Understanding Macrophage Complexity in Metabolic Dysfunction-Associated Steatotic Liver Disease: Transitioning from the M1/M2 Paradigm to Spatial Dynamics.

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses metabolic dysfunction-associated fatty liver (MASL) and metabolic dysfunction-associated steatohepatitis (MASH), with MASH posing a risk of progression to cirrhosis and hepatocellular carcinoma (HCC). The global prevalence of MASLD is estimated at approximately a quarter of the population, with significant healthcare costs and implications for liver transplantation. The pathogenesis of MASLD involves intrahepatic liver cells, extrahepatic components, and immunological aspects, particularly the involvement of macrophages. Hepatic macrophages are a crucial cellular component of the liver and play important roles in liver function, contributing significantly to tissue homeostasis and swift responses during pathophysiological conditions. Recent advancements in technology have revealed the remarkable heterogeneity and plasticity of hepatic macrophage populations and their activation states in MASLD, challenging traditional classification methods like the M1/M2 paradigm and highlighting the coexistence of harmful and beneficial macrophage phenotypes that are dynamically regulated during MASLD progression. This complexity underscores the importance of considering macrophage heterogeneity in therapeutic targeting strategies, including their distinct ontogeny and functional phenotypes. This review provides an overview of macrophage involvement in MASLD progression, combining traditional paradigms with recent insights from single-cell analysis and spatial dynamics. It also addresses unresolved questions and challenges in this area.

Smad1/5 is acetylated in the dorsal aortae of the mouse embryo before the onset of blood flow, driving early arterial gene expression.

AIMS: During embryonic development, arteriovenous (AV) differentiation ensures proper blood vessel formation and maturation. Defects in arterial or venous identity cause inappropriate fusion of vessels, resulting in atypical shunts, so-called arteriovenous malformations (AVM). Currently, the mechanism behind AVM formation remains unclear and treatment options are fairly limited. Mammalian AV differentiation is initiated before the onset of blood flow in the embryo; however, this pre-flow mechanism is poorly understood. Here, we aimed to unravel the role of Smad1/5 signalling in pre-flow arterial identity, and in the process uncovered an unexpected control mechanism of Smad1/5 signalling. METHODS AND RESULTS: We establish that despite Notch1 being expressed in the pre-flow mouse embryo, it is not activated, nor is it necessary for the expression of the earliest arterial genes in the dorsal aortae (i.e., Hey1 and Gja4). Furthermore, interrupting blood flow by using the Ncx1 KO model completely prevents the activation of Notch1 signalling, suggesting a strong role of shear stress in maintaining arterial identity. We demonstrate that early expression of Hey1 and Gja4 requires SMAD1/5 signalling. Using embryo cultures, we show that Smad1/5 signalling is activated through the Alk1/Alk5/TGFßR2 receptor complex, with TGFß1 as a necessary ligand. Furthermore, our findings demonstrate that early arterial gene expression requires the acetylation of Smad1/5 proteins, rendering them more sensitive to TGFß1 stimulation. Blocking acetyl-CoA production prevents pre-flow arterial expression of Hey1 and Gja4, while stabilizing acetylation rescues their expression. CONCLUSIONS: Our findings highlight the importance of the acetyl-CoA production in the cell and provide a novel control mechanism of Smad1/5 signalling involving protein acetylation. As disturbed canonical Smad1/5 signalling is involved in several vascular conditions, our results offer new insights in treatment options for circumventing canonical Smad1/5 signalling.

Diagnostic utility of DNA methylation analysis in genetically unsolved pediatric epilepsies and CHD2 episignature refinement.

Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases.

Addressing dermatologic concerns and teledermatology in undomiciled and sheltered populations.

