RESUMO
PURPOSE: The association between preoperative mental health and immediate postoperative ambulation in primary Total Joint Arthroplasty (TJA) has sparsely been studied. Thus, this study's objective was to investigate the association between mental health (measured by the Mental Component Score (MCS) from the Veterans RAND 12 (VR-12)) and peri-operative metrics. METHODS: We conducted a retrospective study of patients who underwent primary TJA and completed a VR-12 questionnaire between January 2018 and June 2023 at a single academic hospital. Patients were stratified into terciles based on preoperative MCS. Patient demographics, ambulation within 4 h postop, LOS, and discharge location were compared. The effect of MCS on LOS while controlling discharge location was assessed using negative binomial regression. RESULTS: 1120 patients were included in this analysis (432 THA and 688 TKA). After stratification into terciles (Low: 34.7 ± 6.6, Middle: 49.3 ± 3.7, High:62.1 ± 4.4), comparison of demographics revealed significant differences in age (p = 0.005) and sex distribution (p = 0.04) but no difference in surgery type (p = 0.857). There was no significant difference in ambulation rate between MCS groups (p = 0.789) or in distance covered during first ambulation (p = 0.251). Low MCS patients had a longer LOS (p = 0.000, p = 0.002) and a lower rate of discharged home (p = 0.016). After controlling discharge location, no significant association was found between MCS and LOS (p = 0.288). CONCLUSION: Patient with low MCS tended to be younger, women, and had poorer preoperative HOOS/KOOS scores. Low MCS was associated with longer LOS and lower rates of discharge home. However, MCS was not associated with early ambulation rate and LOS after controlling discharge location.
Assuntos
Artroplastia de Quadril , Artroplastia do Joelho , Tempo de Internação , Alta do Paciente , Humanos , Tempo de Internação/estatística & dados numéricos , Feminino , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Alta do Paciente/estatística & dados numéricos , Idoso , Saúde Mental , Período Pré-Operatório , Readmissão do Paciente/estatística & dados numéricos , Deambulação Precoce/estatística & dados numéricosRESUMO
Glucocorticoids (GCs) are efficacious drugs used for treating many inflammatory diseases, but the dose and duration of administration are limited because of severe side effects. We therefore sought to identify an approach to selectively target GCs to inflamed tissue. Previous work identified that anti-tumor necrosis factor (TNF) antibodies that bind to transmembrane TNF undergo internalization; therefore, an anti-TNF antibody-drug conjugate (ADC) would be mechanistically similar, where lysosomal catabolism could release a GC receptor modulator (GRM) payload to dampen immune cell activity. Consequently, we have generated an anti-TNF-GRM ADC with the aim of inhibiting pro-inflammatory cytokine production from stimulated human immune cells. In an acute mouse model of contact hypersensitivity, a murine surrogate anti-TNF-GRM ADC inhibited inflammatory responses with minimal effect on systemic GC biomarkers. In addition, in a mouse model of collagen-induced arthritis, single-dose administration of the ADC, delivered at disease onset, was able to completely inhibit arthritis for greater than 30 days, whereas an anti-TNF monoclonal antibody only partially inhibited disease. ADC treatment at the peak of disease was also able to attenuate the arthritic phenotype. Clinical data for a human anti-TNF-GRM ADC (ABBV-3373) from a single ascending dose phase 1 study in healthy volunteers demonstrated antibody-like pharmacokinetic profiles and a lack of impact on serum cortisol concentrations at predicted therapeutic doses. These data suggest that an anti-TNF-GRM ADC may provide improved efficacy beyond anti-TNF alone in immune mediated diseases while minimizing systemic side effects associated with standard GC treatment.
Assuntos
Anticorpos , Artrite Experimental , Imunoconjugados , Esteroides , Humanos , Animais , Camundongos , Preparações Farmacêuticas , Receptores de Glucocorticoides/uso terapêutico , Inibidores do Fator de Necrose Tumoral/uso terapêutico , Glucocorticoides/farmacologia , Glucocorticoides/uso terapêutico , Fator de Necrose Tumoral alfa/metabolismo , Modelos Animais de Doenças , Imunoconjugados/farmacologia , Imunoconjugados/uso terapêuticoRESUMO
BACKGROUND: Artificial intelligence in the field of orthopaedics has been a topic of increasing interest and opportunity in recent years. Its applications are widespread both for physicians and patients, including use in clinical decision-making, in the operating room, and in research. In this study, we aimed to assess the quality of ChatGPT answers when asked questions related to total knee arthroplasty. METHODS: ChatGPT prompts were created by turning 15 of the American Academy of Orthopaedic Surgeons Clinical Practice Guidelines into questions. An online survey was created, which included screenshots of each prompt and answers to the 15 questions. Surgeons were asked to grade ChatGPT answers from 1 to 5 based on their characteristics: (1) relevance, (2) accuracy, (3) clarity, (4) completeness, (5) evidence-based, and (6) consistency. There were 11 Adult Joint Reconstruction fellowship-trained surgeons who completed the survey. Questions were subclassified based on the subject of the prompt: (1) risk factors, (2) implant/intraoperative, and (3) pain/functional outcomes. The average and standard deviation for all answers, as well as for each subgroup, were calculated. Inter-rater reliability (IRR) was also calculated. RESULTS: All answer characteristics were graded as being above average (ie, a score > 3). Relevance demonstrated the highest scores (4.43 ± 0.77) by surgeons surveyed, and consistency demonstrated the lowest scores (3.54 ± 1.10). ChatGPT prompts in the Risk Factors group demonstrated the best responses, while those in the Pain/Functional Outcome group demonstrated the lowest. The overall IRR was found to be 0.33 (poor reliability), with the highest IRR for relevance (0.43) and the lowest for evidence-based (0.28). CONCLUSIONS: ChatGPT can answer questions regarding well-established clinical guidelines in total knee arthroplasty with above-average accuracy but demonstrates variable reliability. This investigation is the first step in understanding large language model artificial intelligence like ChatGPT and how well they perform in the field of arthroplasty.