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BMC Musculoskeletal Disorders logoLink to BMC Musculoskeletal Disorders
. 2024 Dec 4;25:992. doi: 10.1186/s12891-024-08099-1

Understanding preoperative health-related quality of life in rotator cuff tear patients: role of patients’ characteristics

Daniela Brune 1,2,, Thomas Stojanov 1,3,4, Andreas Marc Müller 3, David Weibel 2,5, Sabina Hunziker 6, Stephanie Erdbrink 7; ARCR_Pred Study Group, Laurent Audigé 1,3,8
PMCID: PMC11619111  PMID: 39633338

Abstract

Background

Assessing health-related quality of life (HRQoL) is a widely employed method in orthopedics to evaluate patient well-being and measure the effectiveness of surgical interventions. Understanding the relationship between specific baseline factors and preoperative HRQoL can help clinicians identify patients at risk for low quality of life and thus, develop preventive strategies that adequately address individual patient needs. The objective was to assess associations between baseline factors and preoperative HRQoL in patients undergoing arthroscopic rotator cuff repair (ARCR).

Methods

This study is part of a multicenter prospective Swiss cohort study that included patients undergoing ARCR between June 2020 and November 2021. Data were derived from baseline and surgery forms. HRQoL was assessed using the European Quality of Life 5-Dimension 5-Level (EQ-5D-5L) questionnaire to calculate EQ-5D index and EQ VAS scores. Univariable and multivariable linear regression models examined associations between the 21 factors and preoperative HRQoL. Final models were determined using stepwise backward regression.

Results

A total of 973 included patients (mean age [SD], 57.3 [9.4] years; 611 men [63%]) had a mean [SD] EQ-5D index and EQ VAS of 0.70 [0.23] and 68.7 [19.8], respectively. Being male (regression coefficient (β), 0.05; 95% CI [0.02–0.08]), having a higher age (β, 0.02; 95% CI [0.01–0.03]) and higher education levels (e.g., university, college: β, 0.11; 95% CI [0.06–0.16]) were associated with a higher EQ-5D index. Increased body mass index (β, -0.02; 95% CI [-0.04 to -0.01]) and worse sleep quality (β, -0.03; 95% CI [-0.04 to -0.03]) were associated with a lower EQ-5D index. Factors negatively associated with overall EQ VAS health were depression (e.g., moderate: β, -12.70; 95% CI [-16.18 to -9.21]), presence of at least one comorbidity (β, -3.71; 95% CI [-5.91 to -1.52]), and pain (β, -1.81; 95% CI [-2.36 to -1.26]).

Conclusion

Our results suggest that preoperative HRQoL is highly associated with sociodemographic and patient-related factors. Specifically addressing these factors may improve orthopedic care.

Keywords: Health related quality of life, Arthroscopy, Shoulder, EQ-5D-5L

Introduction

Understanding patients’ perception of their health and assessing health-related quality of life (HRQoL) is important for evaluating medical interventions and their economic impact [15]. There is no generally accepted definition of HRQoL. According to a recent review [6], the following definitions are used: HRQoL may include measures of functioning and well-being in physical, mental, and social domains, or it may refer exclusively to health-related factors. Furthermore, HRQoL may refer to scores associated with different health conditions or to self-perceived well-being that is influenced by health conditions or treatments.

One of the most widely used generic tools for collecting HRQoL data is the European Quality of Life [7] 5-Dimension 5-Level Questionnaire (EQ-5D-5L) [8]. Despite the large ceiling effects observed in general population samples, the EQ-5D-5L is proven as a reliable and valid instrument to describe health states in a wide range of populations and settings [2, 911]. In the field of orthopedic shoulder surgery, it is commonly used to assess HRQoL status and its improvement after surgery [12, 13], notably in the context of cost-utility analyses [14].

Several studies have examined predictors of postoperative functional outcomes [1518] and complications [17, 19] in patients undergoing arthroscopic rotator cuff repair (ARCR). Although HRQoL outcomes are considered essential for the evaluation of medical interventions [5], the number of studies reporting associations between potential predictors and HRQoL remains limited. Lower perceived quality of life correlates with worse functional outcomes, increased symptoms of anxiety and depression as well as higher pain scores two years after rotator cuff repair surgery [20]. The severity of preoperative psychological distress such as depression and anxiety is linked to increased functional impairment and reduced HRQoL in patients scheduled for rotator cuff repair [21]. However, these baseline predictors do not predict poorer HRQoL after ARCR [22]. Higher HRQoL scores two years after surgical repair of the rotator cuff are associated with male sex, minor tear retraction, no social benefits, and duration of presurgical complaints for more than six months [23]. These distinct predictors were identified by using a disease-specific quality of life instrument, the Western Ontario Rotator Cuff Index, yet were not associated with higher HRQoL scores when assessed using the generic EQ-5D questionnaire.

While many studies have shown significant improvements in HRQoL following rotator cuff repair [13, 24, 25], there is a lack of literature investigating predictors associated with HRQoL both before and after surgery. Current research provides a limited understanding of the patient and shoulder characteristics associated with this outcome. Identifying predictors associated with HRQoL is critical to target patients at risk, identify modifiable factors and consequently, refine surgical indications for improving patient quality of life outcomes. Therefore, the purpose of this exploratory analysis was to report associations between baseline factors and preoperative HRQoL as defined by the EQ-5D index (1) and EQ VAS (2) scores in patients undergoing ARCR.

