98%
921
2 minutes
20
Background: Screening for depression remains a priority for people living with HIV (PLWH) accessing care. The 9-item Patient Health Questionnaire (PHQ-9) is a widely used depression screening tool, but has limited accuracy when applied across various cultural contexts. We aimed to evaluate the performance of alternative PHQ-9 scoring algorithms in sub-Saharan African PLWH.
Setting: Five HIV programs in Cameroon, Côte d'Ivoire, Kenya, Senegal, and the Republic of Congo.
Methods: Adult PLWH were screened for depression during the 2018-2022 period. Diagnosis confirmation was done by psychiatrist blinded clinical evaluation (gold standard). Diagnostic performances, including sensitivity and area under the curve (AUC) of the traditional PHQ-9 scoring (positive screening - score ≥ 10), were compared to alternative scoring algorithms including (1) the presence of ≥1 mood symptom (PHQ-9 items 1 and 2) combined with ≥2 other symptoms listed in the PHQ-9, and (2) a simplified recoding of each 4-response item into 2 categories (absence/presence).
Results: A total of 735 participants were included [54% women, median age 42 years (interquartile range 34-50)]. Depression was diagnosed by a psychiatrist in 95 (13%) participants. Alternative scoring sensitivities (0.59-0.74) were higher than that of the traditional score's (0.39). Compared to traditional scoring, AUC was significantly higher for PHQ-9 alternative scoring. Across settings, alternative scoring algorithms increased sensitivity and reduced variability.
Conclusions: As a primary screening test, new scoring algorithms seemed to improve the PHQ-9 sensitivity in identifying depression and reducing heterogeneity across settings. This alternative might be considered to identify PLWH in need of referral for further diagnostic evaluations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11708998 | PMC |
http://dx.doi.org/10.1097/QAI.0000000000003551 | DOI Listing |
BMC Oral Health
September 2025
Oral and Maxillofacial Radiology Department, Cairo university, Cairo, Egypt.
Aim: The purpose of this study was to assess the accuracy of a customized deep learning model based on CNN and U-Net for detecting and segmenting the second mesiobuccal canal (MB2) of maxillary first molar teeth on cone beam computed tomography (CBCT) scans.
Methodology: CBCT scans of 37 patients were imported into 3D slicer software to crop and segment the canals of the mesiobuccal (MB) root of the maxillary first molar. The annotated data were divided into two groups: 80% for training and validation and 20% for testing.
Zhonghua Jie He He Hu Xi Za Zhi
September 2025
Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
To explore the feasibility and accuracy of predicting respiratory tract infections (RTIs) using physiological data obtained from consumer-grade smartwatches. The study used smartwatches and paired mobile applications to continuously collect physiological parameters while participants slept. A personalized baseline model was established using multi-day data, followed by the construction of RTIs risk prediction algorithm based on deviations from physiological parameter trends.
View Article and Find Full Text PDFMed Eng Phys
October 2025
College of Basic Medical Science, Shanxi University of Chinese Medicine, Jinzhong, 030619, Shanxi, China.
Pulse diagnosis holds a pivotal role in traditional Chinese medicine (TCM) diagnostics, with pulse characteristics serving as one of the critical bases for its assessment. Accurate classification of these pulse pattern is paramount for the objectification of TCM. This study proposes an enhanced SMOTE approach to achieve data augmentation, followed by multi-domain feature extraction.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Computer Science, COMSATS University Islamabad, Sahiwal, Pakistan.
The widespread dissemination of fake news presents a critical challenge to the integrity of digital information and erodes public trust. This urgent problem necessitates the development of sophisticated and reliable automated detection mechanisms. This study addresses this gap by proposing a robust fake news detection framework centred on a transformer-based architecture.
View Article and Find Full Text PDFPLoS One
September 2025
Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Background: Metabolic syndrome (MetS) and sarcopenia are major global public health problems, and their coexistence significantly increases the risk of death. In recent years, this trend has become increasingly prominent in younger populations, posing a major public health challenge. Numerous studies have regarded reduced muscle mass as a reliable indicator for identifying pre-sarcopenia.
View Article and Find Full Text PDF