Abstract
Background:
Shoulder arthroplasty has been shown to improve function in patients with advanced shoulder disease. However, the response to surgery and final outcomes are not easily predictable. This study assessed the effect of residual pain, age, sex, diabetes, hypertension, and depression on changes and status at one-year following arthroplasty with respect to shoulder function and overall physical and mental health status.
Methods:
A retrospective analysis of a prospective cohort of 140 patients tested preoperatively and one-year following shoulder arthroplasty was conducted at our tertiary hospital. Pearson’s correlations and multiple regression analysis were performed to test the impact of predictors on shoulder pain and function assessed using the American Shoulder and Elbow Surgery (ASES) questionnaire, and on physical and mental health assessed using the Short Form-12.
Results:
Pain and female sex were significant predictors of poorer function at one-year (R = .56, p = .001); and with other predictors, they explained 32% of the variability in function. The explained variability of changes in function scores was 15% with pain being the only significant predictor. Physical health was lower in older patients (r = -.31, p < .05) and was less predictable for physical health change scores (12%) and the physical status at one-year (14%).
Conclusions:
Residual pain is associated with poorer function status and less clinical benefits. Female sex is not associated with less change in function which suggests that men and women get equal benefit from the surgery. Advanced age relates to poorer physical health and to a lesser extent physical change over the year.
Level of Evidence: III
Keywords: shoulder arthroplasty, function, physical health status
Introduction
Shoulder arthroplasty is widely used to treat patients with severe arthritic changes in the joint.1 This surgical procedure has been shown to be effective in reducing pain, improving shoulder function and increasing range of motion (ROM).2,3 However, the overall improvement in shoulder functional outcomes is not always predictable and can be influenced by several factors.4 These factors were examined by several studies;2,4,5 however, the results of these studies have conflicted with one another. Young age was associated with better shoulder function on constant score at one-year follow-up after hemiarthroplasty performed for patients with proximal humeral fracture.6 Further, the improvement over time on shoulder clinical scores was associated with young age at the time of shoulder arthroplasty surgery but not with the later follow-up years in patients with rheumatoid arthritis.5 In contrast, advanced age was associated with greater improvement (change) in shoulder function as demonstrated on the Simple Shoulder Test (SST) following total shoulder arthroplasty (TSA).2 However, other studies found no correlations between age and the improvement in shoulder function.4,7 Lastly, studies that assessed the effect of gender on the improvement in shoulder function found that men had better post-operative function assessed using SST.4,7
Physical health is expected to decline with age4 and be adversely affected by comorbidities.8 However, factors that influence physical health following shoulder arthroplasty have rarely been examined. Advanced age is negatively associated with physical function (r = -.23) and the better pre-operative physical health is associated with better post-operative physical function (r = .4) as demonstrated on the Short Form-36 (SF-36) survey following TSA.4
The presence of comorbidities, including diabetes and hypertension, has been shown to have no effect on postoperative shoulder function,7,9 except for internal rotation ROM (R = -.2) which was decreased with diabetes.9 However, depression has been associated with lower shoulder function assessed using the American Shoulder and Elbow Surgery (ASES) in 176 patients two-year following TSA.10
There is a limited pool of studies which addressed the factors that influence postoperative functional outcomes following shoulder arthroplasty. In addition, a number of these studies do not report regression coefficients or explain the effect size attributable to these predictors. This makes it difficult to determine how much these should influence decision-making. Finally, comorbidities such as diabetes, hypertension and depression are rarely examined although they are present in 20-60 % of patients undergoing shoulder arthroplasty.1
Identifying preoperative factors that are predictive of one-year outcomes could assist surgeons and health care providers in providing patients more realistic expectations on outcomes and may help plan postoperative pain management and rehabilitation. Therefore, the current study was designed to address the following questions: 1) Do age, sex, diabetes, hypertension, and depression predict patient-reported outcomes including shoulder pain and function, and physical and mental health status one-year following shoulder arthroplasty? 2) Do these factors predict the clinical benefits following surgery as reflected in the change of outcome scores? Is residual pain (pain at one-year) associated with poorer functional outcomes?
