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Malnutrition or nutritional risk is often found in elderly inpatients[1-2], primarily due to aging, effects of diseases and drugs, and inadequate dietary intake. Malnutrition or nutritional risk is associated with poor clinical outcomes, longer hospitalizations, a higher likelihood of hospital readmission, higher rates of mortality, and greater hospital expenditures[3-6]. Many nutritional screening or assessment tools are used in hospitals in order to recognize these patients as early as possible, facilitate earlier nutritional intervention, and improve health outcomes. The Nutritional Risk Screening (NRS 2002)[7] has been successfully implemented throughout Europe and is recommended for nutritional risk screening of hospitalized patients in China. The Subjective Global Assessment (SGA)[8] is widely used in nutritional assessment and has been recommended as the outcome measure in clinical trials[9-10]. The SGA score can predict health outcomes in elderly hospitalized patients[11]. NRS 2002 is used to identify nutritional risk, whereas SGA detects malnutrition, which is the greatest distinction between the two. They are similar because they both consider the metabolic stress of disease and changes in food intake, although NRS 2002 classifies metabolic stress using numerical scores, whereas SGA depends on the investigatora's experience to indicate the metabolic stress of disease[12]. SGA has questions related to the detection of chronic malnutrition; in contrast, NRS 2002 contains questions that indicate a more recent or acute change in nutritional status[13]. These assessment tools are closely related to body weight, particularly, the circumstances surrounding weight that can be determined in an accurate physical assessment conducted by trained staff. It is difficult to carry out such an assessment on every patient, as there are many hospitalized patients in China. Although malnutrition and nutritional risk cannot be assessed using a single parameter, the search is on for an indicator that is a simple and rapid measurement and can increase the accuracy of nutritional evaluation tools.
Patients with malnutrition or nutritional risk have lower hand grip strength (HGS). The potential explanation for this is that malnutrition can reduce protein synthesis, cause muscle fiber atrophy, and reduce muscle mass, further leading to decreased muscle function. Some studies hypothesized that the pathogenesis of impaired muscle function in malnutrition involves reduction of glycolytic enzyme[14-15], creatine[16], and mitochondrial complex activities[17], leading to reductions in muscle glycolysis, phosphocreatine, and oxidative phosphorylation, respectively. Additionally, muscle protein stores have been found to respond rapidly to restoration of nutrition[18]. Together, these mechanisms account for the ability of HGS to predict nutritional status. HGS, a commonly used tool for the assessment of muscle function, has been regarded as an indicator of nutritional status in recent reports[18-19]. HGS can also independently predict nutritional status and changes in nutritional status defined by the Patient-Generated Subjective Global Assessment (PG-SGA) score and category[19]. In addition, HGS may be useful for forecasting prognosis in patients with congestive heart failure[20]. HGS is a rapid, cost-effective nutrition assessment tool; to the best of our knowledge, there is no evaluation standard, and there are no cut-points for malnutrition or nutritional risk in elderly inpatients in China.
The present study aims to assess the nutritional status and the application of HGS in nutrition assessment of elderly inpatients at hospital admission. We anticipate that HGS will show a significant correlation with NRS 2002 and SGA scores and that a combination of the two can be used as an accurate predictor of nutrition status.
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The characteristics of the 1, 343 patients are shown in Table 1. There was no difference in age between men and women. Respiratory (14.59%), endocrinological (15.26%), neurological (22.93%), gastroenterological (11.39%), and cardiological (25.76%) diseases were common at hospital admission. BMI, WC, CC, and HGS; serum levels of TP, Cr, TG, TC, Hb, and CRP; and the number of internal medicine patients were significantly different between women and men.
