The distribution of breast density in women aged 18 years and older

PURPOSE

Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI.

METHODS

Breast density measures were estimated for 1,961 Australian women aged 18-97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI.

RESULTS

The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI.

CONCLUSION

This unique study describes the distribution of breast density measures for women aged 18-97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.

Breast composition during and after puberty: the Chilean Growth and Obesity Cohort Study

BACKGROUND

Breast density (BD) is a strong risk factor for breast cancer. Little is known about how BD develops during puberty. Understanding BD trajectories during puberty and its determinants could be crucial for promoting preventive actions against breast cancer (BC) at early ages. The objective of this research is to characterize % fibroglandular volume (%FGV), absolute fibroglandular volume (AFGV), and breast volume (BV) at different breast Tanner stages until 4-year post menarche in a Latino cohort and to assess determinants of high %FGV and AFGV during puberty and in a fully mature breast.

METHODS

This is a longitudinal follow-up of 509 girls from low-middle socioeconomic status of the Southeast area of Santiago, recruited at a mean age of 3.5 years. The inclusion criteria were singleton birth born, birthweight between 2500 and 4500 g with no medical or mental disorder. A trained dietitian measured weight and height since 3.5 years old and sexual maturation from 8 years old (breast Tanner stages and age at menarche onset). Using standardized methods, BD was measured using dual-energy X-ray absorptiometry (DXA) in various developmental periods (breast Tanner stage B1 until 4 years after menarche onset).

RESULTS

In the 509 girls, we collected 1,442 breast DXA scans; the mean age at Tanner B4 was 11.3 years. %FGV increased across breast Tanner stages and peaked 250 days after menarche. AFGV and BV peaked 2 years after menarche onset. Girls in the highest quartiles of %FGV, AFGV, and BV at Tanner B4 and B5 before menarche onset had the highest values thereafter until 4 years after menarche onset. The most important determinants of %FGV and AFGV variability were BMI z-score (R2 = 44%) and time since menarche (R2 = 42%), respectively.

CONCLUSION

We characterize the breast development during puberty, a critical window of susceptibility. Although the onset of menarche is a key milestone for breast development, we observed that girls in the highest quartiles of %FGV and AFGV tracked in that group afterwards. Following these participants in adulthood would be of interest to understand the changes in breast composition during this period and its potential link with BC risk.

The economic and resource burden of e-scooter-related orthopaedic injuries: A district general hospital's experience

PURPOSE

Electric scooters (e-scooters) are an increasingly popular method of transportation worldwide. However, there are concerns regarding their safety, specifically with regards to orthopaedic injuries. We aimed to investigate the overall burden and financial impact on orthopaedic services as a result of e-scooter-related orthopaedic injuries.

METHODS

We retrospectively identified all e-scooter-related injuries requiring orthopaedic admission or surgical intervention in a large District General Hospital in England over a 16-month period between September 2020 and December 2021. Injuries sustained, surgical management, inpatient stay and resources used were calculated.

RESULTS

Seventy-nine patients presented with orthopaedic injuries as a result of e-scooter transportation with a mean age of 30.1 years (SD 11.6), of which 62 were males and 17 were females. A total of 86 individual orthopaedic injuries were sustained, with fractures being the most common type of injury. Of these, 23 patients required 28 individual surgical procedures. The combined theatre and recovery time of these procedures was 5500 min, while isolated operating time was 2088 min. The total cost of theatre running time for these patients was estimated at £77,000. A total of 17 patients required hospital admission under Trauma and Orthopaedics, which accounted for total combined stay of 99 days with a mean length of stay of 5.8 days.

CONCLUSION

While there are potential environmental benefits to e-scooters, we demonstrate the risks of injury associated with their use and the associated increased burden to the healthcare system through additional emergency attendances, frequent outpatient clinic appointments, surgical procedures, and hospital inpatient admissions.

3D Convolutional Deep Learning for Nonlinear Estimation of Body Composition from Whole-Body Morphology

Total and regional body composition are strongly correlated with metabolic syndrome and have been estimated non-invasively from 3D optical scans using linear parameterizations of body shape and linear regression models. Prior works produced accurate and precise predictions on many, but not all, body composition targets relative to the reference dual X-Ray absorptiometry (DXA) measurement. Here, we report the effects of replacing linear models with nonlinear parameterization and regression models on the precision and accuracy of body composition estimation in a novel application of deep 3D convolutional graph networks to human body composition modeling. We assembled an ensemble dataset of 4286 topologically standardized 3D optical scans from four different human body shape databases, DFAUST, CAESAR, Shape Up! Adults, and Shape Up! Kids and trained a parameterized shape model using a graph convolutional 3D autoencoder (3DAE) in lieu of linear PCA. We trained a nonlinear Gaussian process regression (GPR) on the 3DAE parameter space to predict body composition via correlations to paired DXA reference measurements from the Shape Up! scan subset. We tested our model on a set of 424 randomly withheld test meshes and compared the effects of nonlinear computation against prior linear models. Nonlinear GPR produced up to 20% reduction in prediction error and up to 30% increase in precision over linear regression for both sexes in 10 tested body composition variables. Deep shape features produced 6-8% reduction in prediction error over linear PCA features for males only and a 4-14% reduction in precision error for both sexes. Our best performing nonlinear model predicting body composition from deep features outperformed prior work using linear methods on all tested body composition prediction metrics in both precision and accuracy. All coefficients of determination (R2) for all predicted variables were above 0.86. We show that GPR is a more precise and accurate method for modeling body composition mappings from body shape features than linear regression. Deep 3D features learned by a graph convolutional autoencoder only improved male body composition accuracy but improved precision in both sexes. Our work achieved lower estimation RMSEs than all previous work on 10 metrics of body composition.

Untargeted serum metabolomic profiles and breast density in young women

PURPOSE OF THE STUDY

Breast density is an established risk factor for breast cancer. However, little is known about metabolic influences on breast density phenotypes. We conducted untargeted serum metabolomics analyses to identify metabolic signatures associated with breast density phenotypes among young women.

METHODS

In a cross-sectional study of 173 young women aged 25-29 who participated in the Dietary Intervention Study in Children 2006 Follow-up Study, 449 metabolites were measured in fasting serum samples using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariable-adjusted mixed-effects linear regression identified metabolites associated with magnetic resonance imaging measured breast density phenotypes: percent dense breast volume (%DBV), absolute dense breast volume (ADBV), and absolute non-dense breast volume (ANDBV). Metabolite results were corrected for multiple comparisons using a false discovery rate adjusted p-value (q).

RESULTS

The amino acids valine and leucine were significantly inversely associated with %DBV. For each 1 SD increase in valine and leucine, %DBV decreased by 20.9% (q = 0.02) and 18.4% (q = 0.04), respectively. ANDBV was significantly positively associated with 16 lipid and one amino acid metabolites, whereas no metabolites were associated with ADBV. Metabolite set enrichment analysis also revealed associations of distinct metabolic signatures with %DBV, ADBV, and ANDBV; branched chain amino acids had the strongest inverse association with %DBV (p = 0.002); whereas, diacylglycerols and phospholipids were positively associated with ANDBV (p ≤ 0.002), no significant associations were observed for ADBV.

CONCLUSION

Our results suggest an inverse association of branched chain amino acids with %DBV. Larger studies in diverse populations are needed.

The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

BACKGROUND

Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians' offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the 'BIA International Database' project and encourage researchers to join the consortium.

METHODS

The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants.

CONCLUSION

The BIA International Database represents a key resource for research on body composition.

Time-specific impact of mono-benzyl phthalate (MBzP) and perfluorooctanoic acid (PFOA) on breast density of a Chilean adolescent Cohort

INTRODUCTION

High mammographic density is among the strongest and most established predictors for breast cancer risk. Puberty, the period during which breasts undergo exponential mammary growth, is considered one of the critical stages of breast development for environmental exposures. Benzylbutyl phthalate (BBP) and perfluorooctanoic acid (PFOA) are pervasive endocrine disrupting chemicals that may increase hormone-sensitive cancers. Evaluating the potential impact of BBP and PFOA exposure on pubertal breast density is important to our understanding of early-life environmental influences on breast cancer etiology.

OBJECTIVE

To prospectively assess the effect of biomarker concentrations of monobenzyl phthalate (MBzP) and PFOA at specific pubertal window of susceptibility (WOS) on adolescent breast density.

METHOD

This study included 376 Chilean girls from the Growth and Obesity Cohort Study with data collection at four timepoints: Tanner breast stages 1 (B1) and 4 (B4), 1- year post- menarche (1YPM) and 2-years post-menarche (2YPM). Dual-energy X-ray absorptiometry was used to assess the absolute fibroglandular volume (FGV) and percent breast density (%FGV) at 2YPM. We used concentrations of PFOA in serum and MBzP in urine as an index of exposure to PFOA and BBP, respectively. Parametric G-formula was used to estimate the time-specific effects of MBzP and PFOA on breast density. The models included body fat percentage as a time-varying confounder and age, birthweight, age at menarche, and maternal education as fixed covariates.

RESULTS

A doubling of serum PFOA concentration at B4 resulted in a non-significant increase in absolute FGV (β:11.25, 95% confidence interval (CI): -0.28, 23.49)), while a doubling of PFOA concentration at 1YPM resulted in a decrease in % FGV (β:-4.61, 95% CI: -7.45, -1.78). We observed no associations between urine MBzP and breast density measures.

CONCLUSION

In this cohort of Latina girls, PFOA serum concentrations corresponded to a decrease in % FGV. No effect was observed between MBzP and breast density measures across pubertal WOS.