Materials and Methods
Study design and patients
A retrospective query of prospective collected data of patients who underwent shoulder arthroplasty was conducted at a tertiary care referral hospital. Demographic data were collected and recorded into a computerized database for 477 patients with shoulder arthroplasty. All patients who completed the ASES (n = 140) and the SF-12 (n = 103) questionnaires at baseline and at one-year follow-up visits and who completed a self-reported comorbidity survey (n = 140) were included in this analysis. This cohort included all patients treated with shoulder arthroplasty regardless of the type of surgery based on a previous study11 that showed non-significant differences in ASES and SF-12 scores between patients with different surgical intervention (TSA, reverse TSA, hemiarthroplasty). Exclusion criteria included an inability or refusal to complete tests/measures. The University Ethics board approved the protocol and written consents was obtained from all patients.
Outcome measures
The dependent variables included the ASES,12 which assessed shoulder pain and function, and the SF-12 which assessed physical and mental health status.13 Both questionnaires have been shown to be valid and reliable self-reported assessment tools13,14 and have been previously used to assess patients after shoulder arthroplasty.10 In this study, self-reported pain severity (VAS: 0-10) and activities of daily living (maximum 30 scores) information were obtained from the ASES. The Physical Component Summary Score (PCS) and the Mental Component Summary Score (MCS) scores were obtained from the SF-12. A full description of ASES and SF-12 questionnaires is published.12,13 Both questionnaires were administered preoperatively and at one-year follow-up visit. Next, scores from both questionnaires were averaged and were compared among patients based on their age, sex, and the presence of diabetes, hypertension, and depression (Table 1). To estimate the clinical benefits of shoulder arthroplasty, we calculated the change in scores from baseline (preoperative) to the one-year follow-up visit for the ASES function and SF-12 PCS.
Table 1.
Patient Demographics and its Influence on ASES and SF-12 One-year Following Shoulder Arthroplasty
| Patient’s demographics | ASES (n = 140) | SF-12 (n = 103) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Number of patients (%) | Age Mean ( SD) | Pain: (VAS:0-10) Mean (SD) | Function: (scores: 0-30) Mean (SD) | Number of patients (%) | Age (years) Mean (SD) | PCS (scores: 0-100) Mean (SD) | MCS (scores: 0-100) Mean (SD) | ||
| Sex: | Male | 57 (41) | 68 (12)* | 1.5 (2) | 20 (8)* | 45 (44) | 72 (7) | 42 (11) | 55 (8) |
| Female | 83 (59) | 73 (9) | 2 (2) | 17 (7) | 58 (56) | 73 (8) | 38 (11) | 52 (10) | |
| Diabetes: | Yes | 28 (20) | 75 (9)* | 2 (2) | 18 (6) | 20 (19) | 73 (9) | 38 (8) | 53 (6) |
| No | 112 (80) | 70 (11) | 2 (2) | 18 (8) | 83 (81) | 73 (8) | 40 (12) | 53 (10) | |
| Hypertension: | Yes | 54 (39) | 74 (8)* | 2 (2) | 18 (7) | 39 (38) | 74 (7) | 38 (11) | 51 (10) |
| No | 86 (61) | 69 (12) | 2 (2) | 19 (7) | 64 (62) | 72 (8) | 41 (11) | 54 (9) | |
| Depression: | Yes | 17 (12) | 64 (8)* | 3 (3) | 18 (6) | 11 (11) | 65 (9)* | 39 (8) | 48 (12)* |
| No | 123 (88) | 72 (11) | 2 (2) | 18 (8) | 92 (89) | 74 (7) | 40 (11) | 54 (9) | |
Independent sample t-test was used to detect differences between groups for each predictor (mean (SD)). *Significant difference between groups at p < 0.05. ASES: American Shoulder and Elbow Surgeons, SF-12: Short Form-12 survey, PCS: physical component summary, MCS: mental component summary.
