Comparison of adductor pollicis muscle thickness measurement with malnutrition detection tools in the determination of malnutrition in hospitalized pediatric patients

Adductor Pollicis muscle thickness (APKK), which is located at the top of an imaginary angle formed by the extension of the thumb and index finger, is used in the evaluation of muscle wasting and malnutrition in adult and elderly patients, but the number of studies regarding its usability in the pediatric population is limited. The study aimed to evaluate the efficacy of the measurement of APMT in determining malnutrition in pediatric inpatients. A total of 236 pediatric patients, aged between 4-9 years, received inpatient treatment at Dr. Behçet Uz Children's Hospital (Izmir/Turkey) between October and March 2020 were included in the study. Of the patients, 122 were female and 114 were male. Food intakes of the patients were evaluated using the 24-hour recall method. Body weight, height, mid-upper arm circumference (MUAC), skinfold thickness (TSF) and APMT measurements oft he patients were taken. Screening Tool for Risk of Impared Nutritional Status and Growth (STRONGkids) and Pediatric Nutritional Risk Score (PNRS) were used to determine the risk of malnutrition, and Subjective Global Nutritional Assessment (SGNA) was used to evaluate nutritional status of the patients. There were significant associations of severe malnutrition (assessed by the SGNA) and high nutritional risk (assessed by the STRONGkids and PNRS) with reduced APMT (p <0.05). Positive and strong correlations were found between weight (r=0.663, p=0.000), BMI (r=0.623, p=0.000), MUAC (r=0.720, p=0.000), TSF (r=0.648, p=0.000), mid-upper arm muscle circumference (r=0.640, p=0.000), mid-upper arm muscle area (r=0.639, p=0.000) measurements, BMI z scores for age (r=0.612, p=0.000) and APMT (p<0.05). The correlation between height-for-age z score (r=0.355, p=0.000) and height (r=0.461, p=0.000) and APMT were found to be positive and moderate (p<0.05). A weak negative correlation was detected between the hospital stay and the APMT (r=-0.137, p=0.035). The APMT were evaluated by dividing into tertiles; values corresponding to the 25th, 50th and 75th percentiles were found to be 5 mm, 6 mm and 8 mm, respectively. Height for age and BMI for age were considered as standard reference criteria for malnutrition. The cut-off point for diagnosing malnutrition (Youden index=0.429; 95% CI: 0.288-0.537) was ≤ 4 mm for APMT determined by using diagnostic tests. The AUC (Area Under Curve) was calculated by ROC analysis and found to be 0.78 (95% CI: 0.72 - 0.83); its sensitivity in diagnosing malnutrition was 55.9% (95% CI: 42.6-68.9) and specificity was 87.0% (95% CI: 81.1-91.6). In this study, it was determined that APMT measurement is an effective method that can be used in the detection of malnutrition in hospitalized pediatric patients.