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Original Communication

Journal of Parenteral and Enteral Nutrition Volume 45 Number 2 February 2021 394–402 © 2020 American Society for Parenteral and Enteral Nutrition DOI: 10.1002/jpen.1840 wileyonlinelibrary.com

Use of Bedside Ultrasound to Assess Muscle Changes in the Critically Ill Surgical Patient

Christan Bury, MS, RD1 ; Robert DeChicco, MS, RD1; Diane Nowak, RD, LD, CNSC1; Rocio Lopez, MS, MPH1; Lulu He, DO1,2; Sandhya Jacob, MD1; Donald F. Kirby, MD, CNSC1; Nadeem Rahman, MD1,3; and Gail Cresci, PhD, RD1

Abstract Background: Critical illness causes hypercatabolism, loss of lean body mass (LBM), and poor outcomes. Evaluating LBM in the critically ill is challenging, and it is uncertain whether nutrition support (NS) impacts LBM. This study measured quadriceps muscle layer thickness (QMLT) by bedside ultrasound (US) to estimate LBM changes in surgical intensive care unit (SICU) patients and healthy controls (HCs). Methods: Trained RDNs measured QMLT via US at the midpoint and one-third distance between the superior margin of the patella and the anterior superior iliac spine. QMLT measurements were taken upon enrollment and repeated 1–2 times over 10 days. Results: Fifty-two SICU patients and 15 HCs were enrolled. Average SICU percent QMLT loss per day at the midpoint and one-third landmarks was 3.2 ± 3.8 (P < 0.001) and 2.9 ± 5.7 (P = 0.001); and QMLT loss was higher between the second and third measurements (4.0 ± 8.0, P = 0.005 and 4.3 ± 9.8, P = 0.017 at the midpoint and one-third landmarks) compared with that at the first and second measurements (1.7 ± 9.2, P = 0.20 & 1.7 ± 9.4, P = 0.22). Changes were not associated with NS received. No significant QMLT change was found in HCs. Conclusions: SICU patients significantly lost QMLT over 10 days, with greater losses occurring after 5 days. These results support RDNs performing USs to detect QMLT changes and suggest this technique could be valuable to evaluate LBM changes in critically ill patients. (JPEN J Parenter Enteral Nutr. 2021;45:394–402)

Clinical Relevancy Statement

The association between suboptimal nutrient delivery, loss of muscle mass, and poor clinical outcomes in critically ill patients is well established. Unfortunately, it is challeng- ing to accurately assess and monitor short-term or subtle changes in muscle mass from a practical and clinically rele- vant standpoint. Using bedside ultrasound (US) to measure the quadriceps muscle layer thickness (QMLT) is a potential tool to assess muscle loss in critically ill patients because it is widely available, easy to learn and perform, cost- effective, and minimally invasive. This study demonstrated that critically ill patients acutely lose muscle, as assessed by bedside US measurements of QMLT, and that losses were not associated with the amount of energy or protein the patient received. QMLT losses were not reflective in changes in the physical exam component of the malnutrition diag- nosis using American Society for Parenteral and Enteral Nutrition (ASPEN)/Academy of Nutrition and Dietetics (AND) guidelines, suggesting that this assessment tool is not sensitive enough to detect short-term changes in muscle mass in critically ill patients. Therefore, since measurement of QMLT by US can be easily taught to registered dieti- tian nutritionists and other bedside clinicians, it should be considered as an additional tool to evaluate and monitor changes in muscle mass in critically ill patients.

Introduction

The inflammatory stress response caused by a metabolic insult or sepsis induces a cascade of events that contribute to muscle catabolism and multiorgan failure in critically ill patients.1-3 The resulting loss of lean body mass (LBM) is associated with increases in mortality,4 intensive care unit (ICU) length of stay (LOS),1 and hospital LOS.5

Muscle wasting begins early during critical illness, and patients with multiorgan failure can lose as much as 15% of LBM during the first week.1 Besides increased protein catabolism, other factors inherent to the ICU environment

From the 1Cleveland Clinic in Cleveland, Cleveland, Ohio, USA; 2St. Clair Hospital, Pittsburgh, Pennsylvania, USA; and the 3Cleveland Clinic in, Abu Dhabi, United Arab Emirates.

