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Background Radionuclide SPECT/computed tomography (CT) is standard for diagnosing transthyretin cardiac amyloidosis (ATTR-CM), but the prognostic value of quantitative metrics remains incompletely defined. We investigated their prognostic utility and additive value beyond existing staging systems. Methods Retrospective study of patients undergoing technetium-99m-pyrophosphate (PYP) SPECT/CT, including consecutive clinically referred patients (October 2023 to 2024) and trial participants with positive scans from January 2022. Myocardial PYP was quantified using standardized uptake values (SUV mean and SUV max ) and volumetric measures [percent injected dose (%ID), cardiac amyloid activity (CAA)]. Major adverse cardiovascular events (MACEs) comprised heart failure hospitalization or death. Cox and Kaplan–Meier analyses assessed associations; likelihood ratio testing and change in area under the curve (AUC) evaluated the additive prognostic value to existing staging systems. Results Among 43 patients with ATTR-CM, 16 experienced MACE over a median 518 days. AUCs ranged from 0.74 to 0.88 at 3 months and 0.56–0.62 at 12 months. All variables trended toward association with MACE: SUV mean ( P = 0.02), SUV max ( P = 0.03), %ID ( P = 0.06), and CAA ( P = 0.06). After age adjustment, cut-points for SUV max (5.8) and SUV mean (3.5) remained associated with MACE. Adding imaging variables to the National Amyloidosis Centre and Columbia staging systems did not significantly improve prognostic accuracy (Δ χ 2 : 0.40–2.48, P = 0.11–0.53). Interobserver reproducibility was high (intraclass correlation coefficients = 0.89–0.99). Conclusion Quantitative Tc-99m–PYP SPECT/CT metrics were associated with short-term outcomes in ATTR-CM, but did not improve established staging systems. Findings are hypothesis-generating and require validation in larger cohorts.

Importance Assisted ventilation during delayed cord clamping (DCC) may improve the physiologic transition of extremely preterm infants immediately after birth. Objective To determine whether assisted ventilation during 120 seconds of DCC was associated with reduced higher-level resuscitative interventions (intubation, chest compressions, or epinephrine administration) compared with DCC for 30 to 60 seconds followed by resuscitation. Design, Setting, and Participants This was a secondary analysis of the VentFirst randomized clinical trial that was conducted from September 2, 2016, through February 21, 2023, at 12 centers in the US and Canada. Infants born at 23 weeks 0 days’ to 28 weeks 6 days’ gestational age (GA) were included. Intervention Infants randomized to the intervention received either positive-pressure ventilation or continuous positive airway pressure from 30 to 120 seconds after birth, followed by umbilical cord clamping. Those randomized to control received 30 to 60 seconds of DCC followed by assisted ventilation. Main Outcomes and Measures The main outcome was the odds of higher-level resuscitative interventions in the delivery room (DR). Intention-to-treat analyses within 2 a priori cohorts (infants breathing well and not breathing well 30 seconds after birth) used the Cochran-Mantel-Haenszel method to estimate the odds ratios (ORs) of intervention vs control. Results All 570 infants enrolled in the trial were included. Infants had a median (IQR) GA of 26.6 (25.2-27.9) weeks and 273 (47.9%) were female. A total of 271 infants (47.5%) were assessed as not breathing well 30 seconds after birth (150 intervention and 121 control), and 299 (52.5%) were assessed as breathing well 30 seconds after birth (128 intervention and 171 control). In the not-breathing-well cohort, 146 infants (53.9%) were intubated in the DR, 4 received chest compressions (2 intervention and 2 control), and 1 received epinephrine (control). Intubation was less frequent in the intervention group (71 infants [47.3%] vs 75 infants [62.0%]; OR, 0.52; 95% CI, 0.30-0.89). When adjusted by GA strata at randomization, infants in the 26 to 28 weeks’ GA stratum who were in the intervention group were less likely to be intubated in the DR (18 of 79 infants [22.8%] vs 29 of 60 infants [48.3%]; OR, 0.32; 95% CI, 0.15-0.65). However, there was no difference in intubation rates for infants in the 23 to 25 weeks’ GA stratum (53 of 71 infants [74.7%] vs 46 of 61 infants [75.4%]; OR, 0.96; 95% CI, 0.44-2.12). Among infants breathing well at 30 seconds, 74 (24.7%) were intubated in the DR, and none received compressions or epinephrine. Intubation rates were similar between intervention and control in the breathing-well cohort. Conclusions and Relevance While the VentFirst trial did not find a difference in death or intraventricular hemorrhage, this secondary analysis found that assisted ventilation during DCC was associated with less intubation in the DR, primarily among infants born at 26 to 28 weeks’ gestation who were not breathing well 30 seconds after birth. Additional studies are needed before implementing assisted ventilation during DCC in clinical practice. Trial Registration ClinicalTrials.gov Identifier: NCT02742454

