Objectives: The purpose of this study was to develop a new specific weight estimation formula for small-for-gestational-age (SGA) fetuses that differentiated between symmetric and asymmetric growth patterns.
Methods: A statistical estimation technique known as component-wise gradient boosting was applied to a group of 898 SGA fetuses (symmetric, n = 750; asymmetric, n = 148). A new formula was derived from the data obtained and was then compared to other commonly used equations.
Results: The new formula derived is as follows: estimated fetal weight = e^[1.3734627 + 0.0057133 × biparietal diameter + 0.0011282 × head circumference + 0.0201147 × abdominal circumference + 0.0183081 × femur length - 0.0000177 × biparietal diameter(2) - 0.0000018 × head circumference(2) - 0.0000297 × abdominal circumference(2) -0.0001007 × femur length(2) + 0.0397563 × I(sex = male) + 0.0064505 × gestational age (days) + 0.0096528 × I(SGA = asymmetric)], where the function I denotes an indicator function, which is 1 if the expression is fulfilled (sex = male; SGA type = asymmetric) and otherwise 0. In the whole study group and the 2 subgroups, the new formula showed the lowest median absolute percentage error, mean percentage error, and random error and the best distribution of absolute percentage errors within prespecified error bounds.
Conclusions: The new formula substantially improves weight estimation in SGA fetuses.
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http://dx.doi.org/10.7863/ultra.15.09084 | DOI Listing |
Sci Rep
January 2025
School of Mathematics and Statistics, Shaoguan University, Shaoguan, 512005, China.
Recently, deep latent variable models have made significant progress in dealing with missing data problems, benefiting from their ability to capture intricate and non-linear relationships within the data. In this work, we further investigate the potential of Variational Autoencoders (VAEs) in addressing the uncertainty associated with missing data via a multiple importance sampling strategy. We propose a Missing data Multiple Importance Sampling Variational Auto-Encoder (MMISVAE) method to effectively model incomplete data.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Health Sciences, Graduate Program in Public Health, University of Brasilia, Brasília, 70910-900, Brazil.
We compared the BMI-for-age (BMI/A) trajectory of Brazilian adolescents monitored in the primary health care (PHC) setting based on a simulated scenario. We used a real-life cohort of adolescents monitored by the Food and Nutrition Surveillance System (Sisvan) between 2008 and 2018. The LMS method was employed to estimate the simulated BMI/A evolution curve, assuming that the adolescents maintained the conditions observed during their first assessment (simulation curve).
View Article and Find Full Text PDFBr J Nutr
January 2025
Laboratório de Nutrição e Metabolismo, Faculdade de Nutrição, Universidade Federal de Alagoas, Maceió, Brazil.
To determine the prevalence of FA in individuals with type 2 diabetes and to assess the association between FA and type 2 diabetes. MEDLINE, EMBASE, Web of Sciences, Latin American and Caribbean Literature in Health Sciences, ScienceDirect, Scopus, and PsycINFO were searched until November 2024. This study was registered with PROSPERO (CRD42023465903).
View Article and Find Full Text PDFLancet Diabetes Endocrinol
January 2025
School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK.
The extent to which newer, incretin-based drugs for obesity improve disease outcomes via weight loss versus the direct effects of these drugs is the subject of intense interest. Although reductions in major adverse cardiovascular events appear to be predominantly driven by the direct tissue effects of such drugs, the associated weight loss effects must be relevant to the benefits observed in other major outcomes, albeit to differing extents. In this Personal View, we draw on evidence to support that weight loss is at least partly responsible (albeit to differing extents) for the reported benefits of incretin-based drugs for obesity in people living with heart failure with preserved ejection fraction, hypertension, chronic kidney disease, and type 2 diabetes.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Amazon Health Services, Seattle, Washington.
Importance: Medication nonadherence imposes high morbidity, mortality, and costs but is challenging to address given its multiple causes. Subscription models are increasingly used in health care to encourage healthy behaviors; in January 2023, Amazon Pharmacy launched RxPass, a subscription program offering Amazon Prime members (hereafter, company members) in 45 states access to 60 common generic medications for a flat $5 monthly fee.
Objective: To evaluate the associations of program enrollment with medication refills, days' supply, and out-of-pocket costs.
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