Methods

Study design and patient selection

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [26] was used as a reporting guideline. Data were obtained from the ARCR_Pred cohort study [27], a prospective multicenter cohort study of patients undergoing ARCR. The main objective of the ARCR_Pred cohort study is to evaluate and predict the safety and effectiveness of ARCR and was conducted in 18 Swiss clinics and 1 clinic in Germany. Among 2,385 patients screened for eligibility, 973 patients underwent primary ARCR to treat a rotator cuff tear between June 3, 2020 and November 10, 2021, and were documented up to 24 months postoperatively. In addition to recording clinical examination parameters and surgical details, patient-reported outcome measures were recorded using a study-specific questionnaire that was completed by each patient at baseline (preoperative) as well as 6, 12 and 24 months post-ARCR. For this specific analysis, all data originate from baseline and surgery forms only and include the entire ARCR_Pred patient cohort.

Study participants were adult patients diagnosed with either a partial or complete rotator cuff tear on magnetic resonance imaging (MRI), confirmed intraoperatively and scheduled for primary arthroscopic surgical repair. Patients with irreparable tears undergoing specific procedures (i.e., tendon transfer, subacromial spacer or superior capsular reconstruction), revision surgery and surgical techniques other than arthroscopy (i.e., open or mini-open) were excluded. Patients with bilateral ARCR were only included for their first intervention. Patients who were not fluent in German, French, Italian or English, patients who were unable to attend the clinics for follow-up visits and pregnant women were also excluded.

The study and resulting analysis of the prospectively documented clinical data were approved by the lead ethics committee in April 2020 (Ethikkommission Nordwest- und Zentralschweiz (EKNZ), Basel, Switzerland; ID: 2019–02076). All patients provided written informed consent for their data to be used for research purposes at the time of inclusion.

Response variable

HRQoL was assessed using the EQ-5D-5L questionnaire [7, 28], a generic multiattribute health utility instrument comprising 5 dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has 5 response options coded on an ordinal scale ranging from 1 to 5, where 1 indicates no problem, 2 a mild problem, 3 moderate, 4 severe and 5 an extreme problem. Combined responses form a 5-digit health state that reflects the score on each dimension (e.g., where 11111 indicates the best health state and 55555, the worst). When the descriptive system profile is linked to a value set, the result is a summary index value representative of the assessed health state that can be used in economic evaluations of health interventions [29]. The EQ-5D index provides weights for each description of the health state according to the preferences of the general population of a country or region [7]. Due to the lack of a value set for the Swiss population, the index value was based on the German value set [30, 31]. The EQ-5D-5L utility index demonstrates robust construct validity, responsiveness and discriminative capacity in patients following ARCR and emerges as a suitable tool for quantifying HRQoL despite encountering large ceiling effects [10]. In addition, the overall health state was assessed using a visual analog scale (EQ VAS) [7] ranging from 0 (worst imaginable health) to 100 (best imaginable health).

Baseline prognostic variables

Twenty-one predictors of interest were retrieved from the ARCR_Pred cohort study and included in the final analysis. Sociodemographic and patient-related variables were assessed using a study-specific questionnaire and included sex, age (at the time of surgery), marital status (married, in a partnership or single/widowed, divorced or separated), current employment status (employed, unemployed or retired), current smoking status (never, former smoker or current smoker), weekly frequency of physical activity/sport (never, less than once a week, once a week or twice a week or more), presence of comorbidities (yes or no) and highest educational achievement. The latter was divided into three categories: compulsory education (representing the years of mandatory [primary] education); apprenticeship or high school (including all forms of secondary or vocational education; and tertiary education involving the completion of a university or college degree. In addition, body mass index (BMI) [32] and the American Society of Anesthesiologists (ASA) physical status classification [33] were retrieved from the respective clinical data pool of each participating study center. Patients’ mental health status (i.e., depression and anxiety levels) was assessed using the Patient-Reported Outcome Measurement Information System (PROMIS) Short Form 4a [34]. The PROMIS measure scores use T-scores [35] generated using a software application of the “HealthMeasures Scoring Service” (accessed via www.assessmentcenter.net). Based on PROMIS score cut point guidelines, depression and anxiety levels were categorized as normal (< 50), mild (55–60), moderate (60–70) and severe (> 70). Baseline pain (numeric rating scale (NRS) with 0 = no pain; 10 = intolerable pain), duration of shoulder complaints prior to surgery (0–1 months, > 1–3 months, > 3–6 months, > 6 months to 1 year or > 1 year) and baseline sleep quality (NRS with 0 = best possible sleep; 10 = worst possible sleep) were also assessed using a patient questionnaire.

Disease-related factors included intraoperatively assessed tear size (partial tear, single full tear, two or three tendons with only one tendon fully teared or massive tear), tear onset (traumatic or degenerative), signs of acromioclavicular joint arthritis (yes or no), and the degree of fatty infiltration of the supraspinatus, infraspinatus and subscapularis tendons (normal, moderate or severe) according to Fuchs et al. [36]. These factors were assessed by the primary surgeon on preoperative radiographs or MRI images with intraoperative confirmation.

Statistical analysis

Univariable and multivariable ordinary least-square linear regression models with robust standard errors (SEs) were used to estimate the associations between the 21 aforementioned factors with preoperative HRQoL scores based on both the EQ-5D index and EQ VAS as outcome variables. Robust SEs were applied as the outcome variable did not meet the heteroscedasticity assumptions for linear regression [37]. Regression coefficients (β) with 95% confidence intervals (CIs) and associated p-values were reported.

