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Introduction Measurement of energy expenditure (EE) is recommended to guide nutrition in critically ill patients. Availability of a gold standard indirect calorimetry is limited, and continuous measurement is unfeasible. Equations used to predict EE are inaccurate. The purpose of this study was to provide proof of concept that EE can be accurately assessed on the basis of ventilator-derived carbon dioxide production (VCO 2 ) and to determine whether this method is more accurate than frequently used predictive equations. Methods In 84 mechanically ventilated critically ill patients, we performed 24-h indirect calorimetry to obtain a gold standard EE. Simultaneously, we collected 24-h ventilator-derived VCO 2 , extracted the respiratory quotient of the administered nutrition, and calculated EE with a rewritten Weir formula. Bias, precision, and accuracy and inaccuracy rates were determined and compared with four predictive equations: the Harris–Benedict, Faisy, and Penn State University equations and the European Society for Clinical Nutrition and Metabolism (ESPEN) guideline equation of 25 kcal/kg/day. Results Mean 24-h indirect calorimetry EE was 1823 ± 408 kcal. EE from ventilator-derived VCO 2 was accurate (bias +141 ± 153 kcal/24 h; 7.7 % of gold standard) and more precise than the predictive equations (limits of agreement −166 to +447 kcal/24 h). The 10 % and 15 % accuracy rates were 61 % and 76 %, respectively, which were significantly higher than those of the Harris–Benedict, Faisy, and ESPEN guideline equations. Large errors of more than 30 % inaccuracy did not occur with EE derived from ventilator-derived VCO 2 . This 30 % inaccuracy rate was significantly lower than that of the predictive equations. Conclusions In critically ill mechanically ventilated patients, assessment of EE based on ventilator-derived VCO 2 is accurate and more precise than frequently used predictive equations. It allows for continuous monitoring and is the best alternative to indirect calorimetry.

Background The sequential organ failure assessment score (SOFA) is increasingly used as an endpoint in intensive care randomized controlled trials (RCTs). Although serially measured SOFA is independently associated with mortality in observational cohorts, the association between treatment effects on SOFA vs. effects on mortality has not yet been quantified in RCTs. The aim of this study was to quantify the relationship between SOFA and mortality in RCTs and to identify which SOFA derivative best reflects between-group mortality differences. Methods The review protocol was prospectively registered (Prospero CRD42016034014). We performed a literature search (up to May 1, 2016) for RCTs reporting both SOFA and mortality, and analyzed between-group differences in these outcomes. Treatment effects on SOFA and mortality were calculated as the between-group SOFA standardized difference and log odds ratio (OR), respectively. We used random-effects meta-regression to (1) quantify the linear relationship between RCT treatment effects on mortality (logOR) and SOFA (i.e. responsiveness) and (2) quantify residual heterogeneity (i.e. consistency, expressed as I 2 ). Results Of 110 eligible RCTs, 87 qualified for analysis. Using all RCTs, SOFA was significantly associated with mortality (slope = 0.49 (95% CI 0.17; 0.82), p  = 0.006, I 2  = 5%); the overall mortality effect explained by SOFA score ( R 2 ) was 9%. Fifty-eight RCTs used Fixed-day SOFA as an endpoint (i.e. the score on a fixed day after randomization), 25 studies used Delta SOFA as an endpoint (i.e. the trajectory from baseline score) and 15 studies used other SOFA derivatives as an endpoint. Fixed-day SOFA was not significantly associated with mortality (slope = 0.35 (95% CI −0.04; 0.75), p  = 0.08, I 2  = 12%) and explained 3% of the overall mortality effect ( R 2 ). Delta SOFA was significantly associated with mortality (slope = 0.70 (95% CI 0.26; 1.14), p  = 0.004, I 2  = 0%) and explained 32% of the overall mortality effect ( R 2 ). Conclusions Treatment effects on Delta SOFA appear to be reliably and consistently associated with mortality in RCTs. Fixed-day SOFA was the most frequently reported outcome among the reviewed RCTs, but was not significantly associated with mortality. Based on this study, we recommend using Delta SOFA rather than Fixed-day SOFA as an endpoint in future RCTs.

Vitamin C deficiency is common in critically ill patients. Vitamin C, the most important antioxidant, is likely consumed during oxidative stress and deficiency is associated with organ dysfunction and mortality. Assessment of vitamin C status may be important to identify patients who might benefit from vitamin C administration. Up to now, vitamin C concentrations are not available in daily clinical practice. Recently, a point-of-care device has been developed that measures the static oxidation-reduction potential (sORP), reflecting oxidative stress, and antioxidant capacity (AOC). The aim of this study was to determine whether plasma vitamin C concentrations were associated with plasma sORP and AOC. Plasma vitamin C concentration, sORP and AOC were measured in three groups: healthy volunteers, critically ill patients, and critically ill patients receiving 2- or 10-g vitamin C infusion. Its association was analyzed using regression models and by assessment of concordance. We measured 211 samples obtained from 103 subjects. Vitamin C concentrations were negatively associated with sORP (R2 = 0.816) and positively associated with AOC (R2 = 0.842). A high concordance of 94–100% was found between vitamin C concentration and sORP/AOC. Thus, plasma vitamin C concentrations are strongly associated with plasma sORP and AOC, as measured with a novel point-of-care device. Therefore, measuring sORP and AOC at the bedside has the potential to identify and monitor patients with oxidative stress and vitamin C deficiency.