Homelessness in the United States is a significant public health issue, with dermatologic disease being the most prevalent health concern among the undomiciled and sheltered populations. Despite a growing need for dermatologic care, the supply of dermatologists remains insufficient, contributing to disparities in healthcare access for this vulnerable group. This review aims to detail the spectrum of dermatologic conditions experienced by homeless individuals, identify barriers to adequate care, and explore teledermatology as a potential solution to bridge these gaps. A comprehensive literature review was conducted, analyzing studies and reports on dermatologic issues prevalent among the homeless population and the efficacy of teledermatology in addressing these concerns. Homeless individuals face a wide range of dermatologic problems, from common conditions like acne and eczema to severe issues such as cellulitis, leg ulcers, and skin cancer. Drug abuse, domestic and sexual abuse, and parasitic infestations further complicate the dermatologic health of this population. Teledermatology has emerged as a promising tool to enhance access to dermatologic care, showing significant improvements in clinical outcomes and accessibility, especially in underserved urban settings. However, challenges remain, such as the digital divide affecting the elderly and low-income populations, which could potentially exacerbate disparities. Addressing the dermatologic needs of the homeless population requires a multifaceted approach. Teledermatology offers a viable solution to improve care access and efficiency, but additional efforts are necessary to ensure inclusivity and avoid further marginalization. Volunteer-driven multidisciplinary clinics also play a crucial role in providing care, though they face challenges in continuity and resource availability. Future strategies should focus on integrating teledermatology with other supportive services to create a comprehensive care model for this underserved population.

Risk of incident gout following exposure to recombinant zoster vaccine in US adults aged ≥50 years.

OBJECTIVE: To assess whether recombinant zoster vaccine (RZV) is associated with an increased risk of new-onset gout among US adults aged ≥50 years. METHODS: We conducted a real-world, retrospective safety study with a self-controlled risk interval (SCRI) design using administrative claims data. We included health plan members aged ≥50 years with RZV exposure, followed by incident gout within 60 days. Days 1-30 following RZV exposure were considered the risk window (RW), and days 31-60 were considered the control window (CW). We estimated the risk ratio (RR) of gout in the RW versus CW, using a conditional Poisson model. The primary analysis estimated the risk of incident gout following any RZV dose. Sensitivity analyses evaluated dose 1- and dose 2-specific risks, risk among patients compliant with recommended dose spacing of 60-183 days, adjustment for seasonality, and restriction to the pre-COVID-19 era (before December 1, 2019). RESULTS: A total of 461,323 individuals received ≥1 RZV dose; we included 302 individuals (mean age 72.5 years; 66 % male) with evidence of new-onset gout within 60 days in SCRI analyses. A total of 153 (50.7 %) individuals had gout events in the RW and 149 (49.3 %) in the CW (RR 1.03; 95 % confidence interval 0.81, 1.29). All sensitivity analyses had consistent results, with no association of RZV with incident gout. CONCLUSION: In a population of US adults aged ≥50 years, there was no statistically significant increase in the risk of gout during the 30 days immediately after RZV exposure, compared with a subsequent 30-day CW.

Web Site Accessibility Among Doctor of Physical Therapy Programs in the United States.

INTRODUCTION: Given the impetus to improve accessibility for diverse learners seeking physical therapist education, it is critical that all entry points to access information have minimal barriers. This study identified Web site accessibility barriers among Doctor of Physical Therapy (DPT) programs in the United States. REVIEW OF LITERATURE: Web site accessibility has been evaluated among many institutions of higher education, but none focused on DPT education. Individuals with disabilities may be adversely affected by Web site accessibility barriers. SUBJECTS: This cross-sectional study included 262 DPT programs in the United States. Doctor of Physical Therapy program characteristics collected were geographic region, institutional control type (public/private), medical school affiliation, accreditation status, total institutional enrollment, and DPT class size. METHODS: The Web Accessibility Evaluation (WAVE) Tool assessed data related to accessibility barriers among DPT program homepage Uniform Resource Locators. Three primary outcomes from the WAVE Tool included WAVE Total Errors, Error Density, and Total Alerts. RESULTS: Web site homepage accessibility barriers varied among programs for WAVE Total Errors (range 0-150), Error Density (range 0-14.6%), and Total Alerts (range 1-331). Median Total Errors were greater among private (9.0) versus public (5.0) institution Web sites (P < .001). Median Total Errors were greater among those institutions not affiliated with a medical school (9.0) compared with those that had an affiliated medical school (7.0) (P = .04). No differences in accessibility barriers were identified according to geographic region or accreditation status (P > .05). Median Total Errors were significantly different between institutional enrollment quartiles (H[3] = 17.9, P < .001), with no differences noted between DPT class size quartiles for any outcome (P > .05). Generally, weak-fair inverse correlations were observed between student enrollment for the institution and Web site accessibility barrier outcomes. DISCUSSION AND CONCLUSION: Homepage accessibility barriers varied greatly among DPT programs in the United States. Factors, including being a private institution, no medical school affiliation, and lower institutional enrollment, were related to increased accessibility barriers.

