1. Introduction
Racial disparities are well-documented in orthopaedic surgery. Compared with non-Hispanic White patients, minority patients have lower rates of surgical utilization because of lesser access to care resulting from systemic biases, differences in patient attitudes and expectations regarding surgical care and outcomes, and socioeconomic barriers.1–5 Such discrepancies are seen during the postoperative course, with racial disparities being associated with opioid pain management, length of hospital stay, rehabilitation use and outcomes, and postoperative complications.6–11 Consequently, both long-term and short-term functional outcomes are worse for Black and Hispanic patients, compared with their White counterparts, even after controlling for socioeconomic measures12–14; fracture care is unfortunately no exception to these trends.
Fractures distal to the knee are among the most common orthopaedic injuries that present to emergency departments, with a range of 14%–72% requiring operative treatment.15,16 Recent reports estimate the total incidence of ankle fractures to be approximately 4.22 cases per 10,000 person-years—2.85/10,000 person-years for White patients and 3.01/10,000 person-years for Black patients.17 Previous studies have established race-based differences in surgical management of hip fractures and pathological fractures of the lower extremity, with some indicating that Black patients experience delays in evaluation and time to surgery despite similar indications and preoperative considerations.9,18–21 They also have higher rates of postoperative adverse events, including reintubation, pulmonary embolism, renal failure, cardiac arrest, and mortality.13,19,20 Despite the high volume of fractures that occur distal to the knee, studies assessing racial disparities in their management are lacking. With the aging of the population and subsequent rise in the prevalence of such fractures, especially among the elderly,22,23 understanding race-based inequalities in outcome is becoming increasingly important. Furthermore, national initiatives have been used in recent years to address racial disparities in surgical care, and continued analysis of their trends—whether inequalities have improved, worsened, or remained the same—is essential to guide current and future efforts.5
The aims of this study were to determine whether (1) 30 days postoperative complications and (2) time to surgery for operative fixation of fractures distal to the knee differ for Black versus White patients after controlling for confounding variables using propensity score matching. A secondary aim of this study was to assess whether disparities exist by fracture pattern.
2. Materials and Methods
This study was deemed exempt from institutional review board and committee on research ethics approval because it used only a publicly available, deidentified database. The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database was queried for the years 2010–2019. NSQIP contains patient-level, aggregated data from more than 700 participating institutions in the United States, each with clinical reviewers trained in collecting and submitting data. Data on preoperative demographic information and risk factors, intraoperative variables, and short-term postoperative complications are recorded for patients 18 years or older undergoing surgical procedures. Previous studies have demonstrated high inter-rater reliability and validity with data collection using NSQIP, and the database has been widely used throughout the orthopaedic literature.19,24,25
2.1. Patient Selection
To determine our cohort, we first used the appropriate International Classification of Diseases (ICD)–9 and ICD-10 codes to identify patients who presented with fractures distal to the knee at participating NSQIP sites between 2010 and 2019 (ICD-9: 823–826.9, ICD-10: S82-S82.9, S92-S92.9). We then refined our cohort to include only patients who underwent operative fixation for the specified fractures using Current Procedural Terminology (CPT) codes. The following codes were included on the basis of open fixation of fractures distal to the knee: 27758, 27759, 27766, 27769, 27784, 27792, 27814, 27822, 27823, 27826, 27827, 27828, 28415, 28420, 28445, 28465, 28485, 28505, 28525, and 28531. These criteria yielded 43,904 cases of operatively treated fractures distal to the knee in adult patients from 2010 to 2019. Cases were excluded if they had missing values (n = 32,283) or if patients were of races that were not Black or non-Hispanic White (n = 2449). Patients of other races were not included in the analysis because low sample sizes did not allow for adequate comparison. Non-White races were not grouped into one heterogeneous category because this practice is suspected to hinder the accurate determination of potential disparities.26 After exclusion, 9172 cases were included in the final analysis. Of these, 1120 patients (12%) were Black.
