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.
DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.
SETTING: General Intensive Care Unit, University of Malaya Medical Centre.
PATIENTS: Mechanically ventilated critically ill patients.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.
CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.
DESIGN: Systematic review and meta-analysis.
SETTING: Electronic search for randomized controlled trials and observational studies (MEDLINE, EMBASE, CENTRAL).
PARTICIPANTS: Hospitalized adults ≥ 18 years old who were SARS-CoV-2 PCR positive.
INTERVENTIONS: High-dose and low-dose corticosteroids.
MEASUREMENTS AND MAIN RESULTS: A total of twelve studies (n=2759 patients) were included in this review. The pooled analysis demonstrated no significant difference in mortality rate between the high-dose and low-dose corticosteroids groups (n=2632; OR: 1.07 [95%CI 0.67, 1.72], p=0.77, I2=76%, trial sequential analysis=inconclusive). No significant differences were observed in the incidence of intensive care unit (ICU) admission rate (n=1544; OR: 0.77[95%CI 0.43, 1.37], p=0.37, I2= 72%), duration of hospital stay (n=1615; MD: 0.53[95%CI -1.36, 2.41], p=0.58, I2=87%), respiratory support (n=1694; OR: 1.51[95%CI 0.77, 2.96], p=0.23, I2=84%), duration of mechanical ventilation (n=419; MD: -1.44[95%CI -4.27, 1.40], p=0.32, I2=93%), incidence of hyperglycemia (n=516, OR: 0.91[95%CI 0.58, 1.43], p=0.68, I2=0%) and infection rate (n=1485, OR: 0.86[95%CI 0.64, 1.16], p=0.33, I2=29%).
CONCLUSION: The meta-analysis demonstrated high-dose corticosteroids did not reduce mortality rate. However, high-dose corticosteroids did not pose higher risk of hyperglycemia and infection rate for COVID-19 patients. Due to the inconclusive trial sequential analysis, substantial heterogeneity and low level of evidence, future large-scale randomized clinical trials are warranted to improve the certainty of evidence for the use of high-dose compared to low-dose corticosteroids in COVID-19 patients.
METHODS: We systematically searched PubMed, Cochrane Central Register of Controlled Trials, Google Scholar, and medRxiv (preprint repository) databases (up to 7 January 2021). Pooled effect sizes with 95% confidence interval (CI) were generated using random-effects and inverse variance heterogeneity models. The risk of bias of the included RCTs was appraised using version 2 of the Cochrane risk-of-bias tool for randomized trials.
RESULTS: Six RCTs were included: two trials with an overall low risk of bias and four trials had some concerns regarding the overall risk of bias. Our meta-analysis did not find significant mortality benefits with the use of tocilizumab among patients with COVID-19 relative to non-use of tocilizumab (pooled hazard ratio = 0.83; 95% CI 0.66-1.05, n = 2,057). Interestingly, the estimated effect of tocilizumab on the composite endpoint of requirement for mechanical ventilation and/or all-cause mortality indicated clinical benefits, with some evidence against our model hypothesis of no significant effect at the current sample size (pooled hazard ratio = 0.62; 95% CI 0.42-0.91, n = 749).
CONCLUSION: Despite no clear mortality benefits in hospitalized patients with COVID-19, tocilizumab appears to reduce the likelihood of progression to mechanical ventilation.
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.
MATERIALS AND METHODS: In this multicenter cross-sectional study, data on mechanical ventilation and clinical outcomes were collected. Predictors of mortality were analyzed by univariate and multivariable logistic regression. A scoring system was generated to predict 28-day mortality.
RESULTS: A total of 1408 patients were enrolled. In 138 patients with acute respiratory distress syndrome (ARDS), 65.9% were on a tidal volume ≤ 8 ml/kg predicted body weight (PBW), and 71.3% were on sufficient PEEP. In 1270 patients without ARDS, 88.8% were on a tidal volume ≤ 10 ml/kg PBW. A plateau pressure
METHODS: A cross-sectional study was conducted in a steel factory in Terengganu, Malaysia to assess the metal dust exposure and its relationship to lung function values among 184 workers. Metal dust concentrations values (Co, Cr, and Ni) for each worker were collected using air personal sampling. Lung function values (FEV1, FVC, and %FEV1/FVC) were determined using spirometer.
RESULTS: Exposure to cobalt and chromium were 1-3 times higher than permissible exposure limit (PEL) while nickel was not exceeding the PEL. Cumulative of chromium was the predictor to all lung function values (FEV1, FVC, and %FEV1/FVC). Frequency of using mask was positively associated with FVC (Adj b = 0.263, P = 0.011) while past respiratory illnesses were negatively associated with %FEV1/FVC (Adj b = -1.452, P = 0.026). Only few workers (36.4%) were found to wear their masks all times during the working hours.
CONCLUSIONS: There was an exposure-response relationship of cumulative metal dust exposure with the deterioration of lung function values. Improvement of control measures as well as proper and efficient use or personal protection equipment while at work could help to protect the respiratory health of workers.