Amphibian mast cells serve as barriers to chytrid fungus infections.

Global amphibian declines are compounded by deadly disease outbreaks caused by the chytrid fungus, Batrachochytrium dendrobatidis (Bd). Much has been learned about the roles of amphibian skin-produced antimicrobial components and microbiomes in controlling Bd, yet almost nothing is known about the roles of skin-resident immune cells in anti-Bd defenses. Mammalian mast cells reside within and serve as key immune sentinels in barrier tissues like skin. Accordingly, we investigated the roles of Xenopus laevis frog mast cells during Bd infections. Our findings indicate that enrichment of X. laevis skin mast cells confers anti-Bd protection and ameliorates the inflammation-associated skin damage caused by Bd infection. This includes a significant reduction in infiltration of Bd-infected skin by neutrophils, promoting mucin content within cutaneous mucus glands, and preventing Bd-mediated changes to skin microbiomes. Mammalian mast cells are known for their production of the pleiotropic interleukin-4 (IL4) cytokine and our findings suggest that the X. laevis IL4 plays a key role in manifesting the effects seen following cutaneous mast cell enrichment. Together, this work underscores the importance of amphibian skin-resident immune cells in anti-Bd defenses and illuminates a novel avenue for investigating amphibian host-chytrid pathogen interactions.

Pathogenic variants in KMT2C result in a neurodevelopmental disorder distinct from Kleefstra and Kabuki syndromes.

Trithorax-related H3K4 methyltransferases, KMT2C and KMT2D, are critical epigenetic modifiers. Haploinsufficiency of KMT2C was only recently recognized as a cause of neurodevelopmental disorder (NDD), so the clinical and molecular spectrums of the KMT2C-related NDD (now designated as Kleefstra syndrome 2) are largely unknown. We ascertained 98 individuals with rare KMT2C variants, including 75 with protein-truncating variants (PTVs). Notably, ∼15% of KMT2C PTVs were inherited. Although the most highly expressed KMT2C transcript consists of only the last four exons, pathogenic PTVs were found in almost all the exons of this large gene. KMT2C variant interpretation can be challenging due to segmental duplications and clonal hematopoesis-induced artifacts. Using samples from 27 affected individuals, divided into discovery and validation cohorts, we generated a moderate strength disorder-specific KMT2C DNA methylation (DNAm) signature and demonstrate its utility in classifying non-truncating variants. Based on 81 individuals with pathogenic/likely pathogenic variants, we demonstrate that the KMT2C-related NDD is characterized by developmental delay, intellectual disability, behavioral and psychiatric problems, hypotonia, seizures, short stature, and other comorbidities. The facial module of PhenoScore, applied to photographs of 34 affected individuals, reveals that the KMT2C-related facial gestalt is significantly different from the general NDD population. Finally, using PhenoScore and DNAm signatures, we demonstrate that the KMT2C-related NDD is clinically and epigenetically distinct from Kleefstra and Kabuki syndromes. Overall, we define the clinical features, molecular spectrum, and DNAm signature of the KMT2C-related NDD and demonstrate they are distinct from Kleefstra and Kabuki syndromes highlighting the need to rename this condition.

Multivariate signal-to-noise ratio as a metric for characterizing spectral computed tomography.

Objective.With the introduction of spectral CT techniques into the clinic, the imaging capacities of CT were expanded to multiple energy levels. Due to a variety of factors, the acquired signal in spectral CT datasets is shared between these images. Conventional image quality metrics assume independence between images which is not preserved within spectral CT datasets, limiting their utility for characterizing energy selective images. The purpose of this work was to develop a metrology to characterize energy selective images by incorporating the shared information between images within a spectral CT dataset.Approach.The signal-to-noise ratio (SNR) was extended into a multivariate space where each image within a spectral CT dataset was treated as a separate information channel. The general definition was applied to the specific case of contrast to define a multivariate contrast-to-noise ratio (CNR). The matrix contained two types of terms: a conventional CNR term which characterized image quality within each image in the spectral CT dataset and covariance weighted CNR (Covar-CNR) which characterized the contrast in each image relative to the covariance between images. Experimental data from an investigational photon-counting CT scanner was used to demonstrate the insight of this metrology. A cylindrical water phantom containing vials of iodine and gadolinium (2, 4, and 8 mg ml-1) was imaged under conditions of variable tube current, tube voltage, and energy threshold. Two image series (threshold and bin images) containing two images each were defined based upon the contribution of photons to reconstructed images. Analysis of variance (ANOVA) was calculated between CNR terms and image acquisition variables. A multivariate regression was then fitted to experimental data.Main Results.Image type had a major difference on how Covar-CNR values were distributed. Bin images had a slightly higher mean and wider standard deviation (Covar-CNRlo: 3.38 ±17.25, Covar-CNRhi: 5.77 ± 30.64) compared to threshold images (Covar-CNRlo: 2.08 ±1.89, Covar-CNRhi: 3.45 ± 2.49) across all conditions. ANOVA found that each acquisition variable had a significant relationship with both Covar-CNR terms. The multivariate regression model suggested that material concentration had the largest impact on all CNR terms.Signficance.In this work, we described a theoretical framework to extend the SNR to a multivariate form that is able to characterize images independently and also provide insight regarding the relationship between images. Experimental data was used to demonstrate the insight that this metrology provides about image formation factors in spectral CT.

