Open Access

Disorder-related risk factors for revision total hip arthroplasty after hip hemiarthroplasty in displaced femoral neck fracture patients: a nationwide population-based cohort study

  • Chun-Hao Tsai1, 2, 3,
  • Chih-Hsin Muo4,
  • Chih-Hung Hung5,
  • Tsung-Li Lin1,
  • Ta-Ii Wang1,
  • Yi-Chin Fong1, 6, 7 and
  • Horng-Chaung Hsu1, 2, 3Email author
Journal of Orthopaedic Surgery and Research201611:66

https://doi.org/10.1186/s13018-016-0400-3

Received: 17 October 2015

Accepted: 19 May 2016

Published: 8 June 2016

Abstract

Background

The choice of primary hip hemiarthroplasty or total hip arthroplasty for displaced femoral neck fracture is still controversial. Revision hip arthroplasty not only increases risk and cost but also could result in worse outcome. Determining the risk factors for revision can help inform medical decision-making and aid in risk stratification of publicly reported outcomes. Therefore, we conducted a nationwide population-based study to identify the disease-related risk factors and construct a risk score nomogram to predict revision surgery.

Methods

Records of all 68,030 femoral neck fracture patients receiving partial hemiarthroplasty (HA) in 2000–2010, with no total hip arthroplasty (THA) or revision HA history, were collected from the National Health Insurance Research Database. Cox proportional hazard regression was used to estimate the risk of revision hip replacement (RHA). The score of each risk factor was the quotient of the regression coefficient of the variable by the regression coefficient for a 10-year increase in age. The predictive accuracy was tested using the area under the receiver operating characteristic curve (AUROC).

Results

The revision risk for hemiarthroplasty increased in male, those with schizophrenia and end-stage renal disease patients had 1.58-, 1.88-, and 1.74-fold revision HA risk (95 % confidence interval (CI) = 1.40–1.78, 1.26–2.79, and 1.29–2.34, respectively). In a predictive model, the cumulative risk score ranged from 0 to 13 with a 5.08 to 91.82 % 10-year predicted RHA risk. The percentage of AUROC for 10-year RHA risk in nomogram was 61.9 (95 % CI = 60.0–63.4).

Conclusions

Males, schizophrenia and end-stage renal disease patients have higher risk of revision surgery after hemiarthroplasty for femoral neck fracture.

Background

With the rapid development of the aging population, the total number of patients worldwide with hip fracture is predicted to rise to 6.26 million per year by 2050 [1]. Based on location, femoral neck fractures account for 45 to 53 % of hip fractures. The three major treatments for femoral neck fractures in clinical practice are internal fixation, hemiarthroplasty (HA), and total hip arthroplasty (THA) [2, 3]. While internal fixation applies to undisplaced intracapsular fractures [4], the other two operative methods are advisable for displaced fractures in the elderly [5]. Since HA is a standardized surgical method that allows early weight bearing and recovery, it has become an established procedure with low risk of postoperative complications. Nonetheless, higher physical demands, even in older adults, occasionally necessitate conversion surgery to THA; this processes likely to increase both the possible risks and the associated costs [6, 7]. While debate continues on whether primary THA or HA is best for displaced femoral neck fracture [6, 810], the high complication rate of revision HA in comparison with THA is clearly known [11].

Therefore, it has become critical to determine the specific risk factors associated with the conversion of HA to revision hip replacement (RHA), to better assess the relative risks of each surgical procedure. The few studies of the risk factors associated with conversion to THA for hemiarthroplasty have identified several risk factors, such as younger age and male gender [12]. However, the weight of each risk factor has not yet been determined. Thus, we conducted a population-based, case-control study using the nationwide population-based database of a universal insurance program to evaluate the disease-related risk factors for conversion of HA to THA in femoral neck fracture in older adults.

Methods

Data source

The Taiwan Bureau of National Health Insurance (TBNHI) set up a single-payer National Health Insurance (NHI) Program on March 1, 1995. Almost all residents in Taiwan join this program. TBNHI commissioned the National Health Research Institutes to maintain the National Health Insurance Research Databases (NHIRDs) derived from the NHI program. We obtained from the NHIRDs data on all inpatient claims from 1996 to 2011. To be in compliance with the Personal Information Protection Act, the insurance information was de-identified and the scientists signed an agreement that they had no intention of obtaining personal information. This study was approved by the local institutional review board. The identification of disease was based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes in the NHIRDs.

