Search

Abstract Purpose To identify key components and variations in family-centered care practices. Methods A cross-sectional study, conducted across ESICM members. Participating ICUs completed a questionnaire covering general ICU characteristics, visitation policies, team-family interactions, and end-of-life decision-making. The primary outcome, self-rated family-centeredness, was assessed using a visual analog scale. Additionally, respondents completed the Maslach Burnout Inventory and the Ethical Decision Making Climate Questionnaire to capture burnout dimensions and assess the ethical decision-making climate. Results The response rate was 53% (respondents from 359/683 invited ICUs who actually open the email); participating healthcare professionals (HCPs) were from Europe (62%), Asia (9%), South America (6%), North America (5%), Middle East (4%), and Australia/New Zealand (4%). The importance of family-centeredness was ranked high, median 7 (IQR 6–8) of 10 on VAS. Significant differences were observed across quartiles of family centeredness, including in visitation policies availability of a waiting rooms, family rooms, family information leaflet, visiting hours, night visits, sleep in the ICU, and in team-family interactions, including daily information, routine day-3 conference, and willingness to empower nurses and relatives. Higher family centeredness correlated with family involvement in rounds, participation in patient care and end-of-life practices. Burnout symptoms (41% of respondents) were negatively associated with family-centeredness. Ethical climate and willingness to empower nurses were independent predictors of family centeredness. Conclusions This study emphasizes the need to prioritize healthcare providers’ mental health for enhanced family-centered care. Further research is warranted to assess the impact of improving the ethical climate on family-centeredness.

Abstract Background The optimal amount and timing of protein intake in critically ill patients are unknown. REPLENISH (Replacing Protein via Enteral Nutrition in a Stepwise Approach in Critically Ill Patients) trial evaluates whether supplemental enteral protein added to standard enteral nutrition to achieve a high amount of enteral protein given from ICU day five until ICU discharge or ICU day 90 as compared to no supplemental enteral protein to achieve a moderate amount of enteral protein would reduce all-cause 90-day mortality in adult critically ill mechanically ventilated patients. Methods In this multicenter randomized trial, critically ill patients will be randomized to receive supplemental enteral protein (1.2 g/kg/day) added to standard enteral nutrition to achieve a high amount of enteral protein (range of 2–2.4 g/kg/day) or no supplemental enteral protein to achieve a moderate amount of enteral protein (0.8–1.2 g/kg/day). The primary outcome is 90-day all-cause mortality; other outcomes include functional and health-related quality-of-life assessments at 90 days. The study sample size of 2502 patients will have 80% power to detect a 5% absolute risk reduction in 90-day mortality from 30 to 25%. Consistent with international guidelines, this statistical analysis plan specifies the methods for evaluating primary and secondary outcomes and subgroups. Applying this statistical analysis plan to the REPLENISH trial will facilitate unbiased analyses of clinical data. Conclusion Ethics approval was obtained from the institutional review board, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia (RC19/414/R). Approvals were also obtained from the institutional review boards of each participating institution. Our findings will be disseminated in an international peer-reviewed journal and presented at relevant conferences and meetings. Trial registration ClinicalTrials.gov, NCT04475666 . Registered on July 17, 2020.

Background: Oxygen supplementation is ubiquitous in intensive care unit (ICU) patients with chronic obstructive pulmonary disease (COPD) and acute hypoxaemia, but the optimal oxygenation target has not been established. Methods: This was a pre-planned subgroup analysis of the Handling Oxygenation Targets in the ICU (HOT-ICU) trial, which allocated patients with acute hypoxaemia to a lower oxygenation target (partial pressure of arterial oxygen [Pao2] of 8 kPa) vs a higher target (Pao2 of 12 kPa) during ICU admission, for up to 90 days; the allocation was stratified for presence or absence of COPD. Here, we report key outcomes for patients with COPD. Results: The HOT-ICU trial enrolled 2928 patients of whom 563 had COPD; 277 were allocated to the lower and 286 to the higher oxygenation group. After allocation, the median Pao2 was 9.1 kPa (inter-quartile range 8.7–9.9) in the lower group vs 12.1 kPa (11.2–12.9) in the higher group. Data for arterial carbon dioxide (Paco2) were available for 497 patients (88%) with no between-group difference in time-weighted average; median Paco2 6.0 kPa (5.2–7.2) in the lower group vs 6.2 kPa (5.4–7.3) in the higher group. At 90 days, 122/277 patients (44%) in the lower oxygenation group had died vs 132/285 patients (46%) in the higher (relative risk 0.98; 95% confidence interval 0.82–1.17; P=0.67). No statistically significant differences were found in any secondary outcome. Conclusions: In ICU patients with COPD and acute hypoxaemia, a lower vs a higher oxygenation target did not reduce mortality. There were no between-group differences in Paco2 or in secondary outcomes. Clinical trial registration: NCT 03174002, EudraCT number 2017-000632-34.