2.2. Patient Characteristics and Outcomes
We assessed the following patient characteristics and preoperative risk factors: race/ethnicity, age, sex, body mass index (BMI), American Society of Anesthesiologists (ASA) physical status classification, anemia, hypertension, diabetes, congestive heart failure, end-stage renal disease, pulmonary disease, steroid use, functional dependence, and smoking status. BMI was calculated using height and weight measurements provided by NSQIP. Fracture subtypes were further parsed out for more nuanced analyses. These were tibia and/or fibula shaft fractures (CPT codes: 27758, 27759, and 27784; n = 1569), isolated malleolar fractures (CPT codes: 27766, 27769, and 27792; n = 1794), bi/trimalleolar fractures (CPT codes: 27814, 27822, and 27823; n = 4922), and pilon fractures (CPT codes: 27826, 27827, and 27828; n = 811). Subanalysis for foot fractures by race was inadequately powered and thus not performed (n = 76).
The primary outcome was incidence of 30 days postoperative complications. We analyzed for major adverse events (failure to wean off mechanical ventilation, cerebrovascular events, renal failure, cardiovascular events [myocardial infarction and cardiac arrest], unplanned reoperation, and death), minor adverse events (reintubation, wound complications [surgical site infection and wound dehiscence], pneumonia, thromboembolic events [deep vein thrombosis and pulmonary embolism], and urinary tract infections), and unplanned readmission. Complications were considered an adverse event only if they developed in the postoperative course, not if they initially presented in the preoperative phase and continued postoperatively. The secondary outcome was time to surgical fixation from hospitalization.
2.3. Propensity Score Matching
As has been performed for previous NSQIP studies in the orthopaedic literature,19,27,28 we performed 1:1 nearest-neighbor propensity score matching to minimize confounding effects. We matched Black and non-Hispanic White patients based on age, sex, BMI, functional status (independent, partially dependent, or totally dependent), anemia, end-stage renal disease, congestive heart failure, and pulmonary disease.
Of the 8052 non-Hispanic White patients in our cohort, we identified 1120 with equal propensity scores as our Black patients (P = 0.90). Before matching, Black patients were significantly younger than White counterparts (51 ± 16 vs. 59 ± 17 years, P < 0.001) with higher BMIs (32 ± 7.9 vs. 31 ± 7.7, P = 0.005). A higher proportion of Black patients also had anemia (45% vs. 37%, P < 0.001) and end-stage renal disease (3.7% vs. 1.2%, P < 0.001), whereas a greater proportion of White patients were female (64% vs. 60%, P = 0.02) and had pulmonary disease (12% vs. 6.2%, P < 0.001). After propensity score matching, characteristics and comorbidities were comparable by race (P > 0.05) (Table 1).
TABLE 1 -
Characteristics and Comorbidities of 9172 Adult Patients Who Underwent Open Fixation of Below-Knee Fracture by Race, 2010–2019.
| Parameter |
Total (%), N = 9172 |
Black (%), N = 1120 |
White Unmatched, N = 8052 |
White Matched, N = 1120 |
| N (%) |
P
|
N (%) |
P
|
| Age, yrs*
|
58 ± 17 |
51 ± 16 |
59 ± 17 |
<0.001 |
51 ± 17 |
0.59 |
| BMI, kg/m2
*
|
31 ± 7.7 |
32 ± 7.9 |
31 ± 7.7 |
0.005 |
32 ± 8.8 |
0.72 |
| Female patients |
5810 (63) |
673 (60) |
5137 (64) |
0.02 |
675 (60) |
0.93 |
| ASA class†
|
| 1 |
558 (6.1) |
83 (7.4) |
475 (5.9) |
<0.001 |
102 (9.1) |
0.21 |
| 2 |
3847 (42) |
520 (46) |
3327 (41) |
480 (43) |
| 3 |
4142 (45) |
444 (40) |
3698 (46) |
466 (42) |
| 4 |
620 (6.8) |
70 (6.3) |
550 (6.8) |
72 (6.4) |
| 5 |
0 (0.0) |
0 (0.0) |
0 (0.0) |
0 (0.0) |
| 6 |
1 (0.01) |
1 (0.09) |
0 (0.0) |
0 (0.0) |
| Anemia |
3479 (38) |
506 (45) |
2973 (37) |
<0.001 |
481 (43) |
0.29 |
| End-stage renal disease |
135 (1.5) |
41 (3.7) |
94 (1.2) |
<0.001 |
38 (3.4) |
0.73 |
| Congestive heart failure |
142 (1.6) |
14 (1.3) |
128 (1.6) |
0.39 |
17 (1.5) |
0.59 |
| Pulmonary disease |
995 (11) |
69 (6.2) |
926 (12) |
<0.001 |
70 (6.3) |
0.93 |
| Functionally dependent |
632 (6.9) |
67 (6.0) |
565 (7.0) |
0.20 |
76 (6.8) |
0.44 |
*Data displayed as mean ± SD.