Variables Men (n = 691) Women (n = 652) Total (n = 1, 343) P Value Age (years) 74.0 ± 6.1 73.6 ± 5.6 73.8 ± 5.9 0.286 Body Measurement Height (cm) 169.6 ± 5.9 157.5 ± 5.7 163.7 ± 8.3 < 0.001 Weight (kg) 69.2 ± 11.1 61.2 ± 11.6 65.3 ± 12.0 < 0.001 BMI (kg/m2) 24.1 ± 3.7 24.7 ± 4.4 24.3 ± 4.0 0.007 WC (cm) 91.3 ± 10.9 88.9 ± 11.4 90.1 ± 11.2 < 0.001 CC (cm) 34.5 ± 3.6 33.0 ± 3.7 33.8 ± 3.8 < 0.001 Left HGS (kg) 25.1 ± 8.4 15.4 ± 5.8 20.3 ± 8.8 < 0.001 Right HGS (kg) 26.5 ± 8.7 16.6 ± 6.1 21.7 ± 9.0 < 0.001 Optimal HGS (kg) 26.7 ± 8.6 16.6 ± 6.0 21.8 ± 9.0 < 0.001 Mean HGS (kg) 25.8 ± 8.3 15.9 ± 5.8 21.0 ± 8.7 < 0.001 Blood Biochemical Assays ALB (g/L) 38.44 ± 5.12 38.61 ± 5.07 38.52 ± 5.09 0.534 TP (g/L) 64.82 ± 7.23 66.46 ± 7.62 65.64 ± 7.46 < 0.001 BUN (mmol/L) 6.88 ± 5.32 6.67 ± 4.37 6.78 ± 4.88 0.447 Cr (μmol/L) 93.51 ± 55.0 84.81 ± 88.89 89.31 ± 73.42 0.031 TG (mmol/L) 1.29 ± 0.90 1.67 ± 1.88 1.48 ± 1.48 < 0.001 TC (mmol/L) 4.20 ± 2.21 4.73 ± 1.42 4.46 ± 1.89 < 0.001 Hb (g/L) 129.91 ± 21.04 119.52 ± 18.09 124.83 ± 20.32 < 0.001 CRP (mg/dL) -median (P25-P75) 2.1 (0.51-11.81) 2.53 (0.54-9.20) 2.3 (0.51-10.7) 0.675 Patients of internal medicine [n(%)] < 0.001 Respiratory 123 (17.80) 73 (11.20) 196 (14.59) Endocrinology 90 (13.02) 115 (17.64) 205 (15.26) Neurology 183 (26.48) 125 (19.17) 308 (22.93) Gastroenterology 78 (11.29) 75 (11.50) 153 (11.39) Cardiology 166 (24.03) 180 (27.61) 346 (25.76) Nephrology 26 (3.76) 38 (5.83) 64 (4.77) Rheumatology 25 (3.62) 46 (7.06) 71 (5.29) Note. Data are expressed as mean± SD or number (percentage) of subjects. Statistical significance of difference is calculated between men and women subjects. BMI: body mass index; HGS: handgrip strength; WC: waist circumference; CC: calf circumference; ALB: albumin; TP: total protein; Cr: creatinine; TG: triglyceride; TC: total cholesterol; Hb: hemoglobin; BUN: blood urea nitrogen; CRP: C-reactive protein. Table 1. Baseline Characteristics of Study Subjects
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The classification of nutritional status by NRS 2002 showed that 63.81% of the population was at nutritional risk (men 69.75%, women 57.52%), while the classification of nutritional status by SGA showed that 28.22% were malnourished (men 25.57%, women 31.13%). Women were at a lower nutritional risk, but at a higher risk of being malnourished (Figure 1).
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The left HGS, right HGS, mean HGS, optimal HGS, BMI, WC, and CC and the serum levels of ALB, TG, and Hb of inpatients with malnutrition or nutritional risk were significantly lower than those of well-nourished inpatients, both male and female. However, in women, age and CRP were higher, and the serum level of TP was significantly lower in malnutrition or nutritional risk inpatients than in well-nourished inpatients (Table 2).
