Citations

Arthroplasty of the proximal interphalangeal joint (PIPJ) has evolved since its inception over 60 years ago. This review examines the indications for surgery, highlights the differences in current arthroplasty designs, variances in surgical techniques, clinical controversies, current implant outcomes data and salvage options for the failed implant. Overall, PIPJ implant arthroplasty is a good and reliable option for symptomatic PIPJ degenerative, post-traumatic or inflammatory arthritis given the proper clinical setting. If current techniques for implantation and rehabilitation are followed, predictable pain relief and satisfactory function can be anticipated. The purpose of this review article is to examine the current evidence-based indications for PIPJ arthroplasty and examine the reported, implant-specific outcomes of this procedure. Various techniques and rehabilitation strategies will also be outlined.

Degenerative wrist conditions, such as scapholunate advanced collapse and scaphoid nonunion advanced collapse, often require salvage procedures to reduce pain and improve function. For early stages of disease, both proximal row carpectomy and scaphoid excision four-corner arthrodesis are viable motion-preserving options. There remains controversy on which technique is superior. Selection is a nuanced decision that requires consideration of patient characteristics and stage of disease. The traditional notion that proximal row carpectomy should be reserved for older individuals with low demands has been challenged; long-term studies in younger populations demonstrate similar patient-reported outcomes, pain relief and survivorship without conversion to total wrist arthrodesis between proximal row carpectomy and four-corner arthrodesis. The existing evidence suggests proximal row carpectomy has advantages of greater range of motion, fewer complications and lower costs. Advancements such as arthroscopic techniques for both procedures show potential, although mastery involves a steep learning curve.

The intrinsic force production capability of human muscle can be expressed as “Specific Tension,” or, the maximum force generated per cross-sectional area of muscle fibers. This value can be used to determine, for example, whether muscle quality changes during exercise, atrophy, disease, or hypertrophy. A value of 22.5 N/cm 2 for mammalian muscle has generally become accepted based on detailed studies of small mammals. Determining the specific tension of human muscle is much more challenging as almost all determinations are indirect. Calculation of human muscle specific tension requires an understanding of that muscle’s contribution to joint torque, its activation magnitude, tendon compliance, and joint moment arm. Determining any of these parameters is technically challenging in humans and thus, it is no surprise that human specific tension values reported vary from 2 to 73 N/cm 2 . In this systematic review, we screened 1,506 published papers and identified the 30 studies published between 1983 and 2023 that used appropriate methods and which reported 96 human specific tension values. We weighted each parameter based on whether it was directly measured, estimated, or calculated based on the literature, with decreasing weighting used, the more indirect the methods. Based on this exhaustive review of the relevant human literature, we suggest that the most accurate value that should be used for human muscle specific tension is 26.8 N/cm 2 .

AbstractAging is associated with cardiac contractile abnormalities, but the etiology of these contractile deficits is unclear. We hypothesized that cardiac contractile and regulatory protein expression is altered during aging. To investigate this possibility, left ventricular (LV) lysates were prepared from young (6 months) and old (24 months) Fischer344 rats. There are no age‐related changes in SERCA2 expression or phospholamban phosphorylation. Additionally, neither titin isoform expression nor phosphorylation differed. However, there is a significant increase in β‐isoform of the myosin heavy chain (MyHC) expression and phosphorylation of TnI and MyBP‐C during aging. In permeabilized strips of papillary muscle, force and Ca2+ sensitivity are reduced during aging, consistent with the increase in β‐MyHC expression and TnI phosphorylation. However, the increase in MyBP‐C phosphorylation during aging may represent a mechanism to compensate for age‐related contractile deficits. In isolated cardiomyocytes loaded with Fura‐2, the peak of the Ca2+ transient is reduced, but the kinetics of the Ca2+ transient are not altered. Furthermore, the extent of shortening and the rates of both sarcomere shortening and re‐lengthening are reduced. These results demonstrate that aging is associated with changes in contractile and regulatory protein expression and phosphorylation, which affect the mechanical properties of cardiac muscle.

