Oxidative Substitution of Organocopper(II) by a Carbon-Centered Radical.

Copper-catalyzed coupling reactions of alkyl halides are believed to prominently involve copper(II) species and alkyl radicals as pivotal intermediates, with their exact interaction mechanism being the subject of considerable debate. In this study, a visible light-responsive fluoroalkylcopper(III) complex, [(terpy)Cu(CF3)2(CH2CO2tBu)] Trans-1, was designed to explore the mechanism. Upon exposure to blue LED irradiation, Trans-1 undergoes copper-carbon bond homolysis, generating Cu(II) species and carbon-centered radicals, where the carbon-centered radical then recombines with the Cu(II) intermediate, resulting in the formation of Cis-1, the Cis isomer of Trans-1. Beyond this, a well-defined fluoroalkylcopper(II) intermediate ligated with a sterically hindered ligand was isolated and underwent full characterization and electronic structure studies. The collective experimental, computational, and spectroscopic findings in this work strongly suggest that organocopper(II) engages with carbon-centered radicals via an "oxidative substitution" mechanism, which is likely the operational pathway for copper-catalyzed C-H bond trifluoromethylation reactions.

Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.

BACKGROUND: The detection and management of intracranial aneurysms (IAs) are vital to prevent life-threatening complications like subarachnoid hemorrhage (SAH). Artificial Intelligence (AI) can analyze medical images, like CTA or MRA, spotting nuances possibly overlooked by humans. Early detection facilitates timely interventions and improved outcomes. Moreover, AI algorithms offer quantitative data on aneurysm attributes, aiding in long-term monitoring and assessing rupture risks. METHODS: We screened four databases (PubMed, Web of Science, IEEE and Scopus) for studies using artificial intelligence algorithms to identify IA. Based on algorithmic methodologies, we categorized them into classification, segmentation, detection and combined, and then their merits and shortcomings are compared. Subsequently, we elucidate potential challenges that contemporary algorithms might encounter within real-world clinical diagnostic contexts. Then we outline prospective research trajectories and underscore key concerns in this evolving field. RESULTS: Forty-seven studies of IA recognition based on AI were included based on search and screening criteria. The retrospective results represent that current studies can identify IA in different modal images and predict their risk of rupture and blockage. In clinical diagnosis, AI can effectively improve the diagnostic accuracy of IA and reduce missed detection and false positives. CONCLUSIONS: The AI algorithm can detect unobtrusive IA more accurately in communicating arteries and cavernous sinus arteries to avoid further expansion. In addition, analyzing aneurysm rupture and blockage before and after surgery can help doctors plan treatment and reduce the uncertainties in the treatment process.

Dosage and organic acid residue of MOG35-55 peptide influences immunopathology and development of BCG induced experimental autoimmune encephalomyelitis (EAE).

Experimental autoimmune encephalomyelitis (EAE) serves as a model for studying multiple sclerosis, with immunization strategies utilizing MOG35-55 peptide, emulsified in adjuvant enriched with mycobacterium tuberculosis (Mtb). This study examined the effects of Bacillus Calmette-Guérin (BCG) as an adjuvant, alongside the impact of MOG35-55 peptide doses and their residual counter ions on EAE development. We found that BCG can be effectively used to induce EAE with similar incidence and severity as heat-killed H37Ra, contingent upon the appropriate MOG35-55 peptide dose. Different immunization doses of MOG35-55 peptide significantly affect EAE development, with higher doses leading to a paradoxical reduction in disease activity, probably due to peripheral tolerance mechanisms. Furthermore, doses of MOG35-55 peptides with acetate showed a more pronounced effect on disease development compared to those containing trifluoroacetic acid (TFA), suggesting the potential influence of residual counter ions on EAE activity. We highlighted the feasibility of applying BCG to the establishment of EAE for the first time. Our findings emphasized the importance of MOG peptide dosage and composition in modulating EAE development, offering insights into the mechanisms of autoimmunity and tolerance. This could have implications for autoimmune disease research and the design of therapeutic strategies.