In the statistical modeling, all 21 factors were included as model covariates. Age and BMI were standardized (mean of 0 and a standard deviation [SD] of 1) and pain and sleep quality were treated as continuous variables. The remaining 17 categorical variables were treated as dummy variables and modelled categorically against a respective reference category. The most frequent category was chosen as the reference category to reflect deviations of smaller from larger groups [38]. Categorical variables such as marital status, education and work status were regrouped to 3 categorical levels to facilitate interpretation.

For both outcome variables, a final multivariable linear regression model was selected using a stepwise backward regression procedure based on the Bayesian Information Criterion (BIC), a model selection criterion, which, when minimized, favors the model with few included variables [39]. In addition, the coefficient of determination (R2), expressing the percentage of variability explained by the model, was used for model comparison.

For the EQ-5D index, its associations with depression, anxiety and pain were initially determined in the full model, but then removed from the final model. Two of the 5 EQ-5D-5L dimensions relate to pain/discomfort and anxiety/depression. By removing these factors, we wanted to identify a set of factors that predicted the EQ-5D index with the best accuracy and without introducing conceptual correlation between the explanatory variables and the outcome to be predicted. For EQ VAS, the full model included all 21 factors as this outcome variable represents a measure of global health independently rated by patients.

Study data were managed using the REDCap (Research Electronic Data Capture) system [40] and exported for variable transformation (including score calculations) and statistical analysis using Stata version 17 (StataCorp LP, College Station, TX). A two-sided significance level was set at p < 0.05.

Results

Patient characteristics and baseline score distribution

Of 973 patients, 362 (37%) were women (Table 1). The mean age for the entire cohort at the time of surgery was 57.3 years [SD, 9.4]. Most of the patients experienced shoulder complaints over one year (32%), although more than half of the cohort had tears of traumatic origin. Mean baseline NRS pain was 5.8 [SD, 2.2] and sleep quality was scored with a mean of 6.0 [SD, 2.5].

Table 1.

