.07) 107 (1.46) 1.73 (1.36-2.21) <.001 202 (0.90) 109 (1.48) 1.71 (1.35-2.17) <.001
 Spinal/epidural 26 (1.25) 7 (1.50) 1.21 (0.52-2.83) .653 23 (1.11) 13 (2.79) 3.16 (1.54-6.48) .002
Hematocrit (%)
 Mild anemia 65 (2.02) 25 (2.99) 2.14 (1.28-3.56) .004 45 (1.40) 23 (2.75) 2.27 (1.34-3.82) .002
 Moderate-severe anemia 48 (2.94) 13 (4.21) 1.58 (0.84-2.97) .159 35 (2.15) 19 (6.15) 3.45 (1.92-6.19) <.001
CPT code
  CPT code 27766 15 (1.08) 6 (1.13) 1.11 (0.43-2.90) .826 8 (0.57) 8 (1.50) 2.49 (0.93-6.71) .071
  CPT code 27769 (0.00) (0.00) N/A N/A 2 (0.88) 1 (1.52) 2.36 (0.19-29.55) .506
  CPT code 27792 57 (0.70) 33 (1.22) 1.69 (1.10-2.60) .017 54 (0.66) 41 (1.52) 2.22 (1.47-3.35) <.001
  CPT code 27814 115 (1.23) 45 (1.58) 1.67 (1.15-2.43) .007 115 (1.23) 46 (1.61) 1.39 (0.98-1.97) .065
  CPT code 27822 72 (1.46) 29 (1.90) 1.76 (1.10-2.80) .018 50 (1.01) 25 (1.64) 1.72 (1.06-2.81) .030
  CPT code 27823 28 (1.80) 6 (1.41) 0.76 (0.31-1.84) .540 18 (1.16) 4 (0.94) 1.11 (0.36-3.37) .860
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Abbreviations: ASA, American Society of Anesthesiology; BMI, body mass index; CPT, Current Procedural Terminology; N/A, not applicable; OR, odds ratio.

There are several limitations in this study. The ACS-NSQIP collects information up to 30 days postoperatively; as such, complications occurring past that time cannot be captured. Similarly, functional outcomes cannot be assessed due to the short followup period. Other shortcomings of the database include inability to gather data concerning surgical techniques, postoperative protocols, surgeon experience, venous thromboembolism prophylaxis, use of tourniquet or drains. These limitations, however, should affect both study groups similarly.

Conclusion

Although the 30-day complication rates were low, smokers undergoing ORIF for ankle fractures were at an increased risk of deep wound infection, wound dehiscence, related return to operating room, and related readmissions. Specific patient characteristics that pose further increased risk of these complications include age (40-59 years), Black ethnicity, elevated BMI, anemia, prolonged operative times, and spinal/epidural anesthesia. With a high prevalence of smoking in society, research should focus on identifying those predisposed patients and tailoring specific perioperative measures to reduce the risk of complications. Large-database studies with longer follow-up periods are needed to better validate these findings.

Footnotes

Ethical Approval: In accordance with our institutional guidelines, which follow the US Code of Federal Regulations for the Protection of Human Subjects, institutional review board approval was not needed for our analysis because data were deidentified and collected as part of a quality assurance activity

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. ICMJE forms for all authors are available online.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs: Bernard H. Sagherian, MD, FACS, Inline graphic https://orcid.org/0000-0001-5359-9027

Jawad J. Hoballah, MS, Inline graphic https://orcid.org/0000-0002-6900-5462

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