Financial disclosure: None declared.

Conflicts of interest: None declared.

Received for publication March 22, 2019; accepted for publication March 24, 2020.

This article originally appeared online on May 11, 2020.

Correspondence Author: Christan Bury, MS, RD, LD, CNSC, Cleveland Clinic in Cleveland, Cleveland, OH, USA. Email: [email protected]

Bury et al 395

contribute to muscle loss, including patient immobility and interruptions in nutrient delivery. This combination of factors is especially debilitating in patients with preexist- ing low muscle stores due to sarcopenia, chronic illness, or malnutrition.

The association between suboptimal nutrient delivery, loss of muscle mass, and poor clinical outcomes in critically ill patients is well established.6-9 Unfortunately, accurately measuring muscle mass in this patient population is chal- lenging. A nutrition-focused physical examination (NFPE) is an integral component in the assessment of patients for malnutrition based on the Academy of Nutrition and Di- etetics (AND)/American Society for Parenteral and Enteral Nutrition (ASPEN) Consensus Statement.10 Assessment of subcutaneous fat and muscle stores by observation and palpation is included in a comprehensive NFPE, but these techniques are not sensitive to subtle or short-term changes. Multiple factors interfere with the ability to per- form a full physical examination in critically ill patients, including body position, sedation, edema, hemodynamic instability, and the presence of lines, drains, tubes, and restraints. Therefore, there is a need for objective methods of assessing and monitoring muscle mass in critically ill patients.

Although evaluation of muscle mass utilizing bioelectri- cal impedance analysis, dual-energy x-ray absorptiometry, magnetic resonance imaging, and muscle biopsy are objec- tive, quantifiable, and accurate methods,1,11,12 they are either not practical or not valid in the ICU setting. Computerized tomography (CT) has also been used to assess LBM.13,14

However, this technique is limited because CT scans are not performed in all ICU patients and should not be ordered for the sole purpose of determining body composition, given the radiation exposure and cost. In addition, it is not clear whether a CT scan is sensitive to short-term or subtle changes in LBM.

Recently, bedside ultrasound (US) has emerged as a tool to assess muscle loss in hospitalized and ICU patients because it is widely available, easy to learn and perform,11

cost-effective, and minimally invasive. These advantages make it a potential tool for bedside clinicians (eg, registered dietitian nutritionists [RDNs]) to use to evaluate muscle mass. US can be used to assess muscle mass layer thickness at different body sites, including the mid-upper arm, fore- arm, and quadriceps.12,15-19 The quadriceps muscle is the most common site measured because it is easily accessible in most ICU patients, is indicative of overall LBM,20,21

and is correlated with ICU LOS.15 Serial measurements are useful in detecting the degree of muscle loss from baseline, as well as changes that may result in response to therapies. In previous studies,9,12,15,17-19 Sabatino et al and Fetterplace et al mention RDNs as the primary clinician employing US to assess LBM in the critically ill population. Training RDNs to perform bedside US measurements to

assess muscle mass is logical because dietitians assess and monitor ICU patients for nutrition adequacy regularly, and they can directly integrate US study measurements into the patient’s nutrition assessment and subsequent care plan accordingly.

The primary aim of this study was to determine the rate of LBM loss in critically ill surgical ICU (SICU) patients using bedside US compared with that of age-, gender-, and body mass index (BMI)–matched healthy controls (HCs). The secondary aim was to correlate energy and protein delivery with the rate of muscle loss.

Methods

This study was approved by the Cleveland Clinic Insti- tutional Review Board as minimal risk, so patient con- sent was waived. Patients and their families were provided information sheets describing the details and purpose of the measurements and were given the option to decline enrollment.