Study subjects and end-points

We collected adult patients with a new diagnosis of femoral neck fracture (ICD-9-CM code 820) who received partial hip arthroplasty (HA, ICD-9-operation code 81.52) in 2000–2010 (N = 68,755). The date of HA treatment was defined as the index date. Patients who had received total hip replacement (ICD-9-operation code 81.51, n = 592) or RHA (ICD-9-operation code 81.53, n = 133) before the index date were excluded. All study subjects were followed from the index date to the date of RHA treatment. Those without RHA treatment were followed until the date of withdrawal from the program or the end of 2011.

For the prediction model, we randomly assigned HA patients to either a derivation group or a validation group in a 3:1 ratio.

Risk factors

The risk factors included age, gender, and comorbidity. Comorbidities assessed (using ICD-9-CM codes) included diabetes (250), osteoporosis (733.0, V17.81, V82.81), rheumatoid arthritis (RA; 714), cancer (140–208), chronic obstructive pulmonary disease (COPD; 491,492, 496), previous osteoarthritis hip (715.5), end-stage renal disease (ESRD; 585), systemic lupus erythematosus (SLE; 710.0), ankylosing spondylitis (720), obesity (278.0), extrinsic asthma (493.0), human immunodeficiency virus (HIV; 042, V08, 795.71), atherosclerosis (440), smoking (350.1 and 649.0), psoriasis (696), viral hepatitis (070), depression (296.2, 296.3, 296.82, 300.4, 311), schizophrenia (295), heart failure (428), urinary tract infection (UTI; 599.0), ischemic heart disease (410–414), dementia (290, 294.1, and 331.0–331.2), and alcoholism (291, 303, 305.00–305.03, 790.3, V11.3). All comorbidities were defined before the index date.

Statistical analysis

Incidence of RHA and RHA-associated risk factors

The incidence of RHA (per 1000 person-years) was determined in patients by age, gender, and comorbidity. Cox proportional hazard regression was used to estimate the hazard ratios (HRs) and 95 % confidence interval (CI) of RHA and the RHA-associated risk factor. Multivariable modeling was used, controlling for significant factors using crude Cox proportional hazard regression.

Prediction model

In future analysis, the prediction model was developed according to those risk factors identified as significant in this study. The score of each risk factor was the quotient of the regression coefficient of the variable by the regression coefficient for a 10-year increase in age. The cumulative risk score was the sum of the score of each risk factor. The area under the receiver operating characteristic curve (AUROC) of the nomogram was used to test the association of factors with RHA treatment using logistic regression. In future analysis, the patients were grouped into three groups based on risk scores: low (risk score 0–2), median (risk score 3–4), and high (risk score 5+). We plotted the cumulative incidence among risk score groups by Kaplan-Meier analysis in derivation and validation cohort. All statistical analyses were performed using the SAS software package SAS (version 9.4 for windows; SAS Institute, Cary, NC).

Results

All 68,030 femoral neck fracture patients who received hip hemiarthroplasty (HA) were selected for this study. Most patients were older than 70 years (80.8 %) and the mean age was 77.3 years (standard deviation = 9.26, Table 1). Most HA patients were female (65.0 vs. 35.0 %). The 10 most prevalent comorbidities in HA patients were diabetes (23.7 %), ischemic heart disease (18.2 %), UTI (17.9 %), COPD (10.6 %), heart failure (8.13 %), cancer (7.62 %), ankylosing spondylitis (5.42 %), osteoporosis (4.89 %), dementia (3.52 %), and ESRD (2.88 %).
Table 1

Incidence and hazard ratio for revision hip replacement and associated risk factor

 

n

(%)

Event no.

