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Introduction Geriatric distal femur fractures are associated with mortality rates exceeding 20%, comparable to hip fractures. Traditional single implant fixation often requires weight-bearing restrictions that delay recovery. This pilot study aims to assess the feasibility of conducting a multicentre randomised controlled trial comparing dual vs single implant fixation for geriatric distal femur fractures. Methods and analysis This multicentre, prospective, randomised controlled pilot trial will enrol 80 participants aged 60 years or older with displaced distal femur fractures at five US level 1 trauma centres. Patients will be randomly allocated 1:1 to receive either single implant (lateral plate or retrograde nail) or dual implant (nail-plate or dual plate) fixation. All patients will be permitted immediate weight-bearing. The primary outcome is feasibility assessed through enrolment rate (80 patients in 12 months), protocol adherence (≥90%) and follow-up retention (≥85% at 12 months). Secondary outcomes include post-surgical mobility (AM-PAC, TUG), patient-reported outcomes (PROMIS-PF, PROMIS-29), mortality (90-day and 1 year) and complication rates. Analyses will be on an intention-to-treat basis. Ethics and dissemination The protocol was approved by the University of Utah Institutional Review Board (IRB_00149119) and IRBs at all participating centres. Written informed consent will be obtained from participants or legally authorised representatives. Findings will be disseminated through peer-reviewed publications and conference presentations. Trial registration number NCT05292313 .

ABSTRACT Objective Management of vestibular schwannoma (VS) remains controversial. Very small VSs represent a pivotal group: on one hand, they pose the least risk to the patient from the perspective of being small; yet, not recommending treatment may result in missing a critical window for achieving the best outcome. This debate fundamentally hinges on whether treatment improves upon the natural history of the disease. There is an unproven assumption that very small tumors behave similarly to the broader observed population. To address this central question, we conducted a multicenter retrospective review to compare the natural history of tumor growth and hearing for patients with very small VS (1–3 mm) with a referent cohort with larger tumors. Methods All patients diagnosed with sporadic VS 1–3 mm were reviewed at 3 large skull base referral centers and compared with a referent cohort of patients with tumors > 3 mm. Tumor growth‐free survival rates, treatment‐free survival rates, and rates of maintenance of class A, B, or C hearing were estimated using the Kaplan–Meier method. Results In total, 123 patients with very small VS and a referent cohort of 326 patients were studied. Seventeen patients with very small VS experienced tumor growth at a median of 3.2 years after diagnosis (IQR 2.6–5.1), demonstrating a median growth rate of 1.0 mm per year (IQR 0.9–1.8). In comparison, 167 of the patients in the referent cohort experienced tumor growth at a median of 1.7 years after diagnosis (IQR 0.8–3.1). Tumor growth‐free survival rates (95% CI, number still at risk) at 5 years after diagnosis for the 2 cohorts were 84% (75–93, 39) and 45% (40–52, 100), respectively ( p < 0.001). Six patients with very small VS underwent treatment after tumor growth at a median of 3.2 years after diagnosis (IQR 3.2–3.8), compared with 138 patients in the referent cohort at a median of 2.2 years after diagnosis (IQR 1.4–3.6). Treatment‐free survival rates (95% CI, number still at risk) at 5 years after diagnosis for the 2 cohorts were 92% (86–98, 55) and 54% (49–61, 125), respectively ( p < 0.001). Among the 105 patients with very small VS and class A, B, or C hearing at diagnosis, 3 progressed to class D. Comparatively, among the 225 patients in the referent cohort with class A, B, or C hearing at diagnosis, 70 progressed to class D at a median of 2.6 years after diagnosis (IQR 1.0–4.8). Rates of maintenance of class A, B, or C hearing (95% CI, number still at risk) at 5 years after diagnosis were 96% (92–100, 28) for patients with very small VS and 65% (57–73, 70) for the referent cohort ( p < 0.001). Conclusions The natural history of tumor growth and hearing for very small VS diverges favorably from the cumulative natural history data and provides a more appropriate benchmark to compare clinical outcomes of upfront surgery or radiosurgery for this population. At 5 years after diagnosis, 96% of very small VS maintained class A, B, or C hearing and only 8% received treatment for growth within this multicenter cohort. Cumulatively, these data substantiate initial wait‐and‐scan management via size threshold surveillance in this population. Level of Evidence 3.