Multi-omics analyses and botanical perfumer hypothesis provide insights into the formation and maintenance of aromatic characteristics of Dendrobium loddigesii flowers.

Dendrobium loddigesii, a member of the Orchidaceae family, is a valuable horticultural crop known for its aromatic qualities. However, the mechanisms responsible for the development of its aromatic characteristics remain poorly understood. To elucidate these underlying mechanisms, we assembled the first chromosome-level reference genome of D. loddigesii using PacBio HiFi-reads, Illumina short-reads, and Hi-C data. The assembly comprises 19 pseudochromosomes with N50 contig and N50 scaffold sizes of 55.15 and 89.94 Mb, respectively, estimating the genome size to be 1.68 Gb, larger than that of other sequenced Dendrobium species. During the flowering stages, we conducted a comprehensive analysis combining volatilomics and transcriptomics to understand the characteristics and biosynthetic mechanisms pathways of the floral scent. Our findings emphasize the significant contribution of aromatic terpenoids, especially monoterpenoids, in defining the floral aroma. Furthermore, we identified two crucial terpene synthase (TPS) genes that play a key role in maintaining the aroma during flowering. Through the integration volatilomics data with catalytic assays of DlTPSbs proteins, we identified specific compounds responsible for the aromatic characteristics of D. loddigesii. This integrated analysis of the genome, transcriptome, and volatilome, offers valuable insights into the development and preservation of D. loddigesii's aromatic characteristics, setting the stage for further exploration of the botanical perfumer hypothesis.

What Clinical Factors Affect Length of Transition to Psoriatic Arthritis in Patients With Psoriasis?

OBJECTIVE: We aimed to identify clinical and demographic features associated with the interval between psoriasis (PsO) and psoriatic arthritis (PsA). METHODS: We identified patients with PsO and PsA diagnoses from our tertiary care psoriatic disease biorepository: a longitudinal, real-world database including clinical information and patient-reported outcomes. We used a multivariable a zero-inflated negative binomial model to evaluate several clinical and demographic features that may be associated with the time between PsO and PsA onset. RESULTS: A total of 384 patients were included, of whom 52.2% were female. The mean age of PsO onset was 31.5 years. Advanced age at PsO onset was associated with a shorter interval between PsO and PsA. Based on our model, patients with PsO onset at age 42.6 years (upper end of the interquartile range [IQR]) had a 62% shorter expected interval compared with patients with PsO onset at age 18.9 years (lower end of IQR) (P < 0.001) and were more likely to have concurrent (onset within 6 months) diagnoses (odds ratio 4.56; 95% confidence interval 2.9-7.17). Patients with a body mass index (BMI) of 34 compared with a BMI of 26 had a 10% shorter interval between PsO and PsA, which trended toward statistical significance (P = 0.053). CONCLUSION: Our study demonstrated that patients with a diagnosis of PsO at an older age have a shorter interval between PsO and PsA diagnoses and are more likely to have concurrent diagnoses compared with patients with an onset of PsO at a younger age. These results suggest that patients with a later onset of PsO may benefit from earlier PsA screening.

The association between parenthood and health: A comparison of people in same-sex and different-sex relationships.

Understanding social inequalities in parental health is crucial for family functioning and child development. Theoretically, the double burden of parenting and minority stress may lead to the negative association between parenthood and health outcomes being stronger for people in same-sex relationships. Moreover, drawn from the social control process and the compensation mechanism, the negative association between parenthood and health risk behaviors may become stronger for people in same-sex relationships. Yet, empirical evidence on parental health disparities between parents in same- and different-sex relationships is limited. Using linear and logistic regression models, coarsened exact matching, and entropy balancing on Dutch data between 2008 and 2021 (196 people in same-sex relationships and 6948 people in different-sex relationships), we investigate the relationship between parenthood and three health outcomes (self-rated health, physical health, and mental health) and two health risk behaviors (smoking and heavy episodic drinking). We find that parents on average are less likely to experience heavy episodic drinking than non-parents. The association between parenthood and health does not differ between people in same-sex and different-sex relationships.

Predictive Modeling of Medical- and Orthopaedic-Related 90-Day Readmissions Following Primary Total Hip Arthroplasty.

