Objective: Examine the relationship between 1- and 2-month weight loss (WL) and 8-year WL among participants enrolled in a lifestyle intervention.
Methods: 2,290 Look AHEAD participants (BMI: 35.65 ± 5.93 kg/m(2) ) with type 2 diabetes received an intensive behavioral WL intervention.
Results: 1- and 2-month WL were associated with yearly WL through Year 8 (P's < 0.0001). At Month 1, participants losing 2-4% and >4% had 1.62 (95% CI: 1.32, 1.98) and 2.79 (95% CI: 2.21, 3.52) times higher odds of achieving ≥5% WL at Year 4 and 1.28 (95% CI: 1.05,1.58) and 1.77 (95% CI: 1.40, 2.24) times higher odds of achieving ≥5% WL at Year 8, compared to those losing <2% initially. At Month 2, 3-6% WL resulted in greater odds of achieving ≥5% WL at Year 4 (OR = 1.85; CI: 1.48, 2.32), and >6% WL resulted in the greatest odds of achieving ≥5% WL at Year 4 (OR = 3.85; CI: 3.05, 4.88) and Year 8 (OR = 2.28; CI: 1.81, 2.89), compared to those losing <3%. Differences in adherence between WL categories were observed as early as Month 2.
Conclusions: 1- and 2-month WL was associated with 8-year WL. Future studies should examine whether alternative treatment strategies can be employed to improve treatment outcomes among those with low initial WL.
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http://dx.doi.org/10.1002/oby.21112 | DOI Listing |
J Neurosurg
January 2025
Departments of2Neurological Surgery and.
Objective: Skull base chordomas (SBCs) often present with cranial nerve (CN) VI deficits. Studies have not assessed the prognosis and predictive factors for CN VI recovery among patients presenting with CN VI deficits.
Methods: The medical records of patients who underwent resection for primary chordoma from 2001 to 2020 were reviewed.
Am J Transl Res
December 2024
Department of Infectious Diseases, Shanghai Fifth People's Hospital Shanghai 200240, China.
Objective: To investigate the association between the basic and clinical characteristics of patients with type 2 diabetes mellitus (T2DM) and their susceptibility to Klebsiella pneumoniae colonization (KPC). Additionally, a clinical prediction model was developed to identify high-risk patients for KPC.
Methods: Data from 486 T2DM patients who visited Shanghai Fifth People's Hospital from December 2020 to December 2022 were retrospectively collected.
PLoS One
January 2025
Department of Pediatrics and Child Health Nursing, School of Nursing, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Background: Access to healthcare services for women in low- and middle-income countries (LMICs) is crucial for maternal and child health and achieving the Sustainable Development Goals (SDGs). However, women in LMICs face barriers to accessing healthcare, leading to poor health outcomes. This study used Demographic and Health Survey (DHS) data from 61 LMICs between 2010-2023 to identify women's healthcare access challenges.
View Article and Find Full Text PDFObstet Gynecol
January 2025
Riley Children's, the Division of Maternal-Fetal Medicine, Indiana University Health Fetal Center, and the Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana; the Division of Maternal-Fetal Medicine and Surgery, Fetal Care and Surgery Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; the Department of Obstetrics and Gynecology, Brown University Medical School, Providence, Rhode Island; the Fetal Medicine Unit, St George's Hospital, St George's University of London, London, United Kingdom; the Division of Maternal-Fetal Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania; and the Division of Maternal-Fetal Medicine, The Ohio State University, Columbus, Ohio.
Objective: To investigate short-term maternal and neonatal outcomes in individuals with twin pregnancies and two prior cesarean deliveries who underwent trial of labor after cesarean (TOLAC).
Methods: A cross-sectional study of live-birth data was conducted between 2014 and 2021 in the United States. Individuals with more than two prior cesarean deliveries and multiple gestations higher than twins were excluded.
JMIR Med Educ
January 2025
Department of Ultrasound, Peking University First Hospital, 8 Xishiku Rd, Xicheng District, Beijing, 100034, China, 86 13132150190, 86 314521.
Background: Artificial intelligence advancements have enabled large language models to significantly impact radiology education and diagnostic accuracy.
Objective: This study evaluates the performance of mainstream large language models, including GPT-4, Claude, Bard, Tongyi Qianwen, and Gemini Pro, in radiology board exams.
Methods: A comparative analysis of 150 multiple-choice questions from radiology board exams without images was conducted.
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