Inclusion/Exclusion Criteria

Patients admitted to a 30-bed SICU at Cleveland Clinic Hospital, Cleveland, Ohio, were evaluated for study enroll- ment. Eligible patients were admitted to the SICU <72 hours prior to evaluation and expected to remain in the unit and fed solely via nutrition support (NS) for at least 3 consecutive days. Patients were excluded if 1 of the following criteria was present:

• Under 18 years old • ICU LOS >72 hours prior to study enrollment • Hospital LOS >5 days prior to study enrollment • Anticipated ICU LOS ≤3 days after study enrollment • NS not expected to be sole source of nutrition during

study period • Boarding from another ICU • Pregnant • Comfort care/hospice • Oral diet greater than clear liquids • On protein modular (not recorded on medication

administration record) • Received solid organ transplant during current ad-

mission • Admitted directly from skilled nursing or long-term

acute care facility • Trauma to both lower extremities

Method for Muscle Measurement

There are varying methods for measuring muscle thickness via bedside US, which can affect accuracy. Variables include compression differences (maximal vs minimal) as well as

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Figure 1. Study enrollment flowchart. SICU, surgical intensive care unit; US, ultrasound.

the type of muscle measurement (muscle thickness vs cross- sectional area [CSA]). Muscle thickness measures both the rectus femoris (RF) and vastus intermedius, and CSA refers to the CSA only of the RF.22,23 In this study, a maximal com- pression technique9,11,24 was used, given that a portion of our population in this study was critically ill, and maximum pressure is more reliable in this population.22 In relation to this, muscle thickness evaluation was chosen because this location is more reliable with a maximal compression technique, whereas CSA is more reliable when measuring with a minimal compression technique.22 Notably, muscle thickness often underestimates percent change when com- pared with histological changes of CSA.23

QMLT Training

RDNs who were members of the study team were trained to perform portable US measurements by another RDN inves- tigator with previous training and experience as detailed in Tillquist et al.11 Briefly, the training consisted of reviewing the written instructions; observing a demonstration of the portable US machine; observing hands-on demonstration on an actual patient; and performing multiple measure- ments on patients under direct supervision. Measurements were performed with a Phillips Sparq Diagnostic Ultra-

sound System (Bothell, WA, GMDN 40761) using the L12-4 linear transducer.

QMLT Measurements

Quadriceps muscle layer thickness (QMLT) was measured by US upon study enrollment (day 1). Measurements were acquired every 3–5 days for a maximum of 3 measurements during the 10-day study period (Figure 1). Measurements were completed by 3 RDNs, with the majority (90%) per- formed by 1 RDN. Patients were removed from the study, and their data were not analyzed if they were unable to complete at least 2 US measurements. Patients completed the study once they finished either the second or the third measurement, after which their data were analyzed.

All US measurements were performed on 1 leg for each patient. The side was chosen by the investigator based on accessibility. Measurements were taken at the midpoint and one-third distance between the superior margin of the patella and the anterior superior iliac spine (Figure 2). These landmarks were chosen based on previous data.9,11,22

The investigator applied maximal compression on the pa- tient’s thigh using the US transducer to ensure consistency and compress lower-extremity edema. To reduce variability between measurements, the same investigator performed

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Figure 2. Quadriceps muscle layer thickness measurement. Illustration by David Schumick, BS, CMI. Reprinted with the permission of the Cleveland Clinic Center for Medical Art & Photography © 2020. All Rights Reserved.

all US measurements per patient using their same hand. Once a US image was captured, the QMLT was determined by using electronic calipers on the computer screen to measure the distance from the peak of the femur bone to the beginning of the muscle-fat interface. All measure- ments were reported in centimeters, and the change was reported as percent loss or gain per day. US images were deidentified and interpreted by 1 of 2 musculoskeletal radiologists blinded to patient information. Figure S1 shows an example of a first and third US image for 1 patient enrolled.