Univariable association of factors with HRQoL

Factors a EQ-5D index EQ VAS
β [95% CI] p-value β [95% CI] p-value
Patient-related and sociodemographic
 Sex, n (%)
Female 362 (37) [Reference] NA [Reference] NA
Male 611 (63) 0.07 [0.04 to 0.10] <.001 3.66 [1.07 to 6.26] .006
Age (years) (standardized), mean (SD) 57.3 (9.4) 0.02 [0.01 to 0.04] .003 0.85 [−0.35 to 2.05] .163
 Marital status, n (%)
Married 581 (60) [Reference] NA [Reference] NA
Partnership 109 (11) 0.01 [−0.03 to 0.05] .635 2.83 [−0.83 to 6.49] .129
Single, widowed, divorced, separated 283 (29) −0.03 [−0.06 to 0.01] .116 −3.21 [−6.08 to −0.35] .028
 Education, n (%)
Compulsory school 129 (13) [Reference] NA [Reference] NA
Apprenticeship, High school 493 (51) 0.11 [0.06 to 0.16] <.001 6.24 [1.88 to 10.61] .005
University, College 351 (36) 0.17 [0.12 to 0.23] <.001 10.94 [6.63 to 15.26] <.001
 Current employment status, n (%)
Employed 719 (74) [Reference] NA [Reference] NA
Unemployed 74 (8) −0.10 [−0.17 to −0.03] .006 −6.99 [−12.02 to −1.96] .007
Retired 180 (18) 0.02 [−0.02 to 0.05] .313 1.22 [−1.86 to 4.31] .436
 Smoking status, n (%)
Never smoked 575 (59) [Reference] NA [Reference] NA
Smoked before 194 (20) 0 [−0.04 to 0.04] .914 −2.28 [−5.48-0.93] .163
Current smoker 204 (21) −0.05 [−0.09 to −0.01] .026 −1.83 [−5.08-1.42] .269
 Frequency physical activity/sport, n (%)
Never 221 (23) [Reference] NA [Reference] NA
Less than once a week 95 (10) 0.08 [0.03 to 0.13] .001 2.46 [−2.09-7] .289
Once a week 173 (18) 0.08 [0.04 to 0.13] <.001 1.84 [−2.15-5.84] .366
Twice a week or more 484 (50) 0.08 [0.04 to 0.12] <.001 5.22 [1.77–8.67] .003
 PROMIS Depression Short Form 4a, n (%)
Normal 615 (63) [Reference] NA [Reference] NA
Mild 179 (18) −0.12 [−0.16 to −0.09] <.001 −10.83 [−13.82 to −7.84] <.001
Moderate 160 (16) −0.28 [−0.32 to −0.24] <.001 −15.84 [−19.39 to −12.28] <.001
Severe 19 (2) −0.73 [−0.85 to −0.61] <.001 −47.32 [−55.67 to −38.98] <.001
 PROMIS Anxiety Short Form 4a, n (%)
Normal 695 (71) [Reference] NA [Reference] NA
Mild 147 (15) −0.09 [−0.13 to −0.06] <.001 −8.41 [−11.88 to −4.95] <.001
Moderate 110 (11) −0.28 [−0.33 to −0.23] <.001 −16.68 [−20.85 to −12.5] <.001
Severe 21 (2) −0.71 [−0.83 to −0.58] <.001 −30.95 [−41.81 to −20.1] <.001
BMI (standardized), mean (SD) 26.8 (4.4) −0.03 [−0.04 to −0.01] <.001 −2.36 [−3.58 to −1.13] <.001
 ASA classification, n (%)
I 429 (44) [Reference] NA [Reference] NA
II 472 (49) −0.03 [−0.06 to 0] .101 −3.98 [−6.52 to −1.44] .002
III 72 (7) −0.05 [−0.11 to 0.01] .082 −8.73 [−14.1 to −3.37] .001
 One or more comorbidities
No 462 (47) [Reference] NA [Reference] NA
Yes 511 (53) −0.04 [−0.07 to −0.01] .004 −5.46 [−7.92 to −2.99] <.001
Pain (NRS; 0=no pain; 10=intolerable pain ), mean (SD) 5.8 (2.2) −0.06 [−0.07 to −0.05] <.001 −3.04 [−3.61 to −2.46] <.001
Sleep Quality (NRS; 0=best possible sleep; 10=worst possible sleep), mean (SD) 6.0 (2.5) −0.04 [−0.04 to −0.03] <.001 −2.06 [−2.54 to −1.58] <.001
Disease-related factors
 Tear size (intraoperative), n (%)
Partial tear 147 (15) [Reference] NA [Reference] NA
Single full tear 255 (26) 0.01 [−0.04 to 0.06] .583 −0.03 [−4.36-4.3] .990
Two or three tendons (only one full) 417 (43) 0.04 [−0.01 to 0.09] .093 1.61 [−2.31-5.53] .421
Massive tear 154 (16) 0 [−0.05 to 0.06] .903 2.69 [−1.89-7.26] .249
 Duration of shoulder complaints, n (%)
0–1 months 139 (14) [Reference] NA [Reference] NA
>1–3 months 186 (19) 0 [−0.05 to 0.05] .911 −0.61 [−4.99-3.76] .784
>3–6 months 166 (17) 0.04 [−0.01 to 0.09] .127 0.93 [−3.47-5.34] .677
>6 months to 1 year 173 (18) 0.04 [−0.01 to 0.09] .113 −0.78 [−5.16-3.59] .725
>1 year 309 (32) 0 [−0.04 to 0.05] .912 −1.44 [−5.49-2.62] .487
 Tear origin, n (%)
Degenerative 457 (47) [Reference] NA [Reference] NA
Traumatic 516 (53) 0.02 [−0.01 to 0.05] .111 2.89 [0.4–5.38] .023
 Signs of AC joint arthritis, n (%)
No 385 (40) [Reference] NA [Reference] NA
Yes 588 (60) −0.02 [−0.05 to 0.01] .298 −1.50 [−4.04-1.04] .246
 Fatty infiltration - SSP tendon, n (%)
Normal 879 (90) [Reference] NA [Reference] NA
Moderate 82 (8) −0.02 [−0.07 to 0.03] .407 −0.25 [−4.32-3.83] .906
Severe 12 (1) 0.03 [−0.13 to 0.18] .744 −0.14 [−12.83-12.55] .983
 Fatty infiltration - SSC tendon, n (%)
Normal 922 (95) [Reference] NA [Reference] NA
Moderate 48 (5) −0.04 [−0.12 to 0.03] .273 2.15 [−3.31-7.61] .439
Severe 3 (0) −0.21 [−0.42 to 0.01] .060 −1.60 [−20.79-17.59] .870
 Fatty infiltration - ISP tendon, n (%)
Normal 917 (94) [Reference] NA [Reference] NA
Moderate 53 (5) −0.03 [−0.10 to 0.04] .342 0.70 [−4.60 to 6.01] .795
Severe 3 (0) −0.11 [−0.52 to 0.30] .584 1.68 [−22.7 to 26.06] .893

Abbreviations: HRQoL Health-related quality of life, EQ-5D European quality of life 5-dimension, EQ VAS European quality of life visual analog scale; β, regression coefficient; [Reference], categorical variables were treated as dummy variables and modelled categorically against reference category; NA Not applicable, PROMIS Patient-reported outcome measurement information system, BMI Body mass index, ASA American Society of Anesthesiologists physical status, AC Acromioclavicular, SSP Supraspinatus, SSC Subscapularis, ISP Infraspinatus, VAS Visual analog scale, NRS Numeric rating scale

a N = 973 indicates total number of patients included in the regression analysis

Figure 1 shows the distribution of responses to the EQ-5D-5L questionnaire based on each of the 5 dimensions. The least affected dimensions prior to surgery were mobility and anxiety/depression with 75% and 62% of patients reporting no problems, respectively. Conversely, the dimension of pain/discomfort was most affected after a rotator cuff tear with a total of 73% reporting extreme (2%), severe (22%), and moderate (49%) problems.

Fig. 1.

Fig. 1

Distribution of EuroQoL-5 Dimensions-5-Level questionnaire (EQ-5D-5L) responses per dimension

The mean EQ-5D index was 0.70 [SD, 0.23; median, 0.79] with a distribution skewed towards the best possible health state and a score range of −0.38 to 1 (Fig. 2). Twelve (1%) patients had a score of 1, indicative of the best possible health state. The mean EQ VAS was 68.7 [SD, 19.8; median, 72.0] with a score range of 0 to 100, where 28 (3%) patients reported having the best imaginable overall health.

