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Analysis of Incidence and Outcome Predictors for Patients Admitted to US Hospitals with Acetabular Fractures from 1990 to 2010

Authors:
Author Affiliation | Disclosures

Authors’ Disclosure Statement: The authors report no actual or potential conflict of interest in relation to this article.

Dr. Best is a Resident Physician, Department of Orthopaedic Surgery, Johns Hopkins Hospital, Baltimore, Maryland. Dr. Buller is a Clinical fellow, Adult Reconstruction and Joint Replacement Division, Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, New York. Dr. Quinnan is Assistant Professor of Clinical Orthopaedics, Trauma Surgery, University of Miami/Jackson Memorial Hospital, Miami, Florida.

Address correspondence to: Leonard T. Buller, MD, Hospital for Special Surgery, 535 East 70th street, New York, NY 10021 (tel, 216-780-6534; email, bullerl@hss.edu).

Am J Orthop. 2018;47(9). Copyright Frontline Medical Communications Inc. 2018. All rights reserved.

Abstract

The incidence of acetabular fractures and associated in-hospital complication rates in the United States are poorly defined. Studies evaluating predictors of outcome for isolated acetabular fractures are weakly generalizable due to small sample sizes or the inclusion of all types of pelvic fractures. This study sought to analyze trends in acetabular fractures and associated complications in the US using the largest and most recent national dataset available.

The National Hospital Discharge Survey was queried to identify all patients admitted to US hospitals with acetabular fractures between 1990 and 2010. A representative cohort of 497,389 patients was identified, and multivariable logistic regression was used to identify independent predictors of mortality, adverse events, requirement of blood transfusion, and operative treatment with open reduction and internal fixation (ORIF).

Between 1990 and 2010, the population-adjusted incidence of acetabular fractures increased from 7.8 to 9.5/100,000 capita (P < .001). Mortality declined from 5.9% to 0.4% (P < .001), paralleling an increase in the proportion of patients treated with ORIF (12.6%-20.4%, P < .001), which was the variable associated with the lowest odds of mortality. Surgical intervention was associated with higher odds of adverse events and a requirement for blood transfusion. The average in-hospital length of stay decreased from 17.0 days to 10.3 days (P < .001).

This study provides the largest and most comprehensive epidemiologic analysis of acetabular fractures in the US. Knowledge of the increasing incidence of acetabular fractures and prognostic factors associated with poor outcomes may improve outcomes.




Take-Home Points

  • The population-adjusted incidence of acetabular fractures increased between 1990 and 2010. Mortality associated with acetabular fractures decreased from 5.9% to 0.4% between 1990 and 2010.
  • The proportion of patients treated with ORIF increased from 12.6% to 20.4% between 1990 and 2010.
  • The average in-patient hospital length of stay following acetabular fracture decreased from 17.0 to 10.4 days between 1990 and 2010.
  • ORIF is associated with the lowest odds of mortality following acetabular fracture.

Acetabular fractures are major injuries frequently associated with life-altering sequelae1 and a significant resulting cost to society.2 Acetabular fractures are most often the result of a high-energy trauma3-5 or fall from a height.5,6 Functional outcomes and the prevention of post-traumatic arthritis have been shown to depend upon the accuracy of operative reduction.7-9 However, literature on the epidemiology of acetabular fractures is largely limited to European countries,1,10 and their incidence in the United States is more poorly defined.11 Published mortality rates in the existing literature vary widely from 2% to 45%,12-14 and few studies have identified the risk factors associated with in-hospital complications.15 While age, gender, and high-velocity mechanisms have been linked to increased mortality and complications,14-16 the evidence for these associations is poorly generalizable due to the inclusion of all pelvic fractures in these studies. Some reports suggest that advances in surgical management have improved survival and functional outcome,15,17 but these are based upon small cohorts. Knowledge of the incidence and patterns of disease burden are crucial for the allocation of limited healthcare resources.

This study sought to describe the trends in incidence as well as the factors influencing mortality and the risk of complications for patients admitted to US hospitals with an acetabular fracture using the National Hospital Discharge Survey (NHDS), the most recently available Centers for Disease Control and Prevention data, which is also one of the largest inpatient databases in the US. Knowledge of the factors influencing outcomes for patients admitted with acetabular fractures may improve management and decrease complications.

