1806 - Interim Results With A PROMIS™-based App In Patients Undergoing Total Knee Arthroplasty: Patient-reported Physical Function And Pain Scores
Bibliographic record
Abstract
Disclosures: Michael W. Griffiths (N), G. Daniel G. Langohr (N), George S. Athwal (1-Wright Med Tech, Inc 3B-DePuy Synth 4-Wright Med Tech, Inc 5-Smith & Nephew, Wright Med Tech, Inc 7A-Wright Med Tech, Inc 8-J Shoulder Elbow Arthr, J of Shoulder Elbow Surg 9-Am Shoulder & Elbow Surg), James A. Johnson (8-J of Shoulder Elbow Surg), John B. Medley (8-IMechE Eng in Med, Biotrib)INTRODUCTION: Reverse total shoulder arthroplasty (RTSA) is a relatively new procedure and the polyethylene humeral cup often sustains damage from contact with the scapula. Perhaps for this reason, cross-linked polyethylene (XLPE) has not been widely used. The purpose of the present study is to examine the simulator wear of non-XLPE cups in RTSA. In addition, a finite element analysis (FEA) was used to predict the initial nominal contact area for each of two abduction angles.METHODS: A modified orbital bearing hip simulator was used following the protocols established by Langohr et al [1]. Five RTSA implants (DePuy Synthesis XTEND, 38 mm, high mobility, non-XLPE cups) were testing along with three load-soak controls. The lubricant was alpha calf serum diluted with phosphate buffer solution (PBS) to give 30 g/L protein and also it included 1.5 g/L sodium hyaluronate [1]. A series of progressively larger u201cdefectsu201d were machined into the edges of the humeral cups (2, 3, 4 mm deep; 14, 21, 23 mm wide; 53o, 84o, 94o arc angles) to simulate in vivo scapular notching damage. The FEA was done using ABAQUS (v6.14, Simulia Corp) with further details given by Griffiths [2].RESULTS: Although there was some scatter in wear of the individual cups under nominally identical conditions, each one in itself was remarkably linear. When a linear fit was performed on all the wear results of the five contacts, an average wear rate of 25.3 mm3/Mc was obtained (Fig 1). If each individual wear test was fit by a straight line, the average wear rate was 25.3 u00b1 1.1 mm3/Mc (95% CI). As shown in Fig 1, the defects had no obvious influence on the wear rate but did cause a decrease in initial nominal contact area (Fig 2). The u201cdefect expanded againu201d is not shown in Fig 2.DISCUSSION: Affatato et al [3] reported an average wear rate of about 19 mm3/Mc for hip simulator wear of non-XLPE cups which was comparable (despite being done under somewhat different conditions) to the average wear rate obtained in the present study as the slope of all the data fit together or as an average slope of the individual linear fits of the wear of each cup (which we believe is how wear rates should be determined but, in this case, the average wear rates were essentially identical). In causing a decrease in initial nominal contact area, the defects would cause elevated initial contact stress which would tend to increase wear particle production but the reduced area would act to decrease the number of wear particles produced. These effects appeared to cancel each other out and the initial wear rate over 1 Mc was not influenced. CLINICAL RELEVANCE: Reassuringly, the RTSA cup defects do not have any obvious effect on simulator wear rate. Also, the results are comparable to those obtained for hip simulator wear of non-XLPE cups. This is not so reassuring and suggests some risk of eventual wear problems for RTSA with non-XLPE cups (as occurred in hip arthroplasty). Using the same protocols, sets of simulator wear tests for RTSA with XLPE cups are planned for future studies. REFERENCES: [1] Langohr et al (2016) IMechE Pt H, Eng in Med 230(5):458-69. [2] Griffiths (2017) MES thesis, Western University. [3] Affatato et al (2016) Mech Beh Biomed Mat 53:40-8.ACKNOWLEDGEMENTS: The RTSA implants were provided by DePuy Synthes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".