: The gonadotropin-releasing hormone (GnRH) stimulation test is the gold standard method for diagnosing central precocious puberty (CPP), although it requires multiple blood samplings over 120 min. This study aimed to evaluate if a shorter test may have an equivalent diagnostic accuracy. : We retrospectively reviewed the GnRH tests of 188 consecutive pediatric patients (169 females) referred for signs of early pubertal development. The diagnostic accuracy of the hormonal levels was evaluated at different time points (15, 0, 60, 90, and 120 min after the GnRH stimulus). A diagnosis of CPP was made in 130 cases (69%), with 111 (85%) being female. Sensitivity and specificity ratings higher than 99% for the diagnosis of CPP were achieved for LH levels ≥4.7 mU/mL at 30 and 60 min after the stimulus (area under the ROC curve (AUC) = 1), with no further increase in the diagnostic accuracy in the remaining time points. No sex differences in diagnostic accuracy were found. The LH/FSH ratio at 30 min showed a sensitivity of 94.9%, with an AUC of 0.997 and a value ≥0.76. A short-duration GnRH test of 60 min provided optimal results for the diagnosis of CPP. Extending the test for an extra hour is therefore unnecessary and inadvisable.
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http://dx.doi.org/10.3390/medicina60010024 | DOI Listing |
ACS Sens
January 2025
Department of Physics and Astronomy, Franklin College of Arts and Sciences, The University of Georgia, Athens, Georgia 30602, United States.
Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatment, and disease management. We present a label-free diagnostic platform integrating surface-enhanced Raman scattering (SERS) with deep learning for rapid, quantitative detection of respiratory virus coinfections. Using sensitive silica-coated silver nanorod array substrates, over 1.
View Article and Find Full Text PDFJMIR Cancer
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.
Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.
View Article and Find Full Text PDFReprod Fertil Dev
January 2025
Fertility & Research Centre, Discipline of Women health, School of Clinical Medicine and the Royal Hospital for Women, University of New South Wales, Sydney, NSW, Australia.
Pre-implantation genetic testing for aneuploidy (PGT-A) via embryo biopsy helps in embryo selection by assessing embryo ploidy. However, clinical practice needs to consider the invasive nature of embryo biopsy, potential mosaicism, and inaccurate representation of the entire embryo. This creates a significant clinical need for improved diagnostic practices that do not harm embryos or raise treatment costs.
View Article and Find Full Text PDFJ Am Podiatr Med Assoc
January 2025
†Medical Point Gaziantep Hospital, Gaziantep, Turkey.
Background: The incidence of diabetic foot infections is increasing due to the rising number of persons with diabetes and the prolonged life expectancy. It is vital to differentiate soft-tissue infection (STI) from diabetic foot osteomyelitis (DFO), as treatment modalities and durations vary widely, but this can be challenging. We aimed to assess the blood concentration levels of the high mobility group box 1 protein (HMGB-1) in STI and DFO compared to healthy subjects, and to investigate whether this protein could contribute to differentiating STI from DFO.
View Article and Find Full Text PDFLymphology
January 2025
Medical Biophysics Department, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!