Using YOLO v7 to Detect Kidney in Magnetic Resonance Imaging.

Introduction: This study explores the use of the latest You Only Look Once (YOLO V7) object detection method to enhance kidney detection in medical imaging by training and testing a modified YOLO V7 on medical image formats. Methods: Study includes 878 patients with various subtypes of renal cell carcinoma (RCC) and 206 patients with normal kidneys. A total of 5657 MRI scans for 1084 patients were retrieved. 326 patients with 1034 tumors recruited from a retrospective maintained database, and bounding boxes were drawn around their tumors. A primary model was trained on 80% of annotated cases, with 20% saved for testing (primary test set). The best primary model was then used to identify tumors in the remaining 861 patients and bounding box coordinates were generated on their scans using the model. Ten benchmark training sets were created with generated coordinates on not-segmented patients. The final model used to predict the kidney in the primary test set. We reported the positive predictive value (PPV), sensitivity, and mean average precision (mAP). Results: The primary training set showed an average PPV of 0.94 ± 0.01, sensitivity of 0.87 ± 0.04, and mAP of 0.91 ± 0.02. The best primary model yielded a PPV of 0.97, sensitivity of 0.92, and mAP of 0.95. The final model demonstrated an average PPV of 0.95 ± 0.03, sensitivity of 0.98 ± 0.004, and mAP of 0.95 ± 0.01. Conclusion: Using a semi-supervised approach with a medical image library, we developed a high-performing model for kidney detection. Further external validation is required to assess the model's generalizability.

Triple challenges - Small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: A simulation study.

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these to imprecise incidence proportions derived from sparse control samples. We varied parameters impacting Type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of Type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.

Cell signaling and tissue remodeling in the pulmonary autograft after the Ross procedure: A computational study.

In the Ross procedure, a patient's pulmonary valve is transplanted in the aortic position. Despite advantages of this surgery, reoperation is still needed in many cases due to excessive dilatation of the pulmonary autograft. To further understand the failure mechanisms, we propose a multiscale model predicting adaptive processes in the autograft at the cell and tissue scale. The cell-scale model consists of a network model, that includes important signaling pathways and relations between relevant transcription factors and their target genes. The resulting gene activity leads to changes in the mechanical properties of the tissue, modeled as a constrained mixture of collagen, elastin and smooth muscle. The multiscale model is calibrated with findings from experiments in which seven sheep underwent the Ross procedure. The model is then validated against a different set of sheep experiments, for which a qualitative agreement between model and experiment is found. Model outcomes at the cell scale, including the activity of genes and transcription factors, also match experimentally obtained transcriptomics data.

Development of a separability index for task specific characterization of spectral computed tomography.

PURPOSE: In this work, we define a signal detection based metrology to characterize the separability of two different multi-dimensional signals in spectral CT acquisitions. METHOD: Signal response was modelled as a random process with a deterministic signal and stochastic noise component. A linear Hotelling observer was used to estimate a scalar test statistic distribution that predicts the likelihood of an intensity value belonging to a signal. Two distributions were estimated for two materials of interest and used to derive two metrics separability: a separability index (s') and the area under the curve of the test statistic distributions. Experimental and simulated data of photon-counting CT scanners were used to evaluate each metric. Experimentally, vials of iodine and gadolinium (2, 4, 8 mg/mL) were scanned at multiple tube voltages, tube currents and energy thresholds. Additionally, a simulated dataset with low tube current (10-150 mAs) and material concentrations (0.25-4 mg/mL) was generated. RESULTS: Experimental data showed that conditions favorable for low noise and expression of k-edge signal produced the highest separability. Material concentration had the greatest impact on separability. The simulated data showed that under more difficult separation conditions, difference in material concentration still had the greatest impact on separability. CONCLUSION: The results demonstrate the utility of a task specific metrology to measure the overlap in signal between different materials in spectral CT. Using experimental and simulated data, the separability index was shown to describe the relationship between image formation factors and the signal responses of material.