Methods

National Hospital Discharge Survey

The NHDS, developed by the National Center for Healthcare Statistics division of the Centers for Disease Control and Prevention,18 was used to estimate the incidence of acetabular fractures and to evaluate the risk factors for ensuing mortality and inpatient complications. The NHDS is a publically available survey providing demographic and medical data for inpatients discharged from non-federal, short-stay hospitals in the US.19 The NHDS is the principal database used by the US government for monitoring hospital use and is considered the most comprehensive of all inpatient surgical databases in use today.19 The survey uses International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes20 to classify medical diagnoses and procedures. The NHDS uses a stratified, multistage probability design to collect demographic information (age, gender, race), expected source of payment (insurance status), medical information of up to 7 discharge diagnoses and up to 4 procedures, length of care, hospital size, US region, and inpatient outcomes including discharge destination.21 To ensure unbiased national sampling of inpatient records, the NHDS uses a complex, 3-stage probability design including inflation by reciprocals of the probabilities of sample selection, adjustment for no response, and population weighting ratio adjustments.19 This study did not require approval by the Institutional Review Board because the NHDS is a publically available database with no patient-identifying information.

Patient Selection

All patients admitted to hospitals in the US with a fracture of the acetabulum between 1990 and 2010 were identified using ICD-9-CM codes. Discharges with a diagnosis code (ICD-9-CM) of closed fracture of the acetabulum (808.0) or open fracture of the acetabulum (808.1) were identified using previously described techniques.22 The database was subsequently queried to identify patients treated using open reduction and internal fixation (ORIF) (ICD-9-CM, 79.30/79.39), closed reduction and internal fixation (CRIF) (ICD-9-CM, 79.10/79.19), or external (ICD-9-CM, 78.10/78.19) or internal (ICD-9-CM, 78.50/78.59) fixation without reduction. Demographic variables were then collected, including age, sex, primary diagnosis, associated diagnoses, type of fracture (open vs closed), prevalence of comorbidities, length of stay, and discharge destination. The complication screening package23 was used to determine the incidence of complications. The variable adverse event was created on the basis of the variables postoperative bleeding (998.1), acute postoperative infection (998.5), acute postoperative anemia (285.1), acute renal failure (584), acute myocardial infarction (410), pulmonary embolism (415.1), induced mental disorder (293), pneumonia (480-486), pulmonary insufficiency (518.5), deep venous thrombosis (453.4), intubation (96.xx), and blood transfusion (99.x).

Statistical Analysis

Because of the large sample size, a normal distribution of the data was assumed. Differences between categorical variables were compared using the Pearson chi square test, while the independent-samples t test was used to compare differences between continuous variables. To determine independent predictors of in-hospital outcomes (death, adverse events, requirement for blood transfusion, or treatment with ORIF), all variables present in at least 2% of the population24 were included in a multivariable binary logistic regression model. For in-hospital adverse events, a 1% cutoff was used due to their lower rates of occurrence, as previously described.25 The dichotomous variables were death, presence of adverse events, receipt of blood transfusion, and treatment with ORIF. A multivariable regression model allows for the control of potential confounders, isolating the effect of individual variables on inpatient outcomes. Covariates accounted for in the regression model included gender, age, region of the country, and preexisting comorbidities (diabetes mellitus, hypertension, congestive heart failure, coronary artery disease, atrial fibrillation). To assess the association between individual variables and inpatient outcomes, odds ratios and confidence intervals were calculated. A P value of <.001 was used to define statistical significance, correcting for multiple comparisons, as previously described.25 US census data were used to obtain national population estimates for each year of the study from 1990 to 2010.26 Rates were presented as the number of acetabular fractures per 100,000 standard population. All data were analyzed using the software Statistical Package for the Social Sciences [SPSS] version 20.