Parameters NRS 2002 SGA ≥ 3 < 3 P Value B or C A P Value Men Left HGS (kg) 21.5 ± 8.3* 27.5 ± 7.6 < 0.001 20.1 ± 7.8* 26.7 ± 8.0 < 0.001 Right HGS (kg) 22.6 ± 8.4* 29.1 ± 7.9 < 0.001 21.5 ± 8.3* 28.7 ± 7.9 < 0.001 Mean HGS (kg) 22.0 ± 7.9* 28.3 ± 7.5 < 0.001 20.6 ± 7.7* 27.6 ± 7.7 < 0.001 Optimal HGS (kg) 22.8 ± 8.2* 29.3 ± 7.9 < 0.001 21.1 ± 7.8* 28.4 ± 8.1 < 0.001 Age (year) 75.9 ± 5.6* 72.7 ± 6.0 < 0.001 75.6 ± 6.4* 73.4 ± 5.9 < 0.001 BMI (kg/m2) 22.4 ± 4.0* 25.1 ± 3.0 < 0.001 21.9 ± 3.7* 24.8 ± 3.3 < 0.001 WC (cm) 87.3 ± 11.7* 93.9 ± 9.5 < 0.001 86.1 ± 11.2* 93.1 ± 10.2 < 0.001 CC (cm) 33.3 ± 3.8* 35.4 ± 3.2 < 0.001 32.4 ± 3.7* 35.3 ± 3.3 < 0.001 ALB (g/L) 37.2 ± 4.9* 39.2 ± 5.1 < 0.001 36.2 ± 5.4* 39.2 ± 4.8 < 0.001 TP (g/L) 64.3 ± 7.6 65.2 ± 7.0 0.105 64.1 ± 8.1 65.1 ± 6.9 0.128 TG (mmol/L) 1.09 ± 0.59* 1.42 ± 1.04 < 0.001 1.07 ± 0.56* 1.36 ± 0.98 < 0.001 TC (mmol/L) 4.02 ± 1.04 4.32 ± 2.70 0.094 3.99 ± 1.15 4.27 ± 2.46 0.161 HB (g/L) 125.7 ± 23.2* 132.5 ± 19.1 < 0.001 122.1 ± 23.7* 132.5 ± 19.4 < 0.001 CRP (mg/dL) -median (P25-P75) 2.57 (0.34-21.76) 2.06 (0.56-9.00) 0.514 1.72 (0.67-40.51) 2.10 (0.40-9.94) 0.072 Women Left HGS (kg) 13.1 ± 5.5* 16.9 ± 5.5 < 0.001 12.9 ± 5.4* 16.5 ± 5.6 < 0.001 Right HGS (kg) 14.0 ± 5.5* 18.3 ± 5.8 < 0.001 13.6± 5.6* 17.9 ± 5.8 < 0.001 Mean HGS (kg) 13.5 ± 5.4* 17.5 ± 5.5 < 0.001 13.2 ± 5.6* 17.2 ± 5.5 < 0.001 Optimal HGS (kg) 14.1 ± 5.6* 18.3 ± 5.7 < 0.001 13.6 ± 5.6* 18.0 ± 5.7 < 0.001 Age (year) 75.5 ± 5.5* 72.3 ± 5.4 < 0.001 75.0 ± 6.0* 73.0 ± 5.4 < 0.001 BMI (kg/m2) 22.7 ± 4.5* 26.0 ± 3.9 < 0.001 22.4 ± 4.4* 25.7 ± 4.0 < 0.001 WC (cm) 86.0 ± 12.1* 90.8 ± 10.4 < 0.001 84.9 ± 11.7* 90.6 ± 10.7 < 0.001 CC (cm) 31.6 ± 3.9* 33.9 ± 3.4 < 0.001 31.1 ± 3.9* 33.8 ± 3.3 < 0.001 ALB (g/L) 37.5 ± 5.3* 39.4 ± 4.7 < 0.001 37.3 ± 5.4* 39.2 ± 4.8 < 0.001 TP (g/L) 65.4 ± 7.9* 67.2 ± 7.3 0.003 64.8 ± 8.4* 67.2 ± 7.1 0.002 TG (mmol/L) 1.48 ± 1.38* 1.80 ± 2.14 0.039 1.42 ± 0.87* 1.78 ± 2.17 0.028 TC (mmol/L) 4.74 ± 1.76 4.73 ± 1.15 0.976 4.73 ± 1.94 4.74 ± 1.13 0.949 HB (g/L) 117.0 ± 19.7* 121.1 ± 16.8 0.005 115.7 ± 20.5* 121.2 ± 16.7 0.001 CRP (mg/dL) -median (P25-P75) 3.24 (0.60-13.45)* 1.90 (0.46-7.45) 0.039 3.70 (0.77-13.20)* 2.84 (0.55-8.31) 0.043 Note. Statistical significance of difference is calculated between different nutrition status, *P < 0.05. Table 2. The Comparison HGS, Anthropometry and Blood Biochemical Assays of Different Nutrition Status of Study Subjects
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The multivariate logistic regression model showed that, in male subjects, according to NRS 2002, the odds ratio (OR) of optimal HGS was 0.93 (95% CI 0.90-0.97, P < 0.001), the age OR was 1.05 (95% CI 1.01-1.10, P = 0.018), and the BMI was 0.83 (95% CI 0.74-0.92, P = 0.001). According to SGA, the optimal HGS was 0.93 (95% CI 0.89-0.96, P < 0.001), the BMI was 0.87 (95% CI 0.77-0.99, P = 0.032), the ALB was 0.85 (95% CI 0.78-0.94, P = 0.001), and the TP was 1.07 (95% CI 1.01-1.13, P = 0.017). For female subjects, according to NRS 2002, the OR of optimal HGS was 0.93 (95% CI 0.89-0.98, P = 0.002), the age was 0.93 (95% CI 0.89-0.98, P = 0.002), and the BMI was 0.80 (95% CI 0.72-0.88, P < 0.001). According to SGA, the OR of optimal HGS was 0.93 (95% CI 0.88-0.98, P = 0.003), the BMI was 0.84 (95% CI 0.76-0.94, P = 0.001), and the CC OR was 0.90 (95% CI 0.82-0.99, P = 0.031). There was no significant difference in any other variable (Table 3).
