Accurate Prediction of Three-Dimensional Humanoid Avatars for Anthropometric Modeling.

Objective To evaluate the hypothesis that anthropometric dimensions derived from a person's manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area measurements acquired with a ground-truth 3D optical imaging method. Avatars predicted using this approach, if accurate with respect to anthropometric dimensions, can serve multiple purposes including patient metabolic disease risk stratification in clinical settings. Methods Manifold regression 3D avatar prediction equations were developed on a sample of 570 adults who completed 3D optical scans, dual-energy X-ray absorptiometry (DXA), and bioimpedance analysis (BIA) evaluations. A new prospective sample of 84 adults had ground-truth measurements of 6 body circumferences, 7 volumes, and 7 surface areas with a 20-camera 3D reference scanner. 3D humanoid avatars were generated on these participants with manifold regression including age, weight, height, DXA %fat, and BIA impedances as potential predictor variables. Ground-truth and predicted avatar anthropometric dimensions were quantified with the same software. Results Following exploratory studies, one manifold prediction model was moved forward for presentation that included age, weight, height, and %fat as covariates. Predicted and ground-truth avatars had similar visual appearances; correlations between predicted and ground-truth anthropometric estimates were all high (R 2 s, 0.75-0.99; all p < 0.001) with non-significant mean differences except for arm circumferences (%D ~ 5%; p < 0.05). Concordance correlation coefficients ranged from 0.80-0.99 and small but significant bias (p < 0.05 - 0.01) was present with Bland-Altman plots in 13 of 20 total anthropometric measurements. The mean waist to hip circumference ratio predicted by manifold regression was non-significantly different from ground-truth scanner measurements. Conclusions 3D avatars predicted from demographic, physical, and other accessible characteristics can produce body representations with accurate anthropometric dimensions without a 3D scanner. Combining manifold regression algorithms into established body composition methods such as DXA, BIA, and other accessible methods provides new research and clinical opportunities.

Evaluation of body shape as a human body composition assessment in isolated conditions and remote environments.

Individuals in isolated and extreme environments can experience debilitating side-effects including significant decreases in fat-free mass (FFM) from disuse and inadequate nutrition. The objective of this study was to determine the strengths and weaknesses of three-dimensional optical (3DO) imaging for monitoring body composition in either simulated or actual remote environments. Thirty healthy adults (ASTRO, male = 15) and twenty-two Antarctic Expeditioners (ABCS, male = 18) were assessed for body composition. ASTRO participants completed duplicate 3DO scans while standing and inverted by gravity boots plus a single dual-energy X-ray absorptiometry (DXA) scan. The inverted scans were an analog for fluid redistribution from gravity changes. An existing body composition model was used to estimate fat mass (FM) and FFM from 3DO meshes. 3DO body composition estimates were compared to DXA with linear regression and reported with the coefficient of determination (R2) and root mean square error (RMSE). ABCS participants received only duplicate 3DO scans on a monthly basis. Standing ASTRO meshes achieved an R2 of 0.76 and 0.97 with an RMSE of 2.62 and 2.04 kg for FM and FFM, while inverted meshes achieved an R2 of 0.52 and 0.93 with an RMSE of 2.84 and 3.23 kg for FM and FFM, respectively, compared to DXA. For the ABCS arm, mean weight, FM, and FFM changes were -0.47, 0.06, and -0.54 kg, respectively. Simulated fluid redistribution decreased the accuracy of estimated body composition values from 3DO scans. However, FFM stayed robust. 3DO imaging showed good absolute accuracy for body composition assessment in isolated and remote environments.

Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models.

BACKGROUND AND AIMS: Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer. METHODS: Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass. RESULTS: Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA. CONCLUSIONS: Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

Evaluation of visceral adipose tissue thresholds for elevated metabolic syndrome risk across diverse populations: A systematic review.