AbstractBackgroundAdaptive radiotherapy (ART) workflows have been increasingly adopted to achieve dose escalation and tissue sparing under shifting anatomic conditions, but the necessity of recontouring and the associated time burden hinders a real‐time or online ART workflow. In response to this challenge, approaches to auto‐segmentation involving deformable image registration, atlas‐based segmentation, and deep learning‐based segmentation (DLS) have been developed. Despite the particular promise shown by DLS methods, implementing these approaches in a clinical setting remains a challenge, namely due to the difficulty of curating a data set of sufficient size and quality so as to achieve generalizability in a trained model.PurposeTo address this challenge, we have developed an intentional deep overfit learning (IDOL) framework tailored to the auto‐segmentation task. However, certain limitations were identified, particularly the insufficiency of the personalized dataset to effectively overfit the model. In this study, we introduce a personalized hyperspace learning (PHL)‐IDOL segmentation framework capable of generating datasets that induce the model to overfit specific patient characteristics for medical image segmentation.MethodsThe PHL‐IDOL model is trained in two stages. In the first, a conventional, general model is trained with a diverse set of patient data (n = 100 patients) consisting of CT images and clinical contours. Following this, the general model is tuned with a data set consisting of two components: (a) selection of a subset of the patient data (m < n) using the similarity metrics (mean square error (MSE), peak signal‐to‐noise ratio (PSNR), structural similarity index (SSIM), and the universal quality image index (UQI) values); (b) adjust the CT and the clinical contours using a deformed vector generated from the reference patient and the selected patients using (a). After training, the general model, the continual model, the conventional IDOL model, and the proposed PHL‐IDOL model were evaluated using the volumetric dice similarity coefficient (VDSC) and the Hausdorff distance 95% (HD95%) computed for 18 structures in 20 test patients.ResultsImplementing the PHL‐IDOL framework resulted in improved segmentation performance for each patient. The Dice scores increased from 0.810.05 with the general model, 0.83 for the continual model, 0.83 for the conventional IDOL model to an average of 0.87 with the PHL‐IDOL model. Similarly, the Hausdorff distance decreased from 3.06 with the general model, 2.84 for the continual model, 2.79 for the conventional IDOL model and 2.36 for the PHL‐IDOL model. All the standard deviations were decreased by nearly half of the values comparing the general model and the PHL‐IDOL model.ConclusionThe PHL‐IDOL framework applied to the auto‐segmentation task achieves improved performance compared to the general DLS approach, demonstrating the promise of leveraging patient‐specific prior information in a task central to online ART workflows.

Abstract The Blood and Marrow Transplant (BMT) Clinical Trials Network conducted a phase 3 randomized trial comparing gilteritinib with placebo after allogeneic hematopoietic cell transplantation (HCT) for FLT3-ITD+ acute myeloid leukemia (AML). The primary analysis demonstrated no statistically significant difference in relapse-free survival (RFS); however, patients with FLT3-ITD measurable residual disease (MRD) peri-HCT had significantly longer RFS with gilteritinib. This analysis investigates the effect of post-HCT gilteritinib vs placebo on health-related quality of life (HRQOL). HRQOL was measured with Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT), FACT-Leukemia (FACT-Leu), and EuroQOL-5 Dimensions (EQ-5D-5L) at post-HCT randomization; day 29; months 3, 6, 12, 18, 24; and/or end of therapy. HRQOL and clinically meaningful differences were summarized using descriptive statistics and compared using mixed model repeated measures to evaluate longitudinal change from baseline and stratified Cox model to evaluate time to improvement. HRQOL completion rate was acceptable (&gt;70%) across all time points and measures. There were no differences in HRQOL scores at any time point between cohorts. Clinically meaningful and time to improvement in HRQOL were similar in both arms. Despite higher treatment-emergent adverse effects with gilteritinib, response to the question of being “bothered by side effects of treatment” did not differ between groups. Subgroup analysis of MRD-positive and negative patients demonstrated no differences in HRQOL between arms. For patients with FLT3-ITD+ AML undergoing HCT, gilteritinib maintenance was not associated with any difference in HRQOL or patient-reported impact of side effects. This trial was registered at www.ClinicalTrials.gov as #NCT02997202.