VU Research Portal

(1)

VU Research Portal

Muscle and protein in the ICU

Looijaard, W.G.P.M.

2020

document version

Publisher's PDF, also known as Version of record

Link to publication in VU Research Portal

citation for published version (APA)

Looijaard, W. G. P. M. (2020). Muscle and protein in the ICU: Towards personalized nutrition.

General rights

Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain

• You may freely distribute the URL identifying the publication in the public portal ?

Take down policy

If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

E-mail address:

(2)

(3)

CHAP TER

8

Early high protein intake and

mortality in critically ill ICU

patients with low skeletal muscle

area and -density

W.G.P.M. Looijaard, I.M. Dekker, A. Beishuizen, A.R.J. Girbes, H.M. Oudemans-van Straaten, P.J.M. Weijs Clinical Nutrition. 2019, S0261-5614(19)33067-5

(4)

Chapter 8

Abstract

Background

Optimal nutritional support during the acute phase of critical illness remains controversial. We hypothesized that patients with low skeletal muscle area and -density may specifically benefit from early high protein intake. Aim of the present study was to determine the association between early protein intake (day 2–4) and mortality in critically ill intensive care unit (ICU) patients with normal skeletal muscle area, low skeletal muscle area, or combined low skeletal muscle area and -density.

Methods

Retrospective database study in mechanically ventilated, adult critically ill patients with an abdominal CT-scan suitable for skeletal muscle assessment around ICU admission, admitted from January 2004 to January 2016 (n = 739). Patients received protocolized nutrition with protein target 1.2–1.5 g/kg/day. Skeletal muscle area and -density were assessed on abdominal CT-scans at the 3rd lumbar vertebra level using previously defined cut-offs.

Results

Of 739 included patients (mean age 58 years, 483 male (65%), APACHE II score 23), 294 (40%) were admitted with normal skeletal muscle area and 445 (60%) with low skeletal muscle area. Two hundred (45% of the low skeletal muscle area group) had combined low skeletal muscle area and -density. In the normal skeletal muscle area group, no significant associations were found. In the low skeletal muscle area group, higher early protein intake was associated with lower 60-day mortality (adjusted hazard ratio (HR) per 0.1 g/kg/day 0.82, 95%CI 0.73–0.94) and lower 6-month mortality (HR 0.88, 95%CI 0.79–0.98). Similar associations were found in the combined low skeletal muscle area and -density subgroup (HR 0.76, 95%CI 0.64–0.90 for 60-day mortality and HR 0.80, 95%CI 0.68–0.93 for 6-month mortality).

Conclusions

Early high protein intake is associated with lower mortality in critically ill patients with low skeletal muscle area and -density, but not in patients with normal skeletal muscle area on admission. These findings may be a further step to personalized nutrition, although randomized studies are needed to assess causality.

(5)

High protein intake and mortality in patients with low skeletal muscle area and -density

Introduction

Optimal nutritional support for critically ill patients remains a topic of debate. Particularly the optimal dose of protein and energy during the early phase of critical illness is controversial [1]. Several observational studies found associations between (early or overall) high protein intake and improved outcomes [2-8], although these findings have not been confirmed in RCTs [9-13], and even harmful associations have been found between very early [6, 14] or overall [15] protein intake and mortality. Possibly, optimal early nutrition may differ between individual patients and concomitant early energy overfeeding may be harmful. Several studies found benefit of high protein intake only in specific groups of patients (e.g. non-septic, non-overfed patients [2], high nutrition risk in the critically ill (NUTRIC) score patients [4], or patients with normal kidney function [16]), suggesting that identifying specific patients profiting from early high protein intake may be important.

Previous research shows that patients with low skeletal muscle area (SMA) or low skeletal muscle density (SMD) on intensive care unit (ICU) admission have an increased mortality, independent of severity of disease [17-19]. Since muscle comprises the largest protein pool in the body, these patients have lower protein reserves and may therefore benefit from early high protein intake.

The objective of this retrospective database study was to determine whether the quantity of early protein intake is associated with mortality and other clinical outcomes in critically ill patients admitted with normal or low SMA and SMD. We hypothesized that patients with low SMA and low SMD on abdominal computed tomography (CT) scans may benefit from early high protein intake.

Methods

Patients and data

This retrospective database study evaluated the association between early (day 2–4) protein intake and mortality in three groups of ventilated critically ill patients: normal SMA, low SMA, and a subgroup with combined low SMA and low SMD. Patients were admitted to a medical-surgical ICU of a university hospital (Amsterdam University Medical Center, location VUmc) from January 2004 to January 2016. All patients admitted during this period were screened for eligibility. Inclusion criteria were age ≥18 years, ICU stay ≥4 days, mechanical ventilation, and an abdominal CT-scan made ≤4 days before or after ICU admission. Patients were excluded if the CT-scan was not suitable for muscle analysis (Appendix 1), data on weight or height were missing, or oral intake was initiated within 4 days.

The study was approved by the VUmc institutional review board (IRB00002991, decision 2012/243). The need for informed consent was waived because of the retrospective nature of the study using coded data obtained from standard care. The study has been registered at ClinicalTrials.gov (NCT02817646).

Patient data including age, sex, weight, height, admission diagnosis, acute physiological, age, and chronic health evaluation (APACHE) II score, daily protein and energy intake (including non-nutritional sources), length of ventilation, ICU- and hospital length of

(6)

stay, discharge destination, and mortality were obtained from the ICU patient data management system (Metavision, IMDsoft, Tel-Aviv, Israel), hospital information system (Mirador, iSOFT Nederland BV, Leiden, The Netherlands), civil registry, or general practitioner.

Primary endpoints were short-term mortality 60 days after ICU admission and long-term mortality 6 months after ICU admission. Secondary endpoints were the odds of being discharged to home, length of ventilation, and ICU- and hospital length of stay.

CT-scan analysis

Patients were categorized into three groups; admitted with normal SMA, with low SMA, and a subgroup of the low SMA group admitted with combined low SMA and low SMD [18-19].

All abdominal CT-scans made during the study period for diagnostic or interventional purposes ≤4 days before or after ICU admission were reviewed for suitability for muscle analysis. CT-scans were analyzed using Slice-O-matic versions 4.3 and 5.0 (TomoVision, Montreal, QC, Canada) by two certified investigators (WGPML and IMD, trained by the Cross Cancer Institute, Canada). CT-scans were analyzed at the level of the third lumbar vertebra (L3). The precision of single L3 slice CT-scan analysis is high (inter- and intra-observer variability <2%) [20] and L3 SMA is strongly related to whole-body skeletal muscle volume (r = 0.83–0.99, p < .01) [21-22].

Muscle tissue was identified using boundaries in Hounsfield Units (HU) set to −29 to +150 [23]. All muscles present at the L3 level were analyzed. Low SMA was defined using

previously found ICU-specific cut-off points: males <170 cm2_{and females <110 cm}2_{, which}

were associated with hospital mortality. Patients with a low SMA according to these cut-off points had an odds ratio for hospital mortality of 4.3 (95% confidence interval (CI) 2.0–9.0, p < .001) compared to those with normal SMA [18]. The software automatically calculates SMD from the mean radiological attenuation of all L3 muscle. Low SMD was defined using cut-off points the for the 5th percentile from a healthy population of kidney donors (95% of this healthy population had a SMD above these values and 5% below these values): males <29.3 HU and females <22.0 HU [24].

Protein intake and nutritional protocol

Average daily protein intake over ICU admission day 2–4 was used as early protein intake. Day 1 was excluded to include only full nutrition days. Protein intake was analyzed both as continuous variable and dichotomized using mean day 2–4 intake ≥1.2 g/kg/d or <1.2 g/kg/d.

Enteral nutrition (EN) was initiated within 24 h from ICU admission or after hemodynamic stabilisation. The preferable route was enteral, parenteral nutrition (PN) was provided only when the gut failed, not as supplemental nutrition in the first week.

The protein intake target was 1.2–1.5 g/kg pre-admission body weight per day. Weight

was adjusted to weight at body-mass index (BMI) 20 kg/m2_{for patients with BMI <20}

kg/m2_{and to weight at BMI 27.5 kg/m}2_{for BMI >30 kg/m}2_{[25]. Protein provision was not}

adjusted in case of renal failure or renal replacement therapy.