PY

Ratea

Crude HR (95 % CI)

Adjusted HR (95 % CI)

Total

68,030

 

1114

238,875

4.66

  

Age, year

 20–29

53

(0.08)

9

260

34.57

30.9 (13.4–71.5)***

23.6 (10.2–54.7)***

 30–39

158

(0.23)

11

832

13.23

12.0 (5.43–26.4)***

8.52 (3.85–18.9)***

 40–49

499

(0.73)

25

2302

10.86

9.49 (4.93–18.3)***

6.90 (3.56–13.4)***

 50–59

1862

(2.74)

63

7908

7.97

6.65–3.73 (11.9)***

5.48 (3.06–9.82)***

 60–69

10,492

(15.4)

257

45,526

5.65

4.77 (2.79–8.17)***

4.35 (2.54–7.46)***

 70–79

26,868

(39.5)

458

101,757

4.50

3.59 (2.11–6.12)***

3.38 (1.99–5.76)***

 80–89

24,095

(35.4)

277

71,159

3.89

2.80 (1.64–4.80)***

2.73 (1.60–4.68)***

 ≥90

4003

(5.88)

14

9132

1.53

1.00

1.00

 Mean (SD)

77.3

(9.26)

     

Gender

 Women

44,241

(65.0)

614

163,685

3.75

1.00

1.00

 Men

23,789

(35.0)

500

75,190

6.65

1.69 (1.50–1.90)***

1.58 (1.40-1.78)***

Comorbidity

 Diabetes

  No

51,877

(76.3)

861

191,518

4.50

1.00

 

  Yes

16,153

(23.7)

253

47,357

5.34

1.09 (0.95–1.26)

 

 Osteoporosis

  No

64,702

(95.1)

1057

228,211

4.63

1.00

 

  Yes

3328

(4.89)

57

10,664

5.35

1.11 (0.85–1.45)

 

 RA

  No

67,472

(99.2)

1099

236,796

4.64

1.00

 

  Yes

558

(0.82)

15

2079

7.21

1.57 (0.94–2.61)

 

 Cancer

  No

62,848

(92.4)

1038

226,145

4.59

1.00

 

  Yes

5182

(7.62)

76

12,730

5.97

1.14 (0.90–1.44)

 

 COPD

 

  No

60,853

(89.4)

1008

219,410

4.59

1.00

 

  Yes

7177

(10.6)

106

19,465

5.45

1.07 (0.88–1.31)

 

 ESRD

 

  No

66,073

(97.1)

1068

234,698

4.55

1.00

1.00

  Yes

1957

(2.88)

46

4177

11.01

1.99 (1.48–2.68)***

1.74 (1.29–2.34)***

 SLE

  No

67,963

(99.9)

1112

238,679

4.66

1.00

 

  Yes

67

(0.10)

2

196

10.19

2.03 (0.51–8.14)

 

 Ankylosing spondylitis

  No

64,346

(94.6)

1059

228,091

4.64

1.00

 

  Yes

3684

(5.42)

55

10,785

5.10

1.02 (0.78–1.34)

 

 Extrinsic asthma

  No

67,850

(99.7)

1112

238,299

4.67

1.00

 

  Yes

180

(0.26)

2

576

3.47

0.72 (0.18–2.89)

 

 HIV

  No

68,022

(99.9)

1114

238,853

4.66

1.00

 

  Yes

8

(0.01)

0

22

0.00

––

 

 Atherosclerosis

  No

67,550

(99.3)

1106

237,521

4.66

1.00

 

  Yes

480

(0.71)

8

1355

5.91

1.17 (0.58–2.35)

 

 Psoriasis

  No

67,898

(99.8)

1112

238,505

4.66

1.00

 

  Yes

132

(0.19)

2

370

5.40

1.09 (0.27–4.36)

 

 Viral hepatitis

  No

66,212

(97.3)

1080

234,523

4.61

1.00

1.00

  Yes

1818

(2.67)

34

4353

7.81

1.46 (1.04–2.06)*

1.30 (0.92–1.83)

 Depression

  No

66,091

(97.2)

1081

232,874

4.64

1.00

 

  Yes

1939

(2.85)

33

6002

5.50

1.12 (0.79–1.59)

 

 Schizophrenia

  No

67,399

(99.1)

1088

236,468

4.60

1.00

1.00

  Yes

631

(0.93)

26

2408

10.80

2.43 (1.65–3.58)***

1.88 (1.26–2.79)**

 Heart failure

  No

62,500

(91.9)

1035

22,478

4.59

1.00

 

  Yes

5530

(8.13)

79

13,397

5.90

1.11 (0.89–1.40)

 

 UTI

  No

55,877

(82.1)

936

204,007

4.59

1.00

 

  Yes

12,153

(17.9)

178

34,869

5.10

1.2 (0.87–1.19)

 

 Ischemic heart disease

  No

55,681

(81.9)

