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Measuring self-efficacy can be a valuable means for instructors to predict student performance. However, it is crucial to measure self-efficacy within specific contexts to effectively gauge students' perceptions of their capabilities. This study evaluated the factors comprising the Anatomical Self-Efficacy Instrument (ASEI) and determined whether these factors could predict performance in gross anatomy. Three cohorts of Doctor Physical Therapy (DPT) students completed the ASEI at the start of gross anatomy. An exploratory factor analysis (EFA) analyzed the ASEI's dimensionality, and Cronbach's alpha evaluated the internal consistency of the extracted factors. Linear regression was used to determine whether ASEI's total or subdomain scores predicted final anatomy course performance scores. In total, 142 of 287 (49.5%) DPT students completed the ASEI. EFA revealed three distinct factors, including "cognitive," "psychomotor," and "clinical anatomy self-efficacy", and explained 44.9%, 13.7%, and 5.2% of the total variance, respectively. Only cognitive self-efficacy predicted final gross anatomy course performance (ß = 0.34; R2 = 0.071; F(3,138) = 3.51; p < 0.05). Overall, the ASEI's 3-factor solution implies its multidimensionality, a finding that could inform the development of more comprehensive self-efficacy measures. Notably, "cognitive self-efficacy" was the only subdomain that predicted DPT student performance in anatomy, suggesting its potential as a tool for identifying students in need of additional learning support. The ASEI's practical usability should be further explored through additional psychometric testing.
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BACKGROUND: Acetabular and femoral offset play an important role in total hip arthroplasty (THA) for postoperative stability and biomechanical function. However, it is unknown whether offset impacts patient-reported outcomes (PROs). This study evaluated patients undergoing direct anterior (DA) THA with the hypothesis that patients who have a decrease in hip offset postoperatively would have lower physical function scores and higher pain interference. METHODS: There were 499 patients who underwent DA THA at a single tertiary academic institution who were retrospectively evaluated. Preoperative and postoperative hip offset was measured by 2 reviewers using the Sundsvall method on standing anteroposterior pelvis radiographs. Postoperative changes in hip offset were categorized as increased (> 5 mm), matched (within 5 mm of the preoperative offset measurement), or decreased ( >5 mm). Postoperative PROs with a minimum 1-year follow-up were recorded. A one-way analysis of variance was utilized to compare postoperative pain and PROs between groups. RESULTS: Patients who had decreased offset had the lowest mean postoperative physical function scores at 39.4 (8.0), followed by the increased offset group at 42.2 (10.4) and the matched offset group at 42.8 (9.8) (P < .01). There were significant differences in postoperative physical function scores between matched offset (42.8) and decreased offset (39.4) groups (P < .01), as well as between increased offset (42.2) and decreased offset (39.4) groups (P = .04). There was no difference between matched and increased offset cohorts. CONCLUSIONS: Our data suggests that reducing hip offset may result in worse physical function scores compared to those who have matched or increased hip offset. This should be considered intraoperatively, and efforts should be made to avoid reduced offset even in the presence of hip stability.
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OBJECTIVE: Translation of knee osteoarthritis (KOA) clinical practice guidelines (CPGs) to practice remains suboptimal. The primary purpose of this systematic review was to describe the use of implementation strategies to promote KOA CPG-recommended care. METHODS: Medline (via PubMed), Embase, CINAHL, and Web of Science were searched from inception to February 23, 2023, and the search was subsequently updated and expanded on January 16, 2024. Implementation strategies were mapped per the Expert Recommendations for Implementing Change taxonomy. Risk of bias (RoB) was assessed using the Cochrane Effective Practice and Organisation of Care criteria. The review was registered prospectively (PROSPERO identifier: CRD42023402383). RESULTS: Nineteen studies were included in the final review. All (100% [n = 4]) studies that included the domains of "provide interactive assistance," "train and educate stakeholders" (89% [n = 16]), "engage consumers" (87% [n = 13]), and "support clinicians" (79% [n = 11]) showed a change to provider adherence. Studies that showed a change to disability included the domains of "train and educate stakeholders," "engage consumers," and "adapt and tailor to context." Studies that used the domains "train and educate stakeholders," "engage consumers," and "support clinicians" showed a change in pain and quality of life. Most studies had a low to moderate RoB. CONCLUSION: Implementation strategies have the potential to impact clinician uptake of CPGs and patient-reported outcomes. The implementation context, using an active learning strategy with a patient partner, restructuring funding models, and integrating taxonomies to tailor multifaceted strategies should be prioritized. Further experimental research is recommended to determine which implementation strategies are most effective.
