PurposeTo assess long-term outcomes of restrictive versus standard intravenous (IV) fluid therapy in adult intensive care unit (ICU) patients with septic shock included in the European Conservative versus Liberal Approach to Fluid Therapy in Septic Shock in Intensive Care (CLASSIC) trial.MethodsWe conducted the pre-planned analyses of mortality, health-related quality of life (HRQoL) using EuroQol (EQ)-5D-5L index values and EQ visual analogue scale (VAS), and cognitive function using Mini Montreal Cognitive Assessment (Mini MoCA) test at 1 year. Deceased patients were assigned numerical zero for HRQoL as a state equal to death and zero for cognitive function outcomes as worst possible score, and we used multiple imputation for missing data on HRQoL and cognitive function.ResultsAmong 1554 randomized patients, we obtained 1-year data on mortality in 97.9% of patients, HRQoL in 91.3%, and cognitive function in 86.3%. One-year mortality was 385/746 (51.3%) in the restrictive-fluid group versus 383/767 (49.9%) in the standard-fluid group, absolute risk difference 1.5%-points [99% confidence interval (CI) − 4.8 to 7.8]. Mean differences were 0.00 (99% CI − 0.06 to 0.05) for EQ-5D-5L index values, − 0.65 for EQ VAS (− 5.40 to 4.08), and − 0.14 for Mini MoCA (− 1.59 to 1.14) for the restrictive-fluid group versus the standard-fluid group. The results for survivors only were similar in both groups.ConclusionsAmong adult ICU patients with septic shock, restrictive versus standard IV fluid therapy resulted in similar survival, HRQoL, and cognitive function at 1 year, but clinically important differences could not be ruled out.

The currently recommended dose of dexamethasone for patients with severe or critical COVID-19 is 6 mg per day (mg/d) regardless of patient features and variation. However, patients with severe or critical COVID-19 are heterogenous in many ways (e.g., age, weight, comorbidities, disease severity, and immune features). Thus, it is conceivable that a standardized dosing protocol may not be optimal. We assessed treatment effect heterogeneity in the COVID STEROID 2 trial, which compared 6 mg/d to 12 mg/d, using a causal inference framework with Bayesian Additive Regression Trees, a flexible modeling method that detects interactive effects and nonlinear relationships among multiple patient characteristics simultaneously. We found that 12 mg/d of dexamethasone, relative to 6 mg/d, was probably associated with better long-term outcomes (days alive without life support and mortality after 90 days) among the entire trial population (i.e., no signals of harm), and probably more beneficial among those without diabetes mellitus, that were older, were not using IL-6 inhibitors at baseline, weighed less, or had higher level respiratory support at baseline. This adds more evidence supporting the use of 12 mg/d in practice for most patients not receiving other immunosuppressants and that additional study of dosing could potentially optimize clinical outcomes.

The AID-ICU trial was a randomised, blinded, placebo-controlled trial investigating effects of haloperidol versus placebo in acutely admitted, adult patients admitted in intensive care unit (ICU) with delirium. This pre-planned Bayesian analysis facilitates probabilistic interpretation of the AID-ICU trial results. We used adjusted Bayesian linear and logistic regression models with weakly informative priors to analyse all primary and secondary outcomes reported up to day90, and with sensitivity analyses using other priors. The probabilities for any benefit/harm, clinically important benefit/harm, and no clinically important differences with haloperidol treatment according to pre-defined thresholds are presented for all outcomes. The mean difference for days alive and out of hospital to day90 (primary outcome) was 2.9days (95% credible interval (CrI) -1.1 to 6.9) with probabilities of 92% for any benefit and 82% for clinically important benefit. The risk difference for mortality was -6.8 percentage points (95% CrI -12.8 to -0.8) with probabilities of 99% for any benefit and 94% for clinically important benefit. The adjusted risk difference for serious adverse reactions was 0.3 percentage points (95% CrI -1.3 to 1.9) with 98% probability of no clinically important difference. Results were consistent across sensitivity analyses using different priors, with more than 83% probability of benefit and less than 17% probability of harm with haloperidol treatment. We found high probabilities of benefits and low probabilities of harm with haloperidol treatment compared with placebo in acutely admitted, adult ICU patients with delirium for the primary and most secondary outcomes.

