METHODS: We searched MEDLINE, EMBASE, CENTRAL and CINAHL from database inception through April 1, 2021.We included RCTs of (1) adult (age ≥ 18) critically ill patients that (2) compared higher vs lower protein with (3) similar energy intake between groups, and (4) reported clinical and/or patient-centered outcomes. We excluded studies on immunonutrition. Two authors screened and conducted quality assessment independently and in duplicate. Random-effect meta-analyses were conducted to estimate the pooled risk ratio (dichotomized outcomes) or mean difference (continuous outcomes).
RESULTS: Nineteen RCTs were included (n = 1731). Sixteen studies used primarily the enteral route to deliver protein. Intervention was started within 72 h of ICU admission in sixteen studies. The intervention lasted between 3 and 28 days. In 11 studies that reported weight-based nutrition delivery, the pooled mean protein and energy received in higher and lower protein groups were 1.31 ± 0.48 vs 0.90 ± 0.30 g/kg and 19.9 ± 6.9 versus 20.1 ± 7.1 kcal/kg, respectively. Higher vs lower protein did not significantly affect overall mortality [risk ratio 0.91, 95% confidence interval (CI) 0.75-1.10, p = 0.34] or other clinical or patient-centered outcomes. In 5 small studies, higher protein significantly attenuated muscle loss (MD -3.44% per week, 95% CI -4.99 to -1.90; p
METHODS: We conducted an extensive search via Cochrane Library, PubMed, Scopus, and Web of Science databases to acquire the reported RCTs up to October 2020.
RESULTS: The results showed no effects of α-tocopherol supplementation on lipid profile in DM patients except when used ≥12 weeks.
CONCLUSIONS: α-tocopherol supplementation in DM patients had no significant effect on lipid profiles.
METHODS: This is a retrospective analysis of a single-center prospective observational study that enrolled mechanically ventilated adults with expected ≥96 hours ICU stay. SARC-F and CFS questionnaires were administered to patient's next-of-kin and mNUTRIC were calculated. Calf-circumference was measured at the right calf. Nutrition data was collected from nursing record. The high-risk scores (mNUTRIC ≥5, SARC-CALF >10 or CFS ≥4) of these variables were combined to become the NUTRIC-SF score (range: 0-3).
RESULTS: Eighty-eight patients were analyzed. Multiple logistic model demonstrated increasing mNUTRIC score was independently associated with 60-day mortality while increasing SARC-CALF and CFS showed a strong trend towards higher 60-day mortality. Discriminative ability of NUTRIC-SF for 60-day mortality is better than it's component (AUROC 0.722, 95% confidence interval [CI] 0.677-0.868). Every increment of 300 kcal/day and 30 g/day is associated with a trend towards higher rate of discharge alive for high [≥2; Adjusted Hazard Ratio 1.453 (95% CI 0.991-2.130) for energy, 1.503 (95% CI 0.936-2.413) for protein] but not low (<2) NUTRIC-SF score.
CONCLUSION: NUTRIC-SF score may be a clinically relevant risk stratification tool in the ICU. This article is protected by copyright. All rights reserved.
METHODS: This single-center prospective observational study was conducted in a general ICU. Mechanically ventilated critically ill adult patients (age ≥18 years) without pre-existing systemic neuromuscular diseases and expected to stay for ≥96 h in the ICU were included. US measurements were performed within 48 h of ICU admission (baseline), at day 7, day 14 of ICU stay and at ICU discharge (if stay >14 days). Quadriceps muscle layer thickness (QMLT), rectus femoris cross sectional area (RFCSA), vastus intermedius pennation angle (PA) and fascicle length (FL), and rectus femoris echogenicity (mean and standard deviation [SD]) were measured. Patients' next-of-kin were interviewed by using established questionnaires for their pre-hospitalization nutritional risk (nutrition risk screening-2002) and functional status (SARC-F, clinical frailty scale [CFS], Katz activities of daily living [ADL] and Lawton Instrumental ADL).
RESULTS: Ninety patients were recruited. A total of 86, 53, 24 and 10 US measures were analyzed, which were performed at a median of 1, 7, 14 and 22 days from ICU admission, respectively. QMLT, RFCSA and PA reduced significantly over time. The overall trend of change of FL was not significant. The only independent predictor of 60-day mortality was the change of QMLT from baseline to day 7 (adjusted odds ratio 0.95 for every 1% less QMLT loss, 95% confidence interval 0.91-0.99; p = 0.02). Baseline measures of high nutrition risk (modified nutrition risk in critically ill ≥5), sarcopenia (SARC-F ≥4) and frailty (CFS ≥5) were associated with lower baseline QMLT, RFCSA and PA and higher 60-day mortality.
CONCLUSIONS: Every 1% loss of QMLT over the first week of critical illness was associated with 5% higher odds of 60-day mortality. SARC-F, CFS and mNUTRIC are associated with quadriceps muscle status and 60-day mortality and may serve as a potential simple and indirect measures of premorbid muscle status at ICU admission.
