Longitudinal deep learning clustering of Type 2 Diabetes Mellitus trajectories using routinely collected health records.

Type 2 diabetes mellitus (T2DM) is a highly heterogeneous chronic disease with different pathophysiological and genetic characteristics affecting its progression, associated complications and response to therapies. The advances in deep learning (DL) techniques and the availability of a large amount of healthcare data allow us to investigate T2DM characteristics and evolution with a completely new approach, studying common disease trajectories rather than cross sectional values. We used an Kernelized-AutoEncoder algorithm to map 5 years of data of 11,028 subjects diagnosed with T2DM in a latent space that embedded similarities and differences between patients in terms of the evolution of the disease. Once we obtained the latent space, we used classical clustering algorithms to create longitudinal clusters representing different evolutions of the diabetic disease. Our unsupervised DL clustering algorithm suggested seven different longitudinal clusters. Different mean ages were observed among the clusters (ranging from 65.3±11.6 to 72.8±9.4). Subjects in clusters B (Hypercholesteraemic) and E (Hypertensive) had shorter diabetes duration (9.2±3.9 and 9.5±3.9 years respectively). Subjects in Cluster G (Metabolic) had the poorest glycaemic control (mean glycated hemoglobin 7.99±1.42%), while cluster E had the best one (mean glycated hemoglobin 7.04±1.11%). Obesity was observed mainly in clusters A (Neuropathic), C (Multiple Complications), F (Retinopathy) and G. A dashboard is available at dm2.b2slab.upc.edu to visualize the different trajectories corresponding to the 7 clusters.

A molecular hypothesis to explain direct and inverse co-morbidities between Alzheimer's Disease, Glioblastoma and Lung cancer.

Epidemiological studies indicate that patients suffering from Alzheimer's disease have a lower risk of developing lung cancer, and suggest a higher risk of developing glioblastoma. Here we explore the molecular scenarios that might underlie direct and inverse co-morbidities between these diseases. Transcriptomic meta-analyses reveal significant numbers of genes with inverse patterns of expression in Alzheimer's disease and lung cancer, and with similar patterns of expression in Alzheimer's disease and glioblastoma. These observations support the existence of molecular substrates that could at least partially account for these direct and inverse co-morbidity relationships. A functional analysis of the sets of deregulated genes points to the immune system, up-regulated in both Alzheimer's disease and glioblastoma, as a potential link between these two diseases. Mitochondrial metabolism is regulated oppositely in Alzheimer's disease and lung cancer, indicating that it may be involved in the inverse co-morbidity between these diseases. Finally, oxidative phosphorylation is a good candidate to play a dual role by decreasing or increasing the risk of lung cancer and glioblastoma in Alzheimer's disease.

Accuracy of an Immunochromatographic Diagnostic Test (ICT Malaria Combo Cassette Test) Compared to Microscopy among under Five-Year-Old Children when Diagnosing Malaria in Equatorial Guinea

Conventional malaria diagnosis based on microscopy raises serious difficulties in weak health systems. Cost-effective and sensitive rapid diagnostic tests have been recently proposed as alternatives to microscopy. In Equatorial Guinea; a study was conducted to assess the reliability of a rapid diagnostic test compared to microscopy. The study was designed in accordance with the directives of the Standards for Reporting Diagnostic Accuracy Initiative (STARD). Peripheral thick and thin films for the microscopy diagnosis and a rapid immunochromatographic test (ICT Malaria Combo Cassette Test) were performed on under five-year-old children with malaria suspicion. The ICT test detected Plasmodium spp. infection with a sensitivity of 81.5and a specificity of 81.9while P. falciparum diagnosis occurred with a sensitivity of 69.7and a specificity of 73.7. The sensitivity of the ICT test increased with higher parasitemias. The general results showed little concordance between the ICT test and microscopy (kappa = 0.28; se: 0.04). In Equatorial Guinea; the ICT Malaria Combo Cassette Test has proven to be an acceptable test to detect high P. falciparum parasitemias. However; the decrease of sensitivity at medium and low parasitemias hampers that ICT can replace properly performed microscopy at present in the diagnosis of malaria in children

Accuracy of an Immunochromatographic Diagnostic Test (ICT Malaria Combo Cassette Test) Compared to Microscopy among under Five-Year-Old Children when Diagnosing Malaria in Equatorial Guinea.

Conventional malaria diagnosis based on microscopy raises serious difficulties in weak health systems. Cost-effective and sensitive rapid diagnostic tests have been recently proposed as alternatives to microscopy. In Equatorial Guinea, a study was conducted to assess the reliability of a rapid diagnostic test compared to microscopy. The study was designed in accordance with the directives of the Standards for Reporting Diagnostic Accuracy Initiative (STARD). Peripheral thick and thin films for the microscopy diagnosis and a rapid immunochromatographic test (ICT Malaria Combo Cassette Test) were performed on under five-year-old children with malaria suspicion. The ICT test detected Plasmodium spp. infection with a sensitivity of 81.5% and a specificity of 81.9% while P. falciparum diagnosis occurred with a sensitivity of 69.7% and a specificity of 73.7%. The sensitivity of the ICT test increased with higher parasitemias. The general results showed little concordance between the ICT test and microscopy (kappa = 0.28, se: 0.04). In Equatorial Guinea, the ICT Malaria Combo Cassette Test has proven to be an acceptable test to detect high P. falciparum parasitemias. However, the decrease of sensitivity at medium and low parasitemias hampers that ICT can replace properly performed microscopy at present in the diagnosis of malaria in children.