†Total number of patients does not add up to 9172 because 4 cases did not have ASA classes assigned (Black N = 2, White N = 2).
2.4. Statistical Analysis
After propensity score matching, Black and White patients were statistically similar. Chi-square and Student t tests were performed to investigate associations of race with 30-day postoperative complications (major adverse events, minor adverse events, and unplanned readmission) and time to operative fixation of fractures distal to the knee. Multivariable logistic regression was used to assess race as an independent predictor for adverse events, while Poisson regression was used to assess race as an independent predictor for time to surgery—both further controlled for ASA class. Separate univariate and multivariate analyses were performed for each fracture subtype. All analyses were conducted using Stata, version 15.1, software (StataCorp LLC, College Station, TX). Alpha was set at 0.05.
3. Results
3.1. Overall Complications and Time to Surgery
In the multivariable analysis, Black patients had 1.5 times higher odds (95% confidence interval [CI]: 1.0–2.0) of experiencing any early postoperative adverse event compared with matched White counterparts (P = 0.03). Black patients also had 1.9 times higher odds (95% CI: 1.2–3.0) of requiring unplanned readmission within 30 days of open fixation (P = 0.004). Fifty-eight Black patients (5.3%) required short-term readmission, compared with 351 White patients (4.5%)—32 (2.9%) in the matched cohort (Table 2). The most common reasons for readmission by race are listed in Table 3. There were no significant differences by race in overall major or minor adverse events (P > 0.05). Postoperative renal failure was significantly associated with race in the univariate but not multivariable analysis. Time to surgery was also comparable between White and Black patients (P > 0.05) (Table 2).
TABLE 2 -
Thirty Days Postoperative Complications of 9172 Patients Who Underwent Open Fixation of Below-Knee Fracture by Race, 2010–2019.
| Parameter |
Total (%), N = 9172 |
Black (%), N = 1120 |
White Unmatched, N = 8052 |
White Matched (%), N = 1120 |
| N (%) |
P
|
N (%) |
P
|
| Any adverse event |
818 (8.9) |
92 (8.2) |
726 (9.0) |
0.38 |
67 (6.0) |
0.04 |
| Major adverse event |
324 (3.5) |
36 (3.2) |
288 (3.6) |
0.54 |
22 (2.0) |
0.06 |
| Failure to wean ventilation |
31 (0.34) |
2 (0.18) |
29 (0.36) |
0.33 |
3 (0.27) |
0.65 |
| Cerebrovascular event |
6 (0.07) |
2 (0.18) |
4 (0.05) |
0.11 |
0 (0.0) |
0.16 |
| Renal failure |
12 (0.13) |
5 (0.45) |
7 (0.09) |
0.002 |
0 (0.0) |
0.03 |
| Cardiovascular events |
30 (0.33) |
2 (0.18) |
28 (0.35) |
0.35 |
2 (0.18) |
1.0 |
| Reoperation |
227 (2.5) |
27 (2.4) |
200 (2.5) |
0.88 |
17 (1.5) |
0.13 |
| Death |
55 (0.60) |
2 (0.18) |
53 (0.66) |
0.05 |
3 (0.27) |
0.65 |
| Minor adverse event |
460 (5.0) |
52 (4.6) |
408 (5.1) |
0.54 |
35 (3.1) |
0.06 |
| Reintubation |
41 (0.45) |
2 (0.18) |
39 (0.48) |
0.15 |
2 (0.18) |
1.0 |
| Wound complication |
166 (1.8) |
20 (1.8) |
146 (1.8) |
0.95 |
16 (1.4) |
0.50 |
| Pneumonia |
83 (0.90) |
8 (0.71) |
75 (0.93) |
0.47 |
6 (0.54) |
0.59 |
| Thromboembolic event |
64 (0.70) |
10 (0.89) |
54 (0.67) |
0.40 |
7 (0.63) |
0.47 |
| UTI |
135 (1.5) |
13 (1.2) |
122 (1.5) |
0.36 |
6 (0.54) |
0.11 |
| Readmission |
409 (4.6) |
58 (5.3) |
351 (4.5) |
0.23 |
32 (2.9) |
0.005 |
| Time to surgery, days*
|
0.79 ± 1.6 |
0.77 ± 1.7 |
0.79 ± 1.6 |
0.74 |
0.76 ± 1.6 |
0.84 |
UTI, urinary tract infection.