Predicting Intervention Use in Youth with Rare Variants in Autism-Associated Genes.

Specialized multidisciplinary supports are important for long-term outcomes for autistic youth. Although family and child factors predict service utilization in autism, little is known with respect to youth with rare, autism-associated genetic variants, who frequently have increased psychiatric, developmental, and behavioral needs. We investigate the impact of family factors on service utilization to determine whether caregiver (autistic features, education, income) and child (autistic features, sex, age, IQ, co-occurring conditions) factors predicted service type (e.g., speech, occupational, behavioral) and intensity (hours/year) among children with autism-associated variants (N = 125), some of whom also had a confirmed ASD diagnosis. Analyses revealed variability in the types of services used across a range of child demographic, behavioral, and mental health characteristics. Speech therapy was the most received service (87.2%). Importantly, behavior therapy was the least received service and post-hoc analyses revealed that use of this therapy was uniquely predicted by ASD diagnosis. However, once children received a particular service, there was largely comparable intensity of services, independent of caregiver and child factors. Findings suggest that demographic and clinical factors impact families' ability to obtain services, with less impact on the intensity of services received. The low receipt of therapies that specifically address core support needs in autism (i.e., behavior therapy) indicates more research is needed on the availability of these services for youth with autism-associated variants, particularly for those who do not meet criteria for an ASD diagnosis but do demonstrate elevated and impactful child autistic features as compared to the general population.

A Prospective Study of the Diagnostic Performance of Photon-Counting CT Compared With MRI in the Characterization of Renal Masses.

OBJECTIVES: The aim of this study was to assess the interreader reliability and per-RCC sensitivity of high-resolution photon-counting computed tomography (PCCT) in the detection and characterization of renal masses in comparison to MRI. MATERIALS AND METHODS: This prospective study included 24 adult patients (mean age, 52 ± 14 years; 14 females) who underwent PCCT (using an investigational whole-body CT scanner) and abdominal MRI within a 3-month time interval and underwent surgical resection (partial or radical nephrectomy) with histopathology (n = 70 lesions). Of the 24 patients, 17 had a germline mutation and the remainder were sporadic cases. Two radiologists (R1 and R2) assessed the PCCT and corresponding MRI studies with a 3-week washout period between reviews. Readers recorded the number of lesions in each patient and graded each targeted lesion's characteristic features, dimensions, and location. Data were analyzed using a 2-sample t test, Fisher exact test, and weighted kappa. RESULTS: In patients with von Hippel-Lindau mutation, R1 identified a similar number of lesions suspicious for neoplasm on both modalities (51 vs 50, P = 0.94), whereas R2 identified more suspicious lesions on PCCT scans as compared with MRI studies (80 vs 56, P = 0.12). R1 and R2 characterized more lesions as predominantly solid in MRIs (R1: 58/70 in MRI vs 52/70 in PCCT, P < 0.001; R2: 60/70 in MRI vs 55/70 in PCCT, P < 0.001). R1 and R2 performed similarly in detecting neoplastic lesions on PCCT and MRI studies (R1: 94% vs 90%, P = 0.5; R2: 73% vs 79%, P = 0.13). CONCLUSIONS: The interreader reliability and per-RCC sensitivity of PCCT scans acquired on an investigational whole-body PCCT were comparable to MRI scans in detecting and characterizing renal masses. CLINICAL RELEVANCE STATEMENT: PCCT scans have comparable performance to MRI studies while allowing for improved characterization of the internal composition of lesions due to material decomposition analysis. Future generations of this imaging modality may reveal additional advantages of PCCT over MRI.

Origin and flow-mediated remodeling of the murine and human extraembryonic circulation systems.