Abstract Aims To test whether an index based on the combination of demographics and body volumes obtained with a multisensor 3D body volume (3D-BV) scanner and biplane imaging using a mobile application (myBVI®) will reliably predict the severity and presence of metabolic syndrome (MS). Methods and results We enrolled 1280 consecutive subjects who completed study protocol measurements, including 3D-BV and myBVI®. Body volumes and demographics were screened using the least absolute shrinkage and selection operator to select features associated with an MS severity score and prevalence. We randomly selected 80% of the subjects to train the models, and performance was assessed in 20% of the remaining observations and externally validated on 133 volunteers who prospectively underwent myBVI® measurements. The mean ± SD age was 43.7 ± 12.2 years, 63.7% were women, body mass index (BMI) was 28.2 ± 6.2 kg/m2, and 30.2% had MS and an MS severity z-score of −0.2 ± 0.9. Features β coefficients equal to zero were removed from the model, and 14 were included in the final model and used to calculate the body volume index (BVI), demonstrating an area under the receiving operating curve (AUC) of 0.83 in the validation set. The myBVI® cohort had a mean age of 33 ± 10.3 years, 61% of whom were women, 10.5% MS, an average MS severity z-score of −0.8, and an AUC of 0.88. Conclusion The described BVI model was associated with an increased severity and prevalence of MS compared with BMI and waist-to-hip ratio. Validation of the BVI had excellent performance when using myBVI®. This model could serve as a powerful screening tool for identifying MS.

ImportanceProviding assisted ventilation during delayed umbilical cord clamping may improve outcomes for extremely preterm infants.ObjectiveTo determine whether assisted ventilation in extremely preterm infants (23 0/7 to 28 6/7 weeks’ gestational age [GA]) followed by cord clamping reduces intraventricular hemorrhage (IVH) or early death.Design, Setting, and ParticipantsThis phase 3, 1:1, parallel-stratified randomized clinical trial conducted at 12 perinatal centers across the US and Canada from September 2, 2016, through February 21, 2023, assessed IVH and early death outcomes of extremely preterm infants randomized to receive 120 seconds of assisted ventilation followed by cord clamping vs delayed cord clamping for 30 to 60 seconds with ventilatory assistance afterward. Two analysis cohorts, not breathing well and breathing well, were specified a priori based on assessment of breathing 30 seconds after birth.InterventionAfter birth, all infants received stimulation and suctioning if needed. From 30 to 120 seconds, infants randomized to the intervention received continuous positive airway pressure if breathing well or positive-pressure ventilation if not, with cord clamping at 120 seconds. Control infants received 30 to 60 seconds of delayed cord clamping followed by standard resuscitation.Main Outcomes and MeasuresThe primary outcome was any grade IVH on head ultrasonography or death before day 7. Interpretation by site radiologists was confirmed by independent radiologists, all masked to study group. To estimate the association between study group and outcome, data were analyzed using the stratified Cochran-Mantel-Haenszel test for relative risk (RR), with associations summarized by point estimates and 95% CIs.ResultsOf 1110 women who consented to participate, 548 were randomized and delivered infants at GA less than 29 weeks. A total of 570 eligible infants were enrolled (median [IQR] GA, 26.6 [24.9-27.7] weeks; 297 male [52.1%]). Intraventricular hemorrhage or death occurred in 34.9% (97 of 278) of infants in the intervention group and 32.5% (95 of 292) in the control group (adjusted RR, 1.02; 95% CI, 0.81-1.27). In the prespecified not-breathing-well cohort (47.5% [271 of 570]; median [IQR] GA, 26.0 [24.7-27.4] weeks; 152 male [56.1%]), IVH or death occurred in 38.7% (58 of 150) of infants in the intervention group and 43.0% (52 of 121) in the control group (RR, 0.91; 95% CI, 0.68-1.21). There was no evidence of differences in death, severe brain injury, or major morbidities between the intervention and control groups in either breathing cohort.Conclusions and RelevanceThis study did not show that providing assisted ventilation before cord clamping in extremely preterm infants reduces IVH or early death. Additional study around the feasibility, safety, and efficacy of assisted ventilation before cord clamping may provide additional insight.Trial RegistrationClinicalTrials.gov Identifier: NCT02742454