(7)

Energy target was estimated resting energy expenditure (REE) using the Harris and Benedict 1984 equation [26] +30% for stress and activity.

We previously developed an algorithm to select the best nutritional formula and feeding rate to meet both energy- and protein targets, using several nutritional formulae with a range of energy-to-protein ratios [27].

Statistical analysis

Independent samples T-tests and Mann–Whitney U-tests were used to compare

continuous variables, and Fisher Exact tests and Chi2_{-tests with post-hoc z-test with}

Bonferroni correction for categorical variables. Kaplan Meier survival curves were made for the normal SMA, low SMA, and combined low SMA and low SMD groups; and for protein intake (≥1.2 g/kg/d vs. <1.2 g/kg/d) within these groups, with Log-rank tests to compare survival curves.

Cox regression analysis was used to evaluate the association between protein intake (as continuous variable and dichotomous ≥1.2 g/kg/d vs. <1.2 g/kg/d) and 60-day- and 6-month mortality, with adjustments for APACHE II score and energy intake as proportion of calculated needs.

To evaluate secondary outcome measures in ICU- or hospital survivors, logistic regression analysis was used for discharge to home and linear multiple regression analyses for length of ventilation, and ICU- and hospital length of stay. Finally, we performed sensitivity analyses including only patients who were adequately fed (80– 120% of energy target); pre-ICU hospital stay of <1 week; excluding trauma patients; with additional adjustments for sex, age, and pre-ICU hospital stay; with cut-off points for skeletal muscle index [28]; and with protein intake expressed in g/kg ideal body weight [29]. Additional information on these statistical analyses can be found in Appendix 2. IBM SPSS Statistics 22 (IBM Corp, Armonk, NY, USA); R 3.5.0 (R Foundation for Statistical Computing, Vienna, Austria) with survival-, tidyverse-, and ggfortify packages; and GraphPad Prism 7 (GraphPad Software, La Jolla, CA, USA) were used for statistical analysis. Values are reported as mean (±standard deviation, SD) or median (25–75% interquartile range, IQR). All statistical tests were conducted two-sided. A p < .05 was considered statistically significant.

Results

A total of 3,851 patients were admitted to the ICU during the study period for at least 4 days and mechanically ventilated, with a mean APACHE II score of 24.8 (Supplemental Figure 1). Nine hundred eighty-two patients fulfilled inclusion criteria. After excluding patients with CT-scans not suitable for muscle analysis (n = 210) or missing data (n = 33), 739 patients were available for final analysis.

The CT-scan was made within one day of ICU admission in 595 patients (81%). Of 739 patients, 445 patients (60%) were admitted to the ICU with low SMA, and among these 200 patients (45% of the low SMA group) with combined low SMA and low SMD. Nutritional intake is presented in Supplemental Table 1.

8

(8)

M us cle g ro up s No rm al sk el et al m us cle a re a a Lo w sk el et al m us cle a re a a Co m bi ne d lo w sk el et al m us cle a re a an d -d en sit y su bg ro up a N or m al SM A n = 29 4 Lo w S M A n = 44 5 P-va lu e vs . no rm al SM A Lo w S M A & lo w S M D n = 20 0 P-va lu e vs . no rm al SM A Pr ot ei n < 1. 2 g /k g/ da y b n = 26 0 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 34 P-va lu e pr ot ei n gr ou ps Pr ot ei n < 1. 2 g/ kg /d ay b n = 37 2 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 73 P-va lu e pr ot ei n gr ou ps Pr ot ei n < 1. 2 g/ kg /d ay b n = 17 1 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 29 P-va lu e pr ot ei n gr ou ps Ag e, m ed ia n (IQ R) , y 52 (3 6– 65 ) 66 (5 4– 75 ) <. 00 1 71 (6 2– 77 ) <. 00 1 52 (3 7– 65 ) 50 (3 0– 63 ) .7 8 67 (5 4– 75 ) 62 (5 5– 72 ) .1 2 72 (6 2– 77 ) 68 (5 7– 75 ) .1 0 Se x m al e, N o. (% ) 17 9 (6 1) 30 4 (6 8) .0 4 14 4 (7 2) .0 1 16 3 (6 3) 16 (4 7) .0 9 25 9 (7 0) 45 (6 2) .2 2 12 5 (7 3) 19 (6 6) .5 0 W ei gh t, m ed ia n (IQ R) , k g 80 (7 1– 90 ) 75 (6 5– 82 ) <. 00 1 79 (7 0– 85 ) .0 2 80 (7 3– 90 ) 75 (6 5– 80 ) .0 06 75 (6 5– 83 ) 70 (6 0– 80 ) .0 4 77 (7 0– 85 ) 80 (7 0– 87 ) .3 9 BM I, m ed ia n (IQ R) , k g/ m 2 25 .6 (2 3. 5– 27 .8 ) 24 .4 (2 2. 5– 26 .4 ) <. 00 1 25 .1 (2 3. 2– 27 .9 ) .4 1 25 .7 (2 3. 5– 27 .8 ) 24 .5 (2 3. 0– 25 .8 ) .0 2 24 .5 (2 2. 8– 26 .8 ) 23 .5 (2 1. 5– 24 .9 ) .0 2 25 .3 (2 3. 1– 27 .8 ) 24 .8 (2 3. 3– 29 .4 ) .6 5 U nd er -w ei gh t, N o. (% ) c 2 (1 ) 25 (6 ) 8 (4 ) 2 (1 ) a 0 (0 ) a 18 (5 ) a 7 (9 ) a 6 (3 ) a 2 (7 ) a N or m al w ei gh t, N o. (% ) c 13 5 (4 6) 25 2 (5 6) 92 (4 6) 11 3 (4 3)a 22 (6 5)b 20 3 (5 5)a 49 (6 7)b 77 (4 5)a 15 (5 2)a O ve r-w ei gh t, N o. (% ) c 12 2 (4 1) 12 9 (2 9) 73 (3 7) 11 1 (4 3)a 11 (3 2)a 11 9 (3 2)a 10 (1 5)b 68 (4 0)a 5 (1 7)b O be se , N o. (% ) c 35 (1 2) 39 (9 ) 27 (1 3) 34 (1 3) a 1 (3 ) a 32 (8 ) a 7 (9 ) a 20 (1 2) a 7 (2 4) a AP AC HE II sc or e, m ea n (S D) 22 (8 ) 25 (8 ) <. 00 1 26 (8 ) <. 00 1 21 (7 ) 23 (8 ) .3 4 25 (8 ) 23 (8 ) .0 9 26 (8 ) 22 (8 ) .0 1 Ad m iss io n ca te go ry , N o. (% ) <. 00 1 <. 00 1 .7 0 .2 5 .4 2 M ed ic al 95 (3 2) 22 4 (5 0) 11 7 (5 8) 83 (3 2) 12 (3 5) 19 2 (5 2) 32 (4 3) 10 2 (6 0) 15 (5 2) Su rg ic al 19 9 (6 8) 22 1 (5 0) 83 (4 2) 17 7 (6 8) 22 (6 5) 18 0 (4 8) 41 (5 7) 69 (4 0) 14 (4 8) Ad m iss io n di ag no sis , N o. (% ) <. 00 1 <. 00 1 .1 0 .1 8 .6 7 Ca rd io -v as cu la r 6 (2 ) 29 (6 ) 13 (7 ) 6 (2 ) a 0 (0 ) a 25 (7 ) a 4 (5 ) a 11 (6 ) a 2 (7 ) a M et ab ol ic /R en al 8 (3 ) 11 (3 ) 10 (5 ) 8 (3 )a 0 (0 )a 11 (3 )a 0 (0 )a 10 (6 )a 0 (0 )a N eu ro lo gi c 16 (5 ) 17 (4 ) 4 (2 ) 16 (6 )a 0 (0 )a 14 (4 )a 3 (4 )a 3 (2 )a 1 (3 )a Po st -r es us ci ta tio n 13 (4 ) 29 (6 ) 14 (7 ) 13 (5 )a 0 (0 )a 29 (8 )a 0 (0 )b 14 (8 )a 0 (0 )a Po st -s ur ge ry 60 (2 1) 14 6 (3 3) 74 (3 7) 53 (2 0)a 7 (2 1)a 11 5 (3 1)a 31 (4 3)a 61 (3 6)a 13 (4 5)a Re sp ira to ry in su ffi ci en cy 23 (8 ) 66 (1 5) 36 (1 8) 17 (7 ) a 6 (1 7) b 54 (1 4) a 12 (1 6) a 30 (1 8) a 6 (2 1) a Se ps is 22 (8 ) 48 (1 1) 28 (1 4) 18 (7 )a 4 (1 2)a 40 (1 1)a 8 (1 1)a 23 (1 3)a 5 (1 7)a Tr au m a 13 9 (4 7) 75 (1 7) 9 (4 ) 12 4 (4 8) a 15 (4 4) a 65 (1 7) a 10 (1 4) a 8 (5 ) a 1 (3 ) a O th er 7 (2 ) 24 (5 ) 12 (6 ) 5 (2 )a 2 (6 )a 19 (5 )a 5 (7 )a 11 (6 )a 1 (3 )a T able 1. Char acteristic

s of patients with mean da

y 2 –4 pr otein intake <1.2 g/kg/ da y or ≥1.2 g/kg/ da

y in patients admitted with lo

w skeletal mu scle ar ea or combined lo w skeletal mu scle ar ea and -den sit y

(9)