*Data displayed as mean ± SD, 4 outliers (all White patients) were removed from time to surgery analysis.
TABLE 3 -
Reasons for 30-Day Unplanned Readmissions Suspected to be Related to Open Fixation of Below-Knee Fracture by Race, 2010-2019.
| Reasons for Readmission |
N (%) |
| Black, N = 58 |
White, N = 351 |
| Wound complication |
12 (21) |
65 (17) |
| GI complication |
9 (16) |
18 (4.7) |
| Thromboembolic event |
5 (8.6) |
19 (4.9) |
| Recurrent MSK complication |
3 (5.2) |
25 (6.5) |
| Sepsis |
2 (3.4) |
13 (3.4) |
| Cardiac issue |
2 (3.4) |
11 (2.8) |
| Pneumonia |
1 (1.7) |
17 (4.4) |
| Cellulitis |
1 (1.7) |
10 (2.6) |
| Pulmonary complication |
1 (1.7) |
11 (2.8) |
| UTI |
1 (1.7) |
8 (2.1) |
| Renal failure (acute or chronic) |
1 (1.7) |
1 (0.26) |
| Mechanical implant complication |
0 (0) |
14 (3.6) |
| Pain management |
0 (0) |
6 (1.6) |
| Encephalopathy |
0 (0) |
4 (1.0) |
| Other infectious complication |
0 (0) |
3 (0.78) |
| Other |
3 (5.2)*
|
18 (4.7)†
|
| Unknown |
17 (29) |
108 (31) |
GI, gastrointestinal; MSK, musculoskeletal; UTI, urinary tract infection.
*Other readmission reasons for Black patients were urinary retention (N = 1), diabetic complication (N = 1), and neurological issue (N = 1).
†Other readmission reasons for White patients were neurological issues (N = 8), diabetic complications (N = 3), anemia (N = 2), electrolyte abnormalities (N = 2), pelvic inflammatory disease (N = 1), hematuria (N = 1), and failure to thrive (N = 1).
3.2. Complications and Time to Surgery by Fracture Subtype
In the subanalysis by fracture type, Black patients were significantly more likely to require unplanned readmission after fixation of pilon fractures in the univariate analysis (P = 0.05) (Table 4). With our sample size, there were no significant associations with the multivariable models for adverse events or time to surgery (P > 0.05).
TABLE 4 -
Race Associations With 30 Days Postoperative Complications of 9172 Patients by Fracture Type, 2010–2019.
