La medicina rural: una visión mirando al futuro

The management of any large building stock with limited resources poses a problem of prioritization of refurbishment actions. Also, available technical information about the building stock is often incomplete and the process of standardization and updating is expensive and time consuming. Some public owners are developing preliminary BIM models of their stock, but they are willing to limit the complexity of the models within the lowest amount of information required for management and maintenance, so as to make that process affordable. Indeed, administrations are challenged by their duty relative to planning regular maintenance and operation of buildings, because of the legislation in force, which requires monitoring of their facilities. For the reasons stated above, this paper presents a decision support tool that can help prioritize refurbishment actions on large building assets. To this purpose, many requirements must be jointly considered in this examination, each requirement being assessed by means of one or several indicators. Then the indicators are compared one another, according to a multi-criteria approach, that weighs the several criteria and rank the assets. In order to deal with the extensive and uncertain information that must be managed in this process, indicators are estimated by means of Bayesian Networks. This tool is used first to assess the technical indicators and rank the assets, while marking any facilities not complying with regulations. Then, additional Bayesian Networks are in charge of estimating the budget needed to upgrade non-compliant facilities with minimum legislation requirements. The outcomes of this research can be used even to assess the level of detail of the information that must be included in BIM models of the stock, in fact acting as guidelines for their development. Finally, the application of the decision tool on a real test case will be presented

Optimizing the diagnostic work-up of acute uncomplicated urinary tract infections

<p>Abstract</p> <p>Background</p> <p>Most diagnostic tests for acute uncomplicated urinary tract infections (UTIs) have been previously studied in so-called single-test evaluations. In practice, however, clinicians use more than one test in the diagnostic work-up. Since test results carry overlapping information, results from single-test studies may be confounded. The primary objective of the Amsterdam Cystitis/Urinary Tract Infection Study (ACUTIS) is to determine the (additional) diagnostic value of relevant tests from patient history and laboratory investigations, taking into account their mutual dependencies. Consequently, after suitable validation, an easy to use, multivariable diagnostic rule (clinical index) will be derived.</p> <p>Methods</p> <p>Women who contact their GP with painful and/or frequent micturition undergo a series of possibly relevant tests, consisting of patient history questions and laboratory investigations. Using urine culture as the reference standard, two multivariable models (diagnostic indices) will be generated: a model which assumes that patients attend the GP surgery and a model based on telephone contact only. Models will be made more robust using the bootstrap. Discrimination will be visualized in high resolution histograms of the posterior UTI probabilities and summarized as 5^th, 10^th, 25^th50^th, 75^th, 90^th, and 95^thcentiles of these, Brier score and the area under the receiver operating characteristics curve (ROC) with 95% confidence intervals. Using the regression coefficients of the independent diagnostic indicators, a diagnostic rule will be derived, consisting of an efficient set of tests and their diagnostic values.</p> <p>The course of the presenting complaints is studied using 7-day patient diaries. To learn more about the natural history of UTIs, patients will be offered the opportunity to postpone the use of antibiotics.</p> <p>Discussion</p> <p>We expect that our diagnostic rule will allow efficient diagnosis of UTIs, necessitating the collection of diagnostic indicators with proven added value. GPs may use the rule (preferably after suitable validation) to estimate UTI probabilities for women with different combinations of test results. Finally, in a subcohort, an attempt is made to identify which indicators (including antibiotic treatment) are useful to prognosticate recovery from painful and/or frequent micturition.</p