BACKGROUND: The rate of unplanned hospital readmissions following total hip arthroplasty (THA) varies from 3 to 10%, representing a major economic burden. However, it is unknown if specific factors are associated with different types of complications (ie, medical or orthopaedic-related) that lead to readmissions. Therefore, this study aimed to: (1) determine the overall, medical-related, and orthopaedic-related 90-day readmission rate; and (2) develop a predictive model for risk factors affecting overall, medical-related, and orthopaedic-related 90-day readmissions following THA. METHODS: A prospective cohort of primary unilateral THAs performed at a large tertiary academic center in the United States from 2016 to 2020 was included (n = 8,893 patients) using a validated institutional data collection system. Orthopaedic-related readmissions were specific complications affecting the prosthesis, joint, and surgical wound. Medical readmissions were due to any other cause requiring medical management. Multivariable logistic regression models were used to investigate associations between prespecified risk factors and 90-day readmissions, as well as medical and orthopaedic-related readmissions independently. RESULTS: Overall, the rate of 90-day readmissions was 5.6%. Medical readmissions (4.2%) were found to be more prevalent than orthopaedic-related readmissions (1.4%). The area under the curve for the 90-day readmission model was 0.71 (95% confidence interval: 0.69 to 0.74). Factors significantly associated with medical-related readmissions were advanced age, Black race, education, Charlson Comorbidity Index, surgical approach, opioid overdose risk score, and nonhome discharge. In contrast, risk factors linked to orthopaedic-related readmissions encompassed body mass index, patient-reported outcome measure phenotype, nonosteoarthritis indication, opioid overdose risk, and nonhome discharge. CONCLUSIONS: Of the overall 90-day readmissions following primary THA, 75% were due to medical-related complications. Our successful predictive model for complication-specific 90-day readmissions highlights how different risk factors may disproportionately influence medical versus orthopaedic-related readmissions, suggesting that patient-specific, tailored preventive measures could reduce postoperative readmissions in the current value-based health care setting.

Primate-Specific DAZ Regulates Translation of Cell Proliferation-Related mRNAs and is Essential for Maintenance of Spermatogonia.

Primate-specific DAZ (deleted in azoospermia) has evolved in the azoospermia factor c (AZFc) locus on the Y chromosome. Loss of DAZ is associated with azoospermia in patients with deletion of the AZFc region (AZFc_del). However, the molecular mechanisms of DAZ in spermatogenesis remain uncertain. In this study, the molecular mechanism of DAZ is identified, which is unknown since it is identified 40 years ago because of the lack of a suitable model. Using clinical samples and cell models, it is shown that DAZ plays an important role in spermatogenesis and that loss of DAZ is associated with defective proliferation of c-KIT-positive spermatogonia in patients with AZFc_del. Mechanistically, it is shown that knockdown of DAZ significantly downregulated global translation and subsequently decreased cell proliferation. Furthermore, DAZ interacted with PABPC1 via the DAZ repeat domain to regulate global translation. DAZ targeted mRNAs that are involved in cell proliferation and cell cycle phase transition. These findings indicate that DAZ is a master translational regulator and essential for the maintenance of spermatogonia. Loss of DAZ may result in defective proliferation of c-KIT-positive spermatogonia and spermatogenic failure.

Surgeon Performance as a Predictor for Patient-Reported Outcomes After Arthroscopic Partial Meniscectomy.

