Relationship Between Nutritional Status and the Clinical Outcomes of Patients With and Without Neoplasms According to Multiple Correspondence Analysis

Abstract

-Background -For many years, many studies have reported undesirable outcomes that may occur during the hospital stay of patients diagnosed with malnutrition or even at some nutritional risk. Objective -To investigate the relationship between nutritional status and clinical outcomes during hospital stay using the multiple correspondence analysis technique. Methods -This cross-sectional study included 600 patients with and without neoplasms. The following data were collected: subjective global assessment, nutritional indicators, nutritional risk screening, anthropometric data (body mass index (BMI), mid-upper arm circumference (MUAC), mid-upper arm muscle circumference (MUAMC), triceps skinfold thickness (TST), recent weight loss (RWL)), and habitual energy intake (HEI/ER <75%). The clinical outcomes of interest were complications, length of hospital stay (LOHS), and death. The data were analyzed by the chi-square or Fisher's exact test at a significance level of 5%. Multiple correspondence analysis was used for the multivariate data analysis. Results -The multiple correspondence analysis map for the patients with neoplasms showed that the following characteristics were associated and represented by death, complications, and a greater likelihood of LOHS ≥7 days: underweight according to BMI; TST, MUAC, and MUAMC ≤15th percentile; malnutrition according to the subjective global assessment; at nutritional risk according to the nutritional risk screening; being male; age ≥60 years; and HEI/ER <75%. The multiple correspondence analysis map for the patients without neoplasms showed that the following characteristics were associated and represented by death: underweight according to BMI; TST ≤15th percentile; malnutrition according to the subjective global assessment; and at nutritional risk according to the nutritional risk screening. Complications and LOHS ≥7 days represented the categories male, no recent weight loss, HEI/ER <75%, MUAC and MUAMC ≤15th percentile, TST between the 15th and 85th percentiles, and age <60 years. Conclusion -The results of this study confirm an association between unsatisfactory nutritional indicators and undesirable clinical outcomes.

A cross-sectional analysis of patient care pathways and profiles in a dental emergency department

“…This work also confirmed that users of DE departments are often characterised by poor dental follow-up [17][18][19] and are mostly from disadvantaged social backgrounds 12,21,31 . The MCA was chosen in the present study because it allows simultaneous analysis of all outcomes and characterised patients' profiles 33 . Whereas previous studies provided a general description of subjects who attended the DE department 12,[17][18][19]21,27,30,31 , this study aimed to highlight profiles of patients by linking sociodemographic characteristics to care-seeking behaviours.…”

“…Whereas previous studies provided a general description of subjects who attended the DE department 12,[17][18][19]21,27,30,31 , this study aimed to highlight profiles of patients by linking sociodemographic characteristics to care-seeking behaviours. The MCA was chosen in the present study because it allows simultaneous analysis of all outcomes and characterised patients' profiles 33 . This method led to the identification of two profiles of patients using the DE department, who were characterised by different motivations towards hospital care.…”

Association Between Anthropometric Indicators of Nutrition Status and Length of Hospital Stay in Hospitalized Patients

“…Despite the sustained evidence that anthropometric and derived indicators are related to nutrition risk and undernutrition, 9‐12 previous data on the association of anthropometric and derived indicators with LOS are contradictory 1,10,13‐25 . Whereas in some studies an association between weight, triceps skinfold thickness (TST), mid‐upper arm circumference (MUAC), adductor pollicis muscle thickness (APMT), mid‐upper arm muscle area (AMA), mid‐upper arm muscle circumference (AMC), and body mass index (BMI) with longer LOS has been identified, 1,10,18‐23 in others these associations were not found 1,10,15,19‐26 . However, it is important to highlight that LOS may be influenced by many factors other than nutrition status—for instance, disease, age, and marital status 1,6,15,18,27 —and in some of the mentioned studies, the association between anthropometric and derived indicators with LOS was not adjusted for possible confounding variables 10,13,15,17,20 .…”

“…Whereas in some studies an association between weight, triceps skinfold thickness (TST), mid‐upper arm circumference (MUAC), adductor pollicis muscle thickness (APMT), mid‐upper arm muscle area (AMA), mid‐upper arm muscle circumference (AMC), and body mass index (BMI) with longer LOS has been identified, 1,10,18‐23 in others these associations were not found 1,10,15,19‐26 . However, it is important to highlight that LOS may be influenced by many factors other than nutrition status—for instance, disease, age, and marital status 1,6,15,18,27 —and in some of the mentioned studies, the association between anthropometric and derived indicators with LOS was not adjusted for possible confounding variables 10,13,15,17,20 . Furthermore, the discharge destination was taken into account in only 1 study, and it was shown that MUAC was independently associated with LOS.…”

Fisher linear discriminant analysis for classification and prediction of genomic susceptibility to stomach and colorectal cancers based on six STR loci in a northern Chinese Han population

“…The results were considered statistically significant at p < 0.05. The correspondence between the STR locus typing and IHC and tumor markers was analyzed using multiple correspondence analysis, which is a multivariate statistical technique used to explore the simultaneous relationships between variables (Leandro-Merhi & JLB, 2017).…”