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Background: Malnutrition is a common issue in patients with head and neck squamous cell carcinoma and has a negative effect on surgical outcomes. Objective: We attempted to determine which malnutrition diagnostic variables can be used as predictors of postoperative complications in patients with head and neck squamous cell carcinoma. Methods: Forty-one patients undergoing surgery for head and neck squamous cell carcinoma were submitted to a prospective evaluation. Biochemical data, anthropometric measurements and evaluation of body composition were used in the nutritional analysis. Results: Twenty-two patients (53.6%) developed complications. Serum albumin measured on the first postoperative day was the only variable that significantly differed between groups. A cut-off value of 2.8 g/dL distinguished between patients with a complicated and uncomplicated postoperative course. Normalization of albumin levels occurred more frequently and more rapidly in the noncomplicated group. Conclusion: Serum albumin measured on the first postoperative day was the only variable that was a predicter of postoperative complications after major head and neck squamous cell carcinoma surgery.

The purpose of this article is twofold: to identify the critical risk factors (RFs) that impact supply chains (SC) in the engineering, procurement, and construction of large-scale projects (EPC-LSP) of the oil and gas industry (OGI) and to apply these RFs in a mathematical model developed, based on multiple-criteria decision-making (MCDM) methods in an expert group. The mathematical model was developed in MATLAB and was based on the Preference Ranking Organization Method for Enrichment Evaluations (PROMÉTHÉE) II and (PROMÉTHÉE GDSS) Group Decision Support System methods. The model's criteria were defined with the RF mapping identified using 33 years of literature and the application of questionnaires to specialists. The evaluation process of the alternatives concerning the defined criteria was conducted through questionnaires to specialists. Finally, the functionality and results of the model were validated by the specialists in the field through interviews. As a contribution, managers, companies, and industry could adopt this solution as a practical and dynamic tool to support decision-making. This fact especially holds true in possible critical supply scenarios, where it is necessary to direct resources to minimize risks and other impacts to EPC-LSP SC. Another novelty refers to the critical risk factors identified, originating from an extensive literature mapping covering the three pillars of sustainability. Moreover, this research was to fill the literature gap, given the lack of studies that propose clear, practical, and specific tools for SCRM in EPC-LSP.