Predictors (independent variables)
The predictive variables of interest included patient demographics: age and sex, and comorbidities: diabetes, hypertension and depression. Patients with a preoperative self-report of diabetes, hypertension, and depression were identified and were designated to the study cohort. The prediction effect of these factors has been examined twice; first on the final scores at one-year for ASES pain and function and for SF-12 PCS and MCS, and second on the change of scores from baseline to one-year follow-up visit for ASES function and SF-12 PCS.
Statistical analysis
Statistical analyses were performed using SPSS software, version 23 (SPSS Inc., Chicago, IL, USA). A p value of <0.05 was considered statistically significant. Independent sample t-test was used to detect differences in the ASES and the SF-12 scores between patients based on the predictive variables: patients demographics (age and sex) and the presence of comorbidities (diabetes, hypertension, depression). All values are reported as mean and standard deviation (SD). Pearson’s correlation coefficients (r) were calculated between the dependent and predictive variables and between the predictive variables. The effect size of Pearson’s correlations were classified as follow: r = +/- .1= small effect, r = +/- .3 = medium effect, r = +/- .5 = large effect.15 Next, a multivariable enter regression analysis was performed to examine the effect of the predictive variables on the improvement in ASES and SF-12 one-year following shoulder arthroplasty. For ASES, pain at one-year was added to a second multivariable enter regression model as a predictive variable to examine its effect on function. To predict the clinical benefits of shoulder arthroplasty, we calculated the change in ASES function and SF-12 PCS scores by subtracting scores at one-year follow-up visit from baseline scores. Then, a multivariable enter regression analysis was performed on the change scores of ASES function and SF-12 PCS. All the assumptions of multiple regression including the test of normality, heteroscedasticity, multicollinearity and linearity were examined prior to the regression analysis.
Results
Descriptive statistics
Within this cohort, 140 patients completed the ASES and 103 patients completed the SF-12 survey. The average age of patients was 71 years (range, 47-89 years). 57% of patients underwent TSA, 33% underwent reverse TSA and 10% underwent hemiarthroplasty.
Table 1 represents the influence of the patients’ demographics on ASES and SF-12 scores one-year following shoulder A arthroplasty. For ASES, age was significantly different between patients in all subgroups (p <.05). Males and patients with depression were younger than females and patients without depression while patients with diabetes and hypertension were older than patients without these two conditions. Males had significantly better function compared to females (r = -.27, p = .001) (Table 2). For the SF-12, patients with depression were younger and had worse mental health status compared to patients without depression (Table 1).
Table 2.
Pearson’s Correlations Between Predictors and Dependent Variables One-year Following Shoulder Arthroplasty
| Dependent variables | Predictors | ||||
|---|---|---|---|---|---|
| Age | Sex | Diabetes | Hypertension | Depression | |
| ASES: | |||||
| Pain at one-year | .1 | .11 | .01 | .06 | .2* |
| Function: Model 1 | |||||
| Demographics+ comorbidities Function: Model 2 | -.02 | -.27* | -.07 | .01 | -.03 |
| Demographics+ comorbidities + residual pain Change in function scores SF-12: | -.02 .03 | -.27* -.09 | .01 .11 | -.07 -.01 | -.03 -.02 |
| PCS at one-year | -.31* | -.14 | -.08 | -.14 | -.03 |
| Change in PCS scores | -.17* | -.17 | .07 | -.12* | -.07 |
| MCS at one-year | .08 | -.18* | .01 | -.15 | -.21* |
Change in scores was calculated by subtracting scores at one-year follow-up visit from baseline scores
Function Model 1 predictors: age, sex, diabetes, hypertension, and depression.
Function Model 2 predictors: pain at one-year, age, sex, diabetes, hypertension, and depression
* Significant at p < .05. ASES: American Shoulder and Elbow Surgeons, SF-12: Short Form-12 survey, PCS: physical component summary, MCS: mental component summary.