Background Extended sedentary behavior is a risk factor for chronic disease and mortality, even among those who exercise regularly. Given the time constraints of incorporating physical activity into daily schedules, and the high likelihood of sitting during office work, this environment may serve as a potentially feasible setting for interventions to reduce sedentary behavior. Methods and Results A randomized cross‐over clinical trial was conducted at an employee wellness center. Four office settings were evaluated on 4 consecutive days: stationary or sitting station on day 1 (referent), and 3 subsequent active workstations (standing, walking, or stepper) in randomized order. Neurocognitive function (Selective Attention, Grammatical Reasoning, Odd One Out, Object Reasoning, Visuospatial Intelligence, Limited‐Hold Memory, Paired Associates Learning, and Digit Span) and fine motor skills (typing speed and accuracy) were tested using validated tools. Average scores were compared among stations using linear regression with generalized estimating equations to adjust standard errors. Bonferroni method adjusted for multiple comparisons. Healthy subjects were enrolled (n=44), 28 (64%) women, mean±SD age 35±11 years, weight 75.5±17.1 kg, height 168.5±10.0 cm, and body mass index 26.5±5.2 kg/m 2 . When comparing active stations to sitting, neurocognitive test either improved or remained unchanged, while typing speed decreased without affecting typing errors. Overall results improved after day 1, suggesting habituation. We observed no major differences across active stations, except decrease in average typing speed 42.5 versus 39.7 words per minute with standing versus stepping ( P =0.003). Conclusions Active workstations improved cognitive performance, suggesting that these workstations can help decrease sedentary time without work performance impairment. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT06240286.

Introduction: The effect of obesity on physiologic aging has not been completely established. We previously developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm that predicts age and determines that the difference between AI-ECG age and chronological age (Age-Gap) may reflect accelerated aging, as it is associated with increased total and cardiovascular (CV) mortality. Hypothesis: Obesity is associated with an increased Age-Gap reflecting morbidity and accelerated aging. Methods: We included adults undergoing a wellness evaluation including, body fat percentage (BF%) determination by air displacement plethysmography (Bod-Pod®) and a 12-lead ECG within 2 years. We excluded those with coronary artery disease, congestive heart failure, stroke or being underweight defined as having a BMI<18.5 kg/m2. Logistic regression models tested the association between obesity by BMI (≥30 kg/m2) or BF% quartiles (≥35% for men and ≥25 in women) and being older by AI-ECG. Results: We included 1295 subjects (70% women), mean chronological age 46.7 ± 13.1 years. Mean Age-gap positive difference compared to those with BMI<25 was 1.39, 2.06 and 2.83 for those with BMI 25-29.9, 30-34.9, and >35 respectively (p<0.05). In the BF% group, Age-gap difference compared to those in the 1st quartile was 0.008, 0.37 and 1.52 for those in the 2nd, 3rd, and 4th quartile (p<0.05). Those>3 years older by ECG were more likely to have obesity by BMI and BF%, see figure. Conclusions: Obesity, either by BMI or BF%, is associated with increased physiologic age as measured by AI-ECG, highlighting the importance of obesity as a health threat.

Background: The body Mass Index (BMI) is commonly used in clinical practice to screen for obesity and resulting cardiometabolic conditions. Nonetheless, BMI has limited utility as it cannot differentiate body fat (BF). Hypothesis: We tested the hypothesis that BF content measured by air displacement plethysmography (Bod-Pod®) had a stronger association with prevalent hypertension (HTN), diabetes mellitus (DM) and dyslipidemia (DLP) when compared to BMI. Methods: We performed a community-based cross-sectional study on adults attending an employee wellness center from January 2007-December 2011 who had had a body composition assessment with Bod-Pod®. We excluded subjects with history of myocardial infarction, coronary artery disease, congestive heart failure, stroke at baseline. The prevalence of HTN, DM and DLP was assessed across quartiles of BF% and BMI categories. Their association with BF% and BMI was evaluated using linear regression models that adjusted for age, sex, and white race. Results: We included 3,052 individuals; 68 % were women, and the mean age ± SD was 42.09±12.8, BMI was 27.9±6.2; BF% 31.88±10.69, 892 (29.2%) were obese by BMI. Cardiometabolic conditions were prevalent in 496 (16.2%) with HTN, 378 (12.4%) with DM and 743 (24.4%) with DLP. While the prevalence of DM, HTN and DLP increased across BF% quartiles (all p for linearity>0.01), this was not always the case across BMI categories (p for linearity<0.05 for HTN and DLP, and 0.04 for DM) see Figure A . Elevated BF %, better identified individuals with HTN (AUC 0.766 vs 0.625; p<0.001), DM (AUC 0.643 vs. 0.568; p<0.001), DLP (AUC 0.758 vs. 0.593; p<0.001). Conclusion: BF content is better associated with a higher prevalence of HTN, DM, and DLP. Highlighting the role of body composition assessment in primary prevention. Dyslipidemia.

