Thoracoscore: Predicting risk of in-hospital mortality for patients undergoing pulmonary resection
Abstract
Background/Aim. Thoracic surgery is in need of a widely recognized and dependable risk model which could prospectively make objective conclusions and retrospectively allow comparison of outcomes. Thoracoscore is the first model with multiple variables developed for predicting in-hospital mortality following pulmonary resections. It is integrated in the British Thoracic Society and National Institute of Health and Clinical Excellence guidelines. However, additional evaluation of Thoracoscore is considerably advised in order to demonstrate its validity and potentially make it a dependable tool for thoracic surgeons across the world. Our study assesses the accuracy of Thoracoscore scoring system in estimating in-hospital mortality in patients undergoing pulmonary resections. Methods. Between September 2013 and October 2014 data were retrospectively collected on 196 patients operated on at the Thoracic Surgery Clinic, Institute of Pulmonary Diseases of Vojvodina. The procedures performed were: pneumonectomies, lobectomies and modified lobectomies (including bilobectomy and sleeve-lobectomy), Wedge resections and atypical resections. The Thoracoscore was calculated based on these nine variables: age, sex, American Society of Anaesthesiologists' (ASA) class, performance status classification, dyspnea score, priority of surgery, procedure class, diagnosis group and comorbidities score. Results. Study included one hundred and ninety-six patients, average age of 62 ± 9 years, and 61% were males. Predicted mean in-hospital mortality was 3.6 ± 3.2% 95% confidence interval (CI) 3.16–4.06, and mean actual in-hospital mortality was 6/196 (3.1%) (95% CI 1.78–4.42). Patients who were > 65 years old contributed to 3/6 (50%) of in-hospital mortality, and 4/6 (67%)were males. Four of 6 (67%) patients underwent pneumonectomy due to malignant pathology. Thoracoscore was divided into 4 risk groups: low (0–3), moderate (3.1–5), high (5.1–8) and very high (> 8). The correlation between observed and expected mortality was 0.99, by category of risk. Old age, male gender and malignancy showed to be strong indicators of in-hospital mortality. Conclusion. At our department Thoracoscore presented with good performance and as a practical tool for predicting in-hospital mortality among patients undergoing lung resections. However, any risk scoring system needs further validation before implementation and outcomes must be compared to those of other programs.
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