Association between Controlling Nutritional Status (CONUT) Score and Body Composition, Inflammation and Frailty in Hospitalized Elderly Patients

Abstract

The Controlling Nutritional Status (CONUT) score has demonstrated its ability to identify patients with poor nutritional status and predict various clinical outcomes. Our objective was to assess the association between the CONUT score, inflammatory status, and body composition, as well as its ability to identify patients at risk of frailty in hospitalized elderly patients.

Methods: a total of 361 patients were retrospectively recruited and divided into three groups based on the CONUT score.

Results: patients with a score ≥5 exhibited significantly higher levels of inflammatory markers, such as erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Neutrophil/Lymphocytes ratio (NLR), main platelet volume (MPV), and ferritin, compared to those with a lower score. Furthermore, these patients showed unfavorable changes in body composition, including a lower percentage of skeletal muscle mass (MM) and fat-free mass (FFM) and a higher percentage of fatty mass (FM). A positive correlation was found between the CONUT score and inflammatory markers, Geriatric Depression Scale Short Form (GDS-SF), and FM. Conversely, the Mini Nutritional Assessment (MNA), Mini-Mental Status Examination, activity daily living (ADL), instrumental activity daily living (IADL), Barthel index, FFM, and MM showed a negative correlation. Frailty was highly prevalent among patients with a higher CONUT score. The receiver operating characteristic (ROC) curve demonstrated high accuracy in identifying frail patients (sensitivity).

Conclusions: a high CONUT score is associated with a pro-inflammatory status as well as with unfavorable body composition. Additionally, it is a good tool to identify frailty among hospitalized elderly patients.

Keywords: CONUT score; body composition; elderly; frailty; hospitalized elderly; inflammation; malnutrition; screening tools.

Figure 1

Distribution of CONUT score in the study population.

Figure 2

Correlation matrix between CONUT score and clinical characteristics in the study population. CONUT, controlling nutritional status score; MNA, mini nutritional assessment; MMSE, mini-mental state examination; ADL, activity of daily living; IADL, instrumental activity of daily living; GDS-SF, geriatric depression scale short form; FM, fat mass; FFM, free-fat mass; MM, muscle mass. * p < 0.05, *** p < 0.001, ns: not significant.

Figure 3

Prevalence of frailty according to CONUT groups.

Figure 4

Distribution of CONUT score based on frailty status.

Figure 5

Prevalence of Fried’s criteria based on the CONUT score groups.

Figure 6

Correlation matrix between CONUT score and inflammatory markers in the study population. CONUT, controlling nutritional status score; ESR, erythrocytes sedimentation rate; CPR, c reactive protein; NLR, Neutrophils/lymphocytes ratio; MPV, main platelet volume; IL, Interleukin. ** p < 0.01, *** p < 0.001, ns: not significant.

Figure 7

Area under the receiver operating characteristic (ROC) curve for CONUT score cut off in the diagnosis of frailty. The dashed lines on the x and y axes indicate optimal cutoff points for sensitivity and 1-specificity, while the green solid line represents where the test would fall if the results were no better than chance at predicting the presence of a disease.