Bartolome, J. (Javier)
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- Occult Hepatitis C virus infection among hemodialysis patients(American Society of Nephrology, 2008-12) Arenas, M.D. (María Dolores); Martinez, P. (Pilar); Barril, G. (Guillermina); Alcazar, J.M. (José María); Garcia-Fernandez, N. (Nuria); Castillo, I. (Inmaculada); Gonzalez-Parra, E. (Emilio); Espinosa, M. (Mario); Bartolome, J. (Javier); Sanchez, C. (Carmen); Carreño, V. (Vicente); Diez-Baylon, J.C. (José Carlos); Garcia-Valdecasas, J. (Juan)Occult hepatitis C virus (HCV) infection (i.e., detectable HCV-RNA in the liver or peripheral blood mononuclear cells) in the absence of both serum HCV-RNA and anti-HCV antibodies has not been investigated in hemodialysis patients. In this study, real-time PCR and in situ hybridization was used to test for the presence of genomic and antigenomic HCV-RNA in peripheral blood mononuclear cells of 109 hemodialysis patients with abnormal levels of liver enzymes. Occult HCV infection, determined by the presence of genomic HCV-RNA, was found in 45% of the patients; 53% of these patients had ongoing HCV replication, indicated by the presence of antigenomic HCV-RNA. Patients with occult HCV infection had spent a significantly longer time on hemodialysis and had significantly higher mean alanine aminotransferase levels during the 6 mo before study entry. Logistic regression analysis revealed that mortality was associated with age >60 yr (odds ratio 3.30; 95% confidence interval 1.05 to 10.33) and the presence of occult HCV infection (odds ratio 3.84; 95% confidence interval 1.29 to 11.43). In conclusion, the prevalence of occult HCV infection is high among hemodialysis patients with persistently abnormal values of liver enzymes of unknown cause. The clinical significance of occult HCV infection in these patients requires further study.
- Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence(2022) Orrillo, V. (Virginia); Gabaldón-Figueira, J.C. (Juan C.); Blavia, I. (Isabel); Chaccour, C.J. (Carlos J.); Giménez, G. (Gérard); Chaccour, J. (Juliane); Forouhi, N.G. (Nita G.); Fernandez-Montero, A. (Alejandro); Grandjean-Lapierre, S. (Simon); Bartolome, J. (Javier); Doré, D.H. (Dominique Hélène); Armendáriz, N. (Nuria); Keen, E. (Erik); Small, P. (Peter)Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs.h(-1); p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring.
- Prognostic value of human leukocyte antigen G expression in solid tumors: a systematic review and meta-analysis(2023) Perez-Segura, P. (Pedro); Ocaña, A. (Alberto); Benítez-Fuentes, J.D. (Javier David); Mittal, A. (Abhenil); Amir, E. (Eitan); Fernández-Hinojal, G. (Gonzalo); Molto, C. (Consolación); Bartolome, J. (Javier); Manzano, A. (Aranzazu); Tamimi, F. (Faris)Introduction Identification of modulators of the immune response with inhibitory properties that could be susceptible for therapeutic intervention is a key goal in cancer research. An example is the human leukocyte antigen G (HLA-G), a nonclassical major histocompatibility complex (MHC) class I molecule, involved in cancer progression.Methods In this article we performed a systematic review and meta-analysis on the association between HLA-G expression and outcome in solid tumors. This study was performed in accordance with PRISMA guidelines and registered in PROSPERO.Results A total of 25 studies met the inclusion criteria. These studies comprised data from 4871 patients reporting overall survival (OS), and 961 patients, reporting disease free survival (DFS). HLA-G expression was associated with worse OS (HR 2.09, 95% CI = 1.67 to 2.63; P < .001), that was higher in gastric (HR = 3.40; 95% CI = 1.64 to 7.03), pancreatic (HR = 1.72; 95% CI = 0.79 to 3.74) and colorectal (HR = 1.55; 95% CI = 1.16 to 2.07) cancer. No significant differences were observed between the most commonly utilized antibody (4H84) and other methods of detection. HLA-G expression was associated with DFS which approached but did not meet statistical significance.Discussion In summary, we describe the first meta-analysis associating HLA-G expression and worse survival in a variety of solid tumors.