915

203,038

4.51

1.00

 

  Yes

12,349

(81.9)

199

35,837

5.55

1.13 (0.97–1.32)

 

 Dementia

  No

65,633

(96.5)

1091

231,906

4.70

1.00

1.00

  Yes

2397

(3.52)

23

6969

3.30

0.65 (0.43–0.98)*

0.71 (0.47–1.07)

PY person-years, HR hazard ratio, CI confidence interval, SD standard deviation, RA rheumatoid arthritis, COPD chronic obstructive pulmonary disease, ESRD end-stage renal disease, SLE systemic lupus erythematosus, HIV human immunodeficiency virus, UTI urinary tract infection

*p < 0.05; **p < 0.01; ***p < 0.001

aPer 1000 person-years

After a cumulative 12-years follow-up, 1114 patients received RHA treatment, with an incidence of 4.66 per 1000 person-years (Table 1). In multivariable Cox proportional hazard regression, the RHA risk decreased with aging from 23.6 to 2.73 in those aged 20-29 to 80-89 years, respectively, compared with those aged ≥90 years (95 % CI = 10.2-54.7 and 1.60-4.68, respectively). Compared with women, men had a significantly higher RHA risk (HR = 1.58, 95 % CI = 1.40–1.78). RHA-associated risk factors for the total cohort were schizophrenia (HR = 1.88, 95 % CI = 1.26–2.79) and ESRD (HR = 1.74, 95 % CI = 1.29–2.34).

Table 2 presents the distribution between derivation (75.0 %) and validation (25.0 %) cohort. There was no significant difference of age, gender, ESRD and schizophrenia between two groups. In derivation cohort, the risk score decreased one point with every 10 years of age increasing; for example, the risk score was 7 for patients aged 20–29 years, 6 for those 30–39 years, 5 for those 40–49 years, and so on (Table 3). The risk score was 2 for men, those with ESRD and schizophrenia patients. The percentage of AUROC for 10-year RHA risk in nomogram was 61.9 (95 % CI = 60.0–63.4). In the prediction model, the cumulative risk score ranged from 0 to 13 with a 5.08 to 91.82 %10-year predicted RHA risk (Fig. 1).
Table 2

Distribution of predictor between derivation and validation cohort

 

Derivation cohort

Validation cohort

 

N = 51021 (75.0 %)

N = 17009 (25.0 %)

 

n

%

n

%

Chi-square p value

Age, year

    

0.98

 20–29

40

0.08

13

0.08

 

 30–39

113

0.22

45

0.26

 

 40–49

371

0.73

128

0.75

 

 50–59

1388

2.72

474

2.79

 

 60–69

7878

15.4

2614

15.4

 

 70–79

20,177

39.6

6691

39.3

 

 80–89

18,047

35.4

6048

35.6

 

 ≥ 90

3007

5.89

996

5.86

 

Gender

    

0.97

 Women

33,182

65.0

11,059

65.0

 

 Men

17,839

35.0

5959

35.0

 

Comorbidity

 ESRD

1493

2.93

464

2.73

0.18

 Schizophrenia

455

0.89

176

1.03

0.09

ESRD end-stage renal disease

Table 3

Incidence and hazard ratio for revision hip replacement and associated risk factor in derivation cohort

 

HR (95 % CI)

Regression coefficient

p

Risk score

Age, year

 20–29

40.4 (16.0–10.2)

3.700

< 0.0001

7

 30–39

12.3 (4.85–31.0)

2.506

< 0.0001

6

 40–49

8.40 (3.76–18.8)

2.128

< 0.0001

5

 50–59

6.44 (3.14–12.2)

1.862

< 0.0001

4

 60–69

4.92 (2.52–9.62)

1.593

< 0.0001

3

 70–79

3.97 (2.05–7.71)

1.380

< 0.0001

2

 80–89

3.38 (1.74–6.59)

1.218

0.0003

1

 ≥ 90

Ref.

0

 

0

Gender

 Women

Ref.

0

 

0

 Men

1.57 (1.36–1.80)

0.449

< 0.0001

2

ESRD

 No

Ref.

0

 

0

 Yes

1.72 (1.22–2.43)

0.542

0.002

2

Schizophrenia

 No

Ref.