Examining the impact of COVID-19 on health care utilization among persons with chronic spinal cord injury/dysfunction: a population study

STUDY DESIGN

A retrospective longitudinal cohort time-series analysis study.

OBJECTIVES

To examine healthcare utilization and delivery during the COVID-19 pandemic in individuals with spinal cord injury/dysfunction (SCI/D).

SETTING

Health administrative database in Ontario, Canada.

METHODS

In 5754 individuals with SCI/D diagnosed from 2004-2014 and living in the community, healthcare utilization (physician visits, primary care visits, specialist visits, urologist visits, physiatrist visits, emergency department (ED) visits, and hospital admissions) and delivery (total, in-person, virtual) were determined at the (1) pre-pandemic period (March 2015 to February 2020), (2) initial pandemic onset period (March 2020-May 2020), and (3) pandemic period (June 2020 to March 2022). Autoregressive integrated moving average (ARIMA) modelling was conducted to determine the impact of the pandemic on monthly healthcare utilization and delivery.

RESULTS

The initial pandemic onset period had a significant reduction of 24% in physicians (p = 0.0081), 35% in specialists (p < 0.0001), and 30% in urologist (p < 0.0001) visits, compared to pre-pandemic levels, with a partial recovery as the pandemic progressed. In April 2020, compared to the pre-pandemic period, a significant increase (p < 0.0001) in virtual visits for physicians, specialists, urologists, and primary care was found. The initial pandemic onset period had a 58% decrease in hospital admissions (p = 0.0011), compared to the pre-pandemic period.

CONCLUSION

Healthcare utilization dropped in the initial pandemic onset period as physicians, specialists, and urologists, as well as hospitalization visits decreased significantly (p < 0.05) versus pre-pandemic levels. Virtual visit increases compensated for in-person visit decreases as the pandemic progressed to allow for total visits to partially recover.

Bone and Renal Health in Infants With or Without Breastmilk Exposure to Tenofovir-Based Maternal Antiretroviral Treatment in the PROMISE Randomized Trial

BACKGROUND

We assessed bone and kidney outcomes in infants randomized postdelivery as mother-infant pairs within the IMPAACT PROMISE trial to maternal tenofovir disoproxil fumarate-based antiretroviral treatment (mART) or infant nevirapine prophylaxis (iNVP) to prevent breastfeeding HIV transmission.

METHODS

Infants were coenrolled in the P1084s substudy on randomization day and followed through Week 74. Lumbar spine bone mineral content (LS-BMC) was assessed at entry (6-21 age days) and Week 26 by dual-energy x-ray absorptiometry. Creatinine clearance (CrCl) was calculated at entry; Weeks 10, 26, and 74. Student t tests compared mean LS-BMC and CrCl at Week 26 and mean change from entry between arms.

RESULTS

Of 400 enrolled infants, the mean (SD; n) for entry LS-BMC was 1.68 g (0.35; n = 363) and CrCl was 64.2 mL/min/1.73 m 2 (24.6; n = 357). At Week 26, 98% of infants were breastfeeding and 96% on their assigned HIV prevention strategy. The mean (SD) Week 26 LS-BMC was 2.64 g (0.48) for mART and 2.77 g (0.44) for iNVP; mean difference (95% confidence interval [CI]) -0.13 g (-0.22 to -0.04), P = 0.007, n = 375/398 (94%). Mean absolute (-0.14 g [-0.23 to -0.06]) and percent (-10.88% [-18.53 to -3.23]) increase in LS-BMC from entry was smaller for mART than iNVP. At Week 26, the mean (SD) CrCl was 130.0 mL/min/1.73 m 2 (34.9) for mART vs. 126.1 mL/min/1.73 m 2 (30.0) for iNVP; mean difference (95% CI) 3.8 (-3.0 to 10.7), P = 0.27, n = 349/398 (88%).

CONCLUSION

Week 26 mean LS-BMC was lower in infants in the mART group compared with the iNVP group. However, this difference (∼0.23 g) was less than one-half SD, considered potentially clinically relevant. No infant renal safety concerns were observed.

Abstract P3-04-05: Artificial Intelligence Detects, Classifies, and Describes Lesions in Clinical Breast Ultrasound Images

Purpose Many low-middle income countries (LMIC) suffer from chronic shortages of resources that inhibit the implementation of effective breast cancer screening programs. Advanced breast cancer rates in the U.S. Affiliated Pacific Islands substantially exceed that of the United States. We propose the use of portable breast ultrasound coupled with artificial intelligence (AI) algorithms to assist non-radiologist field personnel in real-time field lesion detection, classification, and biopsy, as well as determination of breast density for risk assessment. In this study, we examine the ability of an AI algorithm to detect and describe breast cancer lesions in clinically-acquired breast ultrasound images in 40,000 women participating in a Hawaii screening program. Materials and Methods The Hawaii and Pacific Islands Mammography Registry (HIPIMR) collects breast health questionnaires and breast imaging (mammography, ultrasound, and MRI) from participating centers in Hawaii and the Pacific and links this information to the Hawaii Tumor Registry for cancer findings. From the women with either screening or diagnostic B-mode breast ultrasound exams, we selected 3 negative cases (no cancer) for every positive case matched by age, excluding Doppler and elastography images. The blinded images were read by the study radiologist to delineate all lesions and describe in terms of the BI-RADS lexicon. These images were split by woman into training (70%), validation and hyperparameter selection (20%) and testing (20%) subsets. An AI model was fine-tuned for lesion and BI-RADS category classification from a Detectron2 framework [1] pre-trained on the COCO Instance Segmentation Dataset [2]. Model performance was evaluated by computation of precision and sensitivity percentages, as well as Area under the Receiver Operator Curve (AUROC). Detections were considered positive if they overlapped a ground truth lesion delineation by at least 50% (Intersection over Union = 0.5), and a maximum of 4 detections were generated for each image. Timing experiments were run on a GPU-enabled (Nvidia Tesla V100) machine on unbatched images. Results Over the 10-year observation period, we identified 5,214 women with US images meeting our criterion. Of these, 111 were diagnosed with malignant breast cancer and 333 were selected as non-cases for a total of 444 women. These 444 women had a total of 4,623 ultrasound images with 2,028 benign and 1,431 malignant lesions identified by the study radiologist. For cancerous lesions, the AI algorithm had 8% precision at a sensitivity of 90% on the testing set. For benign lesions, a sensitivity of 90% resulted in 5% precision on the testing set. The AUROC for bounding box detections of cancerous lesions was 0.90. The AUROC for bounding box detections of benign lesions was 0.87. The model made predictions at a rate of 25 frames/second time (38.7 milliseconds per image). Conclusion Detection, segmentation, and cancer classification of breast lesions are possible in clinically-acquired ultrasound images using AI. Based on our timing experiments, the model is capable of detecting and classifying lesions in real-time during ultrasound capture. Model performance is expected to improve as more data becomes available for training. Future work would involve further fine-tuning of the model on portable breast ultrasound images and increasing model evaluation speed in order to assess utility in low-resource populations [1] Wu Y, Kirillov A, Massa F, Lo W-Y, Girshick R. Detectron2. https://github.com/facebookresearch/detectron2. [2] Lin T-Y, Maire M, Belongie S, et al. Microsoft COCO: Common Objects in Context. Computer Vision – ECCV 2014. Springer International Publishing; 2014:740-755.

Citation Format: Arianna Bunnell, Dustin Valdez, Thomas Wolfgruber, Aleen Altamirano, Brenda Hernandez, Peter Sadowski, John Shepherd. Artificial Intelligence Detects, Classifies, and Describes Lesions in Clinical Breast Ultrasound Images [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-04-05.

Abstract P3-03-02: Can artificial intelligence derived ultrasound breast density provide comparable breast cancer risk estimates to density derived from mammograms

Can artificial intelligence derived ultrasound breast density provide comparable breast cancer risk estimates to density derived from mammograms Dustin Valdez12, Arianna Bunnell2, Thomas Wolfgruber1, Aleen V. Altamirano3, Brandon Quon1, Gertraud Maskarinec1, Peter Sadowski2, John A. Shepherd1 1 University of Hawaii Cancer Center, Honolulu, HI 2 University of Hawaii at Manoa, Honolulu, HI 3 Instituto Radiodiagnóstico, Managua, Nicaragua Background: Breast cancer is the second leading cause of cancer-related death among women in Hawaii and the Pacific. However, while there are programs like the Breast and Cervical Cancer Early Detection Program (BCCEDP) implemented throughout the Pacific, the lack of access to mammography screening and low screening participation rates contributes to very high advanced breast cancer rates in most cases over 50%. Portable breast ultrasound is a promising screening technology for low resource areas. However, without mammography, mammographic density is not available for risk modeling to determine who should participate in screening programs or at what frequency. In this study, we ask if breast ultrasound (US) images can be used to derive an equivalent mammographic density for risk modeling. We utilized artificial intelligence to derive breast density from diagnostic ultrasound images and compared to BI-RADS mammographic density in an established breast cancer risk model1. Methods: We selected women with negative screening visit who either later developed cancer (positives) or did not (negatives) over a 10-year period. Temporally-matched negative mammographic and ultrasound images, cancer outcome status and cancer risk information were sourced from the Hawaii and Pacific Islands Mammography Registry. US images had to have occurred within a year of the mammogram. BI-RADS mammographic density was derived using an existing deep neural network model2. Mammographic density was estimated from US images by training a deep-learning convolutional neural network model. A hold out set of images (Test set of 20% of the total) was used to compare 10-year breast cancer risk using the Tyrer-Cuzick (TC) risk model1 when calculated using breast density from either mammograms or US. The AUC values, confidence intervals, ROC plots and Pearson correlation were calculated and compared. Results: Over the 10-year study period, 1337 had matched mammograms and US images and 65 went on to develop breast cancer. Using the test set, the Pearson’s correlation between breast density from mammography and US was 0.31 (moderate correlation). There were no covariates found to improve this association. The AUC for TC 10-year personal risk was higher when breast density from mammograms was used 0.71 (95% CI=0.57-0.86) versus US images 0.65 (95% CI=0.53-0.76). Conclusion: Overall breast cancer risk was similar when breast density was derived from either mammograms or US. The performance of our US breast density model is expected to improve further when more US training data becomes available. Breast cancer screening programs exclusively using US imaging may be able to provide equivalent risk modeling to clinics using mammography. 1.Tyrer J, Duffy SW, Cuzick J (2004). A breast cancer prediction model incorporating familial and personal risk factors. Stat Med. 2004 Apr 15;23(7):1111-30. doi: 10.1002/sim.1668. Erratum in: Stat Med. 2005 Jan 15;24(1):156. PMID: 15057881. 2. Wu, N., K. J. Geras, Y. Shen, J. Su, S. G. Kim, E. Kim, S. Wolfson, L. Moy and K. Cho (2018). Breast Density Classification with Deep Convolutional Neural Networks. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE.