Healthy Controls

Upon completion of enrollment of critically ill patients, 15 HCs were enrolled and matched to the SICU popu- lation for age, gender, and BMI. The same US machine and techniques used in the SICU population were also used for the HCs. All measurements for HCs were per- formed by 1 dietitian. HCs were recruited by posting flyers at the Cleveland Clinic main campus. Participation was voluntary, and HCs were compensated with a gift card upon completion. Participants were recruited and enrolled based on the following criteria: >55 years of age; no known significant health problems; no major changes in health condition, diet, bowel habits, activity, or weight in the past month; agreement to self-report current height, weight, and age; and agreement to sign a consent form

allowing investigators to perform 2 US measurements of their thigh, 7–10 days apart, at the Cleveland Clinic main campus.

Malnutrition

Patients were assessed for malnutrition by a trained ICU RDN based on the AND/ASPEN Consensus Statement10

and documented as none, moderate, or severe malnutrition. The malnutrition diagnosis used for the study was that which was acquired closest to each QMLT measurement, usually within 1–2 days of each measurement.

Energy and Protein Delivery

Based on the ASPEN/SCCM (Society of Critical Care Medicine) Nutrition Critical Care Guidelines,25 nutrition needs were estimated using 25–35 kcal/kg/d and 1.5–2 g protein/kg for patients with a BMI < 30 kg/m2. For patients with a BMI > 30 kg/m2, the energy and protein ranges used were either 11–14 kcal/kg per actual weight or 22–25 kcal/kg per ideal body weight (IBW) and 2–2.5 g protein/kg IBW, respectively. In addition to intake from NS, energy from intravenous (IV) sedation and IV fluids was calculated based on volumes documented in the medical record. Actual energy and protein intake were calculated as a percentage of estimated nutrition requirements. Participants were also divided into tertiles for level of intake (eg, <60%, 60%–80%, and >80%) based on percent of goal energy and protein received.

Data Points Obtained

The following data were collected on each enrolled pa- tient: age, gender, BMI, Acute Physiologic Assessment and Chronic Health Evaluation (APACHE) III score, C-reactive protein (CRP), serum prealbumin level, serum lactate, white blood cell count (WBC), medications, comorbidities, Rich- mond Agitation-Sedation Scale score, presence of edema, episodes of physical therapy, renal replacement therapy days, energy and protein intake, malnutrition diagnosis, ventilator days, ICU LOS, hospital LOS, and whether the patient was discharged from the hospital alive.

Statistical Methods

Power Calculations

To our knowledge at the commencement of this study, there were no published data on how the rate of QMLT loss per day correlates to the percentage of energy require- ments received by NS. Therefore, we built a regression model with 5 predictors (energy received, protein received, degree of malnutrition at the start of therapy, age, and gender) and assumed that the correlation between the energy/protein groups and the response variable would be

398 Journal of Parenteral and Enteral Nutrition 45(2)

0.45; we estimated that a total of 50 patients were needed for 80% power.

Analysis

Continuous variables were evaluated for normality using the Shapiro-Wilk Test. Normally distributed continuous measures were summarized using means and standard devi- ations, and nonnormally distributed continuous and ordinal measures were summarized using medians and 25th and 75th percentiles. Categorical factors were summarized using frequency and percentage. The rate of QMLT loss was estimated for each patient by calculating the difference in QMLT between follow-up and baseline and dividing this difference by number of days between measures; for patients who had >2 USs performed during their stay, the average rate of change between baseline and each follow-up is reported. Similarly, percent loss per day was estimated by calculating the percent loss in each measure and dividing by number of days between measures. To test for differences be- tween time points and to test for concordance of measures, a Wilcoxon sign test and a concordance correlation coefficient was performed, respectively.

Analysis of variance was used to assess associations between percent loss per day and categorical variables such as gender. In addition, Pearson correlation coefficients were estimated to assess correlation between percent loss per day and continuous variables such as percentage of energy requirement received through NS.

Linear regression analysis was used to assess the associ- ation between percent loss per day in QMLT and adequate amount of energy intake while adjusting for possible con- founders. Percent loss per day was modeled as the outcome with baseline QMLT measure, energy and protein intake groups, and nutrition status at start of therapy as the independent variables.