Pearson’s correlations
Pearson’s correlation between dependent variables and predictors are summarized in Table 2. The coefficients ranged from -.31 to .20. There were significant correlations (p <.05) with a small effect size between ASES pain and depression, ASES function and sex, MCS and sex, MCS and depression, and a medium effect size between PCS and age. Patients with depression reported higher pain and worse mental health status, male patients had better shoulder function and mental health status, and younger patients had better physical health status (Table 2).
When pain at one-year was added as a predictor to examine its effect on function, results revealed a moderate relationship between residual pain and function (r = -.51, p <.001) indicating that patients with higher pain had poorer shoulder function. In addition, there was a negative association between the change in function scores and residual pain (r = -.36, p <.001) indicating that patients who reported pain at one-year follow-up visit had less improvement in shoulder function.
Pearson’s correlations were performed to examine collinearity between predictors. For ASES pain and function, results revealed significant correlations between diabetes and hypertension (r = -.25, p < .002) and between age and depression (r = .26, p < .001). For SF-12 PCS and MSC, results revealed significant correlations between diabetes and hypertension (r = -.33, p < .001) and between age and depression (r = -.34, p < .001). However, these correlations are weak.15 We concluded that there is no collinearity within our data.
Multivariable regression analysis
The regression model is summarized in Table 3. In predicting pain, depression was the only significant predictor of pain (b = 1.5, SE = .63, t (140) = 2.4, p = .02) indicating that the presence of depression increases pain by 1.5 units. Together, all predictors explained 6% of the variability in pain.
Table 3.
Regression Model Summary for Dependent Variables One-year Following Shoulder Arthroplasty
| Dependent variables ASES: | R | R2 | Adj. R2 | SE | F-statistics | Sig |
|---|---|---|---|---|---|---|
| Pain | .25a | .06 | .03 | 2.3 | 1.7 | NS |
| Function: Model 1 | ||||||
| Demographics+ comorbidities | .28a | .08 | .05 | 7.3 | 2.3 | .05 |
| Function: Model 1 | ||||||
| Demographics+ comorbidities + pain at one-year | .56b | .32 | .28 | 6.3 | 10 | .001 |
| Change in function | .38b | .15 | .11 | 6.8 | 3.9 | .0001 |
| SF-12: | ||||||
| PCS | .37a | .14 | .09 | 10.5 | 3.0 | .01 |
| Change in PCS | .34a | .12 | .07 | 10 | 2.5 | .033 |
| MCS | .31a | .10 | .05 | 9.0 | 2.0 | NS |
Dependent variables at one-year
aPredictors: (constant), age, sex, hypertension, diabetes, depression
bPredictors: (constant), pain at one-year, age, sex, hypertension, diabetes, depression
Change in scores was calculated by subtracting scores at one-year follow-up visit from baseline scores
Function Model 1 predictors: age, sex, diabetes, hypertension, and depression.
Function Model 2 predictors: pain at one-year, age, sex, diabetes, hypertension, and depression
ASES: American Shoulder and Elbow Surgeons, SF-12: Short Form-12 survey, PCS: physical component summary, MCS: mental component summary, NS: nonsignificant.
For shoulder function, sex was a significant predictor of function (b = -4.2, SE = 1.3, t (140) = -3.2, p = .002) indicating that being a male improves shoulder function by 4.2 scores on ASES index. All predictors explained 8% of the variability in function. When pain at one-year was added as a predictor in the final model, results revealed that both sex and pain (b = -1.6, SE = .24, t (140) = -6.7, p < .001) were significant predictors of function. This indicated that as pain increases by one unit, shoulder function decreases by 1.6 scores. The explained variability in function increased to 32% with a greater contribution of pain.
In predicting the clinical benefits of shoulder arthro-plasty, only residual pain was a significant predictor of the change in function scores (b = -1.1, SE = .26, t (140) = -4.4, p <.001). This indicated that with 1 unit increase in residual pain, the improvement of shoulder function decreases by 1.1 scores. Together, all predictors explained 15% of the variability in the improvement in function.