Citation Format: Dustin Valdez, Arianna Bunnell, Thomas Wolfgruber, Aleen Altamirano, Brandon Quon, Gertraud Maskarinec, Peter Sadowski, John Shepherd. Can artificial intelligence derived ultrasound breast density provide comparable breast cancer risk estimates to density derived from mammograms [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-03-02.

Alternative methods to measure breast density in younger women

BACKGROUND

Breast density is a strong and potentially modifiable breast cancer risk factor. Almost everything we know about breast density has been derived from mammography, and therefore, very little is known about breast density in younger women aged <40. This study examines the acceptability and performance of two alternative breast density measures, Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry (DXA), in women aged 18-40.

METHODS

Breast tissue composition (percent water, collagen, and lipid content) was measured in 539 women aged 18-40 using OBS. For a subset of 169 women, breast density was also measured via DXA (percent fibroglandular dense volume (%FGV), absolute dense volume (FGV), and non-dense volume (NFGV)). Acceptability of the measurement procedures was assessed using an adapted validated questionnaire. Performance was assessed by examining the correlation and agreement between the measures and their associations with known determinants of mammographic breast density.

RESULTS

Over 93% of participants deemed OBS and DXA to be acceptable. The correlation between OBS-%water + collagen and %FGV was 0.48. Age and BMI were inversely associated with OBS-%water + collagen and %FGV and positively associated with OBS-%lipid and NFGV.

CONCLUSIONS

OBS and DXA provide acceptable and viable alternative methods to measure breast density in younger women aged 18-40 years.

Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models

Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R2s (0.88-0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM - 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings.

Preliminary findings from a risk stratification, quality of life and burden of illness in pulmonary arterial hypertension pilot study

Funding Acknowledgements

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Janssen Australia and New Zealand (Janssen-Cilag Pty Ltd)

Pulmonary Arterial Hypertension (PAH) management strategies focus on lowering mortality risk, extending the patient’s life span through the control and alleviation of disease symptoms, improving Quality of Life (QoL) and decreasing the burden of illness.

This paper describes preliminary results of an Investigator Initiated pilot study exploring the relationship between PRO measures (PAH-SYMPACT, EQ5D5L); Burden of Illness assessment; and the ESC/ERS Risk Stratification.

Findings

Measures of PAH risk and QoL were assessed in 42 patients presenting to the IPAH clinic for management; mean age 69.2 [range 39, 84]; females 35 (83.3%), males 7 (16.7%). Tools analysed and compared included: PAH-SYMPACT and EQ-5D-5L as PRO and QoL measures; and ESC-ERS PAH risk stratification criteria to assess mortality risk. Health utility scores were derived from existing value sets: there was a 20% median reduction in QALYs for our patient population, with detrimental effects being more marked in those patients with greater impairment of EQ-5D-5L physical and cognitive-emotional domains (respectively: r = -0.92, p&lt;0.001; and r = -0.85, p&lt;0.001), PAH-SYMPACT physical domain reduction (r = -0.59, p&lt;0.01), and PAH-SYMPACT cardiovascular symptoms (r = 0.64), p&lt;0.01) and cardiorespiratory (r = 0.64, p&lt;0.01) involvement. Physical domain scores were highly correlated for the two PROs studied (r = 0.74, p&lt;0.001), but an unexpected poor correlation was seen in the cognitive/emotional domain (non-significant negative correlation) which requires further exploration. Unsurprisingly, EQ-5D-5L Visual Analogue Score for well-being was inversely correlated with physical domain impairment (r = -0.59, p&lt;0.01), although it was noted that this did not apply for the cognitive/emotional domain. The agreement between tools was variable, with highest concordance seen for assessment of the physical domain (r = 0.74, p&lt;0.001), and this raises the need to further define the merits of disease-specific (PAH-SYMPACT) vs generic (EQ-5D-5L) PRO analytic approaches. Tools examined in this study were well-correlated with symptomatic impairment, but neither PRO tool correlated with established risk markers as characterized in compound prognostic guides such as ESC-ERS criteria.

Conclusions

The fact that PRO indices showed little correlation with established risk stratification markers implies that the information provided by PROs is not redundant, and it is yet be assessed whether the incorporation of PRO’s may add further to the precision of risk assessment, a little-studied area which this group is further exploring. There should be more widespread and uniform use of PRO measures as part of standard PAH management.

Genome-wide association study of abdominal MRI-measured visceral fat: The multiethnic cohort adiposity phenotype study

Few studies have explored the genetic underpinnings of intra-abdominal visceral fat deposition, which varies substantially by sex and race/ethnicity. Among 1,787 participants in the Multiethnic Cohort (MEC)-Adiposity Phenotype Study (MEC-APS), we conducted a genome-wide association study (GWAS) of the percent visceral adiposity tissue (VAT) area out of the overall abdominal area, averaged across L1-L5 (%VAT), measured by abdominal magnetic resonance imaging (MRI). A genome-wide significant signal was found on chromosome 2q14.3 in the sex-combined GWAS (lead variant rs79837492: Beta per effect allele = -4.76; P = 2.62 × 10-8) and in the male-only GWAS (lead variant rs2968545: (Beta = -6.50; P = 1.09 × 10-9), and one suggestive variant was found at 13q12.11 in the female-only GWAS (rs79926925: Beta = 6.95; P = 8.15 × 10-8). The negatively associated variants were most common in European Americans (T allele of rs79837492; 5%) and African Americans (C allele of rs2968545; 5%) and not observed in Japanese Americans, whereas the positively associated variant was most common in Japanese Americans (C allele of rs79926925, 5%), which was all consistent with the racial/ethnic %VAT differences. In a validation step among UK Biobank participants (N = 23,699 of mainly British and Irish ancestry) with MRI-based VAT volume, both rs79837492 (Beta = -0.026, P = 0.019) and rs2968545 (Beta = -0.028, P = 0.010) were significantly associated in men only (n = 11,524). In the MEC-APS, the association between rs79926925 and plasma sex hormone binding globulin levels reached statistical significance in females, but not in males, with adjustment for total adiposity (Beta = -0.24; P = 0.028), on the log scale. Rs79837492 and rs2968545 are located in intron 5 of CNTNAP5, and rs79926925, in an intergenic region between GJB6 and CRYL1. These novel findings differing by sex and racial/ethnic group warrant replication in additional diverse studies with direct visceral fat measurements.

Variability in urinary phthalates, phenols, and parabens across childhood and relation to adolescent breast composition in Chilean girls

BACKGROUND

Epidemiologic evidence suggests that environmental factors acting as endocrine disrupting chemicals (EDCs) are associated with mammographic breast density and the risk of breast cancer. Exposure to EDCs during puberty, a period of rapid breast development, may affect susceptibility to breast carcinogenesis.

METHODS

In a cohort of 366 Chilean adolescents from the Growth and Obesity Cohort Study, we evaluated the relation between urinary concentrations of 15 suspected EDC biomarkers across three pubertal time points (Tanner breast stage 1 (B1), 4 (B4), and 1-year post-menarche) and breast fibroglandular volume (FGV; percent FGV [%FGV] and absolute FGV [aFGV]) and total breast volume (tBV) at 2-years post-menarche. We used linear mixed models to test differences in creatinine-corrected EDC biomarker concentrations at B4 and 1-year post-menarche compared to B1 and calculated intraclass correlation coefficients (ICC) of EDC concentrations across time points to appraise the consistency of measurements. We fit multivariable generalized estimating equations (GEEs) to evaluate windows of susceptibility for the association between log10-transformed EDCs and log10-transformed breast outcomes. GEEs were adjusted for age, body fat percentage, total caloric intake, and maternal education.

RESULTS

Urinary EDC biomarker concentrations highly varied across pubertal time points (ICC range 0.01-0.30). For 12 EDCs, biomarker concentrations decreased over time. Triclosan measured at 1-year post-menarche was inversely associated with %FGV at 2-years post-menarche (β = -0.025, 95 % confidence interval = -0.041, -0.008). Mono(2-ethyl-5-carboxypentyl) phthalate and the sum of di(2-ethylhexyl) phthalate metabolite concentrations at B4 were positively associated with aFGV and tBV at 2-years post-menarche. No measured phenols were associated with aFGV and tBV, while no measured parabens were associated with %FGV and aFGV.