EDITORIAL article Front. Med., 03 March 2023Sec. Intensive Care Medicine and Anesthesiology Volume 10 - 2023 | https://doi.org/10.3389/fmed.2023.1166202

BackgroundThromboembolism is more common in patients with critical COVID-19 than in other critically ill patients, and inflammation has been proposed as a possible mechanism. The aim of this study was to investigate if 12 mg vs. 6 mg dexamethasone daily reduced the composite outcome of death or thromboembolism in patients with critical COVID-19.MethodsUsing additional data on thromboembolism and bleeding we did a post hoc analysis of Swedish and Danish intensive care unit patients enrolled in the blinded randomized COVID STEROID 2 trial comparing 12 mg vs. 6 mg dexamethasone daily for up to 10 days. The primary outcome was a composite outcome of death or thromboembolism during intensive care. Secondary outcomes were thromboembolism, major bleeding, and any bleeding during intensive care.ResultsWe included 357 patients. Whilst in intensive care, 53 patients (29%) in the 12 mg group and 53 patients (30%) in the 6 mg group met the primary outcome with an unadjusted absolute risk difference of − 0.5% (95% CI − 10 to 9.5%, p = 1.00) and an adjusted OR of 0.93 (CI 95% 0.58 to 1.49, p = 0.77). We found no firm evidence of differences in any of the secondary outcomes.ConclusionsAmong patients with critical COVID-19, 12 mg vs. 6 mg dexamethasone daily did not result in a statistically significant difference in the composite outcome of death or thromboembolism. However, uncertainty remains due to the limited number of patients.

Critically ill patients are at risk of gastrointestinal (GI) bleeding. Counter measures to minimise this risk include the use of pharmacological stress ulcer prophylaxis (SUP). The effect of enteral nutrition as SUP on GI bleeding event rates is unknown. There are conflicting data describing the effect of co-administration of enteral nutrition with pharmacological SUP, and there is substantial variation in practice. We aim to conduct an exploratory post hoc analysis to evaluate the association of enteral nutrition with clinically important GI bleed rates in ICU patients included in the SUP-ICU trial, and to explore any interactions between enteral nutrition and pharmacologic SUP on patient outcomes. The SUP-ICU trial dataset will be used to assess if enteral nutrition is associated with the outcomes of interest. Extended Cox models will be used considering relevant competing events, including treatment allocation (SUP or placebo) and enteral nutrition as a daily time-varying covariate, with additional adjustment for severity of illness (SAPS II). Results will be presented as adjusted hazard ratios for treatment allocation and enteral nutrition, and for treatment allocation and enteral nutrition considering potential interactions with the other variable, all with 95% confidence intervals and p-values for the tests of interaction. All results will be considered as exploratory only. This post hoc analysis may yield important insights to guide practice and inform the design of future randomised clinical trial investigating the effect of enteral nutrition on GI bleeding.

AbstractThis paper aims to propose an integrated workflow for the digitization of the built cultural heritage. To this end, we leverage the power of computational tools and the relevancy of Building Information Modeling (BIM) process to overcome the limitations and challenges faced by Scan-to-BIM. We describe the automatic generation of an as-built BIM model of a heritage building in a three-step procedure. Firstly, we outline the data acquisition method of the point cloud. Secondly, we describe the automatic processing and segmentation of the point cloud according to architectural elements using Machine Learning. Then, we tested and compared various meshing algorithms and utilized a combination depending on the desired level of details. Lastly, the resulting geometry is converted into a BIM object that will be subsequently semantically labeled. We used a UNESCO world heritage in Morocco—Chellah, as a case study to test the robustness of our protocol.

IntroductionThe value set used when calculating quality-adjusted life-years (QALYs) is most often based on stated preference data elicited from a representative sample of the general population. However, having a severe disease may alter a person’s health preferences, which may imply that, for some patient groups, experienced QALYs may differ from those that are estimated via standard methods. This study aims to model 5-level EuroQol 5-dimensional questionnaire (EQ-5D-5L) valuations based on preferences elicited from a sample of patients who have survived a stay in a Danish intensive care unit (ICU) and to compare these with the preferences of the general population. Further, the heterogeneity in the ICU patients’ preferences will be investigated.Methods and analysisThis valuation study will elicit EQ-5D-5L health state preferences from a sample of 300 respondents enrolled in two randomised controlled trials at Danish ICUs. Patients’ preferences will be elicited using composite time trade-off based on the EuroQol Valuation Technology, the same as that used to generate the EQ-5D-5L value set for the Danish general population. The patient-based and the public-based EQ-5D-5L valuations will be compared. Potential underlying determinants of the ICU preferences will be investigated through analyses of demographic characteristics, time since the ICU stay, self-reported health, willingness to trade-off length of life for quality of life, health state reference dependency and EQ-5D dimensions that patients have experienced themselves during their illness.Ethics and disseminationUnder Danish regulations, ethical approval is not required for studies of this type. Written informed consent will be obtained from all patients. The study results will be published in peer-reviewed scientific journals and presented at national and international conferences. The modelling algorithms will be publicly available for statistical software, such as Stata and R.