Background: Surgeon performance has been investigated as a factor affecting patient outcomes after orthopaedic procedures to improve transparency between patients and providers. Purpose/Hypothesis: The purpose of this study was to identify whether surgeon performance influenced patient-reported outcomes (PROMs) 1 year after arthroscopic partial meniscectomy (APM). It was hypothesized that there would be no significant difference in PROMs between patients who underwent APM from various surgeons. Study Design: Case-control study; Level of evidence, 3. Methods: A prospective cohort of 794 patients who underwent APM between 2018 and 2019 were included in the analysis. A total of 34 surgeons from a large multicenter health care center were included. Three multivariable models were built to determine whether the surgeon-among demographic and meniscal pathology factors-was a significant variable for predicting the Knee injury and Osteoarthritis Outcome Score (KOOS)-Pain subscale, the Patient Acceptable Symptom State (PASS), and a 10-point improvement in the KOOS-Pain at 1 year after APM. Likelihood ratio (LR) tests were used to determine the significance of the surgeon variable in the models. Results: The 794 patients were identified from the multicenter hospital system. The baseline KOOS-Pain score was a significant predictor of outcome in the 1-year KOOS-Pain model (odds ratio [OR], 2.1 [95% CI, 1.77-2.48]; P < .001), the KOOS-Pain 10-point improvement model (OR, 0.57 [95% CI, 0.44-0.73), and the 1-year PASS model (OR, 1.42 [95% CI, 1.15-1.76]; P = .002) among articular cartilage pathology (bipolar medial cartilage) and patient-factor variables, including body mass index, Veterans RAND 12-Item Health Survey-Mental Component Score, and Area Deprivation Index. The individual surgeon significantly impacted outcomes in the 1-year KOOS-Pain mixed model in the LR test (P = .004). Conclusion: Patient factors and characteristics are better predictors for patient outcomes 1 year after APM than surgeon characteristics, specifically baseline KOOS-Pain, although an individual surgeon influenced the 1-Year KOOS-Pain mixed model in the LR test. This finding has key clinical implications; surgeons who wish to improve patient outcomes after APM should focus on improving patient selection rather than improving the surgical technique. Future research is needed to determine whether surgeon variability has an impact on longer-term patient outcomes.

High Area Deprivation Index is Associated With Not Achieving the Patient-acceptable Symptom State After TKA.

BACKGROUND: The Area Deprivation Index (ADI) approximates a patient's relative socioeconomic deprivation. The ADI has been associated with increased healthcare use after TKA, but it is unknown whether there is an association with patient-reported outcome measures (PROMs). Given that a high proportion of patients are dissatisfied with their results after TKA, and the large number of these procedures performed, knowledge of factors associated with PROMs may indicate opportunities to provide support to patients who might benefit from it. QUESTIONS/PURPOSES: (1) Is the ADI associated with achieving the minimum clinically important difference (MCID) for the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain, Joint Replacement (JR), and Physical Function (PS) short forms after TKA? (2) Is the ADI associated with achieving the patient-acceptable symptom state (PASS) thresholds for the KOOS pain, JR, and PS short forms? METHODS: This was a retrospective study of data drawn from a longitudinally maintained database. Between January 2016 and July 2021, a total of 12,239 patients underwent unilateral TKA at a tertiary healthcare center. Of these, 92% (11,213) had available baseline PROM data and were potentially eligible. An additional 21% (2400) of patients were lost before the minimum study follow-up of 1 year or had incomplete data, leaving 79% (8813) for analysis here. The MCID is the smallest change in an outcome score that a patient is likely to perceive as a clinically important improvement, and the PASS refers to the threshold beyond which patients consider their symptoms acceptable and consistent with adequate functioning and well-being. MCIDs were calculated using a distribution-based method. Multivariable logistic regression models were created to investigate the association of ADI with 1-year PROMs while controlling for patient demographic variables. ADI was stratified into quintiles based on their distribution in our sample. Achievement of MCID and PASS thresholds was determined by the improvement between preoperative and 1-year PROMs. RESULTS: After controlling for patient demographic factors, ADI was not associated with an inability to achieve the MCID for the KOOS pain, KOOS PS, or KOOS JR. A higher ADI was independently associated with an increased risk of inability to achieve the PASS for KOOS pain (for example, the odds ratio of those in the ADI category of 83 to 100 compared with those in the 1 to 32 category was 1.34 [95% confidence interval 1.13 to 1.58]) and KOOS JR (for example, the OR of those in the ADI category of 83 to 100 compared with those in the 1 the 32 category was 1.29 [95% CI 1.10 to 1.53]), but not KOOS PS (for example, the OR of those in the ADI category of 83 to 100 compared with those in the 1 the 32 category was 1.09 [95% CI 0.92 to 1.29]). CONCLUSION: Our findings suggest that social and economic factors are associated with patients' perceptions of their overall pain and function after TKA, but such factors are not associated with patients' perceptions of their improvement in symptoms. Patients from areas with higher deprivation may be an at-risk population and could benefit from targeted interventions to improve their perception of their healthcare experience, such as through referrals to nonemergent medical transportation and supporting applications to local care coordination services before proceeding with TKA. Future research should investigate the mechanisms underlying why socioeconomic disadvantage is associated with inability to achieve the PASS, but not the MCID, after TKA. LEVEL OF EVIDENCE: Level III, therapeutic study.