CONCLUSIONS

Our study suggests relatively high variability in EDC biomarker concentrations across the peripubertal time period. We also found evidence to suggest that there may be pubertal windows of susceptibility to select EDCs for the association with adolescent breast density.

Stability of a Simple Bioreactor Model with a General Growth Function, Bacterial Feed and Death Rate

Biological reactors are employed in industrial applications to break down organic waste. Here we consider the stability of an open loop CSTR, with a general growth rate function, having both a bacterial and substrate feed and a death rate. Reactors with a bacterial feed are important as every reactor after the first in a cascade will have both bacterial and substrate feeds. We show that stability of a critical point is related to the sign of the slope of the growth rate function, when no bacterial feed is present, and to the sign of the slope of a function, being the product of the growth rate function and a function involving the substrate and bacterial feed concentrations, when a bacterial feed is present.

D3 -creatine dilution for skeletal muscle mass measurement: historical development and current status

The French chemist Michel Eugène Chevreul discovered creatine in meat two centuries ago. Extensive biochemical and physiological studies of this organic molecule followed with confirmation that creatine is found within the cytoplasm and mitochondria of human skeletal muscles. Two groups of investigators exploited these relationships five decades ago by first estimating the creatine pool size in vivo with ¹⁴ C and ¹⁵ N labelled isotopes. Skeletal muscle mass (kg) was then calculated by dividing the creatine pool size (g) by muscle creatine concentration (g/kg) measured on a single muscle biopsy or estimated from the literature. This approach for quantifying skeletal muscle mass is generating renewed interest with the recent introduction of a practical stable isotope (creatine-(methyl-d₃ )) dilution method for estimating the creatine pool size across the full human lifespan. The need for a muscle biopsy has been eliminated by assuming a constant value for whole-body skeletal muscle creatine concentration of 4.3 g/kg wet weight. The current single compartment model of estimating creatine pool size and skeletal muscle mass rests on four main assumptions: tracer absorption is complete; tracer is all retained; tracer is distributed solely in skeletal muscle; and skeletal muscle creatine concentration is known and constant. Three of these assumptions are false to varying degrees. Not all tracer is retained with urinary isotope losses ranging from 0% to 9%; an empirical equation requiring further validation is used to correct for spillage. Not all tracer is distributed in skeletal muscle with non-muscle creatine sources ranging from 2% to 10% with a definitive value lacking. Lastly, skeletal muscle creatine concentration is not constant and varies between muscles (e.g. 3.89-4.62 g/kg), with diets (e.g. vegetarian and omnivore), across age groups (e.g. middle-age, ~4.5 g/kg; old-age, 4.0 g/kg), activity levels (e.g. athletes, ~5 g/kg) and in disease states (e.g. muscular dystrophies, <3 g/kg). Some of the variability in skeletal muscle creatine concentrations can be attributed to heterogeneity in the proportions of wet skeletal muscle as myofibres, connective tissues, and fat. These observations raise serious concerns regarding the accuracy of the deuterated-creatine dilution method for estimating total body skeletal muscle mass as now defined by cadaver analyses of whole wet tissues and in vivo approaches such as magnetic resonance imaging. A new framework is needed in thinking about how this potentially valuable method for measuring the creatine pool size in vivo can be used in the future to study skeletal muscle biology in health and disease.

Implementing an eHealth tool to improve referral services for obstetric emergencies in Sierra Leone

Background

Maternal health remains a major issue of concern in Sierra Leone. In the main referral maternity institution, Princess Christian Maternity Hospital (PCMH), up to 25% of maternal deaths occur during or shortly after transit from another health facility. There is an urgent need to improve referral systems between peripheral health units (PHUs) and PCMH. Our aim was to pilot and evaluate an eHealth tool facilitating referral of obstetric emergency cases through effective teleconsultation between PHUs and PCMH.

Methods

A web application was designed to capture unclear or complicated delivery cases at PHUs and request respective telemedical counselling from the referral institution PCMH. The eHealth tool was piloted at 10 PHUs in Western area urban and rural in August 2021. Necessary devices were provided and delivery staff was trained to use the app. In December 2021, we conducted focus group discussion with 3-6 delivery staff at five PHUs and at PCMH to evaluate utilization and outcomes of the tool.

Results

All participants perceived the eHealth tool as an improvement of referral procedures. Response time from PCMH after a request for counselling from a PHU was mostly &lt;30 minutes. The main perceived advantage of the tool was the systematic documentation of obstetric complications and procedures. This relieved staff from fear of wrong treatment accusations, and recorded communication with PCMH made processes and responsibilities transparent. Another important benefit was PCMH staff being already prepared to receive a specific emergency case after use of the app, thus reducing the ‘third delay’ within the referral facility. As a major obstacle to smooth referral despite the eHealth tool, a lacking ambulance system was mentioned as a critical gap.

Conclusions

Exceedingly positive user experiences with this simple tool seem to make an expansion to more PHUs worthwhile. Benefits of using the app in more remote districts in Sierra Leone should be further investigated.

Key messages

• Delivery staff in Sierra Leone was capable of using a web app for telemedical counselling in a useful and effective manner.

• The eHealth tool was perceived as very helpful in systematically and transparently documenting emergency delivery cases and treatment procedures.

Use of Dual-Energy X-Ray Absorptiometry to Assess Soft Tissue Composition in Breast Cancer Survivors With and Without Lymphedema

Background: In patients with lymphedema (LE), in addition to hand dominance, between-group comparisons of interlimb soft tissue differences need to account for differences in whole-body adiposity, measured directly by dual energy X-ray absorptiometry (DXA) or indirectly by body mass index. No study has evaluated the effects of hand dominance and whole-body adiposity on limb composition in patients with LE. This study's purpose was to compare soft tissue composition of affected and unaffected limbs of women with breast cancer, who did and did not have LE, controlling for dominance and percent body fat. Methods and Results: Whole-body DXA scans were acquired and included measures of percent body fat, upper limb total mass, upper limb fat mass, and upper limb fat-free mass. Participants were classified into one of three groups: women without LE; women with only subjective LE; and women with objective signs of LE at the time of assessment. Differences among the LE groups were evaluated using analysis of variance (ANOVA) and Chi-square analyses. Analysis of covariance (ANCOVA) was used to control for percent body fat and for the affected limb dominance. Compared to women without LE, women with objective signs of LE have greater total limb mass, fat mass, and fat-free mass in their affected limbs, independent of affected side dominance and percent body fat. In addition, the interlimb differences in total mass, fat mass, and fat-free mass were greater for the women with objective signs of LE, compared to the other two groups. Conclusions: DXA is useful in identifying soft tissue changes in patients with LE. Given that limb circumferences measure only changes in limb volume and that bioimpedance provides estimates of extracellular fluid, DXA has the advantage of being able to estimate the volumes of specific tissues in the limb.

Anthropometric evaluation of a 3D scanning mobile application

OBJECTIVE

Three-dimensional (3D) imaging systems are increasingly being used in health care settings for quantifying body size and shape. The potential exists to provide similar phenotyping capabilities outside of professional settings using smartphone applications (apps). The current study aim was to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20-camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites.

METHODS

Fifty-nine adults were scanned with the app and SS20; the same software was used to generate circumference estimates from device-acquired object files that were then compared with reference tape measurements.

RESULTS

The app and SS20 had similar coefficients of variation that were minimally larger than those by the tape (e.g., waist, 0.93%, 0.87%, and 0.06%). Correlations of the app and of SS20 with tape circumferences were all strong (p < 0.001) and similar in magnitude (R² s: 0.72-0.93 and 0.78-0.95, respectively); minimally significant (p < 0.05 to p < 0.01) bias was present between both imaging approaches and some tape measurements.

CONCLUSION

These proof-of-concept observations combined with ubiquitous smartphone availability create the possibility of phenotyping adult body size and shape, with important clinical and research implications, on a global scale.