ABSTRACT The Burkholderia cepacia complex (BCC) is comprised of 24 species of Gram-negative bacteria that cause opportunistic infections. While antimicrobial susceptibility testing (AST) has historically been used to guide treatment for BCC infections, recent work highlighting problems with AST for these organisms led the Clinical and Laboratory Sciences Institute (CLSI) to remove disk diffusion (DD) and minimal inhibitory concentration (MIC) breakpoints for BCC from its M100 standards document. Epidemiological cut-off values (ECVs) may be helpful to clinicians in the absence of breakpoints, as they may be used to determine whether an isolate has a wild-type or non-wild-type phenotype. Here we present an analysis of BCC ECVs for ceftazidime (CAZ), levofloxacin (LVX), meropenem (MEM), minocycline (MIN), and trimethoprim-sulfamethoxazole (TMP-SMX). ECVs were calculated using MIC data from 3 previous studies and 3 independent laboratories for 1,896 BCC isolates. ECVs were 16 μg/ml for CAZ, 8 μg/ml for LVX, 16 μg/ml for MEM, and 8 μg/ml for MIN. The ECV for TMP-SMX varied depending on the analysis from 2 μg/ml, 8 μg/ml, and 16 μg/ml and therefore could not be reliably established. Challenges with establishing ECVs for BCC include limitations with the pooled MIC dataset, broad MIC distributions, and high ECVs that are above the obsolete susceptible MIC breakpoints. These challenges limit the clinical utility of ECVs for these organisms and supported removal of ECVs from the CLSI M100 standards document. IMPORTANCE The Burkholderia cepacia complex is a group of bacterial species that cause difficult-to-treat opportunistic infections. Recently, clinical breakpoints, which are used to determine whether organisms are susceptible to certain antimicrobials, were removed from Clinical and Laboratory Standards Institute (CLSI) standards for these organisms due to problems with antimicrobial susceptibility testing performance. Clinicians are now faced with the challenge of how to treat these complex infections without clinical breakpoints. Here we determine epidemiological cut-off values (ECVs) for relevant antimicrobials for the B. cepacia complex. While we established ECVs for four antimicrobials, we encountered significant challenges in our analyses, including limitations with data for these organisms and high ECVs that are not clinically useful. These challenges limit the practical use of these ECVs in helping guide clinicians on treatment and supported the eventual removal of ECVs from the CLSI M100 standards document.

Clonal acquisition of multiple chromosomal abnormalities in hematopoietic stem and progenitor cells (HSPCs) is a hallmark of high-risk acute myeloid leukemias with complex karyotype (AML-CK). AML-CK is associated with TP53 mutations and chromosome 5q deletions (del5q); however, the drivers and clonal trajectories of aneuploid evolution in HSPCs remain unknown. We have developed a patient-derived induced pluripotent stem cell (iPSC) model in which preleukemic HSPCs clonally evolve to distinct, highly aneuploid states following transient mitotic inhibition. By tracking chromosome evolution at single cell resolution, we show that TP53-mutant HSPCs with del5q, but not TP53­ mutation alone, evolved complex chromosomal changes. Clonal evolution was marked by stepwise acquisition of numerical and structural chromosome changes seen in AML-CK patients, with individual abnormalities conferring fitness advantage. iPSC-derived aneuploid HSPCs and primary AML-CK patient samples exhibited a conserved gene expression signature marked by upregulation of PTEN, cohesins, and anti-apoptotic factor BCL2, indicative of a shared aneuploid cell state in HSPCs. Clinical BCL2 inhibitor venetoclax eradicated BCL2-dependent aneuploid clones, with resistant clones undergoing a lineage switch to upregulate alternative BCL2 factors. In summary, we demonstrate that mutant TP53 and del5q drive chromosome evolution marked by stepwise acquisition of individual abnormalities. Moreover, aneuploid HSPCs exhibit a shared gene expression state which confers unique targetable therapeutic vulnerabilities in AML-CK.