In predicting SF-12 physical and mental health status, age was a significant predictor of physical health status (b = -.48, SE = .15, t (103) = -3.3, p = .001). With one-year increase in age, physical health status decreases by 0.5 scores. Depression had a trend to predict mental health status (b = -6.1, SE = 3.2, t (103) = -1.9, p = .058). Together, all predictors explained 14% of the variance in physical health status and 10% of the variance in mental health status.
In predicting the change in PCS, none of the predictors were significant. However, there was a trend for both age and hypertension to predict the change in PCS (p = .055). The explained variability in PCS change scores was 12%.
Discussion
This study found that residual pain at one-year after shoulder arthroplasty is associated with poorer shoulder function. In addition, residual pain is the most significant predictor of function, and with other predictors, it explains 32% of the variability in shoulder function one-year after shoulder arthroplasty. Furthermore, residual pain is found to be the only predictor of improvement in shoulder function and clinical benefits following shoulder arthroplasty.
It is well established that shoulder pain can significantly affect function and the ability to perform activities of daily living16 and pain relief is the primary goal of patients who undergo shoulder arthroplasty.17 However, for some patients, post-surgical pain persists one to two years after shoulder arthroplasty, being most problematic for patients with fractures or osteoarthritis.18 Our study found that residual pain at one-year is reported by 61% of patients who underwent shoulder arthroplasty but is highly variable in intensity (range: 0.2 - 10, VAS scale). In addition, higher pain is associated with worse shoulder function. Higher pain may be related to arthritis in the contralateral shoulder or in other parts of the arm since often outcome measures do not differentiate the location of the pain. However, it is also possible that closer attention to pain peri-operatively and during rehabilitation could improve these outcomes.
In our study, statistically significant poorer shoulder function is associated with female sex. In addition, although female sex is associated with lower functional scores, it is not associated with less change in function which suggest that men and women get equal benefit from the shoulder arthroplasty. Furthermore, women are more likely to have a negative change in mental health following surgery in comparison to men (Table 2). We showed that pain is highly related to poor shoulder function and, although not significant, women tend to report higher pain (Table 1). This may explain the poorer shoulder function for women. These findings are consistent with previous studies in which male patients had better improvement in function at a longer follow-up periods ranged from two to six years following TSA.2,7
In the present study, age is not a significant factor in predicting the change in shoulder scores nor the one-year shoulder function. However, age relates significantly to physical health status, in which younger patients had better physical health status, and to a lesser extent physical change over the year but not to mental health.
These findings are consistent with the study of Donigan et al. (n = 106) who reported a non-significant correlations between age and improvement in shoulder function7. However, advanced age was associated with significant better change in shoulder function in one study two-year after TSA (n = 102)2 and with less improvement in shoulder function at the time of surgery5 and at one-year follow-up6 after shoulder arthroplasty. Advanced age was also associated with lower physical health status in the study of Matsen et al.4 In addition, Matsen et al.4 reported that the overall well-being of patients before TSA is strongly correlated with the quality of the outcomes.4
These conflicting findings might be related to the conflicting mechanisms by which age can mediate outcomes. Advanced age is associated with lower occupational and life demands for most people. Further, shoulder disorders and pathologies are common in older adults and are associated with general decline in physical health and quality of life.8,19 However, in our regression analysis, we showed that age is not a significant predictor of the change in physical health status. This may indicate that physical health status is expected to improve following shoulder arthroplasty regardless to age. Other reasons for the conflicting conclusions among studies may include the use of different patient-reported assessment tools, the differences in the inclusion criteria, and the various sample sizes.