Results

Incidence and Demographics

A cohort representative of 497,389 patients with a diagnosis of acetabular fracture was identified between 1990 and 2010 (Table 1). In 1990, 19,560 cases (7.84 per 100,000 capita) of acetabular fractures were recoded, while in 2010, the number of cases increased to 29,373 or 9.5 per 100,000 capita (P < .001) (Table 2). The mean age of patients with an acetabular fracture was 52.6 years (standard deviation [SD], 23.7) and 60.6% were male (Table 1). The most frequently associated diagnosis was closed fracture of the pelvis (29.8%) followed by fracture of the femur (13.1%) and closed fracture of the ilium (3.8%) (Table 1). Of the total cohort, 23.2% underwent ORIF (Table 1). In 1990, 12.6% of patients with a diagnosis of acetabular fracture underwent ORIF, whereas 20.4% of patients underwent ORIF in 2010 (P < .001) (Table 2). Average length of hospital stay was 8.3 days (SD, 17.9) overall (Table 1). In 1990 the average length of stay was 17.0 days (SD, 14.9), decreasing to 10.3 days (SD, 9.3) in 2010 (P < .001) (Table 2).

Mortality

In-hospital mortality decreased from 5.9% in 1990 to 0.4% in 2010 (P < .001) (3.5% for the total cohort) (Tables 1 and 2). Multivariable logistic regression analysis demonstrated pulmonary insufficiency (odds ratio [OR], 9.07; 95% confidence interval [CI], 8.52-9.66; P < .01), pneumonia (OR, 3.22; 95% CI, 3.05-3.39; P < .01), and age >85 years (OR, 2.28; 95% CI, 2.16-2.40; P < .01) to be associated with the highest odds of inpatient mortality. CRIF (OR, 1.99; 95% CI, 1.78-2.23; P < .01), external fixator (OR, 1.82; 95% CI, 1.45-2.29; P < .01), and having received a blood transfusion (OR, 1.81; 95% CI, 1.71-1.91; P < .01) were also associated with increased odds of mortality. Treatment with ORIF (OR, 0.19; 95% CI, 0.17-0.20; P < .01) was independently associated with decreased odds of inpatient mortality, as was age <20 years (OR, 0.26; 95% CI, 0.23-0.30; P < .01) (model fit: for omnibus test of model coefficients, X = 25,966 P < .01; Nagelkerke, R2 = 0.20) (Table 3).

Comorbidities and Adverse Events

The prevalence of comorbidities and adverse events is listed in Tables 4 and 5, respectively. Hypertensive disease was the most common comorbidity at 15.3%, followed by diabetes mellitus at 6.9%. Overall, 25.9% of patients experienced an in-hospital adverse event, with the most common being postoperative anemia (7.3%) and blood transfusion (8.1%) (Tables 1 and 5). The percentage of patients experiencing an adverse event increased from 10.9% in 1990 to 37.6% in 2010 (P < .01) (Table 2). Multivariable logistic regression analysis revealed CRIF (OR, 3.08; 95% CI, 2.91-3.26; P < .01), coronary artery disease (OR, 2.02; 95% CI, 1.91-2.15; P < .01), associated femoral neck fracture (OR, 1.53; 95% CI, 1.47-1.60; P < .01), and ORIF (OR, 1.22; 95% CI, 1.20-1.24; P < .01) to be associated with higher odds of inpatient adverse events (model fit: for omnibus test of model coefficients, X = 160,275, P < .01; Nagelkerke, R2 = 0.41) (Table 6).

Blood Transfusion

Overall, 7.3% of patients experienced acute postoperative anemia (Table 5). Between 1990 and 2010, the percentage of patients receiving blood transfusions increased from 0.3% to 9.5%, respectively (P < .01) (Table 2). In multivariable logistic regression analysis, patients treated with ORIF (OR, 8.13; 95% CI, 7.91-8.36; P < .01), those with congestive heart failure (OR, 4.23; 95% CI, 4.06-4.41; P < .01), those with an associated femur fracture (OR, 3.13; 95% CI, 2.99-3.27; P < .01), those with atrial fibrillation (OR, 1.96; 95% CI, 1.88-2.05; P < .01), and those treated with CRIF (OR, 1.42; 95% CI, 1.29-1.56; P < .01) were associated with significantly higher odds of blood transfusion (model fit: omnibus test of model coefficients, X = 42,653, P < .01; Nagelkerke, R2 = 0.19) (Table 7).