A univariable analysis was performed to assess differ- ences between patients receiving NS and HCs. Analysis of variance or nonparametric Kruskal-Wallis tests were used to compare continuous variables, and Pearson χ2 tests were used for categorical factors.

All analyses were performed using SAS (version 9.4, The SAS Institute, Cary, NC), and P < 0.05 was considered statistically significant.

Results

Patient Population

Eighty SICU patients were enrolled in the study. Twenty- eight were withdrawn prior to their second US measurement for not continuing to meet the inclusion criteria. Fifty- two patients had their first set of US measurements upon enrollment (day 1) and a second set of US measurements 3– 5 days later (4.1 ± 1 days). Thirty-eight patients remained

Table 1. Patient Demographics and Clinical Characteristics of Surgical ICU Patients.

Factor Value

Age (y) 65.5 ± 12.9 Gender Female 27 (51.9%) Male 25 (48.1%)

BMI (kg/m2) 31.8 ± 9.6 Nutrition support initiated—ICU day 4.1 ± 1.7 Nutrition support initiated—enrollment day 2.2 ± 1.2 Nutrition support start date

>ICU day 3 30 (57.7%) ≤ICU day 3 22 (42.3%) >ICU day 4 17 (32.7%) ≤ICU day 4 35 (67.3%)

APACHE III a

76.2 ± 24.6 Comorbidities:

<2 1 (1.9%) ≥2 51 (98.1%)

Ventilator days 11.0 [5.0,21.5] Number of times intubated 1.00 [1.00,2.0] ICU LOS (days) 13.0 [9.0,23.0] Expired 9 (17.3%)

Statistics presented as mean ± SD, median [P25,P75], or N (%). APACHE, Acute Physiologic Assessment and Chronic Health Evaluation; BMI, body mass index; ICU, intensive care unit; LOS, length of stay. aData not available for all patients: missing values for 7 patients.

in the enrollment period long enough to have a third set of US measurements 3–5 days (3.9 ± 1.4 days) after the second measurement (Figure 1).

A total of 52 patients were included in the analysis. Table 1 shows a summary of demographic and clinical char- acteristics. Patients enrolled in the study were, on average, >65 years old (age 65.5 ± 12.9 years), were obese (BMI 31.8 ± 9.6), had multiple comorbidities (98.1%), and had a high injury severity risk (APACHE III score 76.2 ± 24.6). A summary of patient characteristics at the time of each US can be found in Table S1. Fluid overload was common, as >96% of study patients demonstrated upper- and/or lower-extremity edema, and of those, >85% demonstrated generalized edema (data not shown).

QMLT Decreases in Critically Ill Patients During ICU Admission

There was a significant decrease in QMLT in the critically ill patients during the study period. Average percent muscle loss per day at the midpoint and one-third landmarks was 3.2 ± 3.8 (P < 0.001) and 2.9 ± 5.7 (P = 0.001), respectively (Figure S2).

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Table 2. Factors Associated With Loss of Quadriceps Muscle Layer Thickness at Midpoint Landmark in Patients Who Started Nutrition Support by Intensive Care Unit Day 3: Multivariable Linear Regression.

Factor Estimate (95% CI) P-value

Midpoint landmark 0.88 (−3.7 to 5.5) 0.69 Energy intake 60%–80%

vs <60% of needs −2.8 (−7.9 to 2.4) 0.27

Energy intake >80% vs <60% of needs

−5.7 (−11.7 to 0.36) 0.064

Protein intake 60%–80% vs <60% of needs

1.3 (−5.7 to 8.3) 0.69

Protein intake >80% vs <60% of needs

1.3 (−4.6 to 7.3) 0.64

Table 3. Factors Associated With Loss of Quadriceps Muscle Layer Thickness at One-Third Landmark: Multivariable Linear Regression.