Body composition changes in a 12-week exercise intervention for breast cancer patients

e12500

Background: Evidence has linked weight gain and obesity to increased breast cancer risk, poorer outcomes, decreased survivorship, and increased risk of recurrence. Adjuvant therapies can increase weight gain, making tailored exercise interventions beneficial in maintaining a healthy weight. In this study, body composition changes were examined after a 12-week exercise program in a cohort of breast cancer survivors. Methods: The Breast Cancer Exercise Rehabilitation Research Study recruited breast cancer survivors to undergo a 12-week exercise program (NCT04013568) and examine body composition changes. Measurements taken included anthropometry (waist circumference, waist-to-hip ratio, BMI), DXA body composition measurements (fat mass-visceral and subcutaneous, trunk to limb, muscle mass-appendicular, and whole body), and BIA (Bio-electrical Impedance Analysis-muscle, fat, and water). 34 participants completed the exercise program and baseline and post-12-week measurements were obtained. Descriptive statistics and a paired t-test analysis was done to analyze changes in body composition using SAS onDemand. A correlation analysis between measurements simple to do in clinic and DXA measurements were run to determine proxy use for DXA. Results: After a 12-week exercise program, reductions in body fat via DXA scan, BIA, and InBody (whole body fat, whole body fat %, trunk fat, leg fat, body fat %, hip width at maximum girth, body fat mass, and percent body fat) were observed. Additionally, increases in lean mass (Appendicular Lean Mass (ALM)/height2, Appendicular Lean/height2, ALM index, and lean body mass), whole body mass measured by DXA, basal metabolic rate, water retention (extracellular water and total body water), and skeletal muscle mass were observed. Correlation analysis revealed BMI can be used as a surrogate measure for whole body mass measured by DXA (r=0.91, p<0.001) and can be utilized to measure change over time. Skinfold sum showed moderate correlation for measuring subcutaneous fat mass by DXA (r=0.45, p=0.0096). Conclusions: In our population of breast cancer survivors, a 12-week exercise program did show various changes in body composition according to InBody, DXA, and BIA measurements. DXA and InBody measurements were feasible, making it readily available for patients. Additionally, simple measures such as BMI and skinfold sum showed moderate to strong correlation with DXA measurements, validating use of these measurements in routine practice. Clinical trial information: NCT04013568. [Table: see text]

Emergence of the adolescent obesity epidemic in the United States: five-decade visualization with humanoid avatars

BACKGROUND/OBJECTIVES

Body size and shape have increased over the past several decades with one in five adolescents now having obesity according to objective anthropometric measures such as weight, height, and body mass index (BMI). The gradual physical changes and their consequences may not be fully appreciated upon visual inspection by those managing the long-term health of adolescents. This study aimed to develop humanoid avatars representing the gradual changes in adolescent body size and shape over the past five decades and to align avatars with key BMI percentile cut points for underweight, normal weight, overweight, and obesity.

PARTICIPANTS/METHODS

Participants included 223 children and adolescents between the ages of 5 and 18 years approximately representative of the race/ethnicity and BMI of the noninstitutionalized US population. Each participant completed a three-dimensional whole-body scan, and the collected data was used to develop manifold regression models for generating humanoid male and female avatars from specified ages, weights, and heights. Secular changes in the mean weights and heights of adolescents were acquired from six U.S. National Health and Nutrition Surveys beginning in 1971-1974 and ending in 2015-2018. Male and female avatars at two representative ages, 10 and 15 years, were developed for each survey and at the key BMI percentile cut points based on data from the 2015-2018 survey.

RESULTS

The subtle changes in adolescent Americans' body size and shape over the past five decades are represented by 24 male and female 10- and 15-year-old avatars and 8 corresponding BMI percentile cut points.

CONCLUSIONS

The current study, the first of its kind, aligns objective physical examination weights and heights with the visual appearance of adolescents. Aligning the biometric and visual information may help improve awareness and appropriate clinical management of adolescents with excess adiposity passing through health care systems.

TRIAL REGISTRATION

ClinicalTrials.Gov NCT03706612.

Prognostic utility of self-reported sarcopenia (SARC-F) in the Multiethnic Cohort

BACKGROUND

Age-related loss in skeletal muscle mass, quality, and strength, known as sarcopenia, is a well-known phenomenon of aging and is determined clinically using methods such as dual-energy X-ray absorptiometry (DXA). However, these clinical methods to measure sarcopenia are not practical for population-based studies, and a five-question screening tool known as SARC-F has been validated to screen for sarcopenia.

METHODS

We investigated the relationship between appendicular skeletal lean mass/height² (ALM/HT² ) (kg/m² ) assessed by DXA and SARC-F in a subset of 1538 (778 men and 760 women) participants in the Multiethnic Cohort (MEC) Study after adjustment for race/ethnicity, age, and body mass index (BMI) at the time of DXA measurement. We then investigated the association between SARC-F and mortality among 71 283 (41 757 women and 29 526 men) participants in the MEC, who responded to the five SARC-F questions on a mailed questionnaire as part of the MEC follow-up in 2012-2016.

RESULTS

In women, SARC-F score was significantly inversely associated with ALM/HT² after adjusting for race/ethnicity, and age and BMI at DXA (r = -0.167, P < 0.001); the result was similar in men although it did not reach statistical significance (r = -0.056, P = 0.12). Among the 71 000+ MEC participants, SARC-F score ≥ 4, as an indicator of sarcopenia, was higher in women (20.9%) than in men (11.2%) (P < 0.0001) and increased steadily with increasing age (6.3% in <70 vs. 41.3% in 90+ years old) (P < 0.0001). SARC-F score ≥ 4 was highest among Latinos (30.8% in women and 16.1% in men) and lowest in Native Hawaiian women (15.6%) and Japanese American men (8.9%). During an average of 6.8 years of follow-up, compared with men with SARC-F score of 0-1 (indicator of no sarcopenia), men with SARC-F 2-3 (indicator of pre-sarcopenia) and SARC-F ≥ 4 had significantly increased risk of all-cause mortality [hazard ratio (HR) = 1.00, 1.77, 3.73, P < 0.001], cardiovascular disease (CVD) mortality (HR = 1.00, 1.85, 3.98, P < 0.001), and cancer mortality (HR = 1.00, 1.46, 1.96, P < 0.001) after covariate adjustment. Comparable risk association patterns with SARC-F scores were observed in women (all-cause mortality: HR = 1.00, 1.47, 3.10, P < 0.001; CVD mortality: HR = 1.00, 1.59, 3.54, P < 0.001; cancer mortality: HR = 1.00, 1.30, 1.77, P < 0.001). These significant risk patterns between SARC-F and all-cause mortality were found across all sex-race/ethnic groups considered (12 in total).

CONCLUSIONS

An indicator of sarcopenia, determined using SARC-F, showed internal validity against DXA and displayed racial/ethnic and sex differences in distribution. SARC-F was associated with all-cause mortality as well as cause-specific mortality.

Emergence of the obesity epidemic: 6-decade visualization with humanoid avatars

BACKGROUND

Visualizations of the emerging obesity epidemic, such as with serial US color prevalence maps, provide graphic images that extend informative public health messages beyond those in written communications. Advances in low-cost 3D optical technology now allow for development of large image databases that include participants varying in race/ethnicity, body mass, height, age, and circumferences. When combined with contemporary statistical methods, these data sets can be used to create humanoid avatar images with prespecified anthropometric features.

OBJECTIVES

The current study aimed to develop a humanoid avatar series with characteristics of representative US adults extending over the past 6 decades.

METHODS

3D optical scans were conducted on a demographically diverse sample of 570 healthy adults. Image data were converted to principal components and manifold regression equations were then developed with body mass, height, age, and waist circumference as covariates. Humanoid avatars were generated for representative adults with these 4 characteristics as reported in CDC surveys beginning in 1960-1962 up to 2015-2018.

RESULTS

There was a curvilinear increase in adult US population body mass, waist circumference, and BMI in males and females across the 9 surveys spanning 6 decades. A small increase in average adult population age was present between 1960 and 2018; height changes were inconsistent. A series of 4 avatars developed at ∼20-y intervals for representative males and females reveal the changes in body size and shape consistent with the emergence of the obesity epidemic. An additional series of developed avatars portray the shapes and sizes of males and females at key BMI cutoffs.

CONCLUSIONS

New mathematical approaches and accessible 3D optical technology combined with increasingly available large and diverse data sets across the life span now make unique visualization of body size and shape possible on a previously unattainable scale. This study is registered at https://clinicaltrials.gov/ct2/show/NCT03637855 as NCT03637855.

145 Best Medical Therapy for Patients with Peripheral Arterial Disease: A Quality Improvement Project in Vascular Surgery, Aberdeen Royal Infirmary

Introduction

Peripheral arterial disease (PAD) is the leading cause of limb amputation and cardiovascular morbidity. The National Institute for Health and Care Excellence (NICE) advocates best medical therapy (BMT) with high-dose statin (atorvastatin 80mg) and antiplatelets (clopidogrel or aspirin) for secondary prevention in patients with PAD. We assessed compliance to BMT prescribing in our vascular department.

Method

Retrospective data were collected for all patients admitted with symptomatic PAD in our vascular department over a 2-week period. Criteria for BMT were as per NICE guidelines with a standard set to 100%. Following cycle 1, a new admission document prompting antiplatelet and statin review was designed and departmental teaching on BMT delivered. Standard compliance was re-audited after 3 months.

Results

Twenty-five patients were admitted with PAD during cycle 1 with 28% of patients (n = 7) on BMT on admission. This increased to 40% (n = 10) on discharge with 100% (n = 25) on an antiplatelet and 28% (n = 7) on high-dose statin. Overall, there were twenty patients in cycle 2 with 25% of patients (n = 5) on BMT on admission. This increased to 80% (n = 16) on discharge with 100% (n = 20) on an antiplatelet and 80% (n = 16) on high-dose statin.

Conclusions

Our data demonstrated poor implementation of BMT for patients with PAD managed in primary care suggesting a need for primary care education. Adaption of our admission proforma to prompt BMT prescribing as well as departmental teaching was associated with drastic improvement of BMT prescription on discharge and standard adherence.

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

Background

Simple visualizations in health research data, such as scatter plots, heat maps, and bar charts, typically present relationships between 2 variables. Interactive visualization methods allow for multiple related facets such as numerous risk factors to be studied simultaneously, leading to data insights through exploring trends and patterns from complex big health care data. The technique presents a powerful tool that can be used in combination with statistical analysis for knowledge discovery, hypothesis generation and testing, and decision support.

Objective

The primary objective of this scoping review is to describe and summarize the evidence of interactive visualization applications, methods, and tools being used in population health and health services research (HSR) and their subdomains in the last 15 years, from January 1, 2005, to March 30, 2019. Our secondary objective is to describe the use cases, metrics, frameworks used, settings, target audience, goals, and co-design of applications.