In general, comorbidities including diabetes, hypertension, and depression did not affect the final outcome status nor the amount of improvement gained with surgery for shoulder function, and physical and mental health status of this cohort’ patients following shoulder arthroplasty. However, depression is associated with higher levels of pain and there is a trend toward worse mental health status (p = .058). Our lack of ability to show significant correlations between function and comorbidities is consistent with previous research.7,9 These results are also consistent with our previous research11 in which we showed that patients with and without diabetes recovered to the same functional level at one-year following shoulder arthroplasty despite significantly worse pre-operative function in diabetic patients. We concluded that patients with diabetes achieve large clinical benefits from shoulder arthroplasty, with follow-up outcomes equally positive to those without diabetes.11 However, the non-significant association between depression and shoulder function may be due to our low sample size of patients with depression (n = 17). This lack of association differs with the study of Werner et al.10 who reported significant effect of depression on shoulder function in 88 patients with depression assessed using ASES scale.10 Our regression model showed a significant effect of depression on ASES pain in which depression, with other predictors, explained 6% of the variability of pain. However, the low percentage of the explained variability in pain might not have a clinical importance. Werner et al.10 did not include a subscale of ASES pain for comparison.
This study provides new information about the impact of age, sex, diabetes, hypertension and depression on shoulder pain and function, and physical and mental health status one-year following shoulder arthroplasty. The data of this study were collected prospectively from a large cohort of patients who underwent shoulder arthro-plasty. Shoulder pain and function, and physical and mental health status were evaluated using valid and reliable outcomes measures which have been used previously by several studies.4,10 However, this study has several limitations. As with all regression models, a significant statistical relationship does not imply causation. Further, in some of our models the explained variation was quite small and thus the clinical importance of even to statistically significant correlations must be questioned. Our data was derived from a single specialty upper extremity program and may not be generalize to other clinical practices. We cannot distinguish the location of pain and thus residual pain is not necessarily related to the operated shoulder. However, none of these limitations diminish the value of this study which presented important information in a way that allow clinicians to incorporate its findings into their decision-making when planning for this surgical procedure.
Conclusion
This study found that residual pain is associated with poorer shoulder function at one-year and less clinical benefits over time. Female sex is associated with worse shoulder function at one-year but not with less change in function over time which suggest that men and women get equal benefit from the surgery. Comorbidities do not affect the final outcomes status and the amount of improvement gained with surgery. Advanced age relates to poorer physical health status and to a lesser extent physical change over the year. Lastly, patients with depression had higher pain than patients without this condition. Identifying risk factors for poor functional outcomes following shoulder arthroplasty can assist clinicians in counselling patients on the expected outcome following shoulder arthroplasty.
Acknowledgment
Dr. Joy C MacDermid was supported by a CIHR Chair in Gender, Work and Health and the Dr. James Roth Research Chair in Musculoskeletal Measurement and Knowledge Translation during the conduct of this study. CIHR FRN: SCA-145102
References
- 1.Kim SH, Wise BL, Zhang Y, Szabo RM. Increasing incidence of shoulder arthroplasty in the United States. JBJS. 2011;93:2249–54. doi: 10.2106/JBJS.J.01994. [DOI] [PubMed] [Google Scholar]
