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OBJECTIVE Craniopharyngiomas are benign intracranial tumors that can be difficult to manage operatively and often result in postoperative complications and prolonged recovery. Understanding the factors that influence length of stay (LOS), discharge disposition, and readmission can guide perioperative planning and patient counseling. The authors examined the clinical, radiographic, and surgical predictors of extended LOS (eLOS), nonhome discharge, 90-day readmission, and hospitalization ratio (HR) after craniopharyngioma resection using a large, multicenter cohort. METHODS A retrospective analysis was conducted using the Registry of Adenomas of the Pituitary and Related Disorders database, encompassing 469 patients who underwent craniopharyngioma resection at 14 US academic centers from 2011 to 2025. Patients were stratified by 4 outcomes: eLOS (> 75th percentile), discharge to home versus skilled nursing facility/rehabilitation, 90-day hospital readmission, and hospitalization ratio (i.e., integration of initial and readmission LOS). Multivariable logistic regression models identified independent predictors for each outcome among patient and surgical variables. RESULTS An eLOS (> 10 days) was independently associated with preoperative memory loss (OR 3.75, 95% CI 1.95–7.21), gait imbalance (OR 5.90, 95% CI 1.53–22.70), and postoperative complications (OR 4.07, 95% CI 2.34–7.06). The use of a nasoseptal flap was protective against an eLOS (OR 0.52, 95% CI 0.28–0.93). Discharge to home was predicted by an endoscopic approach (OR 3.87, 95% CI 1.78–8.44) and postoperative intact thirst (OR 2.22, 95% CI 1.05–4.66) and negatively predicted by preoperative diabetes mellitus (OR 0.21, 95% CI 0.09–0.50), LOS (OR 0.87, 95% CI 0.84–0.91), and postoperative cognitive dysfunction (OR 0.30, 95% CI 0.13–0.72). Among 385 patients with follow-up data, a 90-day readmission was independently associated with postoperative complications (OR 5.62, 95% CI 3.12–10.13), preexisting coronary artery disease (OR 4.30, 95% CI 1.46–12.69), and postoperative cognitive dysfunction (OR 3.33, 95% CI 1.76–6.44). A higher HR was associated with diabetes mellitus (unstandardized B 0.059, 95% CI 0.010–0.108, p = 0.02), postoperative complications (unstandardized B 0.054, 95% CI 0.021–0.086, p = 0.001), and postoperative cognitive dysfunction (unstandardized B 0.049, 95% CI 0.006–0.092, p = 0.02). Tumor pathologic subtype and size, prior treatment, extent of resection, and surgeon experience were not directly predictive of outcomes. CONCLUSIONS Cognitive and functional status, systemic comorbidities, and postoperative complications, in addition to surgical approach, are important predictors of the early clinical course after craniopharyngioma surgery. Early identification of high-risk patients may help to guide treatment decisions, improve discharge planning, and reduce healthcare utilization.

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.