Methods

We adapted standard scoping review guidelines with a peer-reviewed search strategy: 2 independent researchers at each stage of screening and abstraction, with a third independent researcher to arbitrate conflicts and validate findings. A comprehensive abstraction platform was built to capture the data from diverse bodies of literature, primarily from the computer science and health care sectors. After screening 11,310 articles, we present findings from 56 applications from interrelated areas of population health and HSR, as well as their subdomains such as epidemiologic surveillance, health resource planning, access, and use and costs among diverse clinical and demographic populations.

Results

In this companion review to our earlier systematic synthesis of the literature on visual analytics applications, we present findings in 6 major themes of interactive visualization applications developed for 8 major problem categories. We found a wide application of interactive visualization methods, the major ones being epidemiologic surveillance for infectious disease, resource planning, health service monitoring and quality, and studying medication use patterns. The data sources included mostly secondary administrative and electronic medical record data. In addition, at least two-thirds of the applications involved participatory co-design approaches while introducing a distinct category, embedded research, within co-design initiatives. These applications were in response to an identified need for data-driven insights into knowledge generation and decision support. We further discuss the opportunities stemming from the use of interactive visualization methods in studying global health; inequities, including social determinants of health; and other related areas. We also allude to the challenges in the uptake of these methods.

Conclusions

Visualization in health has strong historical roots, with an upward trend in the use of these methods in population health and HSR. Such applications are being fast used by academic and health care agencies for knowledge discovery, hypotheses generation, and decision support.

International Registered Report Identifier (IRRID)

RR2-10.2196/14019

Abstract P3-01-13: Comparing portable and clinical ultrasound systems using 3D printed breast phantom inserts

Background: Late-stage breast cancer rates in the Pacific where mammography services are limited are exceedingly high. Therefore, alternative accessible breast cancer screening technologies such as portable ultrasound is needed. However, little is known about the performance of portable ultrasound when compared to clinical ultrasound for use in breast cancer screening. By utilizing 3D printing technology, it is possible to design breast phantom inserts to replicate various types of lesions. In this study, we utilized 3D printed breast phantom inserts to compare portable and clinical ultrasound lesion detection performance. Methods: Four different breast inserts were designed using FreeCAD (version 0.19) to replicate different lesion detection properties. The first insert compares lesion shape, the second insert investigates depth and size, the third insert looks at fiber diameter, and the fourth insert looks at clusters. The four inserts were printed using a photopolymer resign (Formlabs Inc Rigid resign, Somerville, MA, USA) and then placed in a gelatin-based breast phantom designed for ultrasound use. Using the portable ultrasound (GE Vscan Extend) and clinical ultrasound (Philips EPIQ 5G), various images were captured of identical angle and orientation for both devices. The number of lesions visualized were counted and presented as a percentage of lesions detected. Results: The portable ultrasound had a 100% lesion detection rate for breast insert 1, 90.3% for breast insert 2, 70% for breast insert 3 and 55.8% for breast insert 4. Clinical ultrasound had 100% lesion detection rate for breast insert 1, 93.1% for breast insert 2, 76.6% for breast insert 3, and 99% for breast insert 4. Conclusion: Portable ultrasound shows comparable lesion detection capabilities to clinical ultrasound in 3 of the 4 breast phantom insert tests. Portable ultrasound may have potential as a capable accessible breast cancer screening device in areas without mammography.

Citation Format: Dustin Valdez, Jami Fukui, Thomas Wolfgruber, Lambert Leong, Gertraud Maskarinec, John Shepherd. Comparing portable and clinical ultrasound systems using 3D printed breast phantom inserts [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-01-13.

Assessment of Arm Volume Using a Tape Measure Versus a 3D Optical Scanner in Survivors with Breast Cancer-Related Lymphedema

Background: Lymphedema (LE) is a significant clinical problem for breast cancer survivors. While the water displacement test and circumferential assessment using a tape measure (TM) are common methods to assess differences in arm volumes, faster and more reliable methods are needed. Study purposes, in breast cancer survivors (n = 294), were to compare the average total arm volumes and interlimb volume ratios for women with and without a history of LE, using a TM and three-dimensional (3D), whole-body surface scanner (3D scan); compare the level of agreement between arm volumes and interlimb volume ratios obtained using the two devices; and evaluate the percent agreement between the two measures in classifying cases of LE using three accepted thresholds. Methods and Results: Measurements were done using a spring-loaded TM and Fit3D ProScanner. Paired t-tests and Bland-Altman analyses were used to achieve the study aims. For circumference and volume comparisons, compared with the 3D scan, values obtained using the TM were consistently smaller. In terms of level of agreement, the Bland-Altman analyses demonstrated large biases and wide limits of agreement for the calculated arm volumes and volume ratios. In terms of the classification of caseness, using the 200-mL interlimb volume difference criterion resulted in 81.6% overall agreement; using the >10% volume difference between the affected and unaffected arms resulted in 78.5% overall agreement; and using the volume ratio ≥1.04 criterion resulted in 62.5% overall agreement. For all three accepted threshold criteria, the percentage of cases was significantly different between the TM and 3D scan techniques. Conclusions: The 3D technology evaluated in this study has the potential to be used for self-initiated surveillance for LE. With improvements in landmark identification and software modifications, it is possible that accurate and reliable total arm volumes can be calculated and used for early detection.

Sugar-sweetened beverage consumption and breast composition in a longitudinal study of Chilean girls

Background

Frequent sugar-sweetened beverage (SSB) intake has been associated with indirect markers of breast cancer risk, such as weight gain in adolescents and early menarche. How SSB intake relates to breast composition in adolescent girls has not been explored.

Methods

We evaluated the association between prospective intake of SSB and breast density in a cohort of 374 adolescent girls participating in the Growth and Obesity Cohort Study in Santiago, Chile. Multivariable linear regression models were used to analyze the association between average daily SSB intake quartiles and breast composition (absolute fibroglandular volume [aFGV], percent fibroglandular volume [%FGV], total breast volume [tBV]). Models were adjusted for potential confounding by BMI Z-score, age, daily energy intake (g/day), maternal education, hours of daily television watching after school, dairy intake (g/day), meat intake (g/day), waist circumference, and menarche. To examine the sensitivity of the association to the number of dietary recalls for each girl, analyses were further stratified by girls with one dietary recall and girls with > one dietary recall.

Results

A total of 881 dietary recalls were available for 374 girls prior to the breast density assessment. More than 60% of the cohort had > one dietary recall available. In multivariable analyses, we found no association between SSB intake quartile and aFGV (Q2 vs Q1 β: − 5.4, 95% CI − 15.1, 4.4; Q3 vs Q1 β: 1.3, 95% CI − 8.6, 11.3; Q4 vs Q1 β: 3.0, 95% CI − 7.1, 13). No associations were noted for %FGV and tBV. Among girls with at least one dietary recall, we found no significant associations between SSB intake quartiles and %FGV, aFGV, or tBV.

Conclusion

Overall, we observed no evidence that SSB intake was associated with breast density in adolescent Chilean girls.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01495-8.

Reproducibility and flexibility of monoclonal antibody production with Nicotiana benthamiana

The ongoing SARS-CoV-2 coronavirus pandemic of 2020-2021 underscores the need for manufacturing platforms that can rapidly produce monoclonal antibody (mAb) therapies. As reported here, a platform based on Nicotiana benthamiana produced mAb therapeutics with high batch-to-batch reproducibility and flexibility, enabling production of 19 different mAbs of sufficient purity and safety for clinical application(s). With a single manufacturing run, impurities were effectively removed for a representative mAb product (the ZMapp component c4G7). Our results show for the first time the reproducibility of the platform for production of multiple batches of clinical-grade mAb, manufactured under current Good Manufacturing Practices, from Nicotiana benthamiana. The flexibility of the system was confirmed by the results of release testing of 19 different mAbs generated with the platform. The process from plant infection to product can be completed within 10 days. Therefore, with a constant supply of plants, response to the outbreak of an infectious disease could be initiated within a matter of weeks. Thus, these data demonstrated that this platform represents a reproducible, flexible system for rapid production of mAb therapeutics to support clinical development.

Identifying cases of spinal cord injury or disease in a primary care electronic medical record database

OBJECTIVE

To identify cases of spinal cord injury or disease (SCI/D) in an Ontario database of primary care electronic medical records (EMR).

DESIGN

A reference standard of cases of chronic SCI/D was established via manual review of EMRs; this reference standard was used to evaluate potential case identification algorithms for use in the same database.

SETTING

Electronic Medical Records Primary Care (EMRPC) Database, Ontario, Canada.

PARTICIPANTS

A sample of 48,000 adult patients was randomly selected from 213,887 eligible patients in the EMRPC database.

INTERVENTIONS

N/A.

MAIN OUTCOME MEASURE(S)

Candidate algorithms were evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F-score.

RESULTS

126 cases of chronic SCI/D were identified, forming the reference standard. Of these, 57 were cases of traumatic spinal cord injury (TSCI), and 67 were cases of non-traumatic spinal cord injury (NTSCI). The optimal case identification algorithm used free-text keyword searches and a physician billing code, and had 70.6% sensitivity (61.9-78.4), 98.5% specificity (97.3-99.3), 89.9% PPV (82.2-95.0), 94.7% NPV (92.8-96.3), and an F-score of 79.1.

CONCLUSIONS

Identifying cases of chronic SCI/D from a database of primary care EMRs using free-text entries is feasible, relying on a comprehensive case definition. Identifying a cohort of patients with SCI/D will allow for future study of the epidemiology and health service utilization of these patients.