Treatment with ORIF

Over the 20-year study period, 23.2% of patients with acetabular fractures were treated with ORIF (Table 1). In 1990, 12.6% of patients underwent ORIF, while in 2010 this percentage increased to 20.4% (P < .001) (Table 2). Multivariable logistic regression analysis demonstrated that age between 41 and 60 years (OR, 1.88; 95% CI, 1.78-1.98; P < .01) was associated with the highest odds of undergoing ORIF. Age 20 to 40 years (OR, 1.86; 95% CI, 1.76-1.97; P < .01), age <20 years (OR, 1.82; 95% CI, 1.72-1.93; P < .01), and male gender (OR, 1.65; 95% CI, 1.63-1.68; P < .01) were also associated with being treated by ORIF. In contrast, coronary artery disease (OR, 0.27; 95% CI, 0.25-0.30; P < .01), age >85 years (OR, 0.46; 95% CI, 0.44-0.47; P < .01), and congestive heart failure (OR, 0.48; 95% CI, 0.46-0.51; P < .01) were associated with the lowest odds of undergoing ORIF (model fit: omnibus test of model coefficients, X = 71,118, P < .01; Nagelkerke, R2 = 0.20) (Table 8).

Discussion

This study evaluates the incidence of acetabular fractures in the US between 1990 and 2010, and identifies prognostic factors associated with complications and death. The study demonstrates an increase in the population-adjusted incidence of acetabular fractures between 1990 and 2010 (7.84 cases per 100,000 capita to 9.5 cases per 100,000 capita), in contrast to the decreasing trend reported by Mauffrey and colleagues.11 Some studies suggest that up to 80% of acetabular fractures are associated with motor vehicle collisions and motorcycle accidents.9,27 While the rate of motor vehicle accidents has remained stable over the study period, motorcycle ownership and deaths more than doubled between 2001 and 2008,28 primarily among individuals over 40 years of age. In this study, the mean age of patients with acetabular fractures ranged from 48 to 57 years. The dramatic increase in motorcycle ownership and deaths in these age groups may partially explain the rising incidence of acetabular fractures. The other possibility is that changes in automobile design and safety equipment may have altered the injury patterns observed in patients surviving motor vehicle crashes. Compared to the United Kingdom, in which studies report a fixed incidence of 3 per 100,000 capita1 between 1988 and 2003, the incidence of acetabular fractures in the US is greater. In contrast, the incidence of acetabular fractures reported in this study is less than the 20 per 100,000 reported in Sweden between 1976 and 1985,29 or the 37 per 100,000 reported in Rochester, Minnesota between 1968 and 1977,30 which may be due to increased seatbelt usage.31

In addition to the national incidence, this study demonstrated that the proportion of patients with acetabular fractures treated with ORIF increased from 12.6% to 20.4% between 1990 and 2010. This is substantially lower than the 77% reported by Ochs and colleagues32 in a German population. Concurrent with the increase in ORIF, there was a decrease in in-hospital mortality from 5.9% in 1990 to 0.4% in 2010. The initial mortality rates in this study are comparable to much earlier reports and some small studies,9,32-37 but the rates reported in the later years of this study show a substantial decrease that is likely a more accurate estimation of the current incidence. The improved survival rates may be due to advances in the operative treatment of acetabular fractures, in which mechanical stabilization allows for early patient mobilization and facilitation of optimal nursing care.38 With ORIF becoming the standard of care for displaced acetabular fractures,9 numerous reports have demonstrated an association between early definitive fixation and improved survival.17,39,40 This is similar to our study, which found ORIF to be associated with the lowest odds of mortality in multivariate logistic regression analysis. It is possible that advances in patient care by intensivists over this period have also contributed to the decrease in mortality, but the correlation with operative treatment in this study is very strong and agrees well with prior studies.16 Moreover, multiple studies have demonstrated decreased in-hospital mortality among patients undergoing various orthopedic surgical procedures during this period.41-43 The correlation with operative treatment in this study agrees well with prior studies.16

