Citations

Syndrome of the Trephined (SoT), also known as sunken or sinking skin flap syndrome (SSFS), is a rare sequela of decompressive craniectomy caused by an atmospheric pressure gradient over the underlying brain parenchyma following bone flap removal. Cranioplasty is the definitive treatment of SoT, although some patients are not surgical candidates or require bridging to definitive treatment. This systematic review identified 7 articles describing nonsurgical interventions for patients with SoT. Three treatment modalities emerged: external orthotics, scalp traction, and Trendelenburg positioning. These approaches demonstrated rapid improvements in neurological symptoms, including restored motor function, improved cognition, resolution of midline shifts, and, in some cases, re-expanded brain parenchyma. While these results are limited to case reports and small case series, they demonstrate promising early outcomes for the noninvasive management of Syndrome of the Trephined.

Study Design: Retrospective cohort analysis. Objective: To determine the effect of long-segment posterior cervical decompression and fusion (PCDF) on perioperative changes in vertebral Hounsfield Units (HUs) and the impact of these changes on radiographic outcomes and fusion status. Summary of Background Data: Low preoperative CT HUs have been associated with adverse outcomes after spinal fusion, including hardware complications and reoperation. No existing studies have investigated the preoperative to postoperative change in HUs after cervical spinal fusion. Stress shielding may decrease bone quality within the fusion construct. Whereas, altered junctional loading and increased segmental mobility may precipitate bony hypertrophy in the terminal and adjacent levels. Methods: All adult patients who underwent C2-T2 PCDF for myelopathy/ myeloradiculopathy at an academic center between 2013 and 2020 were retrospectively identified. Preoperative and postoperative HUs were assessed on axial CT images in the cranial, middle, and caudal C2, C6, T2, and T3 vertebral bodies, outside of the region of instrumentation and artifact by 2 independent reviewers. Paired t test compared preoperative to postoperative changes in HUs. Preoperative and long-term postoperative cervical alignment, fusion, and revision rates were assessed. Univariate and regression analysis compared patient factors and outcomes between groups with perioperative increase versus decrease in vertebral HUs. Results: One hundred patients were included. The average preoperative to postoperative change in HUs in the C2, C6, T2, and T3 vertebral bodies were −19.80 (P=0.008), −52.63 (P<0.001), 15.15 (P=0.014), and 9.41 (P=0.346), respectively. Perioperative increase in C2 HUs was predictive of increased postoperative distal junctional angle (β=3.41, P=0.048) and increased T1–T4 kyphosis (β=6.50, P=0.003). Perioperative increase in C6 HU predicted pseudoarthrosis (fusion odds ratio: 0.19, P=0.007). Conclusions: Significant perioperative decreases in C6 HUs within a long-fused construct may demonstrate stress shielding. The significant association between greater distal kyphosis and an increase in C2 HUs may be attributed to a stress riser effect. Level of Evidence: Level III.

Introduction/Background: Despite numerous medical advances, 30% of patients with Fontan circulation require heart transplantation by 21. Current risk stratification relies on clinical metrics that lack strong correlations to patient outcomes, leading to a high waitlist mortality. Hypothesis: Integration of physics-based hemodynamic modeling with interpretable machine learning will improve prediction of patient outcomes (listing for heart transplant and/or cardiac death) by quantifying physiologic mechanisms inaccessible through clinical measures alone. Goals/Aims: 1. Develop a lumped-parameter mechanistic model (LPMM) of Fontan circulation 2. Identify patient clusters and predictors of patient outcomes 3. Validate model-informed classifiers against clinical-only approaches Methods/Approach: A LPMM incorporating ventricular sarcomere mechanics, atrial hemodynamics, and vascular viscoelastic effects was optimized to cardiac catheterization and echocardiography data from 51 patients (age 25±8 years). Thirty-eight parameters (ventricular inotropy, atrial stiffness, pulmonary elastance, etc.) were calibrated via surrogate optimization, minimizing least-squares error versus 11 clinical targets. Partial least-squares regression with leave-one-out cross-validation compared clinical-only versus model-informed classifiers of outcomes. Results/Data: The LPMM achieved 2% mean error across hemodynamic targets, with CVP and pulmonary pressures matching clinical measurements within 1%. Model-derived minimum atrial pressure (4.46±1.78 vs 2.68±0.87 mmHg, p<0.05) outperformed all clinical variables in discriminating patient outcomes. Integration of LPMM parameters increased AUROC from 0.67 to 0.78 for patient outcome prediction. Conclusions: Physics-based modeling identifies ventricular passive stiffness, atrial end-diastolic volume, and minimum atrial pressure, along with patient age (a clinical value) as critical determinants of Fontan failure. Combined mechanistic-machine learning approaches enable phenotype-specific risk stratification, supporting earlier referral for advanced therapies. This methodology establishes a framework for precision management of complex congenital circulations.