The transduction of mechanical stimuli produced by blood flow is an important regulator of vascular development. The vitelline and umbilico-placental circulations are extraembryonic vascular systems that are required for proper embryonic development in mammalian embryos. The morphogenesis of the extraembryonic vasculature and the cardiovascular system of the embryo are hemodynamically and molecularly connected. Here we provide an overview of the establishment of the murine and human vitelline and umbilico-placental vascular systems and how blood flow influences various steps in their development. A deeper comprehension of extraembryonic vessel development may aid the establishment of stem-cell based embryo models and provide novel insights to understanding pregnancy complications related to the umbilical cord and placenta.

Intravoxel incoherent motion as a surrogate marker of perfused vascular density in rat brain.

Intravoxel incoherent motion (IVIM) MRI has emerged as a valuable technique for the assessment of tissue characteristics and perfusion. However, there is limited knowledge about the relationship between IVIM-derived measures and changes at the level of the vascular network. In this study, we investigated the potential use of IVIM MRI as a noninvasive tool for measuring changes in cerebral vascular density. Variations in quantitative immunohistochemical measurements of the vascular density across different regions in the rat brain (cortex, corpus callosum, hippocampus, thalamus, and hypothalamus) were related to the pseudo-diffusion coefficient D* and the flowing blood fraction f in healthy Wistar rats. We assessed whether region-wise differences in the vascular density are reflected by variations in the IVIM measurements and found a significant positive relationship with the pseudo-diffusion coefficient (p < 0.05, ß = 0.24). The effect of cerebrovascular alterations, such as blood-brain barrier (BBB) disruption on the perfusion-related IVIM parameters, is not well understood. Therefore, we investigated the effect of BBB disruption on the IVIM measures in a rat model of metabolic and vascular comorbidities (ZSF1 obese rat) and assessed whether this affects the relationship between the cerebral vascular density and the noninvasive IVIM measurements. We observed increased vascular permeability without detecting any differences in diffusivity, suggesting that BBB leakage is present before changes in the tissue integrity. We observed no significant difference in the relationship between cerebral vascular density and the IVIM measurements in our model of comorbidities compared with healthy normotensive rats.

Using Claims Data to Predict Pre-Operative BMI Among Bariatric Surgery Patients: Development of the BMI Before Bariatric Surgery Scoring System (B3S3).

Background: Lack of body mass index (BMI) measurements limits the utility of claims data for bariatric surgery research, but pre-operative BMI may be imputed due to existence of weight-related diagnosis codes and BMI-related reimbursement requirements. We used a machine learning pipeline to create a claims-based scoring system to predict pre-operative BMI, as documented in the electronic health record (EHR), among patients undergoing a new bariatric surgery. Methods: Using the Optum Labs Data Warehouse, containing linked de-identified claims and EHR data for commercial or Medicare Advantage enrollees, we identified adults undergoing a new bariatric surgery between January 2011 and June 2018 with a BMI measurement in linked EHR data ≤30 days before the index surgery (n=3226). We constructed predictors from claims data and applied a machine learning pipeline to create a scoring system for pre-operative BMI, the B3S3. We evaluated the B3S3 and a simple linear regression model (benchmark) in test patients whose index surgery occurred concurrent (2011-2017) or prospective (2018) to the training data. Results: The machine learning pipeline yielded a final scoring system that included weight-related diagnosis codes, age, and number of days hospitalized and distinct drugs dispensed in the past 6 months. In concurrent test data, the B3S3 had excellent performance (R2 0.862, 95% confidence interval [CI] 0.815-0.898) and calibration. The benchmark algorithm had good performance (R2 0.750, 95% CI 0.686-0.799) and calibration but both aspects were inferior to the B3S3. Findings in prospective test data were similar. Conclusion: The B3S3 is an accessible tool that researchers can use with claims data to obtain granular and accurate predicted values of pre-operative BMI, which may enhance confounding control and investigation of effect modification by baseline obesity levels in bariatric surgery studies utilizing claims data.

Pre-operative BMI is an important potential confounder in comparative effectiveness studies of bariatric surgeries.Claims data lack clinical measurements, but insurance reimbursement requirements for bariatric surgery often result in pre-operative BMI being coded in claims data.We used a machine learning pipeline to create a model, the B3S3, to predict pre-operative BMI, as documented in the EHR, among bariatric surgery patients based on the presence of certain weight-related diagnosis codes and other patient characteristics derived from claims data.Researchers can easily use the B3S3 with claims data to obtain granular and accurate predicted values of pre-operative BMI among bariatric surgery patients.