Controlling Nutritional Status (CONUT) Score as a Predictor of All-Cause Mortality at 3 Months in Stroke Patients.

Malnutrition is frequently observed in patients after stroke and is associated with poor outcomes. Patients at risk of malnutrition may be identified with several nutrition screening tools, but no nutritional screening tool has been validated for use with stroke patients. The aim of this study was to explore the ability of the Controlling Nutritional Status (CONUT) score to predict 3-month mortality in stroke patients. METHOD: Patients were recruited from consecutive admissions at a hyperacute stroke unit and were screened for risk of malnutrition (light, moderate, or severe) using CONUT scores. At the next visit, 3-month outcomes were obtained. RESULTS: Of the 164 recruited patients, 51.2% were male. Mean patient age was 77.7 (SD = 7.0) years, and 85.8% of patients had an ischemic stroke. There was a significant difference in the survival rate (p < .001) at 3 months between patients with moderate risk for malnourishment compared to the other patients. The multivariate regression Cox model showed that moderate risk of malnourishment, according to the CONUT score, increased the risk for death at 3 months (hazard ratio = 1.086; 95% CI [1.057, 8.305]; p < .039). CONCLUSION: The CONUT score has predictive validity for all-cause mortality in stroke patients after 3 months, both in hospital and after discharge. Further prospective multicenter studies with larger samples are needed to clarify the usefulness of the CONUT score in the prognosis of all-cause mortality in stroke patients.

Determinants of Quality of Life in Stroke Survivors After 6 Months, from a Comprehensive Stroke Unit: A Longitudinal Study.

BACKGROUND: In the social model of stroke, health-related quality of life (HRQoL) is the result of interplay among stroke severity, social support, and health-promoting behaviors. Our objective was to identify determinants of HRQoL in stroke survivors. METHODS: Ischemic stroke patients were evaluated at 6 months with the Short Form 12 Health Survey, including physical component survey (PCS) and mental health component survey (MCS) summary scores. Multivariate stepwise regression analyses determined independent predictors of scores. Models included age, gender, socioeconomic class, education, residential environment, social support, previous comorbidity (Charlson Index), previous stroke, side of stroke, National Institutes of Health Stroke Scale (NIHSS) score at admission, Barthel Index (BI) and modified Rankin Scale (mRS) scores at discharge, and length of stay. RESULTS: A total of 131 patients participated (mean age 70.1, SD = 12.5; 62.6% males). In all, 33.6% had a BI score <90 and an mRS score >2 (poor outcome). The mean (SD) PCS score was 39.46 (9.3) and mean (SD) MCS score was 34.86 (10.1). Lower PCS score was associated with female sex (ß = 0.204, p = .009), poor social support (ß = -0.225, p = .003), and poor Charlson Index (ß = -0.162, p = .032) and BI scores (ß = 0.384, p < .0001). Lower MCS score was associated with female sex (ß = 0.162, p = .062) and poor NIHSS (ß = -0.265, p = .019) and BI scores (ß = 0.203, p < .071). CONCLUSION: Stroke severity, disability, gender, social support, and previous stroke have significant impacts on the physical and mental domains of generic HRQoL.