The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population

Skin cancer remains the most commonly diagnosed cancer in the USA with more than 1 million new cases each year. Melanomas account for about 1% of all skin cancers and most skin cancer deaths. Multiethnic individuals whose skin is pigmented underestimate their risk for skin cancers and melanomas and may delay seeking a diagnosis. The use of artificial intelligence may help improve the diagnostic precision of dermatologists/physicians to identify malignant lesions. To validate our artificial intelligence's efficiency in distinguishing between images, we utilized 50 images obtained from our International Skin Imaging Collaboration dataset (n = 25) and pathologically confirmed lesions (n = 25). We compared the ability of our artificial intelligence to visually diagnose these 50 skin cancer lesions with a panel of three dermatologists. The artificial intelligence model better differentiated between melanoma vs. nonmelanoma with an area under the curve of 0.948. The three-panel member dermatologists correctly diagnosed a similar number of images (n = 35) as the artificial intelligence program (n = 34). Fleiss' kappa (ĸ) score for the raters and artificial intelligence indicated fair (0.247) agreement. However, the combined result of the dermatologists panel with the artificial intelligence assessments correctly identified 100% of the images from the test data set. Our artificial intelligence platform was able to utilize visual images to discriminate melanoma from nonmelanoma, using de-identified images. The combined results of the artificial intelligence with those of the dermatologists support the use of artificial intelligence as an efficient lesion assessment strategy to reduce time and expense in diagnoses to reduce delays in treatment.

Mammary collagen architecture and its association with mammographic density and lesion severity among women undergoing image-guided breast biopsy

Background

Elevated mammographic breast density is a strong breast cancer risk factor with poorly understood etiology. Increased deposition of collagen, one of the main fibrous proteins present in breast stroma, has been associated with increased mammographic density. Collagen fiber architecture has been linked to poor outcomes in breast cancer. However, relationships of quantitative collagen fiber features assessed in diagnostic biopsies with mammographic density and lesion severity are not well-established.

Methods

Clinically indicated breast biopsies from 65 in situ or invasive breast cancer cases and 73 frequency matched-controls with a benign biopsy result were used to measure collagen fiber features (length, straightness, width, alignment, orientation and density (fibers/µm²)) using second harmonic generation microscopy in up to three regions of interest (ROIs) per biopsy: normal, benign breast disease, and cancer. Local and global mammographic density volumes were quantified in the ipsilateral breast in pre-biopsy full-field digital mammograms. Associations of fibrillar collagen features with mammographic density and severity of biopsy diagnosis were evaluated using generalized estimating equation models with an independent correlation structure to account for multiple ROIs within each biopsy section.

Results

Collagen fiber density was positively associated with the proportion of stroma on the biopsy slide (p < 0.001) and with local percent mammographic density volume at both the biopsy target (p = 0.035) and within a 2 mm perilesional ring (p = 0.02), but not with global mammographic density measures. As severity of the breast biopsy diagnosis increased at the ROI level, collagen fibers tended to be less dense, shorter, straighter, thinner, and more aligned with one another (p < 0.05).

Conclusions

Collagen fiber density was positively associated with local, but not global, mammographic density, suggesting that collagen microarchitecture may not translate into macroscopic mammographic features. However, collagen fiber features may be markers of cancer risk and/or progression among women referred for biopsy based on abnormal breast imaging.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01482-z.

Multicomponent density models for body composition: Review of the dual energy X-ray absorptiometry volume approach

Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent "body density" models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air-displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual-energy X-ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual-energy X-ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air-displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual-energy X-ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies.

Genome-wide association study of pancreatic fat: The Multiethnic Cohort Adiposity Phenotype Study

Several studies have found associations between higher pancreatic fat content and adverse health outcomes, such as diabetes and the metabolic syndrome, but investigations into the genetic contributions to pancreatic fat are limited. This genome-wide association study, comprised of 804 participants with MRI-assessed pancreatic fat measurements, was conducted in the ethnically diverse Multiethnic Cohort-Adiposity Phenotype Study (MEC-APS). Two genetic variants reaching genome-wide significance, rs73449607 on chromosome 13q21.2 (Beta = -0.67, P = 4.50x10-8) and rs7996760 on chromosome 6q14 (Beta = -0.90, P = 4.91x10-8) were associated with percent pancreatic fat on the log scale. Rs73449607 was most common in the African American population (13%) and rs79967607 was most common in the European American population (6%). Rs73449607 was also associated with lower risk of type 2 diabetes (OR = 0.95, 95% CI = 0.89-1.00, P = 0.047) in the Population Architecture Genomics and Epidemiology (PAGE) Study and the DIAbetes Genetics Replication and Meta-analysis (DIAGRAM), which included substantial numbers of non-European ancestry participants (53,102 cases and 193,679 controls). Rs73449607 is located in an intergenic region between GSX1 and PLUTO, and rs79967607 is in intron 1 of EPM2A. PLUTO, a lncRNA, regulates transcription of an adjacent gene, PDX1, that controls beta-cell function in the mature pancreas, and EPM2A encodes the protein laforin, which plays a critical role in regulating glycogen production. If validated, these variants may suggest a genetic component for pancreatic fat and a common etiologic link between pancreatic fat and type 2 diabetes.

Digital anthropometric volumes: Toward the development and validation of a universal software

PURPOSE

Anthropometry is a method for quantifying body size and shape often used to derive body composition and health risk prediction models. Recent technology advancements led to development of three-dimensional (3D) optical scanners that can overcome most of the limitations associated with manual anthropometric data collection. However, each of the currently available devices offers proprietary measurements that do not match conventional anthropometric definitions. The aim of the current study was to develop and then evaluate the precision and accuracy of new "universal" 3D optical analysis software that calculates digital anthropometric volumes using identical standard landmarks across scanners.

METHODS

Dual-energy x-ray absorptiometry (DXA) and air displacement plethysmography (ADP) total body and regional volume and fat mass reference measurements and 3D optical scans from two proprietary devices were collected from 356 participants to evaluate the robustness of total body and regional volume and fat mass measurements calculated by the developed software. Linear regression modeling with threefold cross validation was used to evaluate total body and regional fat masses from 3D scans.

RESULTS

Total body and regional volumes measured by DXA and ADP had strong associations with corresponding estimates from the commercial 3D optical scanners coupled with the universal software (e.g., R²  = 0.98 for Styku and R²  = 1.00 for SS20, for both DXA and ADP comparisons). Regional body volumes also had strong correlation between DXA and the 3DO scanners (e.g., for arm, leg and trunk, respective R² s of 0.75, 0.86, and 0.97 for Styku and 0.79, 0.89, and 0.98 for SS20). Similarly, there were strong associations between DXA- measured total body and regional fat mass and 3D optical estimates calculated by the universal software (e.g., for total body, arm, leg and trunk, respective R² s of 0.86, 0.72, 0.77, and 0.88 for Styku and 0.84, 0.76, 0.78, and 0.85 for SS20). Absolute differences in volumes and fat mass between the reference methods and the universal software values revealed underlying proprietary scanner differences that can be improved when designing future devices.

CONCLUSIONS

The current study suggests that, when compared against values calculated using DXA and ADP, the universal software was able to measure total and regional body volumes reliably from scans obtained by two different scanners. The universal software, with future refinements, combined with potential optical scanner design improvements, creates new opportunities for developing large multicenter anthropometric databases with uniformly defined body dimensions that can be used for modeling health risks.

CLINICAL TRIAL REGISTRATION ID

Shape Up! Adults Study, NCT0363785.

Development of a novel micro-bead force spectroscopy approach to measure the ability of a thermo-active polymer to remove bacteria from a corneal model

Microbial keratitis occurs from the infection of the cornea by fungi and or bacteria. It remains one of the most common global causes of irreversible blindness accounting for 3.5% (36 million) of blind people as of 2015. This paper looks at the use of a bacteria binding polymer designed to bind Staphylococcus aureus and remove it from the corneal surface. Mechanical unbinding measurements were used to probe the interactions of a thermo-active bacteria-binding polymer, highly-branched poly(N-isopropyl acrylamide), functionalised with modified vancomycin end groups (HB-PNIPAM-Van) to bacteria placed on rabbit corneal surfaces studied ex-vivo. This was conducted during sequential temperature phase transitions of HB-PNIPAM-Van-S. aureus below, above and below the lower critical solution temperature (LCST) in 3 stages, in-vitro, using a novel micro-bead force spectroscopy (MBFS) approach via atomic force microscopy (AFM). The effect of temperature on the functionality of HB-PNIPAM-Van-S. aureus showed that the polymer-bacteria complex reduced the work done in removing bacterial aggregates at T > LCST (p < 0.05), exhibiting reversibility at T < LCST (p < 0.05). At T < LCST, the breaking force, number of unbinding events, percentage fitted segments in the short and long range, and the percentage of unbinding events occurring in the long range (> 2.5 µm) increased (p < 0.05). Furthermore, the LCST phase transition temperature showed 100 × more unbinding events in the long-range z-length (> 2.5 µm) compared to S. aureus aggregates only. Here, we present the first study using AFM to assess the reversible mechanical impact of a thermo-active polymer-binding bacteria on a natural corneal surface.

Manufacturing plant-made monoclonal antibodies for research or therapeutic applications

Monoclonal antibodies (mAbs) hold great promise for treating diseases ranging from cancer to infectious disease. Manufacture of mAbs is challenging, expensive, and time-consuming using mammalian systems. We describe detailed methods used by Kentucky BioProcessing (KBP), a subsidiary of British American Tobacco, for producing high quality mAbs in a Nicotiana benthamiana host. Using this process, mAbs that meet GMP standards can be produced in as little as 10 days. Guidance for using individual plants, as well as detailed methods for large-scale production, are described. These procedures enable flexible, robust, and consistent production of research and therapeutic mAbs.

Associations of the Dietary Inflammatory Index With Total Adiposity and Ectopic Fat and the Mediating Effect of the Gut Microbiota

Objectives

To assess, in a large multiethnic cross-sectional study, associations between the Dietary Inflammatory Index (DII®) and total adiposity and ectopic fat, and whether these associations are mediated by gut microbiota (GM).

Methods

Analyses used data from 1,655 participants (812 men, 843 women, 60–77 y) in the Adiposity Phenotype Study. At clinic visit (2013–2015), DXA-based total fat mass, MRI-based visceral adipose tissue (VAT) area at L1-L5 (cm2), and liver fat (% volume) were measured. Participants provided a stool sample and completed a validated food frequency questionnaire (FFQ). Stool bacterial DNA was amplified and the V1-V3 region of the 16S rRNA gene was sequenced. As ratios, GM data were centered log-ratio transformed. DII score was computed from FFQ data, with a higher DII representing a more inflammatory diet. The relationships between DII, GM and adiposity phenotypes were examined using linear regression and mediation analyses. Bootstrap 95% CI were calculated for the indirect effect (IE).

Results

DII was positively associated with total fat mass (β = 0.71 kg), VAT (β = 4.73 cm2), and liver fat (β = 0.40%) (P-values &lt; 0.001). DII was negatively associated with Eubacterium xylanophilum (β = −2.86), and alpha diversity (β = −0.04), and positively associated with Tyzzerella (β = 5.78) (P-values &lt; 0.001). An inverse relationship was found between E. xylanophilum, VAT (β = −0.11 cm2), and liver fat (β = −0.01%), and between alpha diversity and liver fat (β = −0.93%) (P-values &lt; 0.001). Tyzzerella was positively associated with VAT (β = 0.04 cm2) (P &lt; 0.001). The total effect of DII on VAT was partially mediated by E. xylanophilum (IE = 0.30) and Tyzzerella (IE = 0.26). The association between DII and liver fat was partially mediated by E. xylanophilum (IE = 0.02) and alpha diversity (IE = 0.04). GM did not mediate the total effect between DII and total fat mass.

Conclusions

The total effect of DII on ectopic fat was partially mediated by lower bacterial diversity and E. xylanophilum, a butyrate-producing genera often inversely associated with inflammation. The association between DII and ectopic fat was also mediated by an abundance of Tyzzerella, a genus previously found to be associated with low-quality diets. Following an anti-inflammatory diet may minimize intra-abdominal fat, in part through the indirect effect of the gut microbiota.

Funding Sources

NIH, NCI.

Risk factors for preeclampsia and eclampsia at a main referral maternity hospital in Freetown, Sierra Leone: a case-control study

BACKGROUND

In the African region, 5.6% of pregnancies are estimated to be complicated by preeclampsia and 2.9% by eclampsia, with almost one in ten maternal deaths being associated with hypertensive disorders. In Sierra Leone, representing one of the countries with the highest maternal mortality rates in the world, 16% of maternal deaths were caused by pregnancy-induced hypertension in 2016. In the light of the high burden of preeclampsia and eclampsia (PrE/E) in Sierra Leone, we aimed at assessing population-based risk factors for PrE/E to offer improved management for women at risk.

METHODS

A facility-based, unmatched observational case-control study was conducted in Princess Christian Maternity Hospital (PCMH). PCMH is situated in Freetown and is the only health care facility providing 'Comprehensive Emergency Obstetric and Neonatal Care services' throughout the entire country. Cases were defined as pregnant or postpartum women diagnosed with PrE/E, and controls as normotensive postpartum women. Data collection was performed with a questionnaire assessing a wide spectrum of factors influencing pregnant women's health. Statistical analysis was performed by estimating a binary logistic regression model.

RESULTS

We analyzed data of 672 women, 214 cases and 458 controls. The analysis yielded several independent predictors for PrE/E, including family predisposition for PrE/E (AOR = 2.72, 95% CI: 1.46-5.07), preexisting hypertension (AOR = 3.64, 95% CI: 1.32-10.06), a high mid-upper arm circumflex (AOR = 3.09, 95% CI: 1.83-5.22), presence of urinary tract infection during pregnancy (AOR = 2.02, 95% CI: 1.28-3.19), presence of prolonged diarrhoea during pregnancy (AOR = 2.81, 95% CI: 1.63-4.86), low maternal assets (AOR = 2.56, 95% CI: 1.63-4.02), inadequate fruit intake (AOR = 2.58, 95% CI: 1.64-4.06), well or borehole water as the main source of drinking water (AOR = 2.05, 95% CI: 1.31-3.23) and living close to a waste deposit (AOR = 1.94, 95% CI: 1.15-3.25).

CONCLUSION

Our findings suggest that systematic assessment of identified PrE/E risk factors, including a family predisposition for PrE/E, preexisting hypertension, or obesity, should be performed early on in ANC, followed by continued close monitoring of first signs and symptoms of PrE/E. Additionally, counseling on nutrition, exercise, and water safety is needed throughout pregnancy as well as education on improved hygiene behavior. Further research on sources of environmental pollution in Freetown is urgently required.

Web-Based Peer Support Interventions for Adults Living With Chronic Conditions: Scoping Review

Background

Globally, 1 in 3 adults live with multiple chronic conditions. Thus, effective interventions are needed to prevent and manage these chronic conditions and to reduce the associated health care costs. Teaching effective self-management practices to people with chronic diseases is one strategy to address the burden of chronic conditions. With the increasing availability of and access to the internet, the implementation of web-based peer support programs has become increasingly common.

Objective

The purpose of this scoping review is to synthesize existing literature and key characteristics of web-based peer support programs for persons with chronic conditions.

Methods

This scoping review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for scoping reviews guidelines. Studies were identified by searching MEDLINE, CINAHL, Embase, PsycINFO, and the Physiotherapy Evidence Database. Chronic diseases identified by the Public Health Agency of Canada were included. Our review was limited to peer support interventions delivered on the web. Peers providing support had to have the chronic condition that they were providing support for. The information abstracted included the year of publication, country of study, purpose of the study, participant population, key characteristics of the intervention, outcome measures, and results.

Results

After duplicates were removed, 12,641 articles were screened. Data abstraction was completed for 41 articles. There was a lack of participant diversity in the included studies, specifically with respect to the conditions studied. There was a lack of studies with older participants aged ≥70 years. There was inconsistency in how the interventions were described in terms of the duration and frequency of the interventions. Informational, emotional, and appraisal support were implemented in the studied interventions. Few studies used a randomized controlled trial design. A total of 4 of the 6 randomized controlled trials reported positive and significant results, including decreased emotional distress and increased health service navigation, self-efficacy, social participation, and constructive attitudes and approaches. Among the qualitative studies included in this review, there were several positive experiences related to participating in a web-based peer support intervention, including increased compassion and improved attitudes toward the individual’s chronic condition, access to information, and empowerment.

Conclusions

There is limited recent, high-level evidence on web-based peer support interventions. Where evidence exists, significant improvements in social participation, self-efficacy, and health-directed activity were demonstrated. Some studies incorporated a theoretical framework, and all forms of peer support—emotional, informational, and appraisal support—were identified in the studies included in this review. We recommend further research on web-based peer support in more diverse patient groups (eg, for older adults and chronic conditions outside of cancer, cardiovascular disease, and HIV or AIDS). Key gaps in the area of web-based peer support will serve to inform the development and implementation of future programs.

Total body and regional surface area: Quantification with low-cost three-dimensional optical imaging systems

OBJECTIVES

Body surface area (SA) is a widely used physical measure incorporated into multiple thermophysiology and evolutionary biology models currently estimated in humans either with empirical prediction equations or costly whole-body laser imaging systems. The introduction of low-cost 3D scanners provides a new opportunity to quantify total body (TB) and regional SA, although a critical question prevails: can these devices acquire the quality of depth information and process this initial data to form a mesh that has the fidelity needed to generate accurate SA estimates?

MATERIALS AND METHODS

This question was answered by comparing SA estimates calculated using images from four commercial 3D scanners in 108 adults to corresponding estimates acquired with a whole-body laser system. This was accomplished by processing initial mesh data from all devices, including the laser system, with the same universal software adapted specifically for repairing mesh gaps, identifying landmarks, and generating SA measurements.

RESULTS

TB SA measured on all four 3D scanners was highly correlated with corresponding laser system estimates (R² s, 0.98-0.99; all p < 0.001) with some small but significant mean differences (-0.19 to 0.06 m² ); root-mean square errors (RMSEs) were small (0.02-0.03 m² ); and significant bias was present for one device. Qualitatively similar results (e.g., R² s, 0.78-0.95; mean Δs, -0.05 to 0.02 m² ; RMSEs, 0.01-0.03 m² ) were present for trunk, arm, and leg SA comparisons.

DISCUSSION

The current study observations demonstrate that low-cost and practical 3D optical scanners are capable of accurately quantifying TB and regional SA, thus opening new opportunities for evaluating human phenotypes and related physiological characteristics.

Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes

PURPOSE

We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes.

METHODS

We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group.

RESULTS

All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers.

CONCLUSIONS

Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.