In contrast, higher odds of mortality were seen in patients over the age of 85 years with pulmonary insufficiency, congestive heart failure, pneumonia, or an associated femur or pelvic fracture. This is similar to prior reports in which patients with combined acetabulum and pelvic ring injuries fared worse than those with isolated injures,44,45 as did patients with associated non-musculoskeletal injuries.46 The finding that age over 85 years was associated with higher odds of mortality likely reflects the increased number of comorbidities and decreased physiologic reserve seen in this patient population. Finally, male gender was associated with higher odds of in-hospital mortality. There are 2 possible explanations for this: Either there is gender dimorphism in sex hormones and cytokine activity in response to hemorrhage and sepsis,38,47 or there is a greater tendency for males to be involved in higher energy accidents with more severe concomitant injuries.

The results of multivariable regression analysis demonstrated that patients were more likely to require blood transfusion if they were managed surgically or had atrial fibrillation, congestive heart failure, or associated femur fracture. Not surprisingly, concurrent pelvic fracture was also associated with higher odds of blood transfusion, as pelvic hemorrhage is reported to be the cause of death in up to half of patients who die following a pelvic fracture.46

Between 1990 and 2010, in-hospital days of care decreased from 17.0 days to 10.3 days. While a decreased length of stay has been demonstrated in other orthopedic conditions over the study period,41 it is possible the decrease in length of stay demonstrated in this study is due to improved surgical technique and the implementation of early surgical intervention.39,48-50 Plaisier and colleagues17 demonstrated superior functional outcomes, quicker return to baseline function, and decreased length of stay in patients treated with early ORIF of their acetabular fractures. Other studies have shown that the benefits of early surgery include improved reduction quality and ease of reduction,51 as well as control of bleeding, pain relief, and mobilization of the patient.39 Another possible explanation for the decreased length of stay is the increased rate of discharge to other inpatient facilities, such as rehabilitation facilities, which was demonstrated in this study.

Interestingly, male gender and younger age were associated with operative management of the acetabular fracture. In contrast, there was a decreased likelihood of operative treatment among elderly patients and those patients with cardiac comorbidities. It is possible that the relationship we found between the likelihood of ORIF and age relates to the bimodal distribution of fractures, with higher energy and potentially more displaced fractures occurring in younger patients3-5 and lower energy fractures in the elderly.

In contrast to decreasing in-hospital days of care, there was a rise in the number of adverse events between 1990 (10.9%) and 2010 (37.6%). This can be partially attributed to the increased rates of blood transfusion, which was received by 9.5% of patients with acetabular fractures in the final study year. Additionally, surgical intervention was associated with increased adverse events in this study, and surgical intervention increased over the study period. Other factors that may have contributed to an increase in adverse events include an aging population,52 as advanced age was independently associated with higher odds of adverse events in this study.

Despite the strengths of using large, national databases for epidemiological research,53 this study has several limitations. Like all large databases, the NHDS is subject to error in coding and data entry.54 Additionally, the database only allows for 7 diagnostic codes and 4 procedure codes per entry. As a result, the prevalence of comorbid conditions and adverse events may be underreported.25 Moreover, the severity of a comorbid disease cannot be appreciated when dichotomously classified.55 Another limitation is that the database only provides inpatient data, so complications that arise after discharge, as well as follow-up data, are unknown. Furthermore, the results of this study are limited to practice patterns in the US from 1990 to 2010. This database does not provide injury mechanisms, so we cannot distinguish between high-energy and low-energy injuries. Lastly, analysis of the different types of acetabular fractures was not performed since classification of acetabular fractures cannot be assessed with ICD-9 codes.

Conclusion

This study is the largest epidemiologic analysis of acetabular fractures in the US and also provides predictors of in-hospital mortality. The incidence of acetabular fractures in the US is increasing, while mortality is decreasing. Identifying risk factors associated with poor outcomes has the potential to change treatment strategies, resource allocation, in-hospital monitoring, and discharge planning for this patient population.

This paper will be judged for the Resident Writer’s Award.