Abstract Background Markerless tumor tracking (MTT) using single‐energy (SE) kilovoltage (kV) imaging has been proposed as a technique for lung tumor motion management. However, bony structures can obscure the tumor and make tracking challenging. Dual‐energy (DE) subtraction imaging can suppress the bone and therefore enhance tumor visibility, potentially improving tracking accuracy. Purpose To develop a machine learning model that predicts the reliability of MTT for SE and DE imaging using phantom and patient data. Methods Images were collected at high and low energy (120/60 kV) using fast‐kV switching on dynamic thorax phantom with 5–15 diameter targets and 20 lung cancer patients, including one patient with two tumor locations. DE images were then generated off‐line using weighted logarithmic subtraction. Separately, a template‐based tracking algorithm was used to track the tumor on both phantom and patient images. For phantom data, the ground truth (GT) was defined by the cos 4 waveform programmed into the motion controller. Since the GT was unknown for patient data, it was estimated using a Kalman filter and further refined using visual inspection. The tracking success rate (TSR) was subsequently calculated. Based on TSR, patients were stratified into three tracking groups: good, moderate, and poor. A logistic regression (LR) model was implemented with tracking features, including match score, peak to side‐peak ratio (PSR), x ‐ and y ‐velocity. To address the distribution differences between phantom and patient data, a domain indicator and interaction features were also incorporated. The model was trained on phantom and 17 patient data using leave‐one‐out cross‐validation, and its performance was evaluated on three held‐out patients, one from each tracking group. Separate LR models were developed for each imaging modality, resulting in SE‐LR and DE‐LR models. For each held‐out patient, the confusion matrix, sensitivity, and specificity were reported. Results For both SE‐LR and DE‐LR models, PSR has the largest coefficient value, indicating that it is the most influential factor when determining the reliability of tracking. At a specificity of 95%, the DE‐LR model achieved significantly higher sensitivity than the SE‐LR model (0.908 vs. 0.731, p < 0.01 for phantom data and 0.657 vs. 0.589, p < 0.01 for patient data). In the three held‐out patients, the DE‐LR model outperformed the SE‐LR model across all metrics. The largest gains were found in the patient with good tracking quality. Conclusions The proposed LR models successfully predicted the reliability of SE‐ and DE‐MTT. Across phantom and patient datasets, the DE‐LR model consistently demonstrated improved performance compared with the SE‐LR model, suggesting that DE imaging may be beneficial for MTT applications.

Background: Hypoplastic left heart syndrome (HLHS) is defined as “a spectrum of congenital cardiovascular malformations with normally aligned great arteries without a common atrioventricular junction, characterized by underdevelopment of the left heart with significant hypoplasia of the left ventricle including atresia, stenosis, or hypoplasia of the aortic or mitral valve, or both valves, and hypoplasia of the ascending aorta and aortic arch”. Without treatment, HLHS is usually lethal in the neonate. Many hypotheses have been advanced to explain the etiology of HLHS; however, no single theory appears to fully explain the phenotypic variability seen in HLHS. Furthermore, many of these theories offer no explanations regarding the precipitating events which lead to the development of HLHS. Objective: This review considers and critically evaluates the strengths and weaknesses of the leading theories proposed to explain the pathogenesis of HLHS—including hemodynamic disturbances, primary myocardial structural defects, valvar malformations, and genetic or epigenetic alterations that may provoke developmental and anatomic abnormalities. After presenting each model, we propose a novel, comprehensive, and data-driven framework which may assist researchers in developing models for the pathogenesis of the various subtypes of HLHS. Methods: Key findings from human fetal imaging, histopathology, genetic studies, and animal models were considered, as well as the hypothetical contribution of each in observed HLHS phenotypes. The rationales for these findings as causal factors initiating individual HLHS patterns, as well as how they might contribute to HLHS in general, were critically analyzed. Results: The flow theory is strongly supported by animal models and in utero interventions that demonstrate the impact of altered hemodynamics on cardiac morphogenesis. However, the flow theory fails to identify initial causes of disturbed flow or related histological features of HLHS like endocardial fibroelastosis. The myocardial and valve-first models suggest an important role in developmental defects, but do not necessarily have a strong experimental basis that provides explanations for how they mediate HLHS. Genetic studies in patients with HLHS have identified several candidate causal mutations. However, such genetic causes of HLHS exhibit incomplete phenotypic penetrance and clinical impact. A multifactorial framework attempts to integrate these diverse mechanisms and may provide the most coherent explanation that can accommodate the heterogeneity and variable presentation of HLHS. Such a framework may identify multiple forces that drive disease but does not provide useful pathways for future research about HLHS. Conclusions: No single hypothesis has fully explained how HLHS is initiated, progresses, and presents with the clinical conditions that are encountered by cardiac surgeons and cardiologists. The most current models suggest that the spectrum of HLHS reflects acomplex interaction between genetic susceptibility, flow-dependent cardiac remodeling, and environmental factors in utero. A multifactorial model integrates these diverse mechanisms and may provide the most coherent explanation for the various phenotypic variations in HLHS. Based on our analysis of the most current data and the strengths and weaknesses of the current theoretical frameworks, we propose a novel research strategy aimed at identifying specific cardiac progenitor cell populations whose dysregulation may represent a unifying explanation for the etiology of the various phenotypes of HLHS. Based on the arguments made throughout this manuscript that evaluate the various genetic, structural, and hemodynamic models of initiation of disease, we believe that the significant phenotypic variability across the spectrum of HLHS (i.e., the different anatomic subtypes for “classic” HLHS) most likely reflects different underlying etiologies and mechanisms. At the very least, it is very likely that the timing of the insult is critical in determining anatomic subtype. Based on the published data and the arguments within this manuscript, it seems naive to think that there is a single unifying mechanism explain all forms of HLHLS.