These authors propose a new clinical assessment tool constructed using machine learning - the Shoulder Arthroplasty Smart (SAS) score to quantify outcomes following total shoulder arthroplasty (TSA).
They used clinical data from 3667 TSA patients with 8104 postoperative follow-up reports to quantify the psychometric properties of validity, responsiveness, and clinical interpretability for the proposed SAS score.
Three of the six measures of the SAS are determined by the surgeon or surgeon's staff: active flexion, internal rotation, and active external rotation.
significant ceiling effects preoperatively.
They noted significant ceiling effects occurred postoperatively for the SST, UCLA, ASES, and SPADI measures, especially for anatomic TSA, men, younger patients, and whites.
The SAS score had the least number of patients with floor and ceiling effects and also exhibited no response bias in any patient characteristic analyzed in this study.
Patient satisfaction anchor-based thresholds for minimal clinically importance difference and substantial clinical benefit were quantified for all 6 outcome measures; the SAS score thresholds were most similar in magnitude to the Constant score. Regarding responsiveness, all 6 outcome measures detected a large effect, with the UCLA exhibiting the most responsiveness and the SST exhibiting the least. Each of the SAS, ASES, Constant, and SPADI scores had similarly large standardized response mean and effect size responsiveness.
They concluded that 6-item SAS score is an efficient TSA-specific outcome measure with equivalent or better validity, responsiveness, and clinical interpretability as 5 other historical assessment tools.
Comment: The goals of outcome measurement are to capture the patients' assessment of their comfort and function before and after surgery, to include that highest percentage of patients having the procedure, and to levy the smallest time and cost burden on the patient and the provider.
Shoulder arthroplasty outcome measures can be divided into two groups: (1) those that are based solely on patient self-assessment (the SST, the ASES and the SPADI) and (2) those that require measurements of range of motion and/or strength by the physician or the physician's staff: the SAS, Constant and the UCLA scores.
The challenges with the second group of metrics include (1) observer bias - the person doing the measurements may be inclined to achieve better results in strength and range after surgery, (2) non-response bias - the fact that the patient needs to return to the office for an in-person examination is likely to eliminate patients from inclusion (see this link), (3) cost - measures of motion and strength require physician or staff time as well as travel expenses for the patient, (4) inter-observer variability - measures of motion and strength may not be consistent among different observers and (5) meaningfulness - measures of motion and strength do not correlate well with patient self-assessment of comfort and function (see reference links below).
These authors evaluated the relationship between shoulder elevation strength (SES) and patient reported outcomes (PROMs) after aTSA for the treatment of primary glenohumeral osteoarthritis (GHOA) in a retrospective analysis of 605 patients having aTSA for primary glenohumeral osteoarthritis.
SES was tested using a digital dynamometer before and after surgery. The examiners were instructed to have the patient position the arm at 90 of elevation or maximum elevation below the horizontal in the scapular plane and resist the examiner who was holding the dynamometer.
The correlations between SES and the PROMs were very weak before aTSA and weak after aTSA.
The authors concluded that while measurement of SES provides information about shoulder function and outcome related to the treatment of primary GHOA with aTSA, the actual relevance to the patient is unclear as the correlations between SES and PROMs were weak.
This is an important article, in that it demonstrates that so called "objective" measures, such as shoulder strength, are only weakly associated with patient self-assessed comfort and function. It is also important to recognize that the use of strength and range of motion measures in the assessment of arthroplasty outcomes introduces both observer variability (different examiners are likely to measure strength and range of motion differently) and selection bias (excluding the patients who are unwilling or unable to return to the surgeon's office for followup measurements). Computer based platforms (PROMIS, OBERD) have similar issues with selection bias by eliminating patients without access to the computer based platform. By contrast, the use of so called "subjective" patient reported metric (PRM) forms that can be completed with a pencil and mailed in to the surgeon enable the inclusion of patients unavailable for in-person followup while keeping the observer (the patient) constant. We must recall that the goal of outcome assessment is to capture the self-assessments of largest percentage of patients for the longest period of time after treatment.
Here is a related article, the key finding of which was that active range of motion correlated poorly with patients' self-assessed function of their osteoarthritic shoulders, meaning that the shoulder function was dependent on characteristics of the shoulder and the patient other than the active range of motion.
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Here are some videos that are of shoulder interest
