M G Huisman1, R A Audisio2, G Ugolini3, I Montroni3, A Vigano4, J Spiliotis5, C Stabilini6, N de Liguori Carino7, E Farinella8, G Stanojevic9, B T Veering10, M W Reed11, P S Somasundar12, G H de Bock13, B L van Leeuwen14. 1. University of Groningen, University Medical Center Groningen, Department of Surgery, Hanzeplein 1, 9713 GZ Groningen, The Netherlands. Electronic address: m.g.huisman@umcg.nl. 2. University of Liverpool, St. Helens Teaching Hospital, Department of Surgery, Marshalls Cross Road, St. Helens, WA9 3DA, United Kingdom. 3. University of Bologna, S. Orsola Malpighi Hospital, Department of Surgery, Via Pietro Albertoni, 15, 40138 Bologna, Italy. 4. McGill University Health Center, Montreal General Hospital, Department of Oncology, 1650 Cedar Avenue, Montreal, Quebec H3G 1A4, Canada. 5. Metaxa Cancer Hospital, Department of Surgery, Mpotasi 51, 185 37 Piraeus, Greece; Regional University Hospital of Patras, Department of Surgery, Patras, Greece. 6. San Martino University Hospital, Department of Surgery, Largo Rosanna Benzi, 10, 16132 Genua, Italy. 7. Central Manchester University Hospitals, Manchester Royal Infirmary, Department of Hepato-Pancreato-Biliary Surgery, Oxford Road, Manchester M13 9WL, United Kingdom. 8. S. Maria Hospital, Department of Surgery, Azienda Ospedaliera di Perugia Via Brunamonti, 51 06122 Perugia, Italy. 9. Clinic for General Surgery, Clinical Center Nis, Bulevar Zorana Djindjica 48, 1800 Nis, Serbia. 10. University of Leiden, Leiden University Medical Center, Department of Anesthesiology, Albinusdreef 2, 2333 ZA Leiden, The Netherlands. 11. University of Sheffield, Department of Oncology, Beech Hill Road, Sheffield, South Yorkshire S10 2RX, United Kingdom. 12. Roger Williams Medical Center, Division of Surgical Oncology, Affiliate of Boston University, 50 Maude Street, Providence, RI 02908, United States. 13. University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands. 14. University of Groningen, University Medical Center Groningen, Department of Surgery, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
Abstract
AIMS: The aim of this study was to investigate the predictive ability of screening tools regarding the occurrence of major postoperative complications in onco-geriatric surgical patients and to propose a scoring system. METHODS: 328 patients ≥ 70 years undergoing surgery for solid tumors were prospectively recruited. Preoperatively, twelve screening tools were administered. Primary endpoint was the incidence of major complications within 30 days. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using logistic regression. A scoring system was derived from multivariate logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was applied to evaluate model performance. RESULTS: At a median age of 76 years, 61 patients (18.6%) experienced major complications. In multivariate analysis, Timed Up and Go (TUG), ASA-classification and Nutritional Risk Screening (NRS) were predictors of major complications (TUG>20 OR 3.1, 95% CI 1.1-8.6; ASA ≥ 3 OR 2.8, 95% CI 1.2-6.3; NRS impaired OR 3.3, 95% CI 1.6-6.8). The scoring system, including TUG, ASA, NRS, gender and type of surgery, showed good accuracy (AUC: 0.81, 95% CI 0.75-0.86). The negative predictive value with a cut-off point >8 was 93.8% and the positive predictive value was 40.3%. CONCLUSIONS: A substantial number of patients experience major postoperative complications. TUG, ASA and NRS are screening tools predictive of the occurrence of major postoperative complications and, together with gender and type of surgery, compose a good scoring system.
AIMS: The aim of this study was to investigate the predictive ability of screening tools regarding the occurrence of major postoperative complications in onco-geriatric surgical patients and to propose a scoring system. METHODS: 328 patients ≥ 70 years undergoing surgery for solid tumors were prospectively recruited. Preoperatively, twelve screening tools were administered. Primary endpoint was the incidence of major complications within 30 days. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using logistic regression. A scoring system was derived from multivariate logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was applied to evaluate model performance. RESULTS: At a median age of 76 years, 61 patients (18.6%) experienced major complications. In multivariate analysis, Timed Up and Go (TUG), ASA-classification and Nutritional Risk Screening (NRS) were predictors of major complications (TUG>20 OR 3.1, 95% CI 1.1-8.6; ASA ≥ 3 OR 2.8, 95% CI 1.2-6.3; NRS impaired OR 3.3, 95% CI 1.6-6.8). The scoring system, including TUG, ASA, NRS, gender and type of surgery, showed good accuracy (AUC: 0.81, 95% CI 0.75-0.86). The negative predictive value with a cut-off point >8 was 93.8% and the positive predictive value was 40.3%. CONCLUSIONS: A substantial number of patients experience major postoperative complications. TUG, ASA and NRS are screening tools predictive of the occurrence of major postoperative complications and, together with gender and type of surgery, compose a good scoring system.
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