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence: A Critical Analysis Review.

¼ The application of artificial intelligence (AI) in the field of orthopaedic surgery holds potential for revolutionizing health care delivery across 3 crucial domains: (I) personalized prediction of clinical outcomes and adverse events, which may optimize patient selection, surgical planning, and enhance patient safety and outcomes; (II) diagnostic automated and semiautomated imaging analyses, which may reduce time burden and facilitate precise and timely diagnoses; and (III) forecasting of resource utilization, which may reduce health care costs and increase value for patients and institutions.¼ Computer vision is one of the most highly studied areas of AI within orthopaedics, with applications pertaining to fracture classification, identification of the manufacturer and model of prosthetic implants, and surveillance of prosthesis loosening and failure.¼ Prognostic applications of AI within orthopaedics include identifying patients who will likely benefit from a specified treatment, predicting prosthetic implant size, postoperative length of stay, discharge disposition, and surgical complications. Not only may these applications be beneficial to patients but also to institutions and payors because they may inform potential cost expenditure, improve overall hospital efficiency, and help anticipate resource utilization.¼ AI infrastructure development requires institutional financial commitment and a team of clinicians and data scientists with expertise in AI that can complement skill sets and knowledge. Once a team is established and a goal is determined, teams (1) obtain, curate, and label data; (2) establish a reference standard; (3) develop an AI model; (4) evaluate the performance of the AI model; (5) externally validate the model, and (6) reinforce, improve, and evaluate the model's performance until clinical implementation is possible.¼ Understanding the implications of AI in orthopaedics may eventually lead to wide-ranging improvements in patient care. However, AI, while holding tremendous promise, is not without methodological and ethical limitations that are essential to address. First, it is important to ensure external validity of programs before their use in a clinical setting. Investigators should maintain high quality data records and registry surveillance, exercise caution when evaluating others' reported AI applications, and increase transparency of the methodological conduct of current models to improve external validity and avoid propagating bias. By addressing these challenges and responsibly embracing the potential of AI, the medical field may eventually be able to harness its power to improve patient care and outcomes.

Disease diagnosis and arthroplasty type are strongly associated with short-term postoperative patient-reported outcomes in patients undergoing primary total shoulder arthroplasty.

BACKGROUND: Prognostic factors for total shoulder arthroplasty (TSA) clinical outcomes are incompletely understood. This study investigates the associations of preoperative patient, disease-specific, and surgical factors with 1-year postoperative PENN Shoulder Score (PSS) in patients undergoing primary TSA. METHODS: Cleveland Clinic patients undergoing primary anatomic TSA (aTSA) or reverse TSA (rTSA) for glenohumeral osteoarthritis (GHOA) or rotator cuff tear arthropathy (CTA) between February 2015 and August 2019, and having complete preoperative and 1-year postoperative patient-reported outcome measures (PROMs), were included. Twenty preselected preoperative patient, disease-specific, and surgical factors were used to fit multivariable models for 1-year PSS and its subscores. RESULTS: Of 1427 eligible primary TSAs, 1174 had 1-year follow-up by PROMs (82%), with 1042 analyzed after additional exclusions, including 30% rTSAs for CTA (n = 308), 26% rTSAs for GHOA (n = 275), and 44% aTSAs for GHOA (n = 459). All PROMs showed statistically significant improvements postoperatively, with 89% of patients reaching an acceptable symptom state. Lower 1-year PSS was associated with younger age, female sex, current smoking, chronic pain diagnosis, history of prior surgery, worker's compensation claim, lower preoperative mental health, lower baseline PSS, absence of glenoid bone loss, and diagnosis-arthroplasty type (CTA-rTSA < GHOA-rTSA < GHOA-aTSA). The most important prognostic factors associated with 1-year PSS were diagnosis-arthroplasty type, baseline mental health status, and insurance status. CONCLUSIONS: Disease diagnosis, arthroplasty type, and several other baseline factors are strongly and individually associated with PROMs following primary TSA, with patients undergoing aTSA for GHOA demonstrating the highest PROM scores at 1-year follow-up. Patient, disease-specific, and surgical factors can be used to guide postoperative prognosis following primary TSA for improved preoperative patient counseling regarding expected outcomes of these procedures.

