Background: Acute respiratory infections (ARIs) are common in children. We developed machine learning models to predict pediatric ARI pathogens at admission.
Methods: We included hospitalized children with respiratory infections between 2010 and 2018. Clinical features were collected within 24 h of admission to construct models. The outcome of interest was the prediction of 6 common respiratory pathogens, including adenovirus, influenza virus types A and B, parainfluenza virus (PIV), respiratory syncytial virus (RSV), and Mycoplasma pneumoniae (MP). Model performance was estimated using area under the receiver operating characteristic curve (AUROC). Feature importance was measured using Shapley Additive exPlanation (SHAP) values.
Results: A total of 12,694 admissions were included. Models trained with 9 features (age, event pattern, fever, C-reactive protein, white blood cell count, platelet count, lymphocyte ratio, peak temperature, peak heart rate) achieved the best performance (AUROC: MP 0.87, 95% CI 0.83-0.90; RSV 0.84, 95% CI 0.82-0.86; adenovirus 0.81, 95% CI 0.77-0.84; influenza A 0.77, 95% CI 0.73-0.80; influenza B 0.70, 95% CI 0.65-0.75; PIV 0.73, 95% CI 0.69-0.77). Age was the most important feature to predict MP, RSV and PIV infections. Event patterns were useful for influenza virus prediction, and C-reactive protein had the highest SHAP value for adenovirus infections.
Conclusion: We demonstrate how artificial intelligence can assist clinicians identify potential pathogens associated with pediatric ARIs upon admission. Our models provide explainable results that could help optimize the use of diagnostic testing. Integrating our models into clinical workflows may lead to improved patient outcomes and reduce unnecessary medical costs.
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http://dx.doi.org/10.1016/j.jmii.2023.04.011 | DOI Listing |
Elife
December 2024
Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
An unprecedented amount of SARS-CoV-2 data has been accumulated compared with previous infectious diseases, enabling insights into its evolutionary process and more thorough analyses. This study investigates SARS-CoV-2 features as it evolved to evaluate its infectivity. We examined viral sequences and identified the polarity of amino acids in the receptor binding motif (RBM) region.
View Article and Find Full Text PDFIJID Reg
March 2025
Regional Level Viral Research & Diagnostic Laboratory (RVRDL), Department of Microbiology, Jawaharlal Institute of Post-Graduate Medical Education and Research (JIPMER), Puducherry, India.
Objectives: Human metapneumovirus (hMPV) is recognized as a significant cause of acute respiratory infections among infants under 5 years of age.
Methods: Nasal swabs collected from January 2021 to June 2024 were screened to detect hMPV using reverse transcription-quantitative polymerase chain reaction. Furthermore, representative positive samples were sequenced and subjected to phylogenetic analysis.
Toxicol Rep
December 2024
Laboratory of Forensic Chemistry and Toxicology, School of Forensic Sciences, National Forensic Sciences University, Delhi, India.
Antibiotics are indispensable in modern healthcare, playing a critical role in mitigating bacterial infections. Azithromycin is used to fight upper respiratory tract infections, however has potential toxic effects that remain inadequately understood. In our present study, azithromycin exposure to led to significant physiological and behavioral change, with pronounced effects observed at the studied concentration.
View Article and Find Full Text PDFBiochem Biophys Rep
March 2025
Department of Physiology, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria.
A global decline in male fertility has been reported, and climate change is considered a major cause of this. Climate change refers to long-term shifts in temperatures and weather patterns, and results from greenhouse gas emissions like carbon dioxide and methane that act as a blanket wrapped around the earth, trapping heat and elevating temperatures. Sad to say, the consequences of climatic variation are beyond the dramatic elevated temperature, they include cold stress, increased malnutrition, air pollution, cardiovascular diseases respiratory tract infections, cancer, sexually transmitted infections, mental stress, and heat waves.
View Article and Find Full Text PDFFront Immunol
December 2024
Department of Life Science Frontiers, Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan.
Age-associated differences in the effect of repetitive vaccination, particularly on memory T-cell and B-cell responses, remain unclear. While older adults (aged ≥65 years) exhibited enhanced IgG responses following COVID-19 mRNA booster vaccination, they produced fewer spike-specific circulating follicular helper T cells-1 than younger adults. Similarly, the cytotoxic CD8 T-cell response remained diminished with reduced PD-1 expression even after booster vaccination compared with that in younger adults, suggesting impaired memory T-cell activation in older adults.
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