M us cle g ro up s No rm al sk el et al m us cle a re a a Lo w sk el et al m us cle a re a a Co m bi ne d lo w sk el et al m us cle a re a an d -d en sit y su bg ro up a N or m al SM A n = 29 4 Lo w S M A n = 44 5 P-va lu e vs . no rm al SM A Lo w S M A & lo w S M D n = 20 0 P-va lu e vs . no rm al SM A Pr ot ei n < 1. 2 g /k g/ da y b n = 26 0 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 34 P-va lu e pr ot ei n gr ou ps Pr ot ei n < 1. 2 g/ kg /d ay b n = 37 2 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 73 P-va lu e pr ot ei n gr ou ps Pr ot ei n < 1. 2 g/ kg /d ay b n = 17 1 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 29 P-va lu e pr ot ei n gr ou ps Le ng th o f p re -IC U h os pi ta l s ta y, m ed ia n (IQ R) , d 0 (0 –1 ) 1 (0 –4 ) <. 00 1 2 (0 –6 ) <. 00 1 0 (0 –1 ) 2 (0 –1 3) <. 00 1 0 (0 –3 ) 4 (0 –1 0) <. 00 1 1 (0 –5 ) 4 (1 –1 4) .0 09 Ti m e fr om IC U a dm iss io n to CT -s ca n, m ea n (S D) , d 0 (1 ) 0 (1 ) .7 8 0 (2 ) .1 4 0 (1 ) 0 (2 ) .0 5 0 (1 ) 0 (2 ) .2 0 1 (2 ) 0 (2 ) .1 7 Sk el et al m us cl e ar ea , m ed ia n (IQ R) , c m 2 Fe m al e 12 3 (1 16 –1 38 ) 96 (8 4– 10 2) <. 00 1 89 (7 6– 99 ) <. 00 1 12 2 (1 16 –1 36 ) 12 8 (1 18 –1 41 ) .5 3 95 (8 4– 10 1) 97 (9 0– 10 4) .2 1 88 (7 4– 98 ) 96 (8 7– 10 1) .1 2 M al e 19 4 (1 81 –2 09 ) 14 2 (1 24 –1 58 ) <. 00 1 13 5 (1 16 –1 50 ) <. 00 1 19 4 (1 82 –2 09 ) 18 5 (1 76 –2 00 ) .2 2 14 4 (1 25 –1 58 ) 13 3 (1 21 –1 49 ) .0 1 13 6 (1 17 –1 52 ) 13 3 (1 13 –1 49 ) .4 0 Sk el et al m us cl e in de x, m ed ia n (IQ R) , c m 2/m 2 Fe m al e 44 .5 (4 0. 9– 48 .7 ) 34 .7 (3 1. 2– 37 .6 ) <. 00 1 32 .7 (2 8. 9– 35 .5 ) <. 00 1 44 .4 (4 0. 7– 48 .2 ) 46 .6 (4 1. 1– 50 .1 ) .5 0 34 .5 (3 0. 7– 37 .7 ) 35 .8 (3 3. 1– 37 .4 ) .2 7 32 .0 (2 7. 8– 35 .0 ) 34 .0 (3 2. 8– 36 .9 ) .1 3 M al e 59 .3 (5 5. 2– 64 .1 ) 45 .5 (4 0. 1– 49 .1 ) <. 00 1 42 .8 (3 7. 0– 48 .2 ) <. 00 1 59 .3 (5 5. 2– 64 .2 ) 57 .7 (5 5. 3– 62 .7 ) .7 1 45 .9 (4 0. 4– 49 .5 ) 42 .3 (3 7. 4– 47 .1 ) .0 3 43 .0 (3 7. 7– 48 .2 ) 38 .3 (3 6. 1– 46 .9 ) .1 9 Sk el et al m us cl e de ns ity , m ea n (S D) , H U Fe m al e 31 .6 (1 1. 6) 25 .7 (1 0. 3) <. 00 1 15 .7 (4 .1 ) <. 00 1 32 .0 (1 1. 4) 30 .0 (1 2. 9) .5 2 25 .4 (1 0. 4) 26 .9 (1 0. 0) .4 8 15 .6 (4 .2 ) 16 .1 (3 .8 ) .7 0 M al e 42 .0 (1 1. 3) 30 .9 (1 1. 3) <. 00 1 21 .5 (5 .5 ) <. 00 1 42 .0 (1 1. 1) 41 .9 (1 3. 4) .9 5 31 .0 (1 1. 6) 30 .1 (9 .6 ) .6 1 21 .5 (5 .5 ) 21 .7 (5 .2 ) .8 9 Pr ot ei n in ta ke d ay 2 –4 , m ea n (S D) , g /k g/ d 0. 70 (0 .3 9) 0. 75 (0 .4 2) .1 3 0. 73 (0 .3 9) .4 1 0. 61 (0 .3 1) 1. 38 (0 .1 4) <. 00 1 0. 62 (0 .3 3) 1. 39 (0 .1 7) <. 00 1 0. 62 (0 .3 2) 1. 35 (0 .1 2) <. 00 1 En er gy in ta ke d ay 2 –4 , m ea n (S D) , k ca l/k g/ d 17 .5 (7 .8 ) 18 .8 (8 .5 ) .0 4 17 .7 (7 .6 ) .7 6 16 .0 (6 .8 ) 28 .9 (4 .0 ) <. 00 1 16 .6 (6 .9 ) 30 .3 (6 .5 ) <. 00 1 16 .0 (6 .5 ) 28 .1 (5 .5 ) <. 00 1 En er gy in ta ke d ay 2 –4 , m ea n (S D) , % o f R EE /d 84 (3 6) 90 (3 8) .0 3 89 (3 7) .1 7 77 (3 2) 13 8 (1 4) <. 00 1 80 (3 2) 14 3 (2 3) <. 00 1 80 (3 2) 14 0 (1 9) <. 00 1 a, b V

alues within a musc

le gr

oup on the same r

ow not sharing the same subscript w

er

e significantly differ

ent on post-hoc z-test with Bonferr

oni corr ection a Skeletal musc le ar ea cut-offs: 170 cm 2 for males and 110 cm 2 for females, [15] skeletal musc le densit y cut-offs: 29.3 HU for males and 22. 0 HU for females [21] b Mean pr otein intake on da y 2 –4

c WHO categories; under

w eight: BMI < 18 .5 kg/ m 2, normal w eight: BMI 18 .5–24.9 kg/ m 2, o ver w eight: BMI 25–29.9 kg/ m 2, obesit y: BMI ≥30 kg/ m 2 P

-values in bold indicate a significant test r

esult AP A CHE acute ph ysiological, age , and c hr onic health e valuation, BMI

body mass inde

x, CT computed tomogr aph y, ICU intensiv e car e unit, REE r esting energy e xpenditur e T able 1. Char acteristic

s of patients with mean da

y 2 –4 pr otein intake <1.2 g/kg/ da y or ≥1.2 g/kg/ da

y in patients admitted with lo

w skeletal mu scle ar ea or combined lo w skeletal mu scle ar ea and -den sit y (continued)

8

(10)

Figur

e 1.