ABSTRACT Newly diagnosed patients with non‐Hodgkin lymphoma (NHL) often have a history of other diseases, and these comorbidities can impact patient treatment and management options, as well as overall survival (OS). We developed the Lymphoma Epidemiology of Outcomes (LEO) comorbidity index (LCI) as a sum of 10 comorbidities adapted from the Self‐Report‐Generated Charlson Comorbidity Index (SRG‐CCI) for use in the LEO cohort, a national prospective study of newly diagnosed NHL. Of the 5502 participants with self‐reported comorbidity data, 3107 (56.4%) were male and the mean age at diagnosis was 60.9 years (range, 18–99 years). The LCI ranged from 0 to 6, with 48.6% having 0, 30.2% having 1, 21.2% having 2 or more comorbidities. With a median follow‐up of 62.4 months among surviving participants, 2099 patients had an event and 1219 died. Continuous LCI similarly predicted both 1‐year mortality (c‐statistic = 0.654) and OS (c‐statistic = 0.655), while it showed a weaker but still statistically significant predictive ability for lymphoma‐specific (c‐statistics = 0.617) and event‐free (c‐statistic = 0.574) survival. Participants with 1 (HR = 1.21, 95% CI 1.05–1.39) and 2+ (HR = 1.80, 95% CI 1.56–2.08) comorbidities had inferior OS compared to those with no comorbidities after adjustment for age and sex (c‐statistic = 0.654), and performance strengthened after adjustment for the International Prognostic Index (c‐statistic = 0.672). LCI predicted OS most strongly in marginal zone (c‐statistics = 0.748) and weakest in T‐cell (c‐statistic = 0.579) lymphoma. The cumulative incidence of death due to lymphoma, lymphoma treatment, and other causes all increased with increasing comorbidities, with the greatest increase observed for death due to other causes. The LCI performs comparable to other published comorbidity indices, supporting its use in the LEO cohort to better model real‐world outcomes and more generally providing an approach to implementing comorbidity indices in cancer survivorship cohorts.

560 Background: Early diagnosis remains a critical challenge in oncology, particularly for the five deadliest cancers: lung, breast, prostate, colorectal, and pancreatic. These cancers often present with nonspecific symptoms, leading to repeated healthcare visits without a timely suspicion of malignancy. Artificial intelligence (AI) offers an opportunity to augment clinical decision-making and support earlier identification of cancer. C the Signs , an AI cancer prediction platform, has been widely adopted across the UK with substantial evidence supporting its ability to identify cancer at earlier stages. Methods: This retrospective study assessed the performance of C the Signs in intercepting cancer earlier than physician diagnosis. De-identified electronic medical records were accessed via the Mayo Data Platform, spanning a 20-year period from January 1, 2002 to December 31, 2021. The study cohort included 55,375 patients diagnosed with lung, breast, prostate, colorectal or pancreatic cancer. The primary outcome was the proportion of cases identified earlier by the AI model, measured in annual increments up to five years prior to physician diagnosis. Additional analyses were conducted across the five target cancer types. Results: The C the Signs platform identified 14,528 patients (26.2%) with cancer earlier than the original physician diagnosis. Early identification occurred across multiple time points: 8.9% in year 1, 4.7% in year 2, 4.4% in year 3, 4.3% in year 4, and 3.9% in year 5. Across cancer types, the highest early interception rate was observed in prostate cancer (31.7%), while breast cancer showed the lowest impact (21.0%). Conclusions: Use of the C the Signs AI cancer prediction platform demonstrated meaningful improvements in early cancer interception, particularly for lung and prostate cancers. These findings highlight the potential of AI tools to enhance early diagnosis and support timely clinical interventions, offering a scalable solution to improve cancer outcomes across populations.