Introduction: Estimating body fat content has shown to better predict adiposity-related cardiovascular risk than the commonly used body mass index (BMI). The white-light 3D Body Volume Index Scanner (BVI) is a non-invasive device normally used in the clothing industry to asses body shapes and sizes. We assessed the hypothesis that volume obtained by BVI is comparable to the volume obtained by air displacement plethysmography (BodPod) (COSMED Concord, CA, USA) and thus capable of assessing body fat mass using the bicompartmental principles of body composition. Methods: We compared BVI to BodPod, a validated bicompartmental method to assess body fat percent that uses pressure/volume relationships in isothermal conditions to estimate body volume. Volume is then used to calculate body density (BD) applying the formula density= Body mass/Volume. Body fat mass percentage is then calculated using the Siri formula (4.95/BD – 4.50) х 100. Subjects were members of the Mayo Clinic Dan Abraham Healthy Living Center undergoing a wellness evaluation. Measurements from both devices were obtained the same day. A prediction model for total BodPod volume was developed using linear regression based on 80% of the observations (N=971), as follows: Predicted BodPod Volume (L) = 9.498 + 0.805*(BVI volume, L) - 0.0411*(Age, years) - 3.295*(Male=0, Female=1) + 0.0554*(BVI volume, L)*(Male=0, Female=1) + 0.0282*(Age, years)*(Male=0, Female=1). Predictions for BodPod volume based on the estimated model were then calculated for the remaining 20% (N=243) and compared to the volume measured by the BodPod. Results: Mean (SEM) age was 41.5(0.41) years, 39.4% were men, weight 81.6(0.67) kg, BMI was 27.8 (0.20) kg/m2. Average difference between volume measured by BodPod- predicted volume by BVI was 0.0 L, median: -0.4 L, IQR: -1.8 L to 1.5 L. Average difference between Body fat % measured - predicted was -1%, median: -2.7%, IQR: -13.2 to 9.9, R2 = 0.9845 (Figure 1-A, B). Conclusion: Body fat mass can be estimated using volume measurements obtained by a white- light 3D body scanner (Figure 1-A).

Introduction: Body fat (BF) content better predicts adiposity-related cardiovascular risk than the body mass index (BMI). Accurate and accepted methods to assess BF are complex, expensive, and accessible only in clinical settings. Multi-sensor 3D body volume (3D-BV) measurement technology has been shown to accurately estimate BF. We assessed the hypothesis that 3D models generated from biplane imaging (i.e., front and side facing photographs) using mobile devices (App), could be used to predict body volume measurements and derive BF. Methods: We prospectively enrolled 196 subjects, who underwent 3D-BV (gold standard for body volume) within 24 hours, dual-energy X-ray Absorptiometry (iDEXA) (gold standard for BF) and photographs taken with an Ipad® App at a predefined distance and pose. These photos were post-processed with a computer-assisted algorithm to estimate body length, girth, and volume. These were used to calculate body density (BD) using the bicompartmental principles of body composition (BD=Body Mass/Volume) and derive BF% using the Siri equation [(4.95/BD-4.50) X 100]. Correlation indexes and residual plots were created to compare 3D-BV and iDEXA with the App. Mean differences were compared using a paired t-test. Results: Mean ±SD age was 31.9±9.15 years, 53% were women, weight 72.8±14.1 kg, BMI was 25.5±4.5 kg/m 2 .The App volume correlated with 3D-BV (R 2 =0.95,95%CI 0.90,0.95, p<.0001, Figure 1-A ) ; average difference between App volume vs 3D-BV volume was -1.2 Liters, 95%CI,0.03, 2.42, p=0.06, ( Figure 1-B ). App BF% correlated with iDEXA BF% (R 2 =0.92, 95%CI 0.90,0.94, p<.0001, Figure 1-C ) ; while average difference between App BF% vs iDEXA BF% was -0.13 %, 95%CI -0.6,0.4, p=0.6, ( Figure 1-D ). Conclusion: BF can be estimated using volume measurements obtained by biplane imaging from mobile devices and could serve as a home-based, portable, scalable, cost-effective, and convenient measure to assess BF and track changes in body composition over time.