METHODS: This is a prospective observational study conducted among critically ill patients aged ≥18 years, intubated and mechanically ventilated within 48 h of ICU admission and stayed in the ICU for at least 72 h. Information on baseline characteristics and nutritional risk status (the modified Nutrition Risk in Critically ill [NUTRIC] score) was collected on day 1. Nutritional intake was recorded daily until death, discharge, or until the twelfth evaluable days. Mortality status was assessed on day 60 based on the patient's hospital record. Patients were divided into 3 groups a) received <2/3 of prescribed energy and protein (both <2/3), b) received ≥2/3 of prescribed energy and protein (both ≥2/3) and c) either energy or protein received were ≥2/3 of prescribed (either ≥2/3). The relationship between the three groups with 60-day mortality was examined by using logistic regression with adjustment for potential confounders. Sensitivity analysis was performed to examine the influence of ICU length of stay (≥7 days) and nutritional risk status.
RESULTS: Data were collected from 154 mechanically ventilated patients (age, 51.3 ± 15.7 years; body mass index, 26.5 ± 6.7 kg/m2; 54% male). The mean modified NUTRIC score was 5.7 ± 1.9, with 56% of the patients at high nutritional risk. The patients received 64.5 ± 21.6% of the amount of energy and 56.4 ± 20.6% of the amount of protein prescribed. Provision of energy and protein at ≥2/3 compared with <2/3 of the prescribed amounts was associated with a trend towards increased 60-day mortality (Adjusted odds ratio [Adj OR] 2.23; 95% confidence interval [CI], 0.92-5.38; p = 0.074). No difference in mortality status was found between energy and protein provision at either ≥2/3 compared with <2/3 of the prescribed amounts (Adj OR 1.61, 95% CI, 0.58-4.45; p = 0.357). Nutritional risk status, not ICU length of stay, influenced the relationship between nutritional adequacy and 60-day mortality.
CONCLUSIONS: Energy and protein adequacy of ≥2/3 of the prescribed amounts were associated with a trend towards increased 60-day mortality among mechanically ventilated critically ill patients. However, neither energy nor protein adequacy alone at ≥ or <2/3 adequacy affect 60-day mortality. Increased mortality was associated with provision of energy and protein at ≥2/3 of the prescribed amounts, which only affected patients with low nutritional risk.
Methods: We conducted a cluster randomized controlled intervention trial (16-week intervention and 8-week follow-up). Malaysian government employees in Putrajaya, Malaysia, with metabolic syndrome were randomly assigned by cluster to a point-of-decision prompt group (n = 44), an aerobics group (n = 42) or a control group (n = 103) based on sample size calculation formula. Step counts were evaluated by Lifecorder e-STEP accelerometers for all participants. Metabolic syndrome was defined according to the 'harmonizing' definition, in which individuals who have at least three of the five metabolic risk factors (waist circumference, high-density lipoprotein cholesterol, triglycerides, fasting glucose levels, systolic and diastolic blood pressure) will be classified as having metabolic syndrome. A total of 80% of the enrolled government employees with metabolic syndrome completed the programme. Data were analyzed using SPSS for Windows (version 20, SPSS, Chicago, IL).
Results: There were significantly higher step counts on average in the aerobics group compared to the control group over assessments. Assessments at baseline, post-intervention and follow-up showed a significant difference in step counts between the intervention and control groups. The greatest reductions in the proportions of individuals with metabolic syndrome were observed in the aerobics group with a reduction of 79.4% in the post-intervention assessment compared to the assessment at baseline.
Conclusion: The findings of this study suggest that physical activity intervention via aerobics classes is an effective strategy for improving step counts and reducing the prevalence of metabolic syndrome.
DESIGN: A randomized, double-blind, parallel-group, controlled clinical trial.
SETTING: Diabetes clinic of a teaching hospital in Kuala Lumpur, Malaysia.
PARTICIPANTS: A total of 136 participants with type 2 diabetes, aged 30-70 years, were recruited and randomly assigned to receive either probiotics (n = 68) or placebo (n = 68) for 12 weeks.
OUTCOMES: Primary outcomes were glycemic control-related parameters, and secondary outcomes were anthropomorphic variables, lipid profile, blood pressure and high-sensitivity C-reactive protein. The Lactobacillus and Bifidobacterium quantities were measured before and after intervention as an indicator of successful passage of the supplement through gastrointestinal tract.
STATISTICAL ANALYSIS: Intention-to-treat (ITT) analysis was performed on all participants, while per-protocol (PP) analysis was performed on those participants who had successfully completed the trial with good compliance rate.
RESULTS: With respect to primary outcomes, glycated hemoglobin decreased by 0.14 % in the probiotics and increased by 0.02 % in the placebo group in PP analysis (p