Factor Estimate (95% CI) P-value

Moderate or severe malnutrition vs none

3.9 (0.05–7.8) 0.047

One-third landmark 5.2 (1.9–8.5) 0.003 Energy intake 60%–80%

vs <60% of needs −0.38 (−4.6 to 3.8) 0.86

Energy intake >80% vs <60% of needs

1.2 (−4.7 to 7.1) 0.69

Protein intake 60%–80% vs <60% of needs

−1.5 (−6.4 to 3.4) 0.54

Protein intake >80% vs <60% of needs

1.1 (−3.3 to 5.6) 0.61

Bold font indicates statistical significance.

QMLT Loss Between US Measurements; Higher Rate of Loss Between US 2 and 3

Between the first and second US, the average daily percent QMLT loss was 1.7%, both at the midpoint and one-third landmark. Between the second and third US, the average daily percent QMLT loss was 4.0% at the midpoint and 4.3% at the one-third landmark. Figure S3 shows the percent muscle loss per day based on each quadriceps landmark.

Malnutrition Affects Rate of QMLT Loss at One-Third Landmark

Factors associated with muscle loss using multivariable linear regression at the midpoint (Table 2) and the one-third landmark (Table 3) are presented. Patients with moderate and severe malnutrition lost more muscle per day (3.9%; P = 0.047) at the one-third landmark compared with patients with no malnutrition diagnosed. There were no differences in average APACHE III scores (76 ± 21 vs 77 ± 27),

ventilator days (13 ± 10 vs 14 ± 8), or ICU LOS (18 ± 14 vs 17 ± 9) in patients diagnosed with moderate or severe malnutrition compared with no malnutrition, respectively.

Medical Interventions and Surgeries for Patients

Physical therapy, mechanical ventilation, and renal replace- ment therapy were tracked during enrollment (Table S2). The number of patients able to participate in physical therapy increased as the enrollment period progressed, with 7.7% participation by the first US to 50% participation by the third US. Conversely, the percentage of patients requiring mechanical ventilation decreased during enroll- ment, with 96.2% of patients ventilated at the first US to 50% ventilated at the third US. The most common operation performed on patients surrounding enrollment was an exploratory laparotomy with bowel resection and/or stoma creation (42.3%). Forty out of the 52 patients enrolled had an operation. A complete list of surgeries can be found in Table S3.

QMLT Loss and Clinical Variables

Univariate relationships between percent muscle loss per day and several continuous clinical variables were analyzed (See Table S4). Of those assessed, body temperature was moderately correlated with percent QMLT loss per day at the midpoint landmark (P = 0.013, ρ = 0.35); higher body temperature was associated with greater muscle loss. Baseline measurements at the one-third landmark were moderately correlated with percent muscle loss per day at the one-third landmark with higher values associated with a higher decrease (P = 0.026). Interestingly, WBC was negatively correlated with percent loss per day at the one- third landmark; a higher WBC correlated with less muscle loss (P = 0.018).

NS Delivery Was Not Associated With QMLT

The cumulative percentage of energy and protein received at the time of each US was analyzed, and patients were further categorized into tertiles, which can be found in Table S5. By the second US (on average, ICU day 4), patients received an average of 59.5% and 68.0% of their estimated energy and protein requirements, respectively. By the third US (on average, ICU day 8), patients received 97.0% and 100% of estimated energy and protein requirements, respectively. Energy and protein intake as a percentage of estimated requirements was not associated with the rate of change in QMLT. A subgroup analysis of patients who were started on NS by day 3 (Table 2) showed less, but not statistically significant, daily QMLT loss at the midpoint landmark when >80% prescribed energy was received (P = 0.064).

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Figure 3. Percent daily muscle change in healthy controls (white boxes) compared with SICU patients (black boxes) at the midpoint and one-third landmarks. Positive numbers represent loss and negative numbers represent gain. Percent daily muscle loss was significantly higher in SICU patients compared with that of healthy controls at both the midpoint and one-third landmarks. * represent statistical significance, P < 0.05. SICU, surgical intensive care unit.