| Parameter*
|
Total (%) |
Black (%) |
White Unmatched |
White Matched (%) |
| N (%) |
P
|
N (%) |
P
|
| Tibia and/or fibula shaft fractures (N = 1569) |
| Any adverse event |
190 (12) |
28 (14) |
162 (12) |
0.29 |
25 (13) |
0.66 |
| Major adverse event |
80 (5.1) |
12 (6.2) |
68 (5.0) |
0.46 |
14 (7.2) |
0.69 |
| Minor adverse event |
105 (6.7) |
15 (7.7) |
90 (6.6) |
0.54 |
12 (6.2) |
0.55 |
| Readmission |
101 (6.6) |
20 (10) |
81 (6.1) |
0.02 |
13 (6.9) |
0.23 |
| Time to surgery, days†
|
0.93 ± 1.4 |
0.91 ± 1.7 |
0.93 ± 1.4 |
0.86 |
0.95 ± 1.3 |
0.81 |
| Isolated malleolar fractures (N = 1794) |
| Any adverse event |
118 (6.6) |
17 (6.1) |
101 (6.7) |
0.72 |
23 (8.2) |
0.33 |
| Major adverse event |
38 (2.1) |
5 (1.8) |
33 (2.2) |
0.68 |
9 (3.2) |
0.28 |
| Minor adverse event |
66 (3.7) |
12 (4.3) |
54 (3.6) |
0.55 |
10 (3.6) |
0.66 |
| Readmission |
64 (3.7) |
8 (3.0) |
56 (3.8) |
0.50 |
17 (6.2) |
0.07 |
| Time to surgery, days†
|
0.58 ± 1.6 |
0.58 ± 1.4 |
0.58 ± 1.6 |
0.96 |
0.62 ± 1.5 |
0.77 |
| Bi/trimalleolar fractures (N = 4922) |
| Any adverse event |
434 (8.8) |
36 (6.9) |
398 (9.0) |
0.11 |
42 (8.1) |
0.48 |
| Major adverse event |
175 (3.6) |
11 (2.1) |
164 (3.7) |
0.06 |
21 (4.0) |
0.07 |
| Minor adverse event |
242 (4.9) |
19 (3.7) |
223 (5.1) |
0.16 |
23 (4.4) |
0.53 |
| Readmission |
196 (4.1) |
20 (3.9) |
176 (4.1) |
0.86 |
15 (2.9) |
0.38 |
| Time to surgery, days†
|
0.80 ± 1.6 |
0.75 ± 1.7 |
0.80 ± 1.6 |
0.47 |
0.88 ± 2.0 |
0.28 |
| Pilon fractures (N = 811) |
| Any adverse event |
74 (9.1) |
11 (9.6) |
63 (9.1) |
0.86 |
7 (6.1) |
0.33 |
| Major adverse event |
31 (3.8) |
8 (7.0) |
23 (3.3) |
0.06 |
3 (2.6) |
0.12 |
| Minor adverse event |
45 (5.6) |
6 (5.2) |
39 (5.6) |
0.87 |
4 (3.5) |
0.52 |
| Readmission |
47 (6.0) |
10 (8.8) |
37 (5.5) |
0.17 |
3 (2.7) |
0.05 |
| Time to surgery, days†
|
0.95 ± 2.2 |
1.2 ± 2.4 |
0.92 ± 2.1 |
0.27 |
1.1 ± 2.3 |
0.76 |
*Subanalysis not performed for foot fractures because of low sample size (N = 76).
†Data displayed as mean ± SD.
4. Discussion
Understanding patterns of racial disparities in operative treatment is critical for basing interventions to target and improve equity of tertiary care. The results of this study demonstrate that for operatively treated fractures distal to the knee, Black patients were significantly more likely to experience any adverse event and require readmission within 30 days of surgery compared with White counterparts matched for major preoperative characteristics and comorbidities. However, time to surgery was comparable, and racial discrepancies were not seen when considering fracture subtypes separately. In context of the current literature, our findings illustrate that racial disparities in operative management of lower extremity trauma extend beyond hip and pathological fractures to more minor fracture patterns.9,18–21
This study identified racial disparities in early adverse events for Black versus White patients after open fixation of fractures distal to the knee. Specifically, this trend is driven by differences in the rate of 30-day readmission by race, with Black patients having 1.9 times greater odds of unplanned readmission for postoperative complications related to fracture fixation. Previous studies have shown this association for other orthopaedic traumas.9,12,29–31 The most common reasons for procedure-related readmission were wound complications, gastrointestinal complications, thromboembolic events, and recurrent musculoskeletal issues. These findings may be due to known socioeconomic risk factors for early readmission that are more commonly seen with minority patients, such as living alone, limited education, poor family support, and less financial resources.32 Genetic factors that have yet to be elucidated, including susceptibility to infection and thromboembolic events, must also be considered. Risk may be further exacerbated by greater hesitancy among Black patients in seeking medical attention, with reasons including mistrust or concerns regarding discrimination.33,34 Communities located in rural areas or with larger proportions of impoverished, uninsured, and Black patients also tend to have lower access to trauma care.35–37 Altogether, these measures can prolong time to presentation to the emergency department, inhibit seeking of adequate postoperative care, and impede timely responsiveness to complications. Moreover, hospitals that care for primarily minority patients have been shown to have worse outcomes because of resource shortage.38–40 Thereby, higher readmission rates in Black patients may be influenced in part by decreased quality of the trauma center, provider training, nursing staff availability, and discharge to postoperative rehabilitation.41,42 Short-term readmission rate is increasingly being considered a metric of quality of care, and efforts to reduce disparities—including increasing trauma center density and related resources around vulnerable populations—must be pursued.
