17 research outputs found

    Forecasting Causes of Death in Northern Iraq Using Neural Network

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    The availability of models for predicting future events is essential for enhancing the efficiency of systems. This paper attempts to predict demographic variation by employing multi-layer perceptron network. Here we present the implementation of a system for predicting the number and causes of deaths, for a future 2-year period. The system was built using predictive models and data that is as accurate as possible under the current conditions of the northern Region of Iraq (the Autonomous Region of Kurdistan). Our predictive model is based on quarterly periods, with the intention of providing predictions on the number of deaths, classified by gender, cause of death, age at death, administrative district (governorate), and hospital where the death occurred. The data was collected from birth and death registry bureaus and forensic medicine departments for the years 2009-2020. The python programming language was used to test the designed multi-layer perceptron network with backpropagation training algorithm. With learning rate 0.01 and 500 epochs we were able to obtain good results, as the neural network was able to represent the string, and predict future values well, with a mean squared error of 0.43, and we found that number of deaths is quite stable, with a slight increase

    The aggregate data problem

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    A data structure for the formal definition of aggregate data

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    Published December 1995Consiglio Nazionale delle Ricerche (CNR). Biblioteca Centrale / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

    ADAMO: a conceptual model for aggregate data

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    Biblioteca Centrale CNR / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

    Could Long\u2010Acting Cabotegravir\u2010Rilpivirine Be the Future for All People Living with HIV? Response Based on Genotype Resistance Test from a Multicenter Italian Cohort

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    Long\u2010acting (LA) formulations have been designed to improve the quality of life of people with HIV (PWH) by maintaining virologic suppression. However, clinical trials have shown that patient selection is crucial. In fact, the HIV\u20101 resistance genotype test and the Body Mass Index of individual patients assume a predominant role in guiding the choice. Our work aimed to estimate the patients eligible for the new LA therapy with cabotegravir (CAB) + rilpivirine (RPV). We selected, from the Antiviral Response Cohort Analysis (ARCA) database, all PWH who had at least one follow\u2010up in the last 24 months. We excluded patients with HBsAg positivity, evidence of non-nucleoside reverse transcriptase inhibitor (except K103N) and integrase inhibitor mutations, and with a detectable HIV\u2010RNA (>50 copies/mL). Overall, 4103 patients are currently on follow\u2010up in the ARCA, but the eligible patients totaled 1641 (39.9%). Among them, 1163 (70.9%) were males and 1399 were Caucasian (85.3%), of which 1291 (92%) were Italian born. The median length of HIV infection was 10.2 years (IQR 6.3\u201316.3) with a median nadir of CD4 cells/count of 238 (106\u2013366) cells/mm3 and a median last available CD4 cells/count of 706 (509\u2013944) cells/mm3. The majority of PWH were treated with a three\u2010drug regimen (n = 1116, 68%). Among the 525 (30.3%) patients treated with two\u2010drug regimens, 325 (18.1%) were treated with lamivudine (3TC) and dolutegravir (DTG) and only 84 (5.1%) with RPV and DTG. In conclusion, according to our snapshot, roughly 39.9% of virologically suppressed patients may be suitable candidates for long\u2010acting CAB+RPV therapy. Therefore, based on our findings, many different variables should be taken into consideration to tailor the antiretroviral treatment according to different individual characteristics

    Evaluation of HIV-1 integrase resistance emergence and evolution in patients treated with integrase inhibitors

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    Objectives: This study evaluated the emergence of mutations associated with integrase strand transfer inhibitors (INSTI) resistance (INSTI-RMs) and the integrase evolution in human immunodeficiency virus type 1 (HIV-1) infected patients treated with this drug class. Methods: The emergence of INSTI-RMs and integrase evolution (estimated as genetic distance between integrase sequences under INSTI treatment and before INSTI treatment) were evaluated in 107 INSTI-naïve patients (19 drug-naïve and 88 drug-experienced) with two plasma genotypic resistance tests: one before INSTI treatment and one under INSTI treatment. A logistic regression analysis was performed to evaluate factors associated with the integrase evolution under INSTI treatment. Results: The patients were mainly infected by B subtype (72.0%). Eighty-seven patients were treated with raltegravir, 13 with dolutegravir and seven with elvitegravir. Before INSTI treatment one patient harboured the major INSTI-RM R263K and three patients the accessory INSTI-RMs T97A. Under INSTI treatment the emergence of ≥1 INSTI-RM was found in 39 (36.4%) patients. The major INSTI-RMs that more frequently emerged were: N155H (17.8%), G140S (8.4%), Y143R (7.5%), Q148H (6.5%), and Y143C (4.7%). Concerning integrase evolution, a higher genetic distance was found in patients with ≥1 INSTI-RM compared with those without emergence of resistance (0.024 [0.012–0.036] vs. 0.015 [0.009–0.024], P = 0.018). This higher integrase evolution was significantly associated with a longer duration of HIV-1 infection, a higher number of past regimens and non-B subtypes. Conclusions: These findings confirm that major INSTI-RMs very rarely occur in INSTI-naïve patients. Under INSTI treatment, selection of drug-resistance follows the typical drug-resistance pathways; a higher evolution characterises integrase sequences developing drug-resistance compared with those without any resistance

    Prevalence and factors associated with HIV-1 multi-drug resistance over the past two decades in the Italian ARCA database

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    Despite successful antiretroviral therapy (ART), patients infected with human immunodeficiency virus (HIV) can develop multi-class drug resistance (MDR). This retrospective study aimed to explore the prevalence of HIV-1 drug resistance over the past two decades by focusing on HIV-MDR and its predictors. ART-experienced patients with HIV with results from at least one plasma genotypic resistance test (GRT) from 1998 to 2018, from the Antiviral Response Cohort Analysis database, were included in this study. The temporal trend of resistance to any drug class was evaluated by considering all GRTs. Prevalence and predictors of HIV-MDR were analysed by consideration of cumulative GRTs. Among 15 628 isolates from 6802 patients, resistance to at least one drug class decreased sharply from 1998 to 2010 (1998–2001: 78%; 2008–2010: 59%; P<0.001) and then remained relatively constant at approximately 50% from 2011 to 2018, with the proportion of isolates with HIV-MDR also stable (approximately 9%). By evaluating factors associated with cumulative HIV-MDR, the following factors were found to be associated with increased risk of HIV-MDR on multi-variate analysis: male gender; sexual and vertical transmission; number of previous protease inhibitors, nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) and non-NRTIs; previous exposure to integrase strand transfer inhibitors, enfuvirtide and maraviroc; and co-infection with hepatitis B virus. In contrast, a nadir CD4 cell count ≥200 cells/mm3, starting first-line ART in 2008 or later and co-infection with hepatitis C virus were associated with lower risk of HIV-MDR. In conclusion, this study revealed that HIV-1 drug resistance has been stable since 2011 despite its dramatic decrease over the past two decades. HIV-MDR is still present, although at a lower rate, suggesting the need for continuous surveillance and accurate management of ART-experienced patients with HIV. © 2020 Elsevier Ltd and International Society of Antimicrobial Chemotherap
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