Kaplan Meier sur

vival cur

ves comparing patients admitted with normal SMA

, lo

w SMA

, and combined lo

w SMA and lo

w SMD (A),

and Kaplan Meier sur

vival cur

ves in patients admitted with normal SMA (B),

lo w SMA (C), and combined lo w SMA and lo w SMD (D) comparing mean da y 2 –4 pr otein intake <1.2 g/kg/ d vs. ≥1.2 g/kg/ d. P

atients admitted with combined lo

w SMA and lo w SMD had the lo w est 6 -month sur vival. Within this gr oup

, those with an early pr

otein intake ≥1.2 g/kg/

d had a better 6

-month sur

vival than those with <1.2 g/kg/

d. L og-r ank tests w er e used to compar e sur vival cur ves. Light-colour ed ar

eas denote the 95% confidence inter

val SMA skeletal musc le ar ea, SMD skeletal musc le densit y Chapter 8

(11)

8

T

able 2.

Outcomes of patients with mean da

y 2 –4 pr otein intake <1.2 g/kg/ da y or ≥1.2 g/kg/ da y within mu scle gr oups a Skeletal musc le ar ea cut-offs: 1 70 cm

2 for males and 110 cm 2 for females,

[15] skeletal musc

le densit

y

cut-offs: 29.3 HU for males and 22.

0 HU

for females [21] b Mean pr

otein intake on da

y 2

–4

c Due to losses to follo

w-up

, standar

dized mor

talit

y was kno

wn for a subset of patients.

Sixt y-da y mor talit y n = 699. Six-month mor talit y n = 690 d L ength of v

entilation and length of IC

U sta y in IC U sur viv or s only , n = 619 e L

ength of hospital sta

y and destination after disc

harge in hospital sur

viv

or

s only

, n = 561

P

-values in bold indicate a significant test r

esult

ICU

i ntensiv

e car

e unit

N or m al sk el et al m us cl e ar ea a Lo w sk el et al m us cl e ar ea a Co m bi ne d lo w sk el et al m us cl e ar ea an d -d en sit y su bg ro up a Pr ot ei n < 1. 2 g/ kg /d ay b n = 26 0 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 34 P-va lu e Pr ot ei n < 1. 2 g/ kg /d ay b n = 37 2 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 73 P-va lu e Pr ot ei n < 1. 2 g/ kg /d ay b n = 17 1 Pr ot ei n ≥ 1. 2 g/ kg /d ay b n = 29 P-va lu e 60 -d ay m or ta lit y, N o. (% ) c 37 (1 5) 3 (9 ) .4 4 12 2 (3 4) 17 (2 5) .1 6 72 (4 3) 3 (1 1) .0 01 6-m on th m or ta lit y, N o. (% ) c 46 (2 0) 5 (1 5) .6 4 15 4 (4 4) 26 (3 8) .5 0 90 (5 4) 8 (2 9) .0 2 Le ng th o f v en til at io n, m ed ia n (IQ R) , d d 10 (5 –1 8) 10 (5 –1 7) .7 2 9 (6 –1 7) 9 (5 –1 8) .3 7 9 (5 –1 7) 10 (4 –2 8) .8 5 Le ng th o f I CU st ay , m ed ia n (IQ R) , d d 13 (7 –2 2) 14 (6 –2 3) .8 6 13 (8 –2 2) 12 (7 –2 1) .3 1 12 (8 –2 1) 13 (6 –2 8) .8 6 Le ng th o f h os pi ta l s ta y, m ed ia n (IQ R) , d e 33 (2 0– 50 ) 41 (2 5– 57 ) .1 9 34 (2 2– 57 ) 45 (3 0– 69 ) .0 1 35 (2 3– 61 ) 63 (3 7– 77 ) .0 1 De st in at io n af te r d isc ha rg e, N o. (% ) e .8 5 .1 0 .4 9 Ho m e 87 (3 8) 13 (4 3) 80 (3 3) 25 (4 5) 33 (3 5) 11 (4 4) O th er h os pi ta l 49 (2 2) 4 (1 3) 68 (2 8) 11 (1 9) 25 (2 8) 4 (1 6) N ur sin g ho m e 42 (1 8) 6 (2 0) 53 (2 1) 14 (2 5) 27 (2 9) 7 (2 8) Re ha bi lit at io n un it 31 (1 4) 5 (1 7) 25 (1 0) 6 (1 1) 5 (5 ) 3 (1 2) O th er 19 (8 ) 2 (7 ) 20 (8 ) 0 (0 ) 3 (3 ) 0 (0 )

(12)

Chapter 8

a _{Average day 2–4 protein intake per 0.1 g/kg/day increase} b _{Average day 2–4 protein intake ≥1.2 g/kg/day vs. <1.2 g/kg/day}

c_{SMA cut-offs: 170 cm}2_{for males and 110 cm}2_{for females, [15] SMD cut-offs: 29.3 HU for males and}

22.0 HU for females [21]. Normal SMA n=294. Low SMA n=444. Low SMA & low SMD n=200

d_{Proportional hazards assumption not met, therefore the time-dependent covariate was added to}

the Cox regression model

Values in bold indicate a significant result, p < .05

APACHE acute physiological, age, and chronic health evaluation, HR hazard ratio, SMA skeletal muscle area, SMD skeletal muscle density

Table 3. Cox regression analyses on the association between mean day 2–4 protein intake and 60-day- and 6-month mortality

Protein intake – continuousa _{Protein intake – dichotomized}b

Unadjusted model Adjusted model Unadjusted model Adjusted model

HR 95%CI HR 95%CI HR 95%CI HR 95%CI

60-day mortality Normal SMAc Protein intake 0.91d_0.79–1.05 _0.92d _0.72–1.18 _0.57 _0.18–1.86 _0.28 _0.07–1.08 APACHE II score 1.07 1.03–1.12 1.08 1.04–1.13 Energy intake 0.92 0.09–9.33 2.33 0.78–7.01 Low SMAc Protein intake 0.92d_0.86–0.99 _0.82d _0.73–0.94 _0.66 _0.40–1.09 _0.53 _0.29–0.98 APACHE II score 1.06 1.04–1.08 1.06 1.04–1.08 Energy intake 3.93 1.20–12.85 1.64 0.94–2.87

Low SMA & low SMDc

Protein intake 0.96 0.90–1.01 0.76 0.64–0.90 0.20 0.06–0.63 0.16 0.05–0.55 APACHE II score 1.06 1.03–1.09 1.05 1.02–1.08 Energy intake 13.65 2.39–77.95 1.98 0.90–4.37 6-month mortality Normal SMAc Protein intake 1.02 0.96–1.09 0.99 0.83–1.19 0.75 0.30–1.90 0.40 0.13–1.19 APACHE II score 1.07 1.04–1.11 1.08 1.04–1.12 Energy intake 1.37 0.18–10.42 2.05 0.78–5.41 Low SMAc Protein intake 0.96d_0.91–1.01 _0.88d _0.79–0.98 _0.79 _0.52–1.20 _0.64 _0.38–1.06 APACHE II score 1.05 1.03–1.07 1.05 1.03–1.07 Energy intake 2.72 0.95–7.79 1.64 1.01–2.68

Low SMA & low SMDc

Protein intake 0.92d_0.86–0.99 _0.80 d_0.68–0.93 _0.40 _0.20–0.83 _0.32 _0.14–0.74

APACHE II score 1.05 1.02–1.07 1.04 1.01–1.07

(13)

Patient characteristics of muscle groups

Patients admitted with low SMA were significantly older, more often male, had a lower weight and BMI, higher APACHE II score, longer pre-ICU hospital stay, and were less often trauma patients when compared to the normal SMA group (Table 1). Early (day 2–4) protein intake was not significantly different between the low- and normal SMA groups (0.70 ± 0.39 vs. 0.75 ± 0.42 g/kg/d, respectively, p = .13). The low SMA group received more energy (90 ± 38% vs. 84 ± 36% of REE, p = .03).

Similar differences were seen between the combined low SMA and low SMD subgroup and the normal SMA group, except that BMI and energy intake were not significantly different (Table 1).

Mortality in muscle groups

Sixty-day and six-month mortality were 14.6% and 22.1% in the normal SMA group, 32.7% and 42.7% in the low SMA group, and 38.3% and 50.0% in the combined low SMA and low SMD subgroup (all p < .001 vs. normal SMA). Kaplan Meier survival curves of the latter two groups were significantly lower than the normal SMA group (Figure 1A).