Beyond obesity, excess levels of visceral adipose tissue (VAT) significantly contribute to the risk of developing metabolic syndrome (MetS), although thresholds for increased risk vary based on population, regions of interest, and units of measure employed. We sought to determine whether a common threshold exists that is indicative of heightened MetS risk across all populations, accounting for sex, age, BMI, and race/ethnicity. A systematic literature review was conducted in September 2023, presenting threshold values for elevated MetS risk. Standardization equations harmonized the results from DXA, CT, and MRI systems to facilitate a comparison of threshold variations across studies. A total of 52 papers were identified. No single threshold could accurately indicate elevated risk for both males and females across varying BMI, race/ethnicity, and age groups. Thresholds fluctuated from 70 to 165.9 cm2, with reported values consistently lower in females. Generally, premenopausal females and younger adults manifested elevated risks at lower VAT compared to their older counterparts. Notably, Asian populations exhibited elevated risks at lower VAT areas (70-136 cm2) compared to Caucasian populations (85.6-165.9 cm2). All considered studies reported associations of VAT without accommodating covariates. No single VAT area threshold for elevated MetS risk was discernible post-harmonization by technology, units of measure, and region of interest. This review summarizes available evidence for MetS risk assessment in clinical practice. Further exploration of demographic-specific interactions between VAT area and other risk factors is imperative to comprehensively delineate overarching MetS risk.

Predictors of visceral and subcutaneous adipose tissue and muscle density: The ShapeUp! Kids study.

BACKGROUND AND AIMS: Body fat distribution, i.e., visceral (VAT), subcutaneous adipose tissue (SAT) and intramuscular fat, is important for disease prevention, but sex and ethnic differences are not well understood. Our aim was to identify anthropometric, demographic, and lifestyle predictors for these outcomes. METHODS AND RESULTS: The cross-sectional ShapeUp!Kids study was conducted among five ethnic groups aged 5-18 years. All participants completed questionnaires, anthropometric measurements, and abdominal MRI scans. VAT and SAT areas at four lumbar levels and muscle density were assessed manually. General linear models were applied to estimate coefficients of determination (R2) and to compare the fit of VAT and SAT prediction models. After exclusions, the study population had 133 male and 170 female participants. Girls had higher BMI-z scores, waist circumference (WC), and SAT than boys but lower VAT/SAT and muscle density. SAT, VAT, and VAT/SAT but not muscle density differed significantly by ethnicity. R2 values were higher for SAT than VAT across groups and improved slightly after adding WC. For SAT, R2 increased from 0.85 to 0.88 (girls) and 0.62 to 0.71 (boys) when WC was added while VAT models improved from 0.62 to 0.65 (girls) and 0.57 to 0.62 (boys). VAT values were significantly lower among Blacks than Whites with little difference for the other groups. CONCLUSION: This analysis in a multiethnic population identified BMI-z scores and WC as the major predictors of MRI-derived SAT and VAT and highlights the important ethnic differences that need to be considered in diverse populations.

Global patterns and drivers of plant-soil microbe interactions.

Plant-soil feedback (PSF) is an important mechanism determining plant community dynamics and structure. Understanding the geographic patterns and drivers of PSF is essential for understanding the mechanisms underlying geographic plant diversity patterns. We compiled a large dataset containing 5969 observations of PSF from 202 studies to demonstrate the global patterns and drivers of PSF for woody and non-woody species. Overall, PSF was negative on average and was influenced by plant attributes and environmental settings. Woody species PSFs did not vary with latitude, but non-woody PSFs were more negative at higher latitudes. PSF was consistently more positive with increasing aridity for both woody and non-woody species, likely due to increased mutualistic microbes relative to soil-borne pathogens. These findings were consistent between field and greenhouse experiments, suggesting that PSF variation can be driven by soil legacies from climates. Our findings call for caution to use PSF as an explanation of the latitudinal diversity gradient and highlight that aridity can influence plant community dynamics and structure across broad scales through mediating plant-soil microbe interactions.

Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study.

