Defining recovery trajectories after shoulder arthroplasty: a latent class analysis of patient-reported outcomes

Variations in 1-year Trajectories of Levels of Pain and Capability After Shoulder Arthroplasty Are Associated With Baseline Mental Health

BACKGROUND

There is variability in the trajectories of pain intensity and magnitude of incapability after shoulder arthroplasty. A better understanding of the degree to which variation in recovery trajectories relates to aspects of mental health can inform the development of comprehensive biopsychosocial care strategies.

QUESTIONS/PURPOSES

(1) Do pain intensities at baseline and the trajectories during recovery differ between groups when stratified by mental health composite summary score, arthroplasty type, and revision surgery? (2) Do magnitudes of capability at baseline and the trajectories during recovery differ between these groups?

METHODS

We used a registry of 755 patients who underwent shoulder arthroplasty by a single surgeon at a specialized urban orthopaedic hospital that recorded the mental component summary (MCS) score of the Veterans RAND 12, a measure of shoulder-specific comfort and capability (American Shoulder and Elbow Surgeons [ASES] score, which ranges from 0 to 100 points, with a score of 0 indicating worse capability and pain and 100 indicating better capability and pain and a minimum clinically important difference of 6.4), and the VAS for pain intensity (range 0 [representing no pain] to 10 [representing the worst pain possible], with a minimum clinically important difference of 1.4) preoperatively, 2 weeks postoperatively, and 6 weeks, 3 months, 6 months, and 1 year after surgery. Forty-nine percent (368 of 755) of the patients were men, with a mean age of 68 ± 8 years, and 77% (585) were treated with reverse total shoulder arthroplasty (rTSA). Unconditional linear and quadratic growth models were generated to identify the general shape of recovery for both outcomes (linear versus quadratic). We then constructed conditional growth models and curves for pain intensity and the magnitude of capability showing mean baseline scores and the rates of recovery that determine the trajectory, accounting for mental health (MCS) quartiles, primary or revision arthroplasty, and TSA or reverse TSA in separate models. Because pain intensity and capability showed quadratic trends, we created trajectories using the square of time.

RESULTS

Patients in the worst two MCS quartiles had greater pain intensity at baseline than patients in the best quartile (difference in baseline for bottom quartile: 0.93 [95% CI 0.72 to 1.1]; p < 0.01; difference in baseline for next-worst quartile: 0.36 [95% CI 0.16 to 0.57]; p < 0.01). The rates of change in recovery from pain intensity were not different among groups (p > 0.10). Patients with revision surgery had greater baseline pain (difference: 1.1 [95% CI 0.7 to 1.5]; p < 0.01) but no difference in rates of recovery (difference: 0.031 [95% CI 0.035 to 0.097]; p = 0.36). There were no differences in baseline pain intensity and rates of recovery between patients with reverse TSA and those with TSA (baseline pain difference: -0.20 [95% CI -0.38 to -0.03]; p = 0.18; difference in rate of recovery: -0.005 [95% CI -0.035 to 0.025]; p = 0.74). Patients in the worst two MCS quartiles had worse baseline capability than patients in the best quartile (difference in baseline for bottom quartile: -8.9 [95% CI -10 to -7.4]; p < 0.001; difference in baseline for the next-worst quartile: -4.9 [95% CI -6.4 to -3.4]; p < 0.01), with no differences in rates of recovery (p > 0.10). Patients with revision surgery had lower baseline capability (difference in baseline: -13 [95% CI -15 to -9.7]; p < 0.01), with a slower rate of recovery (difference in rate of recovery: -0.56 [95% CI -1.0 to -0.079]; p = 0.021). There were no differences in baseline capability or rates of recovery between TSA and reverse TSA.

CONCLUSION

The observation that preoperative and 1-year comfort and capability are associated with mental health factors and with similar recovery trajectories reminds us that assessment and treatment of mental health is best considered an integral aspect of musculoskeletal care. Future studies can address how prioritization of mental health in musculoskeletal care strategies might reduce variation in the 1-year outcomes of discretionary surgeries such as shoulder arthroplasty.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Patients Follow 3 Different Rate-of-Recovery Patterns After Anterior Cruciate Ligament Reconstruction Based on International Knee Documentation Committee Score

PURPOSE

To determine whether subgroups of patients exist based on the rate-of-recovery pattern of International Knee Documentation Committee (IKDC) scores after anterior cruciate ligament reconstruction (ACLR) and to determine clinical predictors for these subgroups.

METHODS

Patients who underwent primary or revision ACLR at a single institution from January 2014 to January 2019 were identified. Latent class growth analyses and growth mixture models (GMMs) with 1 to 6 classes were used to identify subgroups of patients based on functional rate-of-recovery patterns by use of preoperative, 1-year postoperative, and 2-year postoperative IKDC scores.

RESULTS

A total of 245 patients who underwent ACLR were included in the analysis. A 3-class GMM was chosen as the final model after 6 different models were run. Class 1, showing improvement from preoperatively to 1-year follow-up, with sustained improvement from 1 to 2 years postoperatively, constituted 77.1% of the study population (n = 189), whereas class 2, showing functional improvement between 1- and 2-year follow-up, was the smallest class, constituting 10.2% of the study population (n = 25), and class 3, showing slight improvement at 1-year follow-up, with a subsequent decline in IKDC scores between 1- and 2-year follow-up, constituted 12.7% of the study population (n = 31). Revision surgery (P = .005), a psychiatric history (P = .025), preoperative chronic knee pain (P = .024), and a subsequent knee injury within the follow-up period (P = .011) were the predictors of class 2 and class 3 rate-of-recovery patterns. Patient demographic characteristics, graft type, and concomitant ligament, meniscus, or cartilage injury at the time of surgery were not associated with the different recovery patterns described in this study.

CONCLUSIONS

Patients may follow different rate-of-recovery patterns after ACLR. By use of the GMMs, 3 different rate-of-recovery patterns based on IKDC scores were identified. Although most patients follow a more ideal rate-of-recovery pattern, fewer patients may follow less favorable patterns. Revision surgery, a history of psychiatric illness, preoperative chronic knee pain, and a subsequent knee injury within the follow-up period were predictive of less favorable rate-of-recovery patterns.

LEVEL OF EVIDENCE

Level III, retrospective cohort study.