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05 in univariate analysis were entered into a stepwise multivariate logistic regression. For each group of predictive variables (pre-operative patient characteristics, pre-operative functional status, lesion characteristics, operative characteristics and post-operative outcomes), a different model was constructed to eliminate the dependence of regressors. For this reason, we estimated five different models. Odds ratios (ORs) and 95% Bosutinib datasheet confidence intervals (95% CIs) were calculated in each model and for each factor as exponential of the variable coefficient (beta). The risk score was calculated by assigning scores (simple numerical scores: 0,?+1, etc.) in relation to the estimated OR. A score was assigned to each significant variable. A web-based scoring system was developed from these factors to predict the percentage probability of losing baseline functional status at 1 year. The total score was the result of the sum of the single scores (ss). To obtain a standardised score (CLI score), it was necessary to adjust the total score according to its minimum (min) and maximum (max) values: CLIscore=��ss+|min|max+|min|?100. Standardisation of total score enabled the probability of having a certain 1-year functional status after revascularisation to be expressed as percentage risk, facilitating interpretation of the results. To assess the classification score performance, receiver Alpelisib operating curves (ROCs) with optimal specificity and sensitivity levels were reported. Kaplan�CMeier survival analysis and life tables were used to examine the distribution of post-operative outcomes Dabigatran during follow-up. A p value