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Figures/Tables

Table 1. Patient Characteristics for Patients with Acetabular Fractures in the United States from 1990 to 2007

Parameter

Total 1990-2010

Total Number

497,389

Gender (%)

 

Male

60.6

Female

39.4

Age, years (%)

 

<20

6.7

20-40

31.5

41-60

22.3

61-85

30.4

>85

23.5

Race (%)

 

White

66.4

Black

9.3

Asian

1.7

Other

2.4

Not stated

20.2

Primary Diagnosis (%)

 

Closed fracture of acetabulum (808.0)

98.9

Open fracture of acetabulum (808.1)

1.1

Associated diagnoses (%)

 

Closed fracture of pubis (808.2)

26.1

Open fracture of pubis (808.3)

0.1

Closed fracture of ischium (808.42)

1.7

Open fracture of ischium (808.52)

0.0

Closed fracture of ilium (808.41)

3.8

Open fracture of ilium (808.51)

0.0

Closed fracture other part pelvis (808.49)

0.7

Open fracture other part pelvis (808.59)

0.0

Multiple closed pelvic fractures (808.43)

0.5

Multiple open pelvic fractures (808.53)

0.0

Any pelvic fracture from above

29.8

Fracture of neck of femur (820)

7.2

Fracture of any part of femur (820/821)

13.1

Head trauma (959.01)

0.7

Head/face trauma (959.0/959.01)

0.7

Chest trauma (959.11)

0.1

Chest/trunk trauma (959.1/959.11)

0.1

Procedures (%)

 

Open reduction internal fixation (79.30/79.39)

23.2

Closed reduction internal fixation (79.10/79.19)

1.3

External fixation (78.10/78.19)

0.7

Internal fixation without reduction (78.50/78.59)

0.4

Comorbidities (%)

 

No

72.9

Yes

27.1

Adverse Events (%)

 

No

74.1

Yes

25.9

Discharge Disposition (%)

 

Routine/home (1)

45.4

Left against medical advice (2)

0.2

Short term fac (3)

13.1

Long term fac (4)

22.2

Alive, not stated (5)

12

Dead (6)

3.5

Not reported (9)

3.6

Mortality (%)

3.5

Age (y), mean (SD)

52.6 (23.7)

Days of Care, mean (SD)

8.3 (17.9)

Principal Source of Payment (%)

 

Private insurance

39

Medicare

30.5

Medicaid

7.7

Other government

1.9

Self-pay

7.9

Workmen’s comp

4

Other

4.7

Not stated

4.4

Abbreviation: SD, standard deviation.

 

Table 2. Patient Characteristics in 1990, 1995, 1999, 2003, and 2007 Among Patients with Acetabular Fractures

Variable

1990

1995

1999

2003

2007

2010

Total number

19,560

17,506

22,767

27,133

34,027

29,373

Incidence per 100,000 capita

7.84

6.57

8.16

9.35

11.30

9.5

Gender (%)

     

 

  Male

51.0

70.7

61.2

62.6

62.5

64.9

  Female

49.0

29.3

38.8

37.4

37.5

35.1

Fracture (%)

     

 

  Open

2.1

1.7

3.3

1.4

0.1

1.8

  Closed

97.9

98.3

96.7

98.6

99.9

98.2

Underwent ORIF (%)

12.6

20.9

20.2

22.9

27.8

20.4

Adverse events (%)

10.9

16.2

23.7

31

35.1

37.6

Transfusion (%)

0.3

2.2

7.4

6.5

10.5

9.5

Discharge (%)

     

 

  Routine

58

65.6

35.6

45.9

40.2

41.6

  Non-routine to inpatient facility

26.8

23.1

46.4

33.8

40.8

34.6

Mortality (%)

5.9

3.6

2

2.9

1.5

0.4

Mean Age (y)

52.9

48.4

52.3

56.3

57

53.2

Mean DOC (days)

17.0

13.4

8.7

10.8

8.5

10.3

Abbreviations: DOC, days of care; ORIF, open reduction internal fixation.

