Citations

Purpose To report the clinical outcomes and reoperation rates of arthroscopic and endoscopic iliopsoas release at short‐term follow‐up after ipsilateral total hip arthroplasty (THA) at 2 separate medical institutions and to evaluate whether demographic and radiographic parameters are associated with postoperative patient‐reported outcomes (PROs). Methods Patients with iliopsoas tendinitis in the setting of prior THA who underwent arthroscopic iliopsoas fractional lengthening from 1988 to 2023 at 2 academic institutions were reviewed. Patients were included if they had 12 months of follow‐up and underwent evaluation of preoperative anterior acetabular component overhang, surgery satisfaction, postoperative subjective hip flexion strength and anterior groin pain improvement, modified Harris Hip Score, Single Assessment Numeric Evaluation score, Tegner activity scale score, visual analog scale (VAS) score, and revision hip arthroplasty. Results Sixty hips in 58 patients (19 male and 39 female patients) were followed up for a mean of 39.3 months (range, 12.0‐105.9 months) postoperatively. Of the patients, 77% reported feeling “much better” or “slightly better,” 75% reported improved anterior groin pain, and 60% reported improved subjective hip flexion strength. The surgery satisfaction rating was 7.2 ± 3.3 (scale of 0 to 10). The mean postoperative modified Harris Hip Score, VAS score for pain at rest, VAS score for pain with use, and Single Assessment Numeric Evaluation score were 73.9 ± 19.4, 1.3 ± 2.4, 3.8 ± 2.9, and 71.9 ± 21.9, respectively. Preoperative anterior acetabular component overhang was 3.3 ± 6.5 mm and did not significantly correlate with postoperative PROs ( P ≥ .45). The Tegner score improved from 2.5 ± 1.7 preoperatively to 2.9 ± 1.4 postoperatively ( P = .0253). Three patients underwent revision arthroplasty at a mean of 25.3 months (range, 11.6‐40.4 months) postoperatively, with an acetabular component revision rate of 3.3%. Conclusions Satisfactory outcomes and low revision arthroplasty rates were observed in patients undergoing arthroscopic iliopsoas lengthening after THA. There was no statistically significant relation between anterior acetabular component overhang and final PROs. Level of Evidence Level IV, therapeutic case series.

Introduction/Objective: Physicians and other health care professionals are challenged regularly to balance managing pain for patients with chronic pain receiving chronic opioid therapy (COT) with following the national guidelines and standards regarding daily morphine milligram equivalents (MME). This quality improvement project aimed to determine the effect of referral to a multidisciplinary review panel on daily MME for patients receiving COT for chronic pain. Methods: This quality improvement project included patients who had an established relationship with a primary care or community internal medicine clinician at a large health care organization and were referred to a newly created multidisciplinary review panel for their recommendations regarding treatment of pain. Criteria for patient referral were diagnosis of a chronic, painful condition, and use of chronic opioid medications. These patients were selected and referred at the discretion of their primary care clinician from January 2, 2019, through December 31, 2020. Data for this project were collected at the time of initial referral to the panel and 6 months after recommendations. The daily MME were assessed at the 2 time points. Results: Thirteen patients were referred to the review panel during the project period. The median daily MME at the time of referral was 180. Daily MME decreased by a median of 14 MME after 6 months. The MME did not increase during the project period for any participants. Conclusions: Referral of patients receiving COT to a multidisciplinary review panel may reduce their daily opioid dose.

Piezo channels were first described just over a decade ago and their function in the lung is largely unknown. We found that piezo channels are present and functional in the developing airway and contribute to intracellular calcium responses and extracellular matrix remodeling in the setting of stretch. This may improve our understanding of the mechanisms behind development of chronic airway diseases, such as asthma, in former preterm infants exposed to respiratory support, such as continuous positive airway pressure (CPAP).

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 percentage points) compared to the full longitudinal dataset. The submission system remains open via the website https://tadpole.grand-challenge.org, while TADPOLE SHARE (https://tadpole-share.github.io/) collates code for submissions. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.