Interestingly, the data presented did not demonstrate a significant difference in time to surgery for Black versus White patients. This contrasts with previous studies that have largely illustrated a delay in operative fixation of hip and pathological fractures for minorities.9,18–20 It is unclear why a disparity is not seen in our cohort. Our finding may represent that positive changes are occurring in response to evidence on racial disparities in orthopaedic care. We speculate that the lower severity of the fractures included in this study perhaps translates to a lesser need for extensive resources (ie, operating room time and highly trained surgeons) that are scarcer in hospitals that predominantly treat minorities. Similarly, fractures distal to the knee may be less likely to present to large trauma centers, which are subject to crowding and lengthy surgical delays, given their lower complexity.21,43 As a result, systemic biases may play a more minor role in influencing the allocation of resources here than for other, more involved lower extremity traumas. Currently, the value of early surgery is unclear for this group of heterogenous fractures, and further research must be conducted to determine outcomes based on timing of external and internal fixation. It is important to note that NSQIP records the time to surgery from current hospital admission, not initial trauma presentation, so the values in this study are likely falsely low and hide possible discrepancies in surgical delay secondary to patient factors. Future research must continue to assess the factors contributing to the presence or absence of delays in fracture fixation by race to best determine health care gaps, such as patient education and access to postoperative follow-up, and guide direction of available resources.
Furthermore, we determined that adverse events and time to surgery were not independently associated with race for any pattern subtype within fractures distal to the knee. For pilon fractures, higher readmission rates were correlated with Black race in the univariate analysis, which may reflect the challenging nature of the fracture pattern given its combination of articular comminution and metadiaphyseal osseous deficits.44 However, this trend was rendered insignificant when ASA class was considered in the multivariable regression. Given that strong associations were seen when considering the entire cohort, the lack of significance within fracture pattern types is likely secondary to the subanalysis being underpowered.
Our study is subject to the limitations characteristic of all database analyses. First, we were unable to determine and match for the severity of fractures in our patient cohort. Second, our analyses were limited by the variables available in the NSQIP database. We were unable to account for important patient socioeconomic factors (ie, education and insurance status) and community-level and hospital-level factors that have been hypothesized to mediate the relationship between race and care measures. While consideration of these factors may change effect magnitude, the association with race is expected to persist as has been shown in previous studies.9,21,30 Third, the size of our cohort, although large, was not sufficient to completely eliminate age through propensity score matching or to detect significant differences by fracture subtype. Finally, this study was conducted using a retrospective insurance claims database and is subject to coding errors, such as for ICD codes. However, these errors, if present, likely affect only a small percentage of patients and should affect both the Black and White cohorts similarly.
5. Conclusion
Racial disparities in short-term complication rate and unplanned readmission persist for operatively managed fractures distal to the knee after patients are matched by major characteristics and comorbidities. Black patients are subject to greater risk of early postoperative complications requiring unplanned readmission, which may be secondary to a host of patient, community, and institutional factors. Yet, time to surgery was similar by race, and discrepancies were not appreciated within fracture subtypes. Overall, interventions to address racial inequalities in lower extremity trauma must consider the value of differences between proximal and distal fracture patterns and the main causes of persistent differences in outcomes affecting vulnerable communities.
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