Patient characteristics and mortality of protein intake groups within muscle groups In the normal- and low SMA groups, patients with an early protein intake ≥1.2 g/kg/d had a lower body weight and BMI, and longer pre-ICU hospital stay than patients who received <1.2 g/kg/d (Table 1). In the combined low SMA and low SMD subgroup, patients with an early protein intake ≥1.2 g/kg/d had a lower APACHE II score and longer pre-ICU hospital stay.

Mortality was not significantly different between protein intake ≥1.2 g/kg/d vs. <1.2 g/ kg/d in the normal SMA and low SMA groups (Table 2). However, in the combined low SMA and low SMD subgroup, both 60-day and 6-month mortality were significantly lower in patients with an early protein intake ≥1.2 g/kg/d (11% vs. 43%, p = .001 and 29% vs. 54%, p = .02, respectively).

Protein intake as continuous variable

In adjusted Cox regression analysis with protein intake expressed as continuous variable, no significant association between protein intake and mortality was found in the normal SMA group (Table 3). In the low SMA group, higher early protein intake was associated with lower 60-day mortality (adjusted hazard ratio (HR) per 0.1 g/kg/d 0.82, 95% CI 0.73–0.94) and lower 6-month mortality (HR 0.88, 95%CI 0.80–0.98). Similar associations were found in the combined low SMA and low SMD subgroup (HR 0.76, 95%CI 0.64–0.90 for 60-day mortality and HR 0.80, 95%CI 0.68–0.93 for 6-month mortality). Higher early energy intake was associated with higher 60-day and 6-month mortality in the low SMA group and in the combined low SMA and low SMD subgroup, but not in the normal SMA group. The hazard ratios associated with different levels of protein- and energy intake are visualised in Figure 2 (60-day mortality) and Supplemental Figure 2 (6-month mortality).

8

(14)

Figur e 2. Adjusted hazar d r atios for 60 -da y mor talit y of da y 2 -4 pr

otein intake (top r

ow) and da

y 2

-4 energy intake (bottom r

ow).

Hazar

d

ratios in patients admitted with normal SMA (left),

lo w SMA(middle), and combined lo w SMA and lo w SMD (right). Data w er e fit using a co x regr ession model. The gr aphs w er e truncated at a pr otein intake

of 1.5g/kg and an energy intakeof 150% of

REE

because

of

the

limited

number of patients with higher intakes.

Pr

otein intake was adjusted for AP

A

CHE II scor

e and energy intake

, while energy intake was adjusted

for AP A CHE II scor e and pr otein intake . In the lo w SMA gr

oup and in the combined lo

w SMA and lo

w SMD gr

oup

, higher pr

otein intake was

associated with lo w er 60 -da y mor talit

y and higher energy intake was associated with higher 60

-da y mor talit y. The blue ar ea sho ws the 95% confidence inter val REE r esting energy e xpenditur e, SMA skeletal musc le ar ea, SMD skeletal musc le densit y Chapter 8

(15)

8

Protein intake as dichotomized variable

Kaplan Meier survival curves of patients with an early protein intake ≥1.2 g/kg/d were significantly higher than those who received <1.2 g/kg/d in the combined low SMA and low SMD subgroup (Figure 1D), but not in the normal- and low SMA groups (Figure 1B,C). In the normal SMA group, no significant association was found between protein intake and mortality (Table 3). In the low SMA group, early protein intake ≥1.2 g/kg/d was associated with lower 60-day mortality (HR 0.53, 95%CI 0.29–0.98), and in the combined low SMA and low SMD subgroup with lower 60-day mortality (HR 0.16, 95%CI 0.05–0.55) and lower 6-month mortality (HR 0.32, 95%CI 0.14–0.74).

Secondary outcomes

Protein intake was not associated with the odds of discharge to home (Supplemental Table 2). However, higher protein intake as continuous variable was associated with a shorter ICU stay, and both as continuous and dichotomized variable with shorter mechanical ventilation in patients with normal- and low SMA, but not in patients with combined low SMA and low SMD.

Sensitivity analyses

In sensitivity analyses the results remained robust (Supplemental Table 3). Discussion

This study in mechanically ventilated patients admitted to the ICU for at least four days and having an abdominal CT-scan made around admission demonstrates that an early higher protein intake is associated with lower mortality in patients admitted with low skeletal muscle area and -density but not in patients admitted with normal skeletal muscle area when adjusted for confounders energy intake and severity of disease. These findings are relevant because low skeletal muscle area and the combination with low skeletal muscle density on admission are associated with high mortality and appear to be common among critically ill patients (60% and 27% respectively). This study suggests that these patients may benefit from an early high protein intake of ≥1.2 g/kg/d. Although our findings have a physiological rationale and were robust in sensitivity analyses, no inferences about causality can be made in this retrospective study and randomized studies are needed to exclude residual confounding and assess causality. Nevertheless, this is the largest study op to now combining both muscle- and nutritional data and our findings may be a first step to personalized nutritional support during critical illness. High protein intake

We previously found an association between day 4 protein intake of ≥1.2 g/kg/d and lower hospital mortality in non-septic, non-overfed critically ill patients [2]. In the current study, we identify a subgroup which may specifically benefit from early high protein intake. An association between higher protein intake and lower mortality was demonstrated in several observational studies in a heterogeneous ICU population [3, 5, 7]. Few studies specifically report early protein intake. In a retrospective cohort study, Bendavid et al.

(16)

found an association between a protein intake of >0.7 g/kg/d during the first 3 days of ICU admission and lower 60-day all-cause mortality [8]. Additionally, in another large retrospective cohort study, Zusman et al. also found a significant association between day 3 protein intake of 1 g/kg/d and lower mortality [30]. However, higher protein delivery in the first week was found to be associated with greater muscle wasting in a small selected cohort of patients with prolonged critical illness [15]. Additionally, Koekkoek et al. found lower mortality when protein intake was gradually increased during 7 days [6]. Similarly, a post-hoc analysis of the EPaNIC trial suggested that the day 3 protein/amino acid dose, rather than the glucose dose, explained the delayed recovery in the early PN group [14]. However, on day 5 and day 7 this association was not found. Thus, especially the optimal protein dose early during critical illness is still controversial.

These seemingly contrasting findings suggest that optimal nutritional strategies may differ between patients. Certain subgroups may benefit while others may not. Indeed, in a post-hoc subgroup analysis of the Nephro-protective randomized trial, reduced mortality was observed only in patients with normal kidney function allocated to receive high protein [16]. Additionally, an association between greater protein adequacy and lower mortality was found only in patients with a high NUTRIC score [4]. The present study suggests that specifically patients with low SMA and low SMD may benefit from early high protein intake.

The contrasting findings regarding early protein intake may also be attributed to concomitant energy overfeeding. Because of inflammation-induced endogenous energy production, hypocaloric nutrition is recommended during early critical illness [2, 3, 31]. In the well-designed EAT-ICU trial, early goal directed nutrition was not associated with improved outcomes [12]. Furthermore, the INTACT trial was stopped prematurely because of higher mortality in the intensive medical nutrition therapy group [13]. In both trials, the high-protein groups received full energy from day 1 with inherent risk of early energy overfeeding. In the current study, mean energy intake was frequently at or above target as well and higher early energy intake was associated with higher mortality. We therefore adjusted for energy intake and validated our results in a sensitivity analysis including only patients who were not under- nor overfed, and found similar results. Hence, our results are robust but observational. The benefit of early high protein in patients admitted with low SMA and low SMD should now be assessed in a randomized study avoiding energy overfeeding by the use of protein supplements or a high protein-to-energy ratio nutrition.

Low skeletal muscle density and protein intake

In the present study, the association between high protein intake and lower mortality was more pronounced in patients admitted with combined low SMA and SMD. While a low SMA is an indication of low muscle mass and therefore low protein reserves, low SMD is associated with qualitative changes in muscle such as fatty infiltration or myosteatosis [32]. Myosteatosis may create an environment with low-grade inflammation and insulin resistance [33-35], which contribute to anabolic resistance [36]. A higher protein intake may be needed to overcome this anabolic resistance. This may additionally explain why

(17)

the most apparent benefit of protein intake was seen in the patients with combined low SMA (low reserves) and low SMD (anabolic resistance). However, these explanations remain speculation.