Fig. 2.

Fig. 2

Distribution of baseline EQ-5D index value and EQ VAS scores. Index score was multiplied by 100 for better visualization

Univariable factor associations

Table 1 presents the associations between HRQoL and the 21 factors using univariable linear regression models. Higher values of the EQ-5D index were associated with being male (β, 0.07; 95% CI [0.04–0.1]), having a higher age at the time of surgery (β, 0.02, 95% CI [0.01–0.04]) as well as having a higher education (e.g., university, college: β, 0.17; 95% CI [0.12–0.23]) and participating in weekly sports activity (less than once a week: β, 0.08, 95% CI [0.03–0.13]; once a week: β, 0.08, 95% CI [0.04–0.13]; twice a week: β, 0.08, 95% CI [0.04–0.12]).

The factors of being male (β, 3.66, 95% CI [1.07–6.26]), having a higher education (e.g. university, college: β, 10.94; 95% CI [6.63–15.26]) and a weekly sport frequency of two times a week (β, 5.22, 95% CI [1.77–8.67]) were also associated with a higher overall health as defined by EQ VAS.

Lower EQ-5D index values were associated with unemployment (β, −0.10, 95% CI [−0.17 to −0.03]), a current smoking status (β, −0.05, 95% CI [−0.09 to −0.01]), higher BMI (β, −0.03, 95%-CI [−0.04 to −0.01]), depression (e.g., moderate: β, −0.28, 95% CI [−0.32 to −0.24]]), anxiety (e.g., moderate: β, −0.28, [95% CI [−0.32 to −0.24]), presence of at least one comorbidity (β, −0.04, 95% CI [−0.07 to −0.01]), pain (β, −0.06, 95% CI [−0.07 to −0.05]) and affected sleep quality (β, −0.04, 95% CI [−0.04 to −0.03]). These 8 aforementioned factors as well as being single, widowed or divorced (β, −3.21, 95% CI [−6.08 to −0.35]) were also associated with a lower EQ VAS score.

Disease-related factors did not have associations with the EQ-5D index. Only traumatic tears (β, 2.89, 95% CI [0.40–5.38]) were associated with higher EQ VAS scores.

Multivariable models of associated factors

Table 2 presents the associations between HRQoL and predictors in the multivariable linear regression models. Being male (β, 0.05, 95% CI [0.02–0.08]) and having a higher age at the time of surgery (β, 0.02, 95% CI [0.01–0.03]) as well as educational level (e.g., university, college (β, 0.11, 95% CI [0.06–0.16]) were associated with a higher EQ-5D index. A higher BMI (β, −0.02, 95% CI [−0.04 to −0.01]) and affected sleep quality (β, −0.03, 95% CI [−0.04 to −0.03]) were associated with a lower EQ-5D index. The frequency of weekly sport activities, a current smoking status and the presence of at least one comorbidity showed a significant association with the HRQoL outcome at the univariable level, however this was no longer apparent once included with other factors in the multivariable regression models.

Table 2.

Multivariable regression models of associations of factors with HRQoL

EQ-5D index value EQ VAS

R 2

BIC

0.194

−6908.970

R 2

BIC

0.243

1655.814

Factors a β [95% CI] p -value β [95% CI] p -value
Sex
 Female [Reference] NA
 Male 0.05 [0.02 – 0.08] .001
Age (years) (standardized) 0.02 [0.01 – 0.03] .003
Education
 Compulsory School [Reference] NA
 Apprenticeship, High School 0.07 [0.02 – 0.12] .003
 University, College 0.11 [0.06 – 0.16]  < .001
BMI (standardized) −0.02 [−0.04 – −0.01] .002
Sleep Quality (NRS 0 – 10) −0.03 [−0.04 – −0.03]  < .001
PROMIS Depression Short Form 4a
 Normal [Reference] NA
 Mild −9.39 [−12.34 – −6.43] < .001
 Moderate −12.70 [−16.18 – −9.21] < .001
 Severe −40.79 [−49.43 – −32.14] < .001
One or more comorbidities
 No [Reference] NA
 Yes −3.71 [−5.91 – −1.52] .001
Pain (VAS-Score 0 – 10) −1.81 [−2.36 – −1.26] < .001

Abbreviations: HRQoL Health-related quality of life, EQ-5D European quality of life 5-dimension, EQ VAS European quality of life visual analog scale, R 2 Coefficient of determination, BIC Bayesian Information Criterion, β Regression coefficient, [Reference] categorical variables were treated as dummy variables and modelled categorically against reference category, NA Not applicable, BMI Body mass index, NRS Numeric rating scale, PROMIS Patient-reported outcome measurement information system, VAS Visual analog scale

a N = 973 indicates total number of patients included in the regression analysis

In terms of EQ VAS, depression (e.g., moderate: β, −12.70; 95% CI [−16.18 to −9.21]) was associated with a lower score as well as the presence of a least one comorbidity (β, −3.71; 95% CI [−5.91 to −1.52]) and pain (β, −1.81; 95% CI [−2.36 to −1.26]).

Model performance

The multivariable models for the EQ-5D index and EQ VAS explained 19.4% and 24.3% of the variability of these HRQoL outcomes, respectively. For EQ VAS, the factor of depression alone was accountable for half of this variability (R2 = 12.4%).