The respiratory system reacts instantaneously to intrinsic and extrinsic inputs. This adaptability results in significant fluctuations in breathing parameters, such as respiratory rate, tidal volume, and inspiratory flow profiles. Breathing variability is influenced by several conditions, including sleep, various pulmonary diseases, hypoxia, and anxiety disorders. Recent studies have suggested that weaning failure during mechanical ventilation may be predicted by low respiratory variability. This review describes methods for quantifying breathing variability, summarises the conditions and comorbidities that affect breathing variability, and discusses the potential implications of breathing variability for anaesthesia and intensive care.

Background Two distinct longitudinal respiratory subphenotypes have recently been described in COVID-19-related acute respiratory distress syndrome (ARDS). These subphenotypes exhibit dynamic immunobiological changes that may help guide immunomodulatory interventions. However, the extent to which the immune response is determined by respiratory subphenotype in the presence of concurrent immunomodulatory treatment remains unclear. We investigated the independent and combined effects of respiratory subphenotype and tocilizumab on inflammatory response and clinical outcomes. Methods We analyzed patients from existing COVID-19 biobanks who were consecutively admitted to the ICU and received more than 4 days of invasive mechanical ventilation between March 2020 and May 2022. Patients were classified into two previously described longitudinal respiratory subphenotypes—characterized by mechanical power, minute volume and ventilatory ratio—referred to as ‘ low-power ’ and ‘ high-power ’ subphenotypes. We analyzed how tocilizumab treatment and respiratory subphenotype were associated with endothelial and inflammatory plasma biomarkers on days 0, 4 and 7, as well as with mortality. Results 720 patients were included, of whom 464 (64%) and 256 (36%) were assigned to the low- and high-power subphenotypes, respectively. 108 (23%) of the low-power subphenotype patients received tocilizumab, and 43 (17%) of the high-power subphenotype. 427 patients had plasma samples available. The high-power subphenotype was associated with slightly higher SP-D, thrombomodulin and TNF-RI plasma concentrations on the day of intubation compared to the low-power subphenotype, along with a more rapid increase in IL-6 and TNF-RI levels in subjects who had received tocilizumab treatment ( β  = 0.14 log ng/ml, p  = 0.022, and β  = 0.06 log ng/ml, p  = 0.014, respectively). Tocilizumab treatment accounted for four times more variance in IL-6 and angiopoietin-2 levels than subphenotype, while subphenotype explained only a small proportion of the variance and slightly more than tocilizumab for TNF-RI and thrombomodulin. Subphenotype did not modify the association between tocilizumab and mortality (IPTW adjusted hazard ratio 1.18; 95%CI 0.60–2.33). Conclusion Respiratory subphenotypes showed varying TNF-RI and IL-6 responses to tocilizumab, but these differences were only minor compared to the drug’s overall immunobiological effect. This suggests that respiratory subphenotype should not determine tocilizumab treatment decisions.

PurposeAlthough the definition of septic shock has been standardized, some variation in mortality rates among clinical trials is expected. Insights into the sources of heterogeneity may influence the design and interpretation of septic shock studies. We set out to identify inclusion criteria and baseline characteristics associated with between-trial differences in control group mortality rates.MethodsWe conducted a systematic review of RCTs published between 2006 and 2018 that included patients with septic shock. The percentage of variance in control-group mortality attributable to study heterogeneity rather than chance was measured by I2. The association between control-group mortality and population characteristics was estimated using linear mixed models and a recursive partitioning algorithm.ResultsSixty-five septic shock RCTs were included. Overall control-group mortality was 38.6%, with significant heterogeneity (I2 = 93%, P < 0.0001) and a 95% prediction interval of 13.5–71.7%. The mean mortality rate did not differ between trials with different definitions of hypotension, infection or vasopressor or mechanical ventilation inclusion criteria. Population characteristics univariately associated with mortality rates were mean Sequential Organ Failure Assessment score (standardized regression coefficient (β) = 0.57, P = 0.007), mean serum creatinine (β = 0.48, P = 0.007), the proportion of patients on mechanical ventilation (β = 0.61, P < 0.001), and the proportion with vasopressors (β = 0.57, P = 0.002). Combinations of population characteristics selected with a linear model and recursive partitioning explained 41 and 42%, respectively, of the heterogeneity in mortality rates.ConclusionsAmong 65 septic shock trials, there was a clinically relevant amount of heterogeneity in control group mortality rates which was explained only partly by differences in inclusion criteria and reported baseline characteristics.