What Are the Diagnosis-Specific Thresholds of Minimal Clinically Important Difference and Patient Acceptable Symptom State in Hip Disability and Osteoarthritis Outcome Score After Primary Total Hip Arthroplasty?

BACKGROUND: This study aimed to determine the minimal clinically important difference (MCID) and Patient Acceptable Symptom State (PASS) thresholds for Hip Disability and Osteoarthritis Outcome Score (HOOS) pain, physical short form (PS), and joint replacement (JR) 1 year after primary total hip arthroplasty stratified by preoperative diagnosis of osteoarthritis (OA) versus non-OA. METHODS: A prospective institutional cohort of 5,887 patients who underwent primary total hip arthroplasty (January 2016 to December 2018) was included. There were 4,184 patients (77.0%) who completed a one-year follow-up. Demographics, comorbidities, and baseline and one-year HOOS pain, PS, and JR scores were recorded. Patients were stratified by preoperative diagnosis: OA or non-OA. Minimal detectable change (MDC) and MCIDs were estimated using a distribution-based approach. The PASS values were estimated using an anchor-based approach, which corresponded to a response to a satisfaction question at one year post surgery. RESULTS: The MCID thresholds were slightly higher in the non-OA cohort versus OA patients. (HOOS-Pain: OA: 8.35 versus non-OA: 8.85 points; HOOS-PS: OA: 9.47 versus non-OA: 9.90 points; and HOOS-JR: OA: 7.76 versus non-OA: 8.46 points). Similarly, all MDC thresholds were consistently higher in the non-OA cohort compared to OA patients. The OA cohort exhibited similar or higher PASS thresholds compared to the non-OA cohort for HOOS-Pain (OA: ≥80.6 versus non-OA: ≥77.5 points), HOOS-PS (OA: ≥83.6 versus non-OA: ≥83.6 points), and HOOS-JR (OA: ≥76.8 versus non-OA: ≥73.5 points). A similar percentage of patients achieved MCID and PASS thresholds regardless of preoperative diagnosis. CONCLUSIONS: While MCID and MDC thresholds for all HOOS subdomains were slightly higher among non-OA than OA patients, PASS thresholds for HOOS pain and JR were slightly higher in the OA group. The absolute magnitude of the difference in these thresholds may not be sufficient to cause major clinical differences. However, these subtle differences may have a significant impact when used as indicators of operative success in a population setting.

Diagnosis-Specific Thresholds of the Minimal Clinically Important Difference and Patient Acceptable Symptom State for KOOS After Total Knee Arthroplasty.

UPDATE: This article was updated on May 1, 2024 because of a previous error, which was discovered after the preliminary version of the article was posted online. The byline that had read "Ahmed K. Emara, MD 1 *, Ignacio Pasqualini, MD 1 *, Alison K. Klika, MS 1 , Melissa N. Orr, BS 1 , Pedro J. Rullán, MD 1 , Nicolas S. Piuzzi, MD 1 , and the Cleveland Clinic Arthroplasty Group†" now reads "Ahmed K. Emara, MD 1 *, Ignacio Pasqualini, MD 1 *, Yuxuan Jin, MS 1 , Alison K. Klika, MS 1 , Melissa N. Orr, BS 1 , Pedro J. Rullán, MD 1 , Nicolas S. Piuzzi, MD 1 , and the Cleveland Clinic Arthroplasty Group†". BACKGROUND: Literature-reported minimal clinically important difference (MCID) and patient acceptable symptom state (PASS) thresholds for patient-reported outcome measures demonstrate marked variability. The purpose of this study was to determine the minimal detectable change (MDC), MCID, and PASS thresholds for the Knee injury and Osteoarthritis Outcome Score (KOOS) Pain subdomain, Physical Function Short Form (PS), and Joint Replacement (JR) among patients with osteoarthritis (OA) who underwent primary total knee arthroplasty (TKA). METHODS: A prospective cohort of 6,778 patients who underwent primary TKA was analyzed. Overall, 1-year follow-up was completed by 5,316 patients for the KOOS Pain, 5,018 patients for the KOOS PS, and 4,033 patients for the KOOS JR. A total of 5,186 patients had an OA diagnosis; this group had an average age of 67.0 years and was 59.9% female and 80.4% White. Diagnosis-specific MDCs and MCIDs were estimated with use of a distribution-based approach. PASS values were estimated with use of an anchor-based approach, which corresponded to a response to a satisfaction question at 1 year postoperatively. RESULTS: The MCID thresholds for the OA group were 7.9 for the KOOS Pain, 8.0 for the KOOS PS, and 6.7 for the KOOS JR. A high percentage of patients achieved the MCID threshold for each outcome measure (KOOS Pain, 95%; KOOS PS, 88%; and KOOS JR, 94%). The MDC 80% to 95% confidence intervals ranged from 9.1 to 14.0 for the KOOS Pain, 9.2 to 14.1 for the KOOS PS, and 7.7 to 11.8 for the KOOS JR. The PASS thresholds for the OA group were 77.7 for the KOOS Pain (achieved by 73% of patients), 70.3 for the KOOS PS (achieved by 68% of patients), and 70.7 for the KOOS JR (achieved by 70% of patients). CONCLUSIONS: The present study provided useful MCID, MDC, and PASS thresholds for the KOOS Pain, PS, and JR for patients with OA. The diagnosis-specific metrics established herein can serve as benchmarks for clinically meaningful postoperative improvement. Future research and quality assessments should utilize these OA-specific thresholds when evaluating outcomes following TKA. Doing so will enable more accurate determinations of operative success and improvements in patient-centered care. LEVEL OF EVIDENCE: Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Does Time to Aseptic Failure After Primary Total Hip Arthroplasty Affect Clinical and Patient-Reported Outcomes?

BACKGROUND: Evidence on the effects of time-to-failure from primary total hip arthroplasty (THA) to aseptic first-revision on clinical results and patient-reported outcome measures (PROMs) is scarce. Therefore, we sought to compare demographics, operative times, lengths of stay, discharge dispositions, 90-day readmissions, re-revision rates, mortalities, and PROMs between early and late aseptic THA revisions. METHODS: This study is a retrospective review of a prospectively collected institutional database of all elective hip procedures. In total, 572 patients who underwent aseptic revision after primary THA from August 2015 to December 2018 were analyzed. Patients were stratified into either early revision (<3-years; n = 176) or late revision (≥3-years; n = 396) cohorts. RESULTS: Significantly more patients were revised earlier for bone-related (ie, periprosthetic fractures) (22.7% versus 8.3%) or other various complications (19.9% versus 5.8%), whereas more late revisions were performed to treat implant-related failures (6.8% versus 37.1%), respectively. Operative time was significantly shorter in early versus late revisions (133 versus 157 minutes). A significantly higher delta-change/improvement from baseline/preoperative to 1-year postoperative was found for hip disability and osteoarthritis outcome score physical function (HOOS-PS), veterans-RAND-12 physical and mental components (VR-12-PCS and MCS, respectively) of early revisions. However, HOOS-PS and HOOS-Pain at 1-year of follow-up were significantly worse in early revisions. CONCLUSION: With exception of operative time, time-to-failure had no significant influence on clinical results. Despite greater improvements on PROMs from preoperative to postoperative, patients undergoing early revisions after primary THA perceive significantly higher levels of pain and worse physical functionality at 1-year of follow-up.