Patient-Reported Outcomes Measurements Information System (PROMIS) upper extremity and pain interference do not significantly predict rotator cuff tear dimensions

Risk factors for intracellular fatty accumulation in rotator cuff muscle: a histologic analysis

BACKGROUND

Fatty accumulation in rotator cuff muscles has been associated with shoulder dysfunction, risk of repair failure, and poor postoperative outcomes. This study sought to assess risk factors associated with true fatty accumulation based on histologic analysis and determine whether preoperative function directly correlated with this fatty rotator cuff accumulation.

METHODS

Supraspinatus muscle biopsy specimens obtained prospectively from patients undergoing arthroscopic rotator cuff repair were stained with LipidTOX to quantify lipid accumulation. Two-step cluster analysis with Goutallier classification was used to define the fatty and non-fatty rotator cuff groups. We further performed a receiver operating characteristic curve analysis to confirm the group cutoff values.

RESULTS

In total, 51 patients (aged 60.1 ± 10.5 years) were included. There were 19 high-grade partial tears, 10 small tears, 7 medium tears, 10 large tears, and 5 massive tears. Both cluster and receiver operating characteristic curve analyses yielded a cutoff value of 30% LipidTOX/4',6-diamidino-2-phenylindole (DAPI) separating the fatty vs. non-fatty groups. In the univariate analysis, patients with fatty rotator cuffs were aged 63.2 years on average compared with 59.7 years in the non-fatty group (P = .038). Female patients made up 57.1% of the fatty cohort, which was statistically higher than the non-fatty group (P = .042). Massive and large tears were more likely to occur in the fatty group (P = .005). In the multivariate analysis, full tendon tears had the largest predictive status of falling into the fatty group (odds ratio, 15.4; P = .008), followed by female sex (odds ratio, 4.9; P = .036). Patients in the fatty group had significantly higher American Shoulder and Elbow Surgeons scores (P = .048) and lower visual analog scale scores (P = .002).

DISCUSSION AND CONCLUSION

This prospective histologic assessment revealed that full-thickness rotator cuff tears and female sex were the largest risk factors for intracellular lipid accumulation. Although tear size correlated with fatty accumulation, the sex disparity is a noteworthy finding that warrants further research.

Advancements in the diagnosis and management of rotator cuff tears. The role of artificial intelligence

Background

This review examined the role of artificial intelligence (AI) in the diagnosis and management of rotator cuff tears (RCTs).

Methods

A literature search was conducted in October 2023 using PubMed (MEDLINE), SCOPUS, and EMBASE databases, included only peer-reviewed studies. Relevant articles on AI technology in RCTs. A critical analysis of the relevant literature was conducted.

Results

AI is transforming RCTs management through faster and more precise identification and assessment using algorithms that facilitate segmentation, quantification, and classification of the RCTs across various imaging modalities. Precise algorithms focusing on preoperative factors to assess RCTs reparability have been developed for personalized treatment planning and outcome prediction. AI also aids in exercise classification and promotes patient adherence during at-home physiotherapy. Despite promising advancements, challenges in data quality and symptom integration persist. Future research should include refining AI algorithms, expanding their integration into various imaging techniques, and exploring their roles in postoperative care and surgical decision-making.

Conclusions

AI-driven solutions improve diagnostic accuracy and have the potential to influence treatment planning and postoperative outcomes through the automated RCTs analysis of medical imaging. Integration of high-quality datasets and clinical symptoms into AI models can enhance their reliability. Current AI algorithms can also be refined, integrated into other imaging techniques, and explored further in surgical decision-making and postoperative care.

Determining the Time Required to Achieve Clinically Significant Outcomes on the PROMIS Upper Extremity Questionnaire After Arthroscopic Rotator Cuff Repair

Background

Clinically significant outcome (CSO) thresholds for the Patient-Reported Outcome Measurement Information System-Upper Extremity (PROMIS-UE) score have been previously defined after arthroscopic rotator cuff repair (RCR). However, the time required to achieve CSOs for the PROMIS-UE score is unknown.

Purpose

To (1) determine the time required to achieve the minimal clinically important difference (MCID), substantial clinical benefit (SCB), and Patient Acceptable Symptom State (PASS) score thresholds after RCR for the PROMIS-UE questionnaire and (2) identify patient factors associated with earlier or delayed achievement of these clinical benchmarks.

Study Design

Case-control study; Level of evidence, 3.

Methods

A prospectively maintained institutional database was retrospectively reviewed for consecutive patients who underwent RCR between January 2018 and January 2019. Patients were included if they completed the PROMIS-UE questionnaire both preoperatively and at standardized postoperative time intervals: 5 to 7 months (6-month time point), 11 to 13 months (1-year time point), and ≥23 months (2-year time point). Kaplan-Meier survival curves with interval censoring were used to define the cumulative percentage of patients who achieved the MCID, SCB, and PASS. Patient variables associated with earlier or delayed achievement of the MCID, SCB, and PASS were determined using Weibull parametric survival regression analysis.

Results

Included were 105 patients undergoing RCR (age, 57.3 ± 10.3 years; body mass index, 31.5 ± 6.1 kg/m²). By 2-year follow-up, the cumulative percentage of patients achieving the MCID, SCB, and PASS was 86.7%, 76.2%, and 74.3%, respectively. The mean time required to reach the MCID, SCB, and PASS score thresholds was 9.5 ± 3.8, 10.3 ± 4.4, and 9.8 ± 4.6 months, respectively. Factors associated with delayed achievement of CSOs included greater baseline PROMIS-UE score (MCID and SCB) and workers' compensation insurance (PASS). Greater baseline PROMIS-UE scores were associated with earlier achievement of the PASS.

Conclusion

Most patients achieved CSOs for the PROMIS-UE within 12 months of RCR. Patient-specific factors found to be associated with earlier or delayed achievement of CSOs can be used to inform patient discussions on the expected timeline for recovery after RCR.