Low skeletal muscle area and -density

The high prevalence of both low SMA and low SMD found in this study, as well as the increased mortality in these groups, are in line with other studies [17-19, 37-38]. Identifying these patients may improve risk-stratification and help guide treatments. However, accurately doing so remains a challenge. BMI or other simple anthropometric measurements are not accurate, because they do not detect sarcopenic obesity [39]. Although CT-scanning may provide accurate measurements of muscle area and density, routine CT-scanning is not feasible in critically ill patients due to costs, time, risks associated with transport, and exposure to radiation. However, some of these limitations may be offset and automatic CT-scans analysis for determining SMA and SMD may become clinically available when novel artificial intelligence-based methods are integrated into routine image analysis [40-41]. Additionally, alternative bedside methods to measure body composition in the ICU are available, although each has their own limitations [42]. Musculoskeletal ultrasound provides both muscle mass and -quality, although standardized protocols and cut-off points are lacking. For bio-electrical impedance analysis these are available, however, concerns exist about the applicability of algorithms to calculate muscle mass in critically ill patients.

Strengths and limitations

The high accuracy of CT-scan analysis to measure SMA and SMD adds to the validity of our findings. Furthermore, the use of an algorithm to select the optimal nutrition from several nutritional formulae with a range of energy-to-protein ratios, rather than using one nutritional formula with a fixed energy-to-protein ratio, provided enough statistical variation to analyze protein intake and energy intake separately.

We also acknowledge several limitations to this study. It is a retrospective study and therefore no inferences about causality can be made: our results are hypothesis-generating only. Possibly, the association between high protein intake and lower mortality is confounded by less severely ill patients reaching higher protein intakes. However, we corrected for severity of illness and the results were robust in a sensitivity analysis including only patients who were adequately fed. Additionally, baseline differences between the protein intake groups exist. For example, patients with an early high protein intake had a significantly lower body weight. To account for these baseline differences we performed sensitivity analyses including all significantly different baseline variables, and recalculated protein intake into g/kg ideal body weight. Results were robust in these analyses. Additionally, while higher protein intake was associated with lower mortality, higher energy intake was associated with higher mortality, supporting a specific role of protein and not volume of nutrition. Nevertheless, residual confounding is possible. Furthermore, we included only patients in whom an early abdominal CT-scan was available. This selection bias limits the generalizability of our findings. Finally, we used

8

(18)

Chapter 8

ICU- and sex-specific cut-off points for SMA which have not yet been validated elsewhere and are not normalized to height [18]. However, in sensitivity analysis using commonly used cut-off points for oncology patients by Martin et al. which are normalized to height [28], we found similar results.

Conclusion

In this retrospective database study in mechanically ventilated critically ill patients, an early high protein intake, particularly of more than 1.2 g/kg/d, was associated with lower mortality in patients admitted with low skeletal muscle area and -density, but not in those with normal muscle area. Further studies are needed to evaluate these findings in a prospective randomized design.

(19)

8

(20)

Supplemental material

Appendix 1. Reasons for excluding CT-scans from analysis. CT-scans were excluded if:

• The scan contained artefacts (e.g. open abdomen, scattering caused by metal, large

amounts of edema) which made analysis impossible

• The scans were cut-off on both lateral sides of the patient due to windowing. If only

one side was cut-off, the contralateral side was analyzed and multiplied by 2.

• Scan quality was deemed too low for analysis

Appendix 2. Additional information about statistical analysis.

For Cox regression analysis, the proportional hazards assumption was tested using log-minus-log plots and by adding the time-dependent covariate to the model. If the assumption was not met, the time-dependent covariate was added to the final model as denoted in the table footnotes. The hazard ratios associated with different levels of protein- and energy intake were visualized by fitting different levels of protein- and energy intake to the Cox regression model with confounders (APACHE II score and energy intake for protein intake and APACHE II score and protein intake for energy intake) set at the mean values. To keep the figures consistent, the time-dependent covariate was not added to the models used to create the figures.

For linear multiple regression analysis, the normality of residuals of the regression model was checked with a normal P-P plot and homoscedasticity using the scatterplot of predicted values and residuals. The dependent variables length of ventilation, and ICU- and hospital length of stay were non-normally distributed and positively skewed, therefore the analysis was performed on the natural logarithm of the variables.

For all analyses, multicollinearity was checked with a maximum variance inflation factor of 10.

To test the robustness of our findings, several post-hoc sensitivity analyses were performed. We included only patients who could be adequately fed (received 80–120% of energy target, Supplemental Table 3A); only patients with a pre-ICU hospital stay of <1 week (Supplemental Table 3B); excluded all trauma patients (Supplemental Table 3C); with additional adjustments for sex, age, BMI, and pre-ICU hospital length of stay (Supplemental Table 3D); with patients divided into low- or normal muscle mass

based on skeletal muscle index cut-off points (SMA in cm2_{normalized to height in m}2_,

Supplemental Table 3E); and with protein intake expressed in g/kg ideal body weight (calculated using the Hamwi equation, Supplemental Table 3F).

(21)

8

Supplemental Figure 1. Flow diagram showing the inclusion process

Patients admitted to the ICU

(Jan 2004 – Jan 2016)

n=13,877

Eligible patients

n=982

Eligible patients with good quality CT-scan

n=772

CT-scans not meeting quality checks

n=210 Artefacts: 104 Cut-off both sides: 45

Low quality: 57 Other: 4 Missing data n=33 BMI: 9 Nutritional data: 24 Patients included n=739 Normal SMA n=294 Low SMA n=445

Combined low SMA & low SMD n=200

Patients ventilated and admitted ≥4 days

n=3,851

(22)

(23)

8

Supplemental T able 1: Pr otein- and energy intake per da y of patients admitted with normal skeletal mu scle ar ea, lo w skeletal mu scle ar ea, and combined lo w skeletal mu scle ar ea and -den sit y V alues pr esented as mean (SD) a Skeletal musc le ar ea cut-offs: 1 70 cm

2 for males and 110 cm 2 for females,

skeletal musc

le densit

y

cut-offs: 29.3 HU for males and 22.

0 HU for females b Mean pr otein intake on da y 2 –4 Da y 1– 4 intensiv e car e unit admission da y 1 –4, REE r esting energy e xpenditur e No rm al sk el et al m us cle a re a a Lo w sk el et al m us cle a re a a Co m bi ne d lo w sk el et al m us cle a re a an d -d en sit y su bg ro up a Pr ot ei n <1 .2 g/ kg /d ay b n= 26 0 Pr ot ei n ≥1 .2 g/ kg /d ay b n= 34 Pr ot ei n <1 .2 g/ kg /d ay b n= 37 2 Pr ot ei n ≥1 .2 g/ kg /d ay b n= 73 Pr ot ei n <1 .2 g/ kg /d ay b n= 17 1 Pr ot ei n ≥1 .2 g/ kg /d ay b n= 29 Pr ot ei n, g/ kg En er gy , kc al /k g En er gy , % R EE Pr ot ei n, g/ kg En er gy , kc al /k g En er gy , % R EE Pr ot ei n, g/ kg En er gy , kc al /k g En er gy , % R EE Pr ot ei n, g/ kg En er gy , kc al /k g En er gy , % R EE Pr ot ei n, g/ kg En er gy , kc al /k g En er gy , % R EE Pr ot ei n, g/ kg En er gy , kc al /k g En er gy , % R EE Da y 1 0. 04 (0 .1 2) 3. 6 (3 .8 ) 17 (1 7) 0. 24 (0 .2 2) 8. 2 (5 .2 ) 40 (2 6) 0. 05 (0 .1 3) 4. 0 (4 .1 ) 19 (1 9) 0. 34 (0 .3 6) 10 .3 (9 .3 ) 48 (4 1) 0. 06 (0 .1 4) 4. 0 (3 .7 ) 20 (1 8) 0. 32 (0 .3 6) 9. 1 (1 0. 1) 43 (4 3) Da y 2 0. 27 (0 .2 9) 10 .6 (6 .7 ) 51 (3 1) 1. 22 (0 .2 9) 26 .4 (6 .2 ) 12 6 (2 7) 0. 31 (0 .3 3) 11 .5 (6 .8 ) 56 (3 2) 1. 26 (0 .3 0) 28 .9 (8 .5 ) 13 7 (3 5) 0. 34 (0 .3 5) 11 .4 (6 .6 ) 57 (3 3) 1. 21 (0 .2 9) 26 .2 (8 .6 ) 13 1 (3 8) Da y 3 0. 67 (0 .4 4) 17 .1 (9 .1 ) 82 (4 2) 1. 47 (0 .2 4) 30 .4 (5 .2 ) 14 5 (2 0) 0. 67 (0 .4 3) 17 .4 (8 .6 ) 84 (4 0) 1. 41 (0 .2 0) 31 .0 (7 .1 ) 14 6 (2 6) 0. 70 (0 .4 3) 17 .1 (8 .2 ) 85 (4 0) 1. 37 (0 .1 8) 28 .7 (6 .0 ) 14 3 (2 2) Da y 4 0. 90 (0 .4 4) 20 .5 (8 .8 ) 99 (4 1) 1. 46 (0 .2 2) 29 .9 (4 .7 ) 14 2 (1 7) 0. 87 (0 .4 7) 20 .7 (9 .8 ) 10 0 (4 5) 1. 50 (0 .3 1) 31 .1 (7 .0 ) 14 7 (2 6) 0. 83 (0 .4 6) 19 .5 (9 .1 ) 97 (4 5) 1. 45 (0 .2 2) 29 .3 (5 .6 ) 14 6 (2 1)

