BackgroundMalnutrition is a significantly poor prognostic factor for a variety of cardiovascular diseases. However, its prevalence and prognostic value in hypertensive patients is still unclear. The present study sought to determine the prevalence and prognostic value of malnutrition in hypertensive patients in a community setting.MethodsWe included 9,949 hypertensive patients from the National Health and Nutrition Examination Survey (NHANES) (2005–2014). The Controlling Nutritional Status (CONUT) score, the Nutritional Risk Index (NRI), and the Naples Prognostic Score (NPS) were applied to assess the nutritional status of participants. A Cox regression model was established to examine the association between malnutrition and cardiovascular and all-cause mortality.ResultsIn all, 19.9, 3.9, and 82.9% hypertensive patients were considered to have malnutrition as evaluated by the CONUT, NRI, and NPS, respectively. Malnutrition assessed by CONUT and NRI was independently associated with cardiovascular mortality (HR [95% CI]) for mild and moderate-to-severe degree of malnutrition, respectively: 1.41 (1.04–1.91) and 5.79 (2.34–14.29) for CONUT; 2.60 (1.34–5.07) and 3.30 (1.66–6.56) for NRI (all P < 0.05), and for all-cause mortality (HR [95% CI]) for mild and moderate-to-severe degree of malnutrition, respectively: 1.48 (1.30–1.70) and 4.87 (3.40–6.98) for CONUT; 1.72 (1.24–2.39) and 2.60 (1.96–3.44) for NRI (all P < 0.01). Naples Prognostic Score could only independently predict all-cause mortality.ConclusionsMalnutrition was common among hypertensive patients and was closely associated with both long-term cardiovascular and all-cause mortality.
In this paper, we focus on group decision making (GDM) with incomplete interval-valued q-rung orthopair fuzzy preference relations (IVq-ROFPRs). On the basis of interval-valued q-rung orthopair fuzzy set (IVq-ROFS), the novel concepts of IVq-ROFPR, incomplete IVq-ROFPR, additive consistent IVq-ROFPR, and acceptably additive consistent IVq-ROFPR are proposed. Subsequently, two optimization models are established for deriving the complete IVq-ROFPRs and acceptably additive consistent IVq-ROFPRs. Inspired by the Markov model, the weight-generating method is designed to obtain the weights of decision makers. For the purpose of improving the consensus level, a modification process is constructed under the consideration of minimizing the deviations between the adjusted IVq-ROFPRs and the original ones. Afterward, a goal programming model is constructed to derive the normalized q-rung orthopair fuzzy (q-ROF) priority weights. The interval-valued q-rung orthopair fuzzy (IVq-ROF) priority weights of alternatives are further determined. Thus, an algorithm for the GDM method with IVq-ROFPRs is completed. Finally, the applications to examples and comparisons with previous approaches are conducted to illustrate the validity and effectiveness of the proposed method.
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