QMLT Measurements in SICU Patients vs HCs

Figure 3 compares the QMLT measurements in HC and SICU patients. The HC and SICU patients were similar in age, gender, and BMI. The SICU patients had significantly lower baseline QMLT at both the midpoint (P = 0.017) and one-third (P = 0.003) landmarks compared with the HCs. As predicted, the average daily percent loss in QMLT was significantly greater in SICU patients compared with the HCs during the study period (P < 0.001) at both midpoint and one-third landmarks, respectively.

Discussion

Here, we report that performing bedside US measurements to assess QMLT loss performed by RDNs is both feasible and consistent. In this study, critically ill surgical patients demonstrated a significant rate of QMLT loss while being cared for in a SICU over a 10-day period, compared with no loss in QMLT in an age-matched HC group over the same time period. Interestingly, preexisting malnutrition had a small effect on the rate of muscle loss, but energy and protein intake did not.

As expected, our data demonstrating decreased QMLT detected by US in the SICU patients corroborate prior stud- ies. However, the overall rate of muscle loss (3.2% and 2.9% per day at the midpoint and one-third landmarks, respec- tively) was higher than other published studies. Puthucheary et al1 demonstrated an average 17.7% reduction in RF CSA in 28 ICU patients over 10 days, an average of 1.8% per day. Interestingly, the pattern of muscle loss in the current study was biphasic. The rate of muscle loss was lower between the first and second measurement compared with the loss

between the second and third measurement. As the acute- phase stress-response curve peaks within the first several days of a metabolic insult and then decreases gradually over the next several weeks in the absence of a new stressor, one may expect muscle loss to be more rapid during the first few days of a metabolic stress.26 However, we found that a higher rate of muscle loss occurred between the second and third US measurements (Figure 4A). This was during a time when the acute-phase response appeared to be resolving demonstrated by a decreasing serum CRP and inotrope use and increasing serum prealbumin level (Figure 4B). Our findings suggest that muscle loss not only continues but also occurs at a higher rate during the resolution phase following metabolic stress, making this time period critical for optimal NS.

As expected, QMLT measurements were stable during a 7–10-day period in the HC group compared with the ICU group (Figure 3), and no significant change was seen in HCs at either the midpoint (P = 0.61) or the one-third measurement (P = 0.61). Although a significant change in QMLT would not be anticipated in healthy individuals, our repeated US measures were not significantly different from each HC’s baseline. This suggests our US technique is con- sistent and demonstrates US assessment can be taught and performed routinely by RDNs and other clinical providers in different populations, including one as vulnerable as the critically ill. Still, validation of the US technique in the critically ill needs to be established.

In this observational study, the finding that energy and protein intake was not associated with the rate of QMLT change was unexpected and conflicts with other published studies. Fetterplace et al9 demonstrated QMLT was atten- uated by 0.22 cm in a 15-day period for ICU patients who received an average of 25 kcal/kg/d and 1.2 g protein/kg/d compared with those who received 18 kcal/kg/d and 0.75 g protein/kg/d at the time of ICU discharge. Ferrie et al27

demonstrated ICU patients receiving an average of 1.1 g protein/kg/d via parenteral nutrition had greater forearm muscle thickness measured by US on day 7 compared with a matched group who received 0.9 g protein/kg/d (P < 0.0001). One possible reason we were not able to detect an effect of energy or protein intake on the percentage of muscle loss is that patients in the current study were all relatively well fed. Most patients received >80% of their estimated nutrition requirements at the time of the third US measurement (81.6% for energy and 84.2% for protein). Additionally, roughly 44% of patients received parenteral nutrition and had minimal interruptions in their NS delivery during the enrollment period. Multivariate analysis demonstrated a weak correlation between QMLT loss and energy and protein intake for patients who started NS by day 3, compared with those started after day 3. These data suggest the timing rather than the quantity of energy and protein delivery might have more of an effect on QMLT

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US 1-2 US 2-3 0

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t m

u s c le

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d a y a

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CRP (mg/dL) Prealbumin (mg/dL) Inotropes (# prescribed)

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Figure 4. Percent muscle loss per day between first and second (white box) and second and third (black box) US measurements (A) compared with acute biochemical markers obtained at the first, second, and third US measurements (B). CRP, C-reactive protein; US, ultrasound.

changes. It is difficult to draw any conclusions from this finding, and it warrants further investigation.

