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5% or less was allowed. Table?3 shows the number of patients with a prolongation of http://www.selleck.cn/products/Cisplatin.html shows the number of patients with a prolongation of http://www.selleckchem.com/products/3-methyladenine.html that higher HbA1c, number of retinal haemorrhages and exudates, longer diabetes duration and blood pressure are associated with a ��no prediction��. These patients always had hard exudates or a haemoglobin A1c value higher than 10.6%, complying with the fact that these patients belonged to a high-risk group that would be recommended a short screening interval per se. This is the first study to present an evidence-based model for individualized determination of the interval to the following examinations in a screening programme for diabetic retinopathy. Several methods could have been used for building such a model. A prediction model based on the Bayesian networks method would have taken into account the fact that the included variables were not independent http://www.selleckchem.com/products/PD-0325901.html and would not have been sensitive to a lack of one or more variables during decision making for the individual patient (Jensen 1996). A prediction model could also have been built as a parametric statistical model with one of the parameters as a regression coefficient for the length of the screening interval. However, because approximately 75% of the patients had not reached a treatment end-point (Mehlsen et?al. 2009), standard parametric survival analysis models could not have been used. Instead, we used logistic regression to estimate the probability of reaching an event within a given time interval that was included as a variable. Screening programmes with fixed intervals between examinations are known in many medical specialties, and the statistical analysis of such data can be handled with standard techniques. However, screening programmes in which the time interval to the following examination depends on the severity of the disease are more difficult to analyse, because the time interval is not allocated at random but acts as a time-dependent confounder.