(24)

Chapter 8

a _{Average day 2–4 protein intake per 0.1 g/kg/day increase} b_{Average day 2–4 protein intake ≥1.2 g/kg/day vs. <1.2 g/kg/day} c_{Adjusted for APACHE II score and energy intake}

d_{SMA cut-offs: 170 cm}2_{for males and 110 cm}2_{for females, SMD cut-offs: 29.3 HU for males and}

22.0 HU for females

e_{Non-normally distributed and positively skewed variables, therefore the analysis was performed}

on the natural logarithm of the variables

Discharge to home and length of hospital stay in hospital survivors, length of ICU stay and length of ventilation in ICU survivors. Values in bold indicate a significant result, p<.05

APACHE acute physiological, age, and chronic health evaluation, B beta, ICU intensive care unit, OR odds ratio, SMA skeletal muscle area, SMD skeletal muscle density

(25)

8

Supplemental Table 2. Logistic- and multiple regression analyses on the association between mean day 2–4 protein intake and the odds of discharge to home, length of ventilation, and length of stay

Protein intake – continuousa _{Protein intake – dichotomized}b

Unadjusted model Adjusted modelc _{Unadjusted model} _{Adjusted model}c

OR 95%CI OR 95%CI OR 95%CI OR 95%CI

Discharge to home Normal SMAd_(n=258) Protein intake 0.98 0.92–1.04 1.10 0.92–1.31 1.24 0.57–2.68 2.00 0.79–5.09 APACHE II score 0.99 0.95–1.02 0.98 0.95–1.02 Energy intake 0.25 0.04–1.76 0.48 0.20–1.10 Low SMAd_(n=302) Protein intake 1.02 0.96–1.08 1.01 0.86–1.18 1.67 0.93–3.02 1.91 0.88–4.13 APACHE II score 0.98 0.95–1.01 0.98 0.95–1.01 Energy intake 1.08 0.19–6.16 0.75 0.34–1.67

Low SMA & low SMDd_(n=118)

Protein intake 1.04 0.95–1.13 1.30 0.97–1.73 1.43 0.58–3.50 1.39 0.40–4.78

APACHE II score 0.96 0.91–1.01 0.95 0.91–1.00

Energy intake 0.07 0.00–1.56 0.80 0.22–2.89

Length of ICU staye _B _95%CI _B _95%CI _B _95%CI _B _95%CI

Normal SMAd_(n=270) Protein intake 0.00 −0.02–0.03 −0.08 −0.14 to −0.03 0.00 −0.26–0.26 −0.19 −0.49–0.12 APACHE II score 0.02 0.01–0.03 0.02 0.01–0.03 Energy intake 0.99 0.38–1.60 0.26 −0.01–0.54 Low SMAd_(n=349) Protein intake −0.01 −0.02–0.01 −0.05 −0.10–0.00 −0.07 −0.26–0.12 −0.12 −0.37–0.12 APACHE II score 0.01 0.00–0.02 0.01 0.00–0.02 Energy intake 0.55 0.02–1.08 0.10 −0.14–0.34

Protein intake 0.01 −0.02–0.04 −0.03 −0.11–0.06 0.06 −0.25–0.37 −0.06 −0.47–0.36

APACHE II score 0.00 −0.01–0.02 0.00 −0.01–0.02

Energy intake 0.42 −0.52–1.36 0.20 −0.22–0.62

Length of hospital staye _OR _95%CI _OR _95%CI _OR _95%CI _OR _95%CI

Normal SMAd_(n=258) Protein intake 0.02 0.00–0.05 −0.02 −0.08–0.04 0.14 −0.14–0.42 −0.08 −0.40–0.25 APACHE II score 0.01 0.00–0.03 0.02 0.00–0.03 Energy intake 0.52 −0.15–1.18 0.32 0.03–0.61 Low SMAd_(n=303) Protein intake 0.03 0.01–0.05 0.00 −0.05–0.06 0.23 0.03–0.44 0.00 −0.26–0.25 APACHE II score 0.00 −0.01–0.01 0.00 −0.01–0.01 Energy intake 0.35 −0.23–0.92 0.38 0.12–0.64

Protein intake 0.06 0.03–0.09 0.06 −0.03–0.16 0.38 0.05–0.70 −0.03 −0.46–0.39

APACHE II score −0.01 −0.03–0.01 −0.01 −0.03–0.01

Energy intake −0.05 −1.04–0.94 0.59 0.15–1.03

Length of ventilatione _OR _95%CI _OR _95%CI _OR _95%CI _OR _95%CI

Normal SMAd_(n=270) Protein intake 0.01 −0.02–0.04 −0.15 −0.22 to −0.08 −0.05 −0.39–0.28 −0.44 −0.83 to −0.05 APACHE II score 0.03 0.02–0.04 0.03 0.02–0.04 Energy intake 1.87 1.10–2.64 0.56 0.22–0.91 Low SMAd_(n=349) Protein intake 0.00 −0.02–0.03 −0.12 −0.18 to −0.06 −0.16 −0.41–0.08 −0.45 −0.76 to −0.15 APACHE II score 0.02 0.00–0.03 0.02 0.00–0.03 Energy intake 1.43 0.76–2.11 0.52 0.21–0.82

Protein intake 0.01 −0.03–0.05 −0.10 −0.21–0.02 −0.13 −0.53–0.28 −0.44 −0.96–0.09

APACHE II score 0.01 0.00–0.03 0.01 −0.01–0.03

(26)

Chapter 8

Supplemental Table 3. Cox regression sensitivity analyses

A. Including only patients who could be adequately fed, receiving 80 - 120% of energy target (estimated energy expenditure by H&B +30%)

Protein intake - continuousa _{Protein intake - dichotomized}b

60-day mortality Normal SMAd_(n=161) Protein intake 0.69e_0.51–0.92 _0.70e_0.50–0.99 _{0.43 0.13–1.43} _{0.36 0.08–1.67} APACHE II score 1.05 1.00–1.11 1.07 1.01–1.13 Energy intake 0.86 0.03–23.37 0.95 0.08–11.61 Low SMAd_(n=273) Protein intake 0.97 0.90–1.05 0.89 0.78–1.02 0.66 0.39–1.12 0.47 0.23–0.96 APACHE II score 1.06 1.04–1.09 1.06 1.04–1.09 Energy intake 3.43 0.71–16.49 2.61 0.81–8.43

Protein intake 0.85 0.75–0.95 0.75 0.61–0.91 0.17 0.05–0.56 0.12 0.03–0.45

APACHE II score 1.05 1.01–1.09 1.05 1.01–1.09

Energy intake 8.45 0.85–83.84 4.44 0.74–26.47

6-month mortality HR 95%CI HR 95%CI HR 95%CI HR 95%CI

Normal SMAd_(n=161) Protein intake 0.92 0.81–1.04 0.92 0.74–1.14 0.57 0.22–1.48 0.55 0.15–1.96 APACHE II score 1.06 1.01–1.11 1.06 1.01–1.12 Energy intake 0.81 0.05–14.34 0.66 0.07–6.13 Low SMAd_(n=273) Protein intake 0.99 0.93–1.06 0.94 0.84–1.06 0.77 0.50–1.20 0.61 0.34–1.10 APACHE II score 1.06 1.03–1.08 1.06 1.03–1.08 Energy intake 2.09 0.52–8.36 2.06 0.74–5.71

