4 research outputs found

    Effectiveness and costs of phototest in dementia and cognitive impairment screening

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    <p>Abstract</p> <p>Background</p> <p>To assess and compare the effectiveness and costs of Phototest, Mini Mental State Examination (MMSE), and Memory Impairment Screen (MIS) to screen for dementia (DEM) and cognitive impairment (CI).</p> <p>Methods</p> <p>A phase III study was conducted over one year in consecutive patients with suspicion of CI or DEM at four Primary Care (PC) centers. After undergoing all screening tests at the PC center, participants were extensively evaluated by researchers blinded to screening test results in a Cognitive-Behavioral Neurology Unit (CBNU). The gold standard diagnosis was established by consensus of expert neurologists. Effectiveness was assessed by the proportion of correct diagnoses (diagnostic accuracy [DA]) and by the kappa index of concordance between test results and gold standard diagnoses. Costs were based on public prices and hospital accounts.</p> <p>Results</p> <p>The study included 140 subjects (48 with DEM, 37 with CI without DEM, and 55 without CI). The MIS could not be applied to 23 illiterate subjects (16.4%). For DEM, the maximum effectiveness of the MMSE was obtained with different cutoff points as a function of educational level [k = 0.31 (95% Confidence interval [95%CI], 0.19-0.43), DA = 0.60 (95%CI, 0.52-0.68)], and that of the MIS with a cutoff of 3/4 [k = 0.63 (95%CI, 0.48-0.78), DA = 0.83 (95%CI, 0.80-0.92)]. Effectiveness of the Phototest [k = 0.71 (95%CI, 0.59-0.83), DA = 0.87 (95%CI, 0.80-0.92)] was similar to that of the MIS and higher than that of the MMSE. Costs were higher with MMSE (275.9 ± 193.3€ [mean ± sd euros]) than with Phototest (208.2 ± 196.8€) or MIS (201.3 ± 193.4€), whose costs did not significantly differ. For CI, the effectiveness did not significantly differ between MIS [k = 0.59 (95%CI, 0.45-0.74), DA = 0.79 (95%CI, 0.64-0.97)] and Phototest [k = 0.58 (95%CI, 0.45-0.74), DA = 0.78 (95%CI, 0.64-0.95)] and was lowest for the MMSE [k = 0.27 (95%CI, 0.09-0.45), DA = 0.69 (95%CI, 0.56-0.84)]. Costs were higher for MMSE (393.4 ± 121.8€) than for Phototest (287.0 ± 197.4€) or MIS (300.1 ± 165.6€), whose costs did not significantly differ.</p> <p>Conclusion</p> <p>MMSE is not an effective instrument in our setting. For both DEM and CI, the Phototest and MIS are more effective and less costly, with no difference between them. However, MIS could not be applied to the appreciable percentage of our population who were illiterate.</p

    Discovering HIV related information by means of association rules and machine learning

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    Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts

    Characteristics and predictors of death among 4035 consecutively hospitalized patients with COVID-19 in Spain

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