Purpose: Surgical video review can be used in urologic training, yet significant barriers to the implementation of video review programs exist, and formal assessment of usage and utility for trainees is limited. Here, we evaluate a novel video review platform to describe patterns of use and determine perceived utility. Materials and Methods: We analyzed learning points entered by trainees during video review of radical prostatectomy cases using our surgical intelligence–enabled Film Room platform between September 2023 and July 2024. Learning point content was categorized according to surgical coaching domains as technical, cognitive, nontechnical, or descriptive. Entries were compared by surgical step and level of training. Anonymous surveys were distributed to trainees to determine perceived utility and reveal patterns of video review. Results: Thirteen trainees entered 480 unique learning points across all radical prostatectomy steps and spanning surgical coaching domains during the study period. Learning points varied by training level, with junior trainees entering points more often than senior trainees for Retzius-space dissection ( N = 73 vs 17, p < 0.01) and seminal vesicle and posterior dissection ( N = 58 vs 27, p < 0.01). Trainees used video review in preparation for both upcoming cases and performance analysis. Ninety-four percent of survey respondents reported they either agreed or strongly agreed that video review helped them develop surgical skills. Conclusions: We found usage across training levels and high perceived utility of our Film Room platform for video review of robotic prostatectomy. Implementation of video review platforms holds promise to augment existing urologic training and should be explored further.

Abstract Background Lymphocyte function and immune competence can be measured by proliferative response to stimuli and is useful in several clinical contexts including primary (or genetic) and secondary immunodeficiencies (e.g., immunosuppression following transplantation). Proliferation assays have traditionally been prepared manually due to the difficulty in maintaining the sterile environment required to prevent bacterial and fungal impact on cell growth. On most automated liquid handlers, the sample and reagents are placed inside a cabinet whose inner surfaces include rails, pullies, pumps, and circuitry that face the sample and are not amenable to sterilization. The Andrew+ (Waters, MA) is a small surface cleanable liquid handler with all machinery enclosed. We demonstrate here the use of an Andrew+ placed in a biological safety cabinet (BSC) to perform sterile assay setup. Methods Peripheral blood monocytes (PBMCs) from five individuals were manually generated via buffy coat isolation, then brought to standardized concentration. An Andrew+ was placed in a 4’ BSC and all surfaces disinfected with Oxivir Tb (Diversey, SC). The Andrew+ prepared three serial dilutions of two stimulant reagents (phytohemagglutinin (PHA) and pokeweed (PWM)), then dispensed stimulant and control reagents horizontally and PBMCs vertically to a 48 well plate. This process was duplicated manually from the same specimens to create a reference plate. The plates were incubated at 37°C and 5% CO2 for three days, then pulsed with EdU (Thermo Fisher, MA) and incubated for one additional day. Cells were harvested and counted via flow cytometry. Overall time and hands-on time were measured. Results A total of five samples were tested inside a using both manual and automation setup under eight conditions including with isotype control, media without stimulant, three concentrations of PHA, and three concentrations of PWM. The percent proliferation for various cell types as induced by each stimulant was calculated from the difference of the highest stimulant signal from the background (media-only) signal. Comparing the automated and manual method results showed a slope of 1.0217 and R2 of 0.9966. For a simulated run of 6 samples, technologist time for automated steps was under 8 minutes with a total time of 56 minutes. When these steps were performed manually, the time was 30 minutes. Automation increased total time by 26 minutes but saved 22 minutes of technologist hands-on time. Conclusion The Andrew+ was able to perform sterile setup of a cell culture assay. While slower overall than manual processing, technologist time was reduced. Ergonomic, inter-tech variability, and sample transcription error issues were subjectively observed to be less likely. The Andrew+ can work with up to four “dominos” (reagent or tip blocks) in width and up to three dominos in depth. Non-custom, standard depth BSCs from a variety of manufacturers (Labconco, Nuaire, ThermoFisher) have room for one domino in depth so, except for timings performed in this evaluation, all steps were broken down to be performed with a max of four dominos. Efficient sterile use of the system would require an extended depth BSC.