Protein intake 0.89 0.81–0.98 0.86 0.72–1.02 0.35 0.16–0.73 0.30 0.11–0.76

APACHE II score 1.04 1.01–1.08 1.04 1.01–1.07

(27)

8

Supplemental Table 3. Cox regression sensitivity analyses (continued)

B. Including only patients with a pre-ICU hospital admission of <1 week

60-day mortality Normal SMAd_(n=274) Protein intake 1.03 0.95–1.12 1.04 0.84–1.30 0.56 0.14–2.34 0.40 0.08–1.95 APACHE II score 1.09 1.05–1.14 1.09 1.05–1.14 Energy intake 0.89 0.08–9.97 1.99 0.66–6.07 Low SMAd_(n=377) Protein intake 1.00 0.96–1.05 0.91 0.80–1.03 0.54e_{0.19–1.52 0.47}e_0.16–1.40 APACHE II score 1.05 1.03–1.08 1.06 1.03–1.08 Energy intake 3.32 0.90–12.20 1.44 0.78–2.66

Protein intake 0.97 0.91–1.04 0.76 0.63–0.92 0.36 0.11–1.16 0.27 0.08–0.98 APACHE II score 1.04 1.01–1.08 1.04 1.00–1.07 Energy intake 13.82 1.98–96.58 1.73 0.73–4.09 6-month mortality Normal SMAd_(n=274) Protein intake 1.01 0.94–1.09 1.00 0.82–1.22 0.46 0.11–1.92 0.34 0.07–1.61 APACHE II score 1.08 1.04–1.12 1.08 1.04–1.12 Energy intake 1.24 0.14–11.12 1.80 0.66–4.91 Low SMAd_(n=377) Protein intake 1.01 0.97–1.05 0.93 0.84–1.04 0.83e_{0.41–1.69 0.67}e_0.31–1.46 APACHE II score 1.05 1.03–1.07 1.05 1.03–1.07 Energy intake 2.64 0.83–8.37 1.57 0.92–2.68

Protein intake 0.99 0.93–1.05 0.85 0.73–1.01 0.44 0.18–1.09 0.33 0.12–0.92 APACHE II score 1.03 1.00–1.06 1.03 1.00–1.06 Energy intake 4.82 0.91–25.42 1.72 0.82–3.60

(28)

Chapter 8

C. Excluding all trauma patients

60-day mortality Normal SMAd_(n=155) Protein intake 0.84e_0.70–1.01 _0.95e_0.69–1.29 _{0.52 0.12–2.20} _{0.31 0.06–1.67} APACHE II score 1.06 1.01–1.11 1.07 1.01–1.12 Energy intake 0.27 0.01–5.06 1.71 0.45–6.50 Low SMAd_(n=370) Protein intake 0.98 0.94–1.02 0.89 0.80–1.01 0.61 0.35–1.04 0.53 0.27–1.03 APACHE II score 1.05 1.03–1.07 1.05 1.03–1.07 Energy intake 3.19 0.92–11.01 1.51 0.84–2.71

Protein intake 0.95 0.90–1.01 0.76 0.64–0.90 0.13 0.03–0.54 0.10 0.02–0.46 APACHE II score 1.06 1.03–1.09 1.05 1.02–1.08 Energy intake 12.52 2.16–72.54 1.96 0.89–4.32 6-month mortality Normal SMAd_(n=155) Protein intake 1.02 0.94–1.10 1.08 0.87–1.36 0.86 0.30–2.45 0.53 0.14–1.97 APACHE II score 1.06 1.02–1.11 1.07 1.02–1.11 Energy intake 0.45 0.04–5.86 1.57 0.47–5.23 Low SMAd_(n=370) Protein intake 0.95e_0.90–1.00 _0.90e_0.81–1.01 _{0.78 0.50–1.20} _{0.70 0.40–1.21} APACHE II score 1.05 1.03–1.06 1.04 1.03–1.06 Energy intake 2.01 0.66–6.06 1.42 0.84–2.38

Protein intake 0.92e_0.85–0.99 _0.80e_0.69–0.94 _{0.36 0.17–0.77} _{0.29 0.12–0.70}

APACHE II score 1.04 1.02–1.07 1.04 1.01–1.06

(29)

8

D. Adjusted for APACHE II score, energy intake, sex, age, BMI, and pre-ICU hospital length of stay

60-day mortality Normal SMAd_(n=294) Protein intake 0.91e_0.79–1.05 _0.94e_0.72–1.23 _{0.57 0.18–1.86} _{0.37 0.09–1.60} APACHE II score 1.08 1.04–1.13 1.08 1.04–1.13 Energy intake 0.90 0.07–11.65 2.47 0.80–7.63 Age 1.03 1.01–1.05 1.03 1.01–1.05 Sex (male) 1.53 0.76–3.05 1.52 0.77–3.01 BMI 0.96 0.88–1.04 0.96 0.88–1.04 Pre-ICU hospital length of stay 0.94 0.85–1.03 0.97 0.89–1.05

Low SMAd_(n=444) Protein intake 0.92e_0.86–0.99 _0.88e_0.77–1.01 _{0.66 0.40–1.09} _{0.58 0.31–1.08} APACHE II score 1.06 1.04–1.08 1.06 1.04–1.08 Energy intake 1.61 0.46–5.67 1.30 0.73–2.32 Age 1.02 1.01–1.04 1.02 1.01–1.04 Sex (male) 0.65 0.45–0.93 0.64 0.45–0.91 BMI 0.96 0.92–1.00 0.96 0.92–1.00

Pre-ICU hospital length of stay 1.00 0.99–1.02 1.00 0.99–1.02

Protein intake 0.96 0.90–1.01 0.83 0.69–1.00 0.20 0.06–0.63 0.18 0.05–0.62 APACHE II score 1.06 1.03–1.10 1.06 1.03–1.09 Energy intake 4.97 0.72–34.48 1.65 0.73–3.73 Age 1.04 1.02–1.07 1.05 1.02–1.06 Sex (male) 0.83 0.50–1.39 0.76 0.46–1.24 BMI 0.97 0.91–1.04 0.96 0.90–1.03 Pre-ICU hospital length of stay 1.01 0.99–1.03 1.01 0.99–1.03

6-month mortality Normal SMAd_(n=294) Protein intake 1.02 0.96–1.09 0.99 0.82–1.20 0.75 0.30–1.90 0.36 0.11–1.14 APACHE II score 1.07 1.03–1.11 1.07 1.04–1.11 Energy intake 1.54 0.17–13.77 2.34 0.86–6.36 Age 1.03 1.01–1.05 1.03 1.01–1.05 Sex (male) 1.37 0.75–2.51 1.31 0.72–2.39 BMI 0.97 0.90–1.04 0.96 0.90–1.03 Pre-ICU hospital length of stay 1.00 0.97–1.02 1.00 0.98–1.02

Low SMAd_(n=444) Protein intake 0.96e_0.91–1.01 _0.94e_0.84–1.05 _{0.79 0.52–1.20} _{0.66 0.40–1.11} APACHE II score 1.05 1.03–1.07 1.05 1.03–1.07 Energy intake 1.22 0.70–3.75 1.34 0.81–2.23 Age 1.02 1.01–1.04 1.03 1.01–1.04 Sex (male) 0.74 0.54–1.02 0.74 0.54–1.01 BMI 0.96 0.92–0.99 0.95 0.92–0.99

Pre-ICU hospital length of stay 1.01 0.99–1.02 1.01 1.00–1.02

Protein intake 0.92e_0.86–0.99 _0.88e_0.74–1.04 _{0.40 0.20–0.83} _{0.36 0.15–0.84} APACHE II score 1.05 1.02–1.08 1.05 1.02–1.08 Energy intake 1.65 0.31–8.88 1.42 0.70–2.88 Age 1.04 1.01–1.06 1.04 1.02–1.06 Sex (male) 0.97 0.62–1.54 0.94 0.60–1.48 BMI 0.94 0.89–1.00 0.94 0.89–1.00