0

 

0

 Yes

1.84 (1.15–2.96)

0.611

0.01

2

Baseline disease–free probability

 At 10 years

96.89

   

AUROC % (95 % CI)

61.9 (60.0–63.4)

   

HR hazard ratio, CI confidence interval, AUROC the area under the receiver operating characteristic curve

Fig. 1

Nomograms for the prediction of the RHA risk

Figure 2 presents cumulative incidence of RHA in different risk score groups. In derivation cohort, the cumulative incidences of RHA were 2.03, 3.85, and 6.06 % in low, median, and high after 10 years follow-up, respectively. In validation cohort, patients with higher risk score had highest cumulative incidence of RHA (6.24 %) and followed by median and low group (3.86 and 1.85 %).
Fig. 2

Cumulative incidence for revision hip replacement among different risk score groups: low (risk score 0–2), median (risk score 3–4), and high (risk score 5+) in derivation (a) and validation (b) cohort

Discussion

The current study revealed that the rate of RHA for primary HA for femoral neck fracture is 4.67 per 1000 person-years. Several risk factors, such as age, gender, ESRD, and schizophrenia, were identified. We also assessed the contribution of each factor to help clinicians predict future revision rate.

Traditionally, surgeons have preferred HA over THA because of concerns about the increased risk of complications of the more complex THA. However, more current data has showed no significant differences in the complication rates of patients undergoing HA versus THA [2, 9, 13, 14]. Moreover, the literature shows a lower risk of reoperation after THA compared with HA [6, 12, 1416] and better functional outcomes for patients after THA versus HA [6, 810, 13, 14, 16, 17].

HA comes with considerable risk of reoperation with conversion to THA [18, 19]. Finite element mode study has proven that HA increases the biomechanical stresses on the acetabular bone that would result in migration of the head and destruction of the acetabulum [20]. Several studies found significant acetabular wear in up to 67 % of cases [21, 22], quantified at an average rate of 0.7 mm per year [22]. The inability to restore the femoral offset is also a factor [23], impairing the ability to balance tissue tension. However, THA is not suitable for every patient, including those with multiple morbidities or those with limited life expectancy [24]. The disadvantages of THA include greater blood loss and higher costs compared with HA [13]. Despite higher initial costs, the overall costs of THA are lower.

Young age and male gender are well-identified risk factors for revision HA surgery [12], but no literature has described schizophrenia or ESRD as risk factors for revision HA surgery. Schizophrenia has been associated with higher odds of perioperative blood transfusion, adverse events, and non-routine discharge following total joint arthroplasty (TJA) [25, 26] or spine surgery [27]. ESRD is also a risk factor for perioperative allogeneic blood transfusions [28], as it increased both mortality and the complication rate in TJR [29, 30].

Risk equations and risk functions have been widely applied for patient counseling, clinical diagnosis, risk stratification, treatment selection, and prognosis prediction; these have especially been useful in medical fields such as cardiovascular disease [31], hepatic disease [32, 33], and cancer [34, 35]. Most risk score systems used in orthopedic surgery are constructed according to the preoperative damage condition [36, 37], bony destruction [38], or postoperative fixation status [39]. In preoperative assessment of displaced femoral neck fracture without complicated bony destruction, using demographic data and underlying comorbidity is an easy way to predict risk of revision. The nomogram of this study does not require complex calculations but allows surgeons to estimate the impact of demographic risk factors by easily adding the risk score. It helps facilitate clinician communication with patients about risk prediction and decision-making.

Our study has several limitations. First, we relied on NHIRDs to identify revisions and risk factors for revision HA surgery. Because the ICD-9 coding is representative of diseases, but not of the life style neither the physical finding. We are not able to analyze the population of smoker, alcohol use, and obesity because the insurance system only could code when the patients ask for medical treatment, which means the life style has threaten the health. Therefore, our data cannot show the risk of RHA in smoker, alcohol use, either BMI for obesity. However, smoke is a risk factor to infection [40], early failure, and revision surgery in total hip arthroplasty. Dislocation risk will be increased in alcoholism after total hip arthroplasty [41].