BACKGROUND: Athletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels. METHODS: The Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) imaging, and bioelectrical impedance (BIA). Each of these methods generated 2- or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/isometric dynamometry. RESULTS: In total, 70 (35 female) athletes with a mean age of 21.8 ± 4.2 years were recruited. Percent hydration (Body Water6CM/FFM6CM) had substantial variation in both males (63-73 %) and females (58-78 %). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin's Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC <0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0 %). Increasing quartiles (significant p < 0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status. CONCLUSION: The criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations. SUMMARY BOX: This study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual-energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.

Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis.

BACKGROUND & AIMS: The multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA). METHODS: Samples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults. RESULTS: 67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95 % limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95 % LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time. CONCLUSIONS: Body composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.

Technical development and feasibility of a reusable vest to integrate cardiovascular magnetic resonance with electrocardiographic imaging.

BACKGROUND: Electrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We therefore developed the CMR-ECGI vest and carried out this technical development study to assess its feasibility and repeatability in vivo. METHODS: CMR was prospectively performed at 3T on participants after collecting surface potentials using the locally designed and fabricated 256-lead ECGI vest. Epicardial maps were reconstructed to generate local EP parameters such as activation time (AT), repolarization time (RT) and activation recovery intervals (ARI). 20 intra- and inter-observer and 8 scan re-scan repeatability tests. RESULTS: 77 participants were recruited: 27 young healthy volunteers (HV, 38.9 ± 8.5 years, 35% male) and 50 older persons (77.0 ± 0.1 years, 52% male). CMR-ECGI was achieved in all participants using the same reusable, washable vest without complications. Intra- and inter-observer variability was low (correlation coefficients [rs] across unipolar electrograms = 0.99 and 0.98 respectively) and scan re-scan repeatability was high (rs between 0.81 and 0.93). Compared to young HV, older persons had significantly longer RT (296.8 vs 289.3 ms, p = 0.002), ARI (249.8 vs 235.1 ms, p = 0.002) and local gradients of AT, RT and ARI (0.40 vs 0.34 ms/mm, p = 0,01; 0.92 vs 0.77 ms/mm, p = 0.03; and 1.12 vs 0.92 ms/mm, p = 0.01 respectively). CONCLUSION: Our high-throughput CMR-ECGI solution is feasible and shows good reproducibility in younger and older participants. This new technology is now scalable for high throughput research to provide novel insights into arrhythmogenesis and potentially pave the way for more personalised risk stratification. CLINICAL TRIAL REGISTRATION: Title: Multimorbidity Life-Course Approach to Myocardial Health-A Cardiac Sub-Study of the MRC National Survey of Health and Development (NSHD) (MyoFit46). National Clinical Trials (NCT) number: NCT05455125. URL: https://clinicaltrials.gov/ct2/show/NCT05455125?term=MyoFit&draw=2&rank=1.

Visceral adipose tissue reference data computed for GE HealthCare DXA from the National Health and Nutrition Examination Survey data set.

OBJECTIVE: The National Health and Nutrition Examination Survey (NHANES) characterizes body composition representative of the US population using dual-energy x-ray absorptiometry (DXA) scans. These population-level trends of abdominal subcutaneous and visceral adipose tissue (SAT and VAT) are useful for identifying measures associated with increased disease risk. Recently, VAT and SAT data collected by Hologic DXA in NHANES were published online; however, there are known differences in the absolute calibration of DXA systems by make. The purpose of this study was to create reference tables suitable for calculating z scores and percentile values for GE HealthCare (GEHC) DXA systems. METHODS: DXA scans were acquired on participants aged 8 to 59 years using Hologic systems. DXA measures were converted to GEHC and described using the least median squares curve fitting method in pediatrics (aged <20 years) and adults (aged 20-59 years). RESULTS: A total of 11,972 adults and 7298 pediatrics were included for this analysis. Adult and pediatric curves were generated by sex and by ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian, Other) and were derived as a function of age. CONCLUSIONS: These results show the ability to generate VAT and SAT reference data for GEHC systems using Hologic DXA data representative of the US youth and adult population.

Standardization of dual-energy x-ray visceral adipose tissue measures for comparison across clinical imaging systems.

