Open AccessThe Patient Acceptable Symptom State as a Predictor of the Sports Activity Available State After Arthroscopic Rotator Cuff Repair
Author(s) -
Dong-Min Kim,
In-Ho Jeon,
Ho Yeon Kim,
Jeong Hee Park,
Hyojune Kim,
Kyoung Hwan Koh
Publication year - 2022
Publication title -
orthopaedic journal of sports medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.329
H-Index - 35
ISSN - 2325-9671
DOI - 10.1177/23259671221084978
Subject(s) - medicine , software as a service , logistic regression , elbow , rotator cuff , physical therapy , surgery , software , software development , computer science , programming language
Background: The patient acceptable symptom state (PASS) has emerged as a metric for evaluating patient satisfaction after treatment. There is little research on the relationship between sports activity and PASS values after arthroscopic rotator cuff repair (ARCR).Purpose: To (1) introduce the sports activity available state (SAAS) as an indicator of whether sports activities are possible based on patient symptoms after ARCR, (2) investigate the correlation between the SAAS and PASS, (3) predict the SAAS using derived PASS values, and (4) identify factors for achieving the PASS and SAAS.Study Design: Case-control study; Level of evidence, 3.Methods: Included were 201 patients who underwent ARCR between January 2015 and December 2016. At a mean follow-up of 38.7 ± 7.0 months, anchor questions were used to classify patients as SAAS+ (sports group) or SAAS– (nonsports group) and derive the PASS values for the pain visual analog scale (pVAS), American Shoulder and Elbow Surgeons (ASES), and Single Assessment Numeric Evaluation (SANE). The authors analyzed the correlation and difference between PASS and SAAS acquisition, and univariate and multivariate logistic regression analyses were performed to determine factors for PASS and SAAS achievement.Results: The final PASS values for the pVAS, ASES, and SANE were 0.5, 93.5, and 82.5, respectively. A significant correlation existed between PASS and SAAS acquisition (phi correlation coefficient, 0.647; P 0.7 for all outcome scores when predicting SAAS using PASS values. A higher preoperative ASES score was significantly associated with achieving both the SAAS (OR, 1.032 [95% CI, 1.005-1.059]; P = .018) and PASS (OR, 2.556 [95% CI, 1.753-3.726]; P < .001). Diabetes (OR, 0.348 [95% CI, 0.130-0.931], P = .036) and a large to massive tear (OR, 0.378 [95% CI, 0.162-0.884]; P = .025) were significantly negatively associated with achieving the SAAS.Conclusion: The authors found the SAAS to be significantly correlated with the PASS. Also, SAAS was able to be predicted using the PASS value. Patients with higher preoperative ASES scores had higher odds of achieving both the PASS and SAAS, and patients with diabetes and those with large to massive tears had lower odds of achieving the SAAS.