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BACKGROUND: Increasing deformity of the lower extremities, as measured by the hip-knee-ankle angle (HKAA), is associated with poor patient outcomes after total hip and knee arthroplasty (THA, TKA). Automated calculation of HKAA is imperative to reduce the burden on orthopaedic surgeons. We proposed a detection-based deep learning (DL) model to calculate HKAA in THA and TKA patients and assessed the agreement between DL-derived HKAAs and manual measurement. METHODS: We retrospectively identified 1,379 long-leg radiographs (LLRs) from patients scheduled for THA or TKA within an academic medical center. There were 1,221 LLRs used to develop the model (randomly split into 70% training, 20% validation, and 10% held-out test sets); 158 LLRs were considered "difficult," as the femoral head was difficult to distinguish from surrounding tissue. There were 2 raters who annotated the HKAA of both lower extremities, and inter-rater reliability was calculated to compare the DL-derived HKAAs with manual measurement within the test set. RESULTS: The DL model achieved a mean average precision of 0.985 on the test set. The average HKAA of the operative leg was 173.05 ± 4.54°; the nonoperative leg was 175.55 ± 3.56°. The inter-rater reliability between manual and DL-derived HKAA measurements on the operative leg and nonoperative leg indicated excellent reliability (intraclass correlation (2,k) = 0.987 [0.96, 0.99], intraclass correlation (2, k) = 0.987 [0.98, 0.99, respectively]). The standard error of measurement for the DL-derived HKAA for the operative and nonoperative legs was 0.515° and 0.403°, respectively. CONCLUSIONS: A detection-based DL algorithm can calculate the HKAA in LLRs and is comparable to that calculated by manual measurement. The algorithm can detect the bilateral femoral head, knee, and ankle joints with high precision, even in patients where the femoral head is difficult to visualize.
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Artroplastia de Quadril , Artroplastia do Joelho , Humanos , Estudos Retrospectivos , Feminino , Masculino , Idoso , Pessoa de Meia-Idade , Articulação do Joelho/diagnóstico por imagem , Articulação do Joelho/cirurgia , Articulação do Quadril/diagnóstico por imagem , Articulação do Quadril/cirurgia , Aprendizado Profundo , Articulação do Tornozelo/cirurgia , Articulação do Tornozelo/diagnóstico por imagem , Reprodutibilidade dos Testes , RadiografiaRESUMO
BACKGROUND: The decision to treat shoulder osteoarthritis (OA) definitively with shoulder arthroplasty (SA) is multifactorial, considering objective findings, subjective information, and patient goals. The first goal of this study was to determine if Patient Reported Outcome Measurement Information System (PROMIS) measures correlated with patients with shoulder OA who underwent SA within 1 year. The second goal of this study was to determine if score cut-offs in PROMIS domains could further discriminate which shoulder OA patients underwent SA within 1 year. METHODS: This retrospective case-control study examined patients with a diagnosis of shoulder OA who consulted an orthopedic provider from November 1, 2020 to May 23, 2022, and recorded PROMIS measures in the domains of Physical Function, Depression, and/or Pain Interference. A surgical group was defined as patients who underwent SA within 1 year of the most recent PROMIS measures and the nonsurgical patients were defined as the control group. Mean PROMIS scores were compared between the surgical and control groups. Separate logistic regression models controlling for age, race, ethnicity, and comorbidity count were performed for each PROMIS domain as a 1) continuous variable, and then as 2) binary variable defined by PROMIS score cut-off points to determine which scores correlated with undergoing SA to further characterize the potential clinical utility of PROMIS score cut-offs in relating to undergoing SA. RESULTS: The surgical group of 478 patients was older (68.2 vs. 63.8 years), more often of White race (82.6% vs. 70.9%), and less often of Hispanic Ethnicity (1.5% vs. 2.9%) than the control group of 3343 patients. Using optimal cut-offs in PROMIS scores, Pain Interference ≥63 (odds ratio [OR] = 2.97 (2.41-3.64), P < .001), Physical Function ≤39 (OR = 1.81 (95% confidence interval, 1.48-2.22), P < .001), and depression ≥49 (OR = 1.82 (95% confidence interval, 1.50-2.22), P < .001) were all found to correlate with undergoing SA within 1 year in multivariable logistic regressions. CONCLUSION: The results of this study demonstrate that cut-off scores for PROMIS measures differentiated patients undergoing SA within 1 year. These cut-off scores may have clinical utility in aiding in decision-making regarding surgical candidates for SA. Further research is needed to validate these cut-off scores and determine how they relate to patient outcomes after SA.
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Aims and Objective: The purpose of this pilot study was to explore whether AIH produces changes in pain sensitivity or in reports of self-reported pain intensity for individuals with low back pain. Methods: In a quasi-experimental, cross-over design we compared participants (n = 9) exposed to normal room air and hypoxia using a commercially available gas blender. The treatment period consisted of 5 consecutive days of randomly assigned to AIH or room air. For the participants initially randomized to AIH there was cross-over to receive 5 more consecutive days of room air. Therefore, this design allowed for between group and within subject assessment of AIH effects. Pain sensitivity was assessed with quantitative sensory testing (QST) for posterior superior iliac spine pressure threshold, plantar thermal threshold, and peak pain ratings. Self-reported pain intensity for low back pain was assessed via the Brief Pain Inventory. Results: There were no between group differences for AIH and room air in pain sensitivity or self-reported pain intensity. In the within subject analyses larger effect sizes favoring AIH were detected for plantar measures of pain sensitivity but not for self-reported pain intensity. Conclusion: This study, while presenting null findings, describes an initial step in determining whether AIH can be used to increase pain relief. Based on this pilot study we offer guidance for future research including study design, AIH dosage, participant selection, and using AIH in combination with non-pharmacologic treatments.