OBJECTIVE: Excess visceral adipose tissue (VAT) is a major risk factor for metabolic syndrome (MetS) and clinical guidelines have been proposed to define VAT levels associated with increased risk. The aim was to standardize VAT measures between two dual-energy x-ray absorptiometry (DXA) manufacturers who provide different VAT estimates to support standardization of measures across imaging modalities. METHODS: Scans from 114 individuals (ages 18-81 years) on GE HealthCare (GEHC) and Hologic DXA systems were compared via Deming regression to standardize VAT between the two systems, validated in a separate sample (n = 15), with κ statistics to assess agreement of VAT measurements for classifying patients into risk categories. RESULTS: The GEHC and Hologic VAT measures were highly correlated and validated in the separate data set (r2 = 0.97). VAT area measures substantially agreed for metabolic risk classification (weighted κ = 0.76) with no significant differences in the population mean values. CONCLUSIONS: VAT measures can be estimated from GEHC and Hologic scans that classify individuals in a substantially similar way into metabolic risk categories, and systematic bias between the measures can be removed using simple regression equations. These findings allow for DXA VAT measures to be used in complement to other imaging modalities, regardless of whether scans used GEHC or Hologic systems.

Assessment of Microvascular Disease in Heart and Brain by MRI: Application in Heart Failure with Preserved Ejection Fraction and Cerebral Small Vessel Disease.

The objective of this review is to investigate the commonalities of microvascular (small vessel) disease in heart failure with preserved ejection fraction (HFpEF) and cerebral small vessel disease (CSVD). Furthermore, the review aims to evaluate the current magnetic resonance imaging (MRI) diagnostic techniques for both conditions. By comparing the two conditions, this review seeks to identify potential opportunities to improve the understanding of both HFpEF and CSVD.

Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans.

BACKGROUND: New recommendations for the assessment of malnutrition and sarcopenia include body composition, specifically reduced muscle mass. Three-dimensional optical imaging (3DO) is a validated, accessible, and affordable alternative to dual X-ray absorptiometry (DXA). OBJECTIVE: Identify strengths and weaknesses of 3DO for identification of malnutrition in participants with low body mass index (BMI) and eating disorders. DESIGN: Participants were enrolled in the cross-sectional Shape Up! Adults and Kids studies of body shape, metabolic risk, and functional assessment and had BMI of <20 kg/m2 in adults or <85% of median BMI (mBMI) in children and adolescents. A subset was referred for eating disorders evaluation. Anthropometrics, scans, strength testing, and questionnaires were completed in clinical research centers. Lin's Concordance Correlation Coefficient (CCC) assessed agreement between 3DO and DXA; multivariate linear regression analysis examined associations between weight history and body composition. RESULTS: Among 95 participants, mean ± SD BMI was 18.3 ± 1.4 kg/m2 in adult women (N = 56), 19.0 ± 0.6 in men (N = 14), and 84.2% ± 4.1% mBMI in children (N = 25). Concordance was excellent for fat-free mass (FFM, CCC = 0.97) and strong for appendicular lean mass (ALM, CCC = 0.86) and fat mass (FM, CCC = 0.87). By DXA, 80% of adults met the low FFM index criterion for malnutrition, and 44% met low ALM for sarcopenia; 52% of children and adolescents were <-2 z-score for FM. 3DO identified 95% of these cases. In the subset, greater weight loss predicted lower FFM, FM, and ALM by both methods; a greater percentage of weight regained predicted a higher percentage of body fat. CONCLUSIONS: 3DO can accurately estimate body composition in participants with low BMI and identify criteria for malnutrition and sarcopenia. In a subset, 3DO detected changes in body composition expected with weight loss and regain secondary to eating disorders. These findings support the utility of 3DO for body composition assessment in patients with low BMI, including those with eating disorders. This trial was registered at clinicaltrials.gov as NCT03637855.

Changes in lung cancer staging and emergency presentations during the first year of the COVID-19 pandemic.

Aim: This study retrospectively analyses the impact of the 1st year of the COVID-19 pandemic on route of presentation and staging in lung cancer compared to the 2 years before and after implementation of the Leicester Optimal Lung Cancer Pathway (LOLCP) in Leicester, United Kingdom. Method: Electronic databases and hospital records were used to identify all patients diagnosed with lung cancer in 2018 (pre-LOLCP), 2019 (post-LOLCP), and March 2020-2021 (post-COVID-19 lockdown). Information regarding patient characteristics, performance status, stage, and route of diagnosis was documented and analysed. Emergency presentation was defined as diagnosis of new lung cancer being made after unscheduled attendance to urgent or emergency care facility. Results: Following implementation of the LOLCP pathway, there was a significant decrease in emergency presentations from 26.8 to 19.6% (p = 0.002) with a stage shift from 33.9% early stage disease to 40.3%. These improved outcomes were annulled during the COVID-19 pandemic, with emergency presentations increasing to 38.9% (p < 0.001) and a reduction in early-stage lung cancer diagnoses to 31.5%. There was a 61% decline in 2 week wait referrals but no significant decline in the LOLCP direct-to-CT referrals. Conclusion: We have demonstrated a significant increase in late-stage lung cancer diagnoses and emergency presentations during the first year of the COVID-19 pandemic. The causes for these changes are likely to be multifactorial. The long-term effect on lung cancer mortality remains to be seen and is an important focus of future study.

Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity.

BACKGROUND: The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown. OBJECTIVES: This study aimed to evaluate 3DO's accuracy and precision by subgroups of age, body mass index, and ethnicity. METHODS: A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test-retest precision. Student's t tests were performed between 3DO and DXA by subgroup to determine significant differences. RESULTS: Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038). CONCLUSIONS: A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).

Clinical and Laboratory Predictors of Dehydration Severity in Children With Diabetic Ketoacidosis.

STUDY OBJECTIVE: Our primary objective was to characterize the degree of dehydration in children with diabetic ketoacidosis (DKA) and identify physical examination and biochemical factors associated with dehydration severity. Secondary objectives included describing relationships between dehydration severity and other clinical outcomes. METHODS: In this cohort study, we analyzed data from 753 children with 811 episodes of DKA in the Pediatric Emergency Care Applied Research Network Fluid Therapies Under Investigation Study, a randomized clinical trial of fluid resuscitation protocols for children with DKA. We used multivariable regression analyses to identify physical examination and biochemical factors associated with dehydration severity, and we described associations between dehydration severity and DKA outcomes. RESULTS: Mean dehydration was 5.7% (SD 3.6%). Mild (0 to <5%), moderate (5 to <10%), and severe (≥10%) dehydration were observed in 47% (N=379), 42% (N=343), and 11% (N=89) of episodes, respectively. In multivariable analyses, more severe dehydration was associated with new onset of diabetes, higher blood urea nitrogen, lower pH, higher anion gap, and diastolic hypertension. However, there was substantial overlap in these variables between dehydration groups. The mean length of hospital stay was longer for patients with moderate and severe dehydration, both in new onset and established diabetes. CONCLUSION: Most children with DKA have mild-to-moderate dehydration. Although biochemical measures were more closely associated with the severity of dehydration than clinical assessments, neither were sufficiently predictive to inform rehydration practice.

Heart failure and excess mortality after aortic valve replacement in aortic stenosis.

INTRODUCTION: In aortic stenosis (AS), the heart transitions from adaptive compensation to an AS cardiomyopathy and eventually leads to decompensation with heart failure. Better understanding of the underpinning pathophysiological mechanisms is required in order to inform strategies to prevent decompensation. AREAS COVERED: In this review, we therefore aim to appraise the current pathophysiological understanding of adaptive and maladaptive processes in AS, appraise potential avenues of adjunctive therapy before or after AVR and highlight areas of further research in the management of heart failure post AVR. EXPERT OPINION: Tailored strategies for the timing of intervention accounting for individual patient's response to the afterload insult are underway, and promise to guide better management in the future. Further clinical trials of adjunctive pharmacological and device therapy to either cardioprotect prior to intervention or promote reverse remodeling and recovery after intervention are needed to mitigate the risk of heart failure and excess mortality.