Discussion

The main objective of this study was to determine the associations between 21 factors and preoperative HRQoL in patients undergoing ARCR using the EQ-5D index and EQ VAS. The findings suggest that being male, being older and having a higher education level were associated with higher preoperative HRQoL, whereas higher BMI and poorer sleep quality were associated with a lower score. For general health as indicated by the EQ VAS score, depression, the presence of at least one comorbidity and pain showed a negative association. Future research is needed to further investigate these associations and assess whether they persist postoperatively, as a clearer understanding of the long-term role of these factors on HRQoL plays an important role in guiding postoperative care strategies.

Compared to other fields [4146], there is a lack of well-conducted studies in orthopedics, especially in shoulder surgery, examining the associations between patient-related, sociodemographic and disease-related factors with preoperative HRQoL. Therefore, our results are not comparable with these indirectly related studies that investigated HRQoL and its associated factors. For example, one study investigated factors associated with HRQoL two years after rotator cuff repair using the disease-specific HRQoL questionnaire and found that higher HRQoL was associated with being male, having a minor tear retraction, having no social benefits and suffering from preoperative complaints spanning more than 6 months [23]. When using the generic HRQoL instrument EQ-5D, none of these factors showed any significant associations with HRQoL, which is inconsistent with our findings. Another study investigated quality of life one year after ARCR using the SF-36, a score that can be delineated into the domains of physical and mental HRQoL [47]. They found that older age, being female, having diabetes and undertaking a low level of sports activities are associated with lower physical HRQoL after surgery and only being female is related to low postoperative mental HRQoL. While our study aligns with these findings in terms of the associations of older age and being female with lower HRQoL scores, there are differences that highlight the complexity and variability of factors affecting HRQoL, particularly when using different measurement tools.

Studies on patients undergoing total knee arthroplasty identified factors such as obesity [4850], advanced age [49, 51], sex [48, 49], persistence of pain after the procedure [4850], a lengthy wait for the surgery [49] and comorbidities [4951] as negatively associated factors with postoperative HRQoL. However, comorbidities were not significantly associated with the baseline EQ-5D index, potentially due to the use of a dichotomized variable in our analysis. Indeed, having more detailed information regarding the comorbidity status of operated patients might lead to a better understanding of the underlying associations.

The EQ-5D index showed a negative association with BMI. Obesity is generally considered a risk factor for poorer postoperative outcomes following rotator cuff repair [52] and has been associated with worse postoperative HRQoL scores after total knee arthroplasty [48, 50, 53]. However, BMI was found to have no impact on functional outcome [54] or quality of life [55] in total shoulder arthroplasty patients; improvements in EQ-5D were, in fact, independent of BMI [55]. Its association with self-reported early outcomes after rotator cuff surgery remains inconclusive as it has been reported that obesity does not significantly impact self-reported early outcomes after the rotator cuff surgery [4, 52, 56].

Depression emerged as the most significant factor associated with preoperative HRQoL, accounting for around half of the total variance (24.3%), even though almost two-thirds of the patients reported having no anxiety/depression problems. This finding aligns with previous research [21, 23] that highlighted the influence of psychological distress on HRQoL in ARCR patients. In contrast to the assessment of HRQoL, the impact of mental health on functional outcomes in patients undergoing ARCR has been extensively investigated [22, 47, 57, 58]. Negative psychosocial factors such as anxiety and depression were consistently associated with poorer function and disability both before and after surgery [57, 59, 60].

Pain perception, closely linked to mental health, has a significant impact on HRQoL [21, 6165]. For example, in group comparisons, patients with pre-existing psychological distress have been found to experience significantly higher average levels of pain compared to patients without such distress, up to six months after surgery [62]. Further supporting this association, research in healthy volunteers identified shoulder pain as an independent risk factor significantly associated with reduced quality of life [66]. Higher pain intensity was also found to correlate with lower scores in both the physical and mental domains of HRQoL, as assessed by the SF-36 questionnaire.

Overall, our findings demonstrate that sociodemographic, patient-related and psychological factors are significantly associated with HRQoL in ARCR patients. Understanding and addressing these factors are important for improving patient outcomes and overall well-being. Disease-related predictors such as tear size, cuff retraction, fatty infiltration and multiple tendon involvement [16, 18, 67] had no significant association with preoperative HRQoL, highlighting the importance of considering psychosocial and health determinants in assessing overall health states.

Limitations

This study is restricted to patients with rotator cuff tears undergoing ARCR in Switzerland, which limits the generalizability of the findings to other patient populations or surgical settings. There is also a lack of studies examining the associations between predictors and HRQoL in this specific cohort, which makes it difficult to compare the results of this study.

In addition, the analysis did not consider associations between core concepts or potential confounding variables that were lacking in the ARCR_Pred study. For example, factors such as ethnicity, resilience or coping strategies, social support or pain catastrophizing were not collected. Moreover, some predictors such as comorbidities were treated as bivariate variables, consequently resulting in the loss of information.

The findings relied on self-reports (EQ-5D-5L) and brief mental health tests (PROMIS Short Form 4a), which may not capture formal diagnoses of major depressive disorder or generalized anxiety disorder. Alternative assessments such as Short Form-36 or Hospital Anxiety and Depression Scale could have been used for a more comprehensive evaluation of mental health. The EQ-5D is useful for measuring general HRQoL but has some limitations. There is no value set for the Swiss population and we applied the German value set to calculate the index values, which may affect the description of the health states according to the preference of the general Swiss population. Also, we treated the EQ-5D index value as a discrete scale while performing a linear regression analysis and we did not use any central tendencies in the statistical analysis.