Abstract Background Acute respiratory failure (ARF) is the leading cause of intensive care unit (ICU) admission in patients with Acute Myeloid Leukemia (AML) and data on prognostic factors affecting short-term outcome are needed. Methods This is a post-hoc analysis of a multicenter, international prospective cohort study on immunocompromised patients with ARF admitted to ICU. We evaluated hospital mortality and associated risk factors in patients with AML and ARF; secondly, we aimed to define specific subgroups within our study population through a cluster analysis. Results Overall, 201 of 1611 immunocompromised patients with ARF had AML and were included in the analysis. Hospital mortality was 46.8%. Variables independently associated with mortality were ECOG performance status ≥ 2 (OR = 2.79, p = 0.04), cough (OR = 2.94, p = 0.034), use of vasopressors (OR = 2.79, p = 0.044), leukemia-specific pulmonary involvement [namely leukostasis, pulmonary infiltration by blasts or acute lysis pneumopathy (OR = 4.76, p = 0.011)] and liver SOFA score (OR = 1.85, p = 0.014). Focal alveolar chest X-ray pattern was associated with survival (OR = 0.13, p = 0.001). We identified 3 clusters, that we named on the basis of the most frequently clinical, biological and radiological features found in each cluster: a “leukemic cluster”, with high-risk AML patients with isolated, milder ARF; a “pulmonary cluster”, consisting of symptomatic, highly oxygen-requiring, severe ARF with diffuse radiological findings in heavily immunocompromised patients; a clinical “inflammatory cluster”, including patients with multi-organ failures in addition to ARF. When included in the multivariate analysis, cluster 2 and 3 were independently associated with hospital mortality. Conclusions Among AML patients with ARF, factors associated with a worse outcome are related to patient’s background (performance status, leukemic pulmonary involvement), symptoms, radiological findings, the need for vasopressors and the liver SOFA score. We identified three specific ARF syndromes in AML patients, which showed a prognostic significance and could guide clinicians to optimize management strategies.

Abstract Background Haloperidol is frequently used in critically ill patients with delirium, but evidence for its effects has been sparse and inconclusive. By including recent trials, we updated a systematic review assessing effects of haloperidol on mortality and serious adverse events in critically ill patients with delirium. Methods This is an updated systematic review with meta-analysis and trial sequential analysis of randomised clinical trials investigating haloperidol versus placebo or any comparator in critically ill patients with delirium. We adhered to the Cochrane handbook, the PRISMA guidelines and the grading of recommendations assessment, development and evaluation statements. The primary outcomes were all-cause mortality and proportion of patients with one or more serious adverse events or reactions (SAEs/SARs). Secondary outcomes were days alive without delirium or coma, delirium severity, cognitive function and health-related quality of life. Results We included 11 RCTs with 15 comparisons (n = 2200); five were placebo-controlled. The relative risk for mortality with haloperidol versus placebo was 0.89; 96.7% CI 0.77 to 1.03; I 2 = 0% (moderate-certainty evidence) and for proportion of patients experiencing SAEs/SARs 0.94; 96.7% CI 0.81 to 1.10; I 2 = 18% (low-certainty evidence). We found no difference in days alive without delirium or coma (moderate-certainty evidence). We found sparse data for other secondary outcomes and other comparators than placebo. Conclusions Haloperidol may reduce mortality and likely result in little to no change in the occurrence of SAEs/SARs compared with placebo in critically ill patients with delirium. However, the results were not statistically significant and more trial data are needed to provide higher certainty for the effects of haloperidol in these patients. Trial registration: CRD42017081133, date of registration 28 November 2017.

Abstract Background Protein intake is recommended in critically ill patients to mitigate the negative effects of critical illness-induced catabolism and muscle wasting. However, the optimal dose of enteral protein remains unknown. We hypothesize that supplemental enteral protein (1.2 g/kg/day) added to standard enteral nutrition formula to achieve high amount of enteral protein (range 2–2.4 g/kg/day) given from ICU day 5 until ICU discharge or ICU day 90 as compared to no supplemental enteral protein to achieve moderate amount enteral protein (0.8–1.2 g/kg/day) would reduce all-cause 90-day mortality in adult critically ill mechanically ventilated patients. Methods The REPLENISH (Replacing Protein Via Enteral Nutrition in a Stepwise Approach in Critically Ill Patients) trial is an open-label, multicenter randomized clinical trial. Patients will be randomized to the supplemental protein group or the control group. Patients in both groups will receive the primary enteral formula as per the treating team, which includes a maximum protein 1.2 g/kg/day. The supplemental protein group will receive, in addition, supplemental protein at 1.2 g/kg/day starting the fifth ICU day. The control group will receive the primary formula without supplemental protein. The primary outcome is 90-day all-cause mortality. Other outcomes include functional and quality of life assessments at 90 days. The trial will enroll 2502 patients. Discussion The study has been initiated in September 2021. Interim analysis is planned at one third and two thirds of the target sample size. The study is expected to be completed by the end of 2025. Trial registration ClinicalTrials.gov Identifier: NCT04475666 . Registered on July 17, 2020.