Second, the most common cause of revision hip replacement is loosening of the prosthesis (Table 4); however, there is no coding about primary surgery method or revision method. Therefore, we were not able to assess the surgical approach and type of prosthesis used (including retained stem, cemented, or noncemented prosthesis). Surgical approach would play a role in dislocation rate after hemiarthroplasty. Direct anterior [42, 43] or anteriorlateral approach has less dislocation rate that posterior approach [44, 45]. Both cemented and uncemented stem have good functional results in hip hemiarthroplasty for displaced femoral neck fractures [46]. But the uncemented hemiarthroplasty has high risk of postoperative periprosthetic femoral fractures to reoperation [4750]. However, previous investigators have reported a reasonable correlation between administrative claims and the clinical record when evaluating causes and types of revision TJA procedures [13]. Third, our study was a retrospective cohort study rather than a prospective randomized trial. Besides, the life style pattern and physical characters of people vary in different countries. The medical insurance data result may be not as the same as other country due to different socioeconomic situations between nations. There may be some risk factors not significant in one population but may play an important role in others due to risk exposure cases number, especially in life style. Our result would not be representative of other country or population. However, the use of a population-based data set allows for the enrollment of a large number of patients and is highly representative of the risk factors of diseases found in a general population. This study reveals the importance of associated diseases affect the outcome in hip hemiarthroplasty for femoral neck fracture. In the future, we still need more cases form other population for comparison and meta-analysis to find out more risk factor or related disease.
Table 4

Top ten reasons due to revision hip replacement (N = 1114)

Disease (ICD-9-CM)

Percentage

Mechanical complication of internal orthopedic device, implant, and graft (996.4)

62.6

Infection and inflammatory reaction due to internal prosthetic device, implant, and graft (996.6)

8.71

Other complications of internal (biological) (synthetic) prosthetic device, implant, and graft (996.7)

3.50

Shaft or unspecified part, closed (821.0)

2.69

Acquired deformities of hip (736.3)

2.60

Peritrochanteric fracture, closed (820.2)

2.60

Unspecified part of neck of femur, closed (820.8)

2.42

Osteoarthrosis, localized, not specified whether primary or secondary (715.3)

1.97

Pyogenic arthritis (711.0)

1.53

Mechanical complication of other specified prosthetic device, implant, and graft (996.5)

1.44

Finally, our results are limited to risk factors for failures that occur within the 10 years after primary HA, and therefore, it is unclear whether the same or other risk factors are associated with longer term follow-up. However, the impact of patient comorbidities on the risk of revision after HA has important clinical and policy implications for the health care system. Finally, these HAs were for femoral neck fracture only; our study does not address the risk factors for HA for osteonecrosis of the femoral head.

Conclusions

In conclusion, to assess the future risk of revision, a risk score system was developed, based on patient demographics and comorbidities. Although the permissible degree of postoperative activity depends entirely on the general health status of each patient, the current result scan help with arranging earlier rehabilitation and developing an appropriate follow-up program to prevent early complications.

Abbreviations

AUROC, area under the receiver operating characteristic curve; CI, confidence interval; HA, hemiarthroplasty; ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; NHI, National Health Insurance; RHA, revision hip arthroplasty; THA, total hip arthroplasty

Declarations

Acknowledgements

We thank the National Health Research Institute in Taiwan for providing the related insurance claims data. This study was supported by the Taiwan Ministry of Health and Welfare Clinical Trial and Research Center of Excellence (MOHW105-TDU-B-212-133019), China Medical University Hospital, Academia Sinica Taiwan Biobank Stroke Biosignature Project (BM10501010037), NRPB Stroke Clinical Trial Consortium (MOST 104-2325-B-039 -005), and the China Medical University Hospital (Grant #1MS1).

Authors’ contributions

All authors made substantive intellectual contributions to this study to qualify as authors. CHT and CHH designed the study. TLL and TIW collected the subjects’ data. CHM performed the statistical analysis. An initial draft of the manuscript was written by CHT. HCH and YCF re-drafted parts of the manuscript and provided helpful advice on the final revision. All authors were involved in writing the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

This study was approved by the Ethics Review Board of China Medical University (CMUH104-REC2-115).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Orthopedic Surgery, China Medical University Hospital
(2)
School of Medicine, China Medical University
(3)
Graduate Institute of Clinical Medicine, China Medical University
(4)
Management Office for Health Data, China Medical University Hospital
(5)
Tainan Municipal An-Nan Hospital-China Medical University
(6)
China Medical University Beigang Hospital
(7)
School of Chinese Medicine, China Medical University

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© The Author(s). 2016

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