Conclusion

This study examining the associations between baseline factors and preoperative HRQoL in a cohort of Swiss ARCR patients using the EQ-5D-5L addresses an important and unmet clinical need in the care of orthopedic patients. It emphasizes the importance of considering psychosocial and health determinants for assessing overall health states and highlights the significance of psychosocial factors in analyzing HRQoL data for rotator cuff injury patients. Additionally, the study underscores the need for a holistic approach to orthopedic care and acknowledges the impact of sociodemographic, patient-related and psychological factors on preoperative HRQoL scores. These observations should be taken into consideration for interpreting cost-utility analyses based on the EuroQoL utility index and may improve the quality of orthopedic care.

Clinicians can use these findings by incorporating assessments of patient psychosocial and health determinants into preoperative evaluations. Understanding the broader context of a patient’s life allows for more effective treatment plans and identification of those needing additional support, leading to more personalized care and better patient outcomes.

Acknowledgements

The authors thank ARCR_Pred study team members for their valuable engagement in all aspect of study implementation and Dr. Melissa Wilhelmi, medical writer at Schulthess Klinik, Zurich, Switzerland, for reviewing the manuscript.

*Members of the ARCR_Pred Study Group are listed below per site and partner institution:

ARTHRO Medics, Basel, CH (ART): Claudio Rosso (Principal Investigator [PI]); Charitè Medicine University, Berlin, DE (BER): Philipp Moroder (PI), Doruk Akgün, Isabella Weiss, Eduardo Samaniego; Cantonal Hospital Baselland, Bruderholz, CH (BRU): Thomas Suter (PI), Sebastian A. Müller, Markus Saner, Claudia Haag-Schumacher; Public Hospital Solothurn, Solothurn, CH (BSS): Mai Lan Dao Trong (PI), Carlos Buitrago-Tellez, Julian Hasler, Ulf Riede; Hôpital du Valais –Centre Hospitalier du Valais Romand, Martigny, CH (CHV): Beat Moor (PI), Matthias Biner, Nicolas Gallusser; Endoclinic, Zurich, CH (END): Christoph Spormann (PI), Britta Hansen; Klinik Gut, St Moritz, CH (GUT): Holger Durchholz (PI); Hirslanden Clinique la Colline, Geneva, CH (HIR): Gregory Cunningham (PI); La Tour Hospital, Meyrin, CH (HUG): Alexandre Lädermann (PI); Inselspital, Bern, CH (INB): Michael Schär (PI), Rainer Egli, Stephanie Erdbrink, Kate Gerber, Paolo Lombardo, Johannes Weihs; In-Motion, Wallisellen, CH (INM): Matthias Flury (PI), Ralph Berther, Christine Ehrmann, Larissa Hübscher; Institute of Social and Preventive Medicine (ISPM), University Bern, Bern, CH: David Schwappach; Cantonal Hospital Baden, Baden, CH (KSB): Karim Eid (PI), Susanne Bensler, Yannick Fritz; Cantonal Hospital Winterthur, Winterthur, CH (KSW): Emanuel Benninger (PI), Philemon Grimm, Markus Pisan; Schulthess Klinik, Zurich, CH (KWS): Markus Scheibel (PI), Laurent Audigé, Daniela Brune, Marije de Jong, Stefan Diermayr, Marco Etter, Florian Freislederer, Michael Glanzmann, Cécile Grobet, Christian Jung, Fabrizio Moro, Ralph Ringer, Jan Schätz, Hans-Kaspar Schwyzer, Martina Wehrli, Barbara Wirth; Ospedale Regionale di Lugano, Lugano, CH (LUG): Christian Candrian (PI), Filippo Del Grande, Pietro Feltri, Giuseppe Filardo, Francesco Marbach, Florian Schönweger; Cantonal Hospital St. Gallen, St. Gallen, CH (SGA): Bernhard Jost (PI), Michael Badulescu, Stephanie Lüscher, Fabian Napieralski, Lena Öhrström, Martin Olach , Jan Rechsteiner, Jörg Scheler, Christian Spross, Vilijam Zdravkovic; Orthopädie Sonnenhof, Bern, CH (SON): Matthias A. Zumstein (PI), Annabel Hayoz, Julia Müller-Lebschi; University Clinic Balgrist, Zurich, CH (UKB): Karl Wieser (PI), Paul Borbas, Samy Bouaicha, Roland Camenzind, Sabrina Catanzaro, Christian Gerber, Florian Grubhofer, Anita Hasler, Bettina Hochreiter, Roy Marcus, Farah Selman, Reto Sutter, Sabine Wyss; University Library Basel, University Basel, Basel, CH: Christian Appenzeller-Herzog; University Hospital Basel, Basel, CH (USB): Andreas Marc Müller (PI), Soheila Aghlmandi, Cornelia Baum, Franziska Eckers, Kushtrim Grezda, Simone Hatz, Sabina Hunziker, Thomas Stojanov, Mohy Taha, Giorgio Tamborrini-Schütz.

Clinical trial number

Not applicable.