Abstract Background Days alive without life support (DAWOLS) and similar outcomes that seek to summarise mortality and non-mortality experiences are increasingly used in critical care research. The use of these outcomes is challenged by different definitions and non-normal outcome distributions that complicate statistical analysis decisions. Methods We scrutinized the central methodological considerations when using DAWOLS and similar outcomes and provide a description and overview of the pros and cons of various statistical methods for analysis supplemented with a comparison of these methods using data from the COVID STEROID 2 randomised clinical trial. We focused on readily available regression models of increasing complexity (linear, hurdle-negative binomial, zero–one-inflated beta, and cumulative logistic regression models) that allow comparison of multiple treatment arms, adjustment for covariates and interaction terms to assess treatment effect heterogeneity. Results In general, the simpler models adequately estimated group means despite not fitting the data well enough to mimic the input data. The more complex models better fitted and thus better replicated the input data, although this came with increased complexity and uncertainty of estimates. While the more complex models can model separate components of the outcome distributions (i.e., the probability of having zero DAWOLS), this complexity means that the specification of interpretable priors in a Bayesian setting is difficult. Finally, we present multiple examples of how these outcomes may be visualised to aid assessment and interpretation. Conclusions This summary of central methodological considerations when using, defining, and analysing DAWOLS and similar outcomes may help researchers choose the definition and analysis method that best fits their planned studies. Trial registration COVID STEROID 2 trial, ClinicalTrials.gov: NCT04509973, ctri.nic.in: CTRI/2020/10/028731.

Abstract 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.

Abstract Background Thromboembolism 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. Methods Using 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. Results We 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. Conclusions Among 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.

Abstract Prediction of survival for patients in intensive care units (ICUs) has been subject to intense research. However, no models exist that embrace the multiverse of data in ICUs. It is an open question whether deep learning methods using automated data integration with minimal pre-processing of mixed data domains such as free text, medical history and high-frequency data can provide discrete-time survival estimates for individual ICU patients. We trained a deep learning model on data from patients admitted to ten ICUs in the Capital Region of Denmark and the Region of Southern Denmark between 2011 and 2018. Inspired by natural language processing we mapped the electronic patient record data to an embedded representation and fed the data to a recurrent neural network with a multi-label output layer representing the chance of survival at different follow-up times. We evaluated the performance using the time-dependent concordance index. In addition, we quantified and visualized the drivers of survival predictions using the SHAP methodology. We included 37,355 admissions of 29,417 patients in our study. Our deep learning models outperformed traditional Cox proportional-hazard models with concordance index in the ranges 0.72–0.73, 0.71–0.72, 0.71, and 0.69–0.70, for models applied at baseline 0, 24, 48, and 72 h, respectively. Deep learning models based on a combination of entity embeddings and survival modelling is a feasible approach to obtain individualized survival estimates in data-rich settings such as the ICU. The interpretable nature of the models enables us to understand the impact of the different data domains.

Abstract Background Fluid overload is a risk factor for organ dysfunction and death in intensive care unit (ICU) patients, but no guidelines exist for its management. We systematically reviewed benefits and harms of a single loop diuretic, the predominant treatment used for fluid overload in these patients. Methods We conducted a systematic review with meta-analysis and Trial Sequential Analysis (TSA) of a single loop diuretic vs. other interventions reported in randomised clinical trials, adhering to our published protocol, the Cochrane Handbook, and PRISMA statement. We assessed the risks of bias with the ROB2-tool and certainty of evidence with GRADE. This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42020184799). Results We included 10 trials (804 participants), all at overall high risk of bias. For loop diuretics vs. placebo/no intervention, we found no difference in all-cause mortality (relative risk (RR) 0.72, 95% confidence interval (CI) 0.49–1.06; 4 trials; 359 participants; I 2 = 0%; TSA-adjusted CI 0.15–3.48; very low certainty of evidence). Fewer serious adverse events were registered in the group treated with loop diuretics (RR 0.81, 95% CI 0.66–0.99; 6 trials; 476 participants; I 2 = 0%; very low certainty of evidence), though contested by TSA (TSA-adjusted CI 0.55–1.20). Conclusions The evidence is very uncertain about the effect of loop diuretics on mortality and serious adverse events in adult ICU patients with fluid overload. Loop diuretics may reduce the occurrence of these outcomes, but large randomised placebo-controlled trials at low risk of bias are needed.

Introduction Intravenous crystalloid fluid resuscitation forms a crucial part of the early intervention bundle for sepsis and septic shock, with the Surviving Sepsis Campaign guidelines recommending a 30 mL/kg fluid bolus within the first hour. Compliance with this suggested target varies in patients with comorbidities such as congestive heart failure, chronic kidney disease and cirrhosis due to concerns regarding iatrogenic fluid overload. However, it remains unclear whether resuscitation with higher fluid volumes puts them at greater risk of adverse outcomes. Thus, this systematic review will synthesise evidence from existing studies to assess the effects of a conservative as compared with a liberal approach to fluid resuscitation in patients at greater perceived risk of fluid overload due to comorbid conditions.Methods and analysis This protocol was registered on PROSPERO and has been drafted following the checklist of Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. We will search MEDLINE, MEDLINE Epub Ahead of Print and In-Process, In-Data-Review & Other Non-Indexed Citations, Embase, Embase Classic, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Web of Science Core Collection, CINAHL Complