20:T40c,ROC curve analysis is often applied to measure the diagnostic accuracy of a biomarker. The analysis results in two gains: diagnostic accuracy of the biomarker and the optimal cut-point value. There are many methods proposed in the literature to obtain the optimal cut-point value. In this study, a new approach, alternative to these methods, is proposed. The proposed approach is based on the value of the area under the ROC curve. This method defines the optimal cut-point value as the value whose sensitivity and specificity are the closest to the value of the area under the ROC curve and the absolute value of the difference between the sensitivity and specificity values is minimum. This approach is very practical. In this study, the results of the proposed method are compared with those of the standard approaches, by using simulated data with different distribution and homogeneity conditions as well as a real data. According to the simulation results, the use of the proposed method is advised for finding the true cut-point.21:T4ce,We conducted a prospective study of non-cardiac surgical patients aged 70 years or more in 23 hospitals in Australia and New Zealand. We studied 4158 consecutive patients of whom 2845 (68%) had pre-existing comorbidities. By day 30, 216 (5%) patients had died, and 835 (20%) suffered complications; 390 (9.4%) patients were admitted to the Intensive Care Unit. Pre-operative factors associated with mortality included: increasing age (80-89 years: OR 2.1 (95% CI 1.6-2.8), p < 0.001; 90+ years: OR 4.0 (95% CI 2.6-6.2), p < 0.001); worsening ASA physical status (ASA 3: OR 3.1 (95% CI 1.8-5.5), p < 0.001; ASA 4: OR 12.4 (95% CI 6.9-22.2), p < 0.001); a pre-operative plasma albumin < 30 g.l⁻¹ (OR: 2.5 (95% CI 1.8-3.5), p < 0.001); and non-scheduled surgery (OR 1.8 (95% CI 1.3-2.5), p < 0.001). Complications associated with mortality included: acute renal impairment (OR 3.3 (95% CI 2.1-5.0), p < 0.001); unplanned Intensive Care Unit admission (OR 3.1 (95% CI 1.9-4.9), p < 0.001); and systemic inflammation (OR 2.5 (95% CI 1.7-3.7), p < 0.001). Patient factors often had a stronger association with mortality than the type of surgery. Strategies are needed to reduce complications and mortality in older surgical patients.

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