The effect of nutrition status on the rate of QMLT loss and clinical outcomes in the current study is unclear. The rate of QMLT loss in patients with moderate or severe malnutrition was significantly greater compared with patients with no malnutrition at the one-third landmark. It is interesting that the presence and degree of malnutrition was consistent through enrollment (Figure S4). During a 10- day period, we found that SICU patients lost a significant percentage of muscle based on bedside US measurements. Given this finding, one might expect the severity of mal- nutrition to increase; however, using ASPEN/AND criteria to assess for malnutrition, the degree of malnutrition was consistent at each time point of QMLT assessment by US (55.4% with no malnutrition, 31.3% with moderate, and 12.1% with severe) (Figure S4). This finding suggests that US may be a more sensitive tool to assess muscle change in the critically ill compared with assessment tools currently used.10

Despite increased muscle loss, there were no differences in ventilator days or ICU LOS between the groups. Patients in this study were of high acuity with multiple comor- bidities. Most (63.5%) were eventually discharged to a long-term acute care or skilled nursing facility, so perhaps the confounding factors overwhelmed the contribution of malnutrition toward clinical outcomes.

This study has several limitations. Patients evaluated for enrollment were a convenience sample primarily based on the availability of study investigators, which may have introduced study bias. Patients were not all measured on the same day in relation to their ICU admission, and the time period between measurements varied. Only 38 of the 52 enrolled patients completed all 3 measurements, so

that component of a planned dataset is incomplete. Also, patients may have been transferred from other facilities and therefore in various stages of metabolic stress. Lastly, no data were collected on organ function, so it was not possible to determine whether multiorgan failure correlated with rate of muscle loss.

A strength of the study is 1 RDN investigator with the most training and experience performed US measurements in 47 of the 52 SICU patients as well as in all of the HCs, which reduced interrater variability. Another strength is the US images were blinded and read by 1 of 2 musculoskeletal radiologists who were not part of the study team.

Conclusions

Critically ill surgical patients demonstrate acute muscle loss indicated by QMLT percent change measured by bedside US that was not reflected by current recommended nutrition assessment tools. Importantly, muscle loss continues despite patients having received nearly the estimated goal energy and protein requirements by NS. These data indicate the need for further evaluation regarding the impact this may have on patient outcomes. Therefore, larger, prospective, randomized investigations are needed to continue to inves- tigate the timing, route, and delivery of feeding, as well as the role of mobility on muscle mass and clinical outcomes in critically ill patients and whether incorporating US mea- surements into daily practice facilitates a more personalized nutrition care plan and improves patient outcomes.

Acknowledgments

We would like to acknowledge others who have meaningfully contributed to the manuscript. David Schumick, BS, CMI, is our medical illustrated and created our quadriceps image in

402 Journal of Parenteral and Enteral Nutrition 45(2)

Figure 2. Rachel Dalton, RD, LD, a previous dietetic intern and now current RDN, collected data for us during enrollment. Moriyah Cope, RD, LD, a previous dietetic intern and now current RDN, helped with the creations of the tables and figures.

Statement of Authorship

C. Bury, G. Cresci, R. DeChicco, and D. Nowak contributed to conception/design of the research; C. Bury, R. DeChicco, G. Cresci, D. Nowak, R. Lopez, L. He, S. Jacob, and N. Rahman contributed to acquisition, analysis, or interpretation of the data; C. Bury, G. Cresci, R. DeChicco, and D. Nowak drafted the manuscript; C. Bury, R. DeChicco, G. Cresci, D. Nowak, and D. F. Kirby critically revised the manuscript; all authors reviewed and approved the final manuscript and agree to be fully accountable for ensuring the integrity and accuracy of the work.

Supplementary Information

Additional supporting information may be found online in the Supporting Information section at the end of the article.

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