Background Adequate antibiotic dosing may improve outcomes in critically ill patients but is challenging due to altered and variable pharmacokinetics. To address this challenge, AutoKinetics was developed, a decision support system for bedside, real-time, data-driven and personalised antibiotic dosing. This study evaluates the feasibility, safety and efficacy of its clinical implementation. Methods In this two-centre randomised clinical trial, critically ill patients with sepsis or septic shock were randomised to AutoKinetics dosing or standard dosing for four antibiotics: vancomycin, ciprofloxacin, meropenem, and ceftriaxone. Adult patients with a confirmed or suspected infection and either lactate > 2 mmol/L or vasopressor requirement were eligible for inclusion. The primary outcome was pharmacokinetic target attainment in the first 24 h after randomisation. Clinical endpoints included mortality, ICU length of stay and incidence of acute kidney injury. Results After inclusion of 252 patients, the study was stopped early due to the COVID-19 pandemic. In the ciprofloxacin intervention group, the primary outcome was obtained in 69% compared to 3% in the control group (OR 62.5, CI 11.4–1173.78, p  < 0.001). Furthermore, target attainment was faster (26 h, CI 18–42 h, p  < 0.001) and better (65% increase, CI 49–84%, p  < 0.001). For the other antibiotics, AutoKinetics dosing did not improve target attainment. Clinical endpoints were not significantly different. Importantly, higher dosing did not lead to increased mortality or renal failure. Conclusions In critically ill patients, personalised dosing was feasible, safe and significantly improved target attainment for ciprofloxacin. Trial registration : The trial was prospectively registered at Netherlands Trial Register (NTR), NL6501/NTR6689 on 25 August 2017 and at the European Clinical Trials Database (EudraCT), 2017-002478-37 on 6 November 2017.

BackgroundLung ultrasound can adequately monitor disease severity in pneumonia and acute respiratory distress syndrome. We hypothesize lung ultrasound can adequately monitor COVID-19 pneumonia in critically ill patients.MethodsAdult patients with COVID-19 pneumonia admitted to the intensive care unit of two academic hospitals who underwent a 12-zone lung ultrasound and a chest CT examination were included. Baseline characteristics, and outcomes including composite endpoint death or ICU stay > 30 days were recorded. Lung ultrasound and CT images were quantified as a lung ultrasound score involvement index (LUSI) and CT severity involvement index (CTSI). Primary outcome was the correlation, agreement, and concordance between LUSI and CTSI. Secondary outcome was the association of LUSI and CTSI with the composite endpoints.ResultsWe included 55 ultrasound examinations in 34 patients, which were 88% were male, with a mean age of 63 years and mean P/F ratio of 151. The correlation between LUSI and CTSI was strong (r = 0.795), with an overall 15% bias, and limits of agreement ranging − 40 to 9.7. Concordance between changes in sequentially measured LUSI and CTSI was 81%. In the univariate model, high involvement on LUSI and CTSI were associated with a composite endpoint. In the multivariate model, LUSI was the only remaining independent predictor.ConclusionsLung ultrasound can be used as an alternative for chest CT in monitoring COVID-19 pneumonia in critically ill patients as it can quantify pulmonary involvement, register changes over the course of the disease, and predict death or ICU stay > 30 days.Trial registration: NTR, NL8584. Registered 01 May 2020—retrospectively registered, https://www.trialregister.nl/trial/8584

To the Editor: The trial that was conducted by Thille et al. (Nov. 17 issue), 1 in which patients receiving mechanical ventilation were randomly assigned to spontaneous-breathing trials with pressure-support ventilation (PSV) or a T-piece, showed no between-group difference in the number of ventilator-free days at day 28. We are concerned, however, with the ability of this trial to detect such a difference owing to a ceiling effect. The sample size was planned to detect a difference of 2 ventilator-free days between the two groups on the assumption that patients with a high risk of extubation failure would have a median . . .

[...]endogeneity occurs when an omitted or unmeasurable variable influences both the propensity for exposure and the outcome. [...]endogeneity occurs when the measurable severity of illness variable is an imperfect reflection of the true baseline risk. Critical care studies are especially at risk because of the complexity of the disease and treatment processes, because illness severity cannot be precisely captured and because treatment dose or intensity is often correlated with illness severity.Endogeneity bias in a clinical practice guideline To illustrate the potential magnitude of endogeneity bias in a commonly used clinical guideline, we screened all references in the Surviving Sepsis Campaign (SSC) guideline [5].