 

Table 3. Logistic Regression for Predictors of Mortality Among Patients with Acetabular Fractures (n = 403,927)

Variable

OR (95% CI)

P

Pulmonary insufficiency

9.07 (8.52–9.66)

< 0.01

Pneumonia

3.22 (3.05–3.39)

< 0.01

Age >85 years

2.28 (2.16–2.40)

< 0.01

Closed reduction internal fixation

1.99 (1.78–2.23)

< 0.01

External Fixator

1.82 (1.45–2.29)

< 0.01

Blood transfusion

1.81 (1.71–1.91)

< 0.01

Gender (male)

1.76 (1.70–1.83)

< 0.01

Associated femoral neck fracture

1.23 (1.15–1.30)

< 0.01

Age 41-60 years

1.19 (1.11–1.29)

< 0.01

Age 61-85 years

1.17 (1.11–1.23)

< 0.01

Congestive heart failure

1.14 (1.07–1.22)

< 0.01

Associated pelvic fracture

1.13 (1.10–1.17)

< 0.01

Geographic region

1.11 (1.09–1.12)

< 0.01

Source of payment

1.02 (1.01–1.02)

< 0.01

Race

0.99 (0.98–0.99)

< 0.01

DOC

0.98 (0.98–0.98)

< 0.01

Hypertension

0.67 (0.64–0.71)

< 0.01

Atrial fibrillation

0.52 (0.48–0.57)

< 0.01

Diabetes mellitus

0.35 (0.32–0.38)

< 0.01

Age 20-40 years

0.32 (0.30–0.35)

< 0.01

Age <20 years

0.26 (0.23–0.30)

< 0.01

Coronary artery disease

0.21 (0.18–0.24)

< 0.01

Open reduction internal fixation

0.19 (0.17–0.20)

< 0.01

Omnibus X 25,966, P < .01

  

Nagelkerke R2= 0.20

  

Abbreviations: CI, confidence interval; DOC, days of care; OR, odds ratio.

 

Table 4. Prevalence of Comorbidities in Patients with Acetabular Fractures Between 1990 and 2007 (n = 403.927)

Parameter (ICD-9)

Percentage of Total

Hypertensive disease (401–405)

15.3%

Diabetes mellitus (250)

6.9%

Atrial fibrillation (427.31)

4.0%

Congestive heart failure (428)

3.9%

Osteoporosis (733.0)

2.1%

Coronary artery disease (414.01)

2.0%

Obesity (278.00, 278.01)

2.0%

Abbreviation: ICD-9, International Classifications of Diseases, 9th Revision.

 

Table 5. Prevalence of In-Hospital Adverse Events Among Patients with Acetabular Fractures Between 1990 and 2007 (n = 403,927)

Parameter (ICD-9)

Percentage of Total

Transfusion of blood (99.0)

8.1%

Acute postoperative anemia (285.1)

7.3%

Intubation (96.x)

4.9%

Acute renal failure (584)

3.4%

Pneumonia (480-486)

3.2%

Pulmonary insufficiency (518.5)

2.3%

Pulmonary embolism (415.1)

1.6%

Deep venous thrombosis (453.4)

1.0%

Acute myocardial infarction (410)

0.9%

Postoperative bleeding (998.1)

0.7%

Acute postoperative infection (998.5)

0.5%

Induced mental disorder (293)

0.4%

Abbreviation: ICD-9, International Classifications of Diseases, 9th Revision.

 

Table 6. Logistic Regression for Predictors of Adverse Events Among Patients Hospitalized for Acetabular Fracture (n = 403,927)

Variable

OR (95% CI)

P

Closed reduction internal fixation

3.08 (2.91-3.26)

< 0.01

Coronary artery disease

2.02 (1.91-2.15)

< 0.01

Associated femoral neck fracture

1.53 (1.47-1.60)

< 0.01

Open reduction internal fixation

1.22 (1.20-1.24)

< 0.01

Gender (male)

1.16 (1.14-1.18)

< 0.01

Associated fracture of any part of femur

1.13 (1.10-1.17)

< 0.01

Age >85 years

1.08 (1.05-1.12)

< 0.01

Geographic region

1.07 (1.06-1.07)

< 0.01

DOC

1.04 (1.04-1.04)

< 0.01

Race

1.02 (1.02-1.03)

< 0.01

Source of payment

1.01 (1.01-1.01)

< 0.01

Congestive heart failure

1.01 (0.96-1.06)

0.78

Atrial fibrillation

0.88 (0.84-0.92)

< 0.01

Age 61-85 years

0.68 (0.66-0.71)

< 0.01

Age <20 years

0.67 (0.64-0.70)

< 0.01

Associated pelvis fracture

0.64 (0.63-0.66)

< 0.01

Age 41-60 years

0.58 (0.56-0.61)

< 0.01

Diabetes mellitus

0.48 (0.46-0.50)

< 0.01

Age 20-40 years

0.45 (0.43-0.47)

< 0.01

Hypertension

0.44 (0.43-0.45)

< 0.01

External Fixator

0.39 (0.35-0.44)

< 0.01

Omnibus X 160,275,  P < .01

  

Nagelkerke R2 = 0.41

  

Abbreviations: CI, confidence interval; DOC, days of care; OR, odds ratio.

 

Table 7. Logistic Regression for Predictors of the Requirement for Blood Transfusion Among Patients with Acetabular Fractures (n = 403,927)

Variable

OR (95% CI)

P

Open reduction internal fixation

8.13 (7.91-8.36)

< 0.01

Congestive heart failure

4.23 (4.06-4.41)

< 0.01

Associated fracture of any part of femur

3.13 (2.99-3.27)

< 0.01

Atrial fibrillation

1.96 (1.88-2.05)

< 0.01

Closed reduction internal fixation

1.42 (1.29-1.56)

< 0.01

Geographic region

1.38 (1.36-1.39)

< 0.01

Hypertension

1.38 (1.34-1.42)

< 0.01

Associated pelvic fracture

1.28 (1.25-1.31)

< 0.01

Age 61-85 years

1.06 (1.02-1.11)

0.01

Source of payment

0.99 (0.98-0.99)

< 0.01

Race

0.98 (0.97-0.98)

< 0.01

DOC

0.96 (0.96-0.96)

< 0.01

Age >85 years

0.74 (0.72-0.77)

< 0.01

External fixator

0.69 (0.59-0.80)

< 0.01

Coronary artery disease

0.62 (0.57-0.68)

< 0.01

Age 41-60 years

0.57 (0.54-0.60)

< 0.01

Gender (male)

0.54 (0.52-0.55)

< 0.01

Diabetes mellitus

0.38 (0.36-0.41)

< 0.01

Age 20-40 years

0.32 (0.30-0.34)

< 0.01

Associated femoral neck fracture

0.29 (0.27-0.31)

< 0.01

Age <20 years

0.24 (0.22-0.26)

< 0.01

Omnibus X = 42,653,  P < .01

  

Nagelkerke R2 = 0.19

  

Abbreviations: CI, confidence interval; DOC, days of care; OR, odds ratio.

 

Table 8. Logistic Regression for Predictors of the Requirement for Discharge to Another Inpatient Facility Among Patients with Acetabular Fractures (n = 403,927)

Variable

OR (95% CI)

P

Age 41-60 years

1.88 (1.78-1.98)

< 0.01

Age 20-40 years

1.86 (1.76-1.97)

< 0.01

Age <20 years

1.82 (1.72-1.93)

< 0.01

Gender (male)

1.65 (1.63-1.68)

< 0.01

Larger hospital bed size

1.46 (1.45-1.47)

< 0.01

Hypertension

1.35 (1.32-1.38)

< 0.01

Diabetes mellitus

1.09 (1.05-1.13)

< 0.01

DOC

1.02 (1.02-1.02)

< 0.01

Source of payment

1.01 (1.01-1.02)

< 0.01

Race

1.00 (0.99-1.00)

0.17

Age 61-85 years

0.94 (0.90-0.99)

0.02

Region

0.92 (0.91-0.93)

< 0.01

Atrial fibrillation

0.83 (0.79-0.87)

< 0.01

Congestive heart failure

0.48 (0.46-0.51)

< 0.01

Age >85 years

0.46 (0.44-0.47)

< 0.01

Coronary artery disease

0.27 (0.25-0.30)

< 0.01

Omnibus X 71,118, P < .01

  

Nagelkerke R2 = 0.20

  

Abbreviations: CI, confidence interval; DOC, days of care; OR, odds ratio.

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