Variable NRS 2002 SGA Standardized β OR (95% CI) P Value Standardized β OR (95% CI) P Value Men Optimal HGS -0.07 0.93 (0.90-0.97) < 0.001 -0.08 0.93 (0.89-0.96) < 0.001 Age 0.05 1.05 (1.01-1.10) 0.018 0.01 1.01 (0.96-1.06) 0.827 BMI -0.19 0.83 (0.74-0.92) 0.001 -0.14 0.87 (0.77-0.99) 0.032 WC -0.02 0.98 (0.94-1.01) 0.198 -0.01 0.99 (0.96-1.04) 0.786 CC 0.02 1.02 (0.92-1.12) 0.756 -0.10 0.90 (0.81-1.01) 0.086 ALB 0.06 0.94 (0.87-1.02) 0.162 -0.16 0.85 (0.78-0.94) 0.001 TP 0.01 1.01 (0.96-1.06) 0.608 0.07 1.07 (1.01-1.13) 0.017 TC -0.13 0.88 (0.68-1.13) 0.311 -0.18 0.84 (0.63-1.12) 0.236 Hb 0.01 1.01 (0.99-1.03) 0.116 0.01 1.01 (0.99-1.03) 0.314 CRP 0.01 1.01 (1.00-1.01) 0.190 0.01 1.01 (1.00-1.03) 0.140 Women Optimal HGS -0.07 0.93 (0.89-0.98) 0.003 -0.07 0.93 (0.88-0.98) 0.003 Age 0.07 0.93 (0.89-0.98) 0.002 0.03 0.93 (0.88-0.98) 0.157 BMI -0.23 0.80 (0.72-0.88) < 0.001 -0.17 0.84 (0.76-0.94) 0.001 WC 0.01 1.01 (0.98-1.04) 0.452 0.01 1.01 (0.98-1.05) 0.415 CC 0.03 0.97 (0.89-1.06) 0.505 -0.10 0.90 (0.82-0.99) 0.031 ALB -0.05 0.96 (0.89-1.03) 0.221 0.05 0.96 (0.89-1.04) 0.286 TP -0.01 0.99 (0.95-1.04) 0.743 -0.02 0.98 (0.94-1.03) 0.393 TC 0.02 1.03 (0.86-1.23) 0.792 0.05 1.07 (0.89-1.30) 0.476 Hb 0.01 1.01 (0.99-1.02) 0.238 0.00 1.00 (0.99-1.01) 0.902 CRP 0.00 1.00 (0.99-1.01) 0.451 0.00 1.00 (0.99-1.01) 0.771 Note. β: regression coefficient; OR: odds ratios; CI: confidence interval Table 3. Multivariate Logistic Regression Analyses for Malnutrition or Nutrition Risk Stratified by Gender
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To determine the optimal HGS value to detect nutritional risk and malnutrition in men and women, we calculated the optimal HGS cut-off values by maximizing the Youden Index by sex and age (Table 4 and Figure 2). Based on the ROC curve of NRS 2002, we identified the optimal cut-off points as 27.5 kg (65-74 years) and 21.0 kg (75-90 years) for men and 17.0 kg (65-74 years) and 14.6 kg (75-90 years) for women. Likewise, for SGA, we determined the optimal cut-off points as 24.9 kg (65-74 years) and 20.8 kg (75-90 years) for men and 15.2 kg (65-74 years) and 13.5 kg (75-90 years) for women.
Variable Age (year) AUC SE P 95% CI Cut-point (kg) Sensitivity (%) Specificity (%) Nutritional Risk/Malnutrition, n (%) Men NRS 65-74 0.734 0.027 < 0.001 0.678-0.786 27.5 69.1 63.6 155 (41.11) 2002 75-90 0.670 0.030 < 0.001 0.611-0.729 21.0 83.3 44.8 97 (30.89) SGA 65-74 0.761 0.029 < 0.001 0.703-0.819 24.9 78.0 58.5 113 (29.97) 75-90 0.715 0.032 < 0.001 0.653-0.777 20.8 81.8 54.3 91 (28.98) Women NRS 65-74 0.688 0.029 < 0.001 0.630-0.746 17.0 70.5 58.6 145 (38.46) 2002 75-90 0.687 0.032 < 0.001 0.624-0.750 14.6 69.3 62.8 132 (48.00) SGA 65-74 0.672 0.033 < 0.001 0.608-0.736 15.2 77.4 53.2 114 (30.24) 75-90 0.720 0.031 < 0.001 0.660-0.781 13.5 71.7 65.1 140 (50.91) Note. AUC: area under the curve; SE: standard error; CI: confidence interval. Table 4. Gender-and Age-Specific ROC Curve of the Optimal HGS to Screen Malnutrition or Nutritional Risk on the Basis of SGA and NRS 2002 in Elderly Inpatients