- 2.Fehringer EV, Kopjar B, Boorman RS, Churchill RS, Smith KL, Matsen III FA. Characterizing the functional improvement after total shoulder arthro-plasty for osteoarthritis. JBJS. 2002;84:1349–53. doi: 10.2106/00004623-200208000-00009. [DOI] [PubMed] [Google Scholar]
- 3.Orfaly RM, Rockwood CA, Esenyel CZ, Wirth MA. A prospective functional outcome study of shoulder arthroplasty for osteoarthritis with an intact rotator cuff. J shoulder Elb Surg. 2003;12:214–21. doi: 10.1016/s1058-2746(02)86882-3. [DOI] [PubMed] [Google Scholar]
- 4.Matsen III FA, Antoniou J, Rozencwaig R, Campbell B, Smith KL. Correlates with comfort and function after total shoulder arthroplasty for degenerative joint disease. J shoulder Elb Surg. 2000;9:465–9. doi: 10.1067/mse.2000.109323. [DOI] [PubMed] [Google Scholar]
- 5.Rozing PM, Nagels J, Rozing MP. Prognostic factors in arthroplasty in the rheumatoid shoulder. HSS J. 2011;7:29–36. doi: 10.1007/s11420-010-9172-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Robinson CM, Page RS, Hill RMF, Sanders DL, Wakefield AE. Primary hemiarthroplasty for treatment of proximal humeral fractures. JBJS. 2003;85:1215–23. doi: 10.2106/00004623-200307000-00006. [DOI] [PubMed] [Google Scholar]
- 7.Donigan JA, Frisella WA, Haase D, Dolan L, Wolf B. Pre-operative and intra-operative factors related to shoulder arthroplasty outcomes. Iowa Orthop J. 2009;29:60. [PMC free article] [PubMed] [Google Scholar]
- 8.Hopman WM, Harrison MB, Coo H, Friedberg E, Buchanan M, VanDenKerkhof EG. Associations between chronic disease, age and physical and mental health status. Chronic Dis Can. 2009;29:108–16. [PubMed] [Google Scholar]
- 9.Levy JC, Ashukem MT, Formaini NT. Factors predicting postoperative range of motion for anatomic total shoulder arthroplasty. J shoulder Elb Surg. 2016;25:55–60. doi: 10.1016/j.jse.2015.06.026. [DOI] [PubMed] [Google Scholar]
- 10.Werner BC, Wong AC, Chang B, Craig EV, Dines DM, Warren RF, et al. Depression and patient-reported outcomes following total shoulder arthroplasty. JBJS. 2017;99:688–95. doi: 10.2106/JBJS.16.00541. [DOI] [PubMed] [Google Scholar]
- 11.Sana’a AA, MacDermid JC, Overend TJ, Faber KJ. Does diabetes affect functional outcomes after shoulder arthroplasty? J Clin Orthop Trauma. 2019. (Published online) [DOI] [PMC free article] [PubMed]
- 12.Richards RR, An K-N, Bigliani LU, Friedman RJ, Gartsman GM, Gristina AG, et al. A standardized method for the assessment of shoulder function. J Shoulder Elb Surg. 1994;3:347–52. doi: 10.1016/S1058-2746(09)80019-0. [DOI] [PubMed] [Google Scholar]
- 13.Ware J, Kosinski M, Keller SD. A 12-item Short-Form health survey : Construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34:220–33. doi: 10.1097/00005650-199603000-00003. [DOI] [PubMed] [Google Scholar]
- 14.Angst F, Pap G, Mannion AF, Herren DB, Ae-schlimann A, Schwyzer H, et al. Comprehensive assessment of clinical outcome and quality of life after total shoulder arthroplasty: usefulness and validity of subjective outcome measures. Arthritis Care Res (Hoboken) 2004;51:819–28. doi: 10.1002/art.20688. [DOI] [PubMed] [Google Scholar]
- 15.Field A. Discovering statistics using IBM SPSS statistics. London,UK: Sage; 2013. [Google Scholar]
- 16.Greenberg DL. Evaluation and treatment of shoulder pain. Med Clin. 2014. –98.pp. 487–504. [DOI] [PubMed]
- 17.Henn III RF, Ghomrawi H, Rutledge JR, Ma-zumdar M, Mancuso CA, Marx RG. Preoperative patient expectations of total shoulder arthroplasty. JBJS. 2011;93:2110–5. doi: 10.2106/JBJS.J.01114. [DOI] [PubMed] [Google Scholar]
- 18.Bjørnholdt KT, Brandsborg B, Søballe K, Niko-lajsen L. Persistent pain is common 1–2 years after shoulder replacement: A nationwide registry-based questionnaire study of 538 patients. Acta Orthop. 2015;86:71–7. doi: 10.3109/17453674.2014.987065. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Burner T, Abbott D, Huber K, Stout M, Fleming R, Wessel B, et al. Shoulder symptoms and function in geriatric patients. J Geriatr Phys Ther. 2014;37:154. doi: 10.1519/JPT.0b013e3182abe7d6. [DOI] [PMC free article] [PubMed] [Google Scholar]