Diseases of the Esophagus · 2019 · 18 citations · 29 references
MedicinePerioperative MedicineSurgeryGeneral SurgeryPerioperative Outcomes ResearchPerioperative SafetyEsophageal SurgeryPreoperative AssessmentPreoperative EvaluationPreoperative Risk AssessmentSurgical ComplicationsThoracic SurgeryClavien-dindo ClassificationMorbidity Risk PredictionOperative Risk PredictionPostoperative Esophageal ComplicationsPostoperative Risk PredictionPredictive PerformanceReceiver Operating Characteristic AnalysisSurgical Outcome Evaluation
Predicting major anastomotic leak (AL) and major complications (Clavien-Dindo 3-5) following esophagectomy improves postoperative management of patients. The role of the NUn score in their prediction is controversial. This study aims to evaluate the predictive ability of this simple score. Data were retrospectively collected for consecutive esophagectomies over a 10-year period, and NUn scores were retrospectively calculated for each patient from informatics data. A standardized definition of major AL was used, excluding minor asymptomatic, radiologically detected leaks. The predictive accuracy of the NUn score and its constituent parts, for major AL and major complications, was assessed using area under receiver operating characteristics curves (AUROCs). Of 382 patients, 48 (13%) developed major AL and 123 (32%) developed major complications. The NUn score calculated on postoperative day 4 was significantly predictive of both outcomes, with AUROCs of 0.77 and 0.71, respectively (both P < 0.001). A NUn score cut-off of 10 had a negative predictive value of 95% for major AL. The NUn score was predictive of major complications on multivariable analysis. The NUn score was found to be a significant predictor of major AL, suggesting that this is a useful early warning score for major AL. The score may also be useful in identifying patients that are the most likely to benefit from enhanced recovery protocols.
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The Clavien-Dindo Classification of Surgical Complications
Pierre A. Clavien, Jeffrey Barkun, Michelle Oliveira et al. · Annals of Surgery · 2009 · 11.3K citations
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