Abbreviations

ARCR

Arthroscopic rotator cuff repair

ASA

American society of anesthesiologists

BIC

Bayesian information criterion

BMI

Body mass index

CI

Confidence interval

EKNZ

Ethikkommission nordwest- und zentralschweiz

EQ-5D-5L

European quality of life 5-dimension 5-level

HRQoL

Health-related quality of life

MRI

Magnetic resonance imaging

NRS

Numeric rating scale

PROMIS

Patient-reported outcome measurement information system

REDCap

Research electronic data capture

SD

Standard deviation

SE

Standard error

VAS

Visual analog scale

Authors' contribution

All authors have made substantial contributions to this article. Concept and design: DB, TS, DW, LA. Data acquisition: DB, TS, AMM, SH, SE, ARCR_Pred Study Group, LA. Analysis: DB, TS, LA. Critical revision of the paper for important intellectual content: DB, TS, AMM, DW, SH, SE, LA; Supervision: TS, DW, LA. The manuscript has been read and approved by all authors.

Funding

This project is funded by the Swiss National Science Foundation (SNF Project ID 320030_184959, http://p3.snf.ch/project-184959). Complementary grants were provided by Swiss Orthopedics to support project site documentation as well as the Swiss National Accident Insurance Fund (SUVA) to perform 12-month magnetic resonance imaging at selected sites. The following sites: Charitè Medicine University, Berlin, Germany (BER); Public Hospital Solothurn, Solothurn, Switzerland (BSS); Endoclinic, Zurich, Switzerland (END); Inselspital, Bern, Switzerland (INB); and University Clinic Balgrist, Zurich, Switzerland (UKB) funded their own participation in the project.

Data Availability

Following an embargo period of at least 2 years after the end of the study in September 2024, metadata describing the type, size and content of the dataset will be published along with the study protocol on the open repository Zenodo (https://zenodo.org/). Researchers wishing to access the full dataset will be able to file a request with the Data Access Committee of the Medical Faculty of the University of Basel (MF-DAC; email: med-dac@unibas.ch). The MF-DAC will act as an independent assessor of the request and grant access to the dataset if all ethical, legal and scientific conditions are met.

Declarations

Ethics approval and consent to participate

This project was carried out in accordance with the protocol and principles enunciated in the current version of the Declaration of Helsinki and guidelines of Good Clinical Practice (GCP) issued by the International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) as well as Swiss law and Swiss regulatory authority requirements.

Ethics approval was obtained on April 1st, 2020 from the lead ethics committee (Ethikkommission Nordwest- und Zentralschweiz (EKNZ), Basel, Switzerland; ID: 2019-02076) followed by subsequent amendments until December 20th, 2022, associated with the implementation of additional MRI examinations.

All participants provided informed written consent before study enrollment .

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Daniela Brune, Email: daniela.brune@kws.ch.

ARCR_Pred Study Group:

Daniela Brune, Thomas Stojanov, Andreas Marc Müller, David Weibel, Sabina Hunziker, Claudio Rosso, Doruk Akgün, Isabella Weiss, Eduardo Samaniego, Thomas Suter, Sebastian A Müller, Markus Saner, Claudia Haag-Schumacher, Mai Lan Dao Trong, Carlos Buitrago-Tellez, Julian Hasler, Ulf Riede, Beat Moor, Matthias Biner, Nicolas Gallusser, Christoph Spormann, Britta Hansen, Holger Durchholz, Gregory Cunningham, Alexandre Lädermann, Michael Schä, Rainer Egli, Kate Gerber, Paolo Lombardo, Johannes Weihs, Matthias Flury, Ralph Berther, Christine Ehrmann, Larissa Hübscher, David Schwappach, Karim Eid, Susanne Bensler, Yannick Fritz, Emanuel Benninger, Philemon Grimm, Markus Pisan, Markus Scheibel, Marije de Jong, Stefan Diermayr, Marco Etter, Florian Freislederer, Michael Glanzmann, Cécile Grobet, Christian Jung, Fabrizio Moro, Ralph Ringer, Jan Schätz, Hans-Kaspar Schwyzer, Martina Wehrli, Barbara Wirth, Christian Candrian, Filippo Del Grande, Pietro Feltri, Giuseppe Filardo, Francesco Marbach, Florian Schönweger, Bernhard Jost, Michael Badulescu, Stephanie Lüscher, Fabian Napieralski, Lena Öhrström, Martin Olach, Jan Rechsteiner, Jörg Scheler, Christian Spross, Vilijam Zdravkovic, Matthias A Zumstein, Annabel Hayoz, Julia Müller-Lebschi, Karl Wieser, Paul Borbas, Samy Bouaicha, Roland Camenzind, Sabrina Catanzaro, Christian Gerber, Florian Grubhofer, Anita Hasler, Bettina Hochreiter, Roy Marcus, Farah Selman, Reto Sutter, Sabine Wyss, Christian Appenzeller-Herzog, Soheila Aghlmandi, Cornelia Baum, Franziska Eckers, Kushtrim Grezda, Simone Hatz, Mohy Taha, Giorgio Tamborrini-Schütz, and Laurent Audigé

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Following an embargo period of at least 2 years after the end of the study in September 2024, metadata describing the type, size and content of the dataset will be published along with the study protocol on the open repository Zenodo (https://zenodo.org/). Researchers wishing to access the full dataset will be able to file a request with the Data Access Committee of the Medical Faculty of the University of Basel (MF-DAC; email: med-dac@unibas.ch). The MF-DAC will act as an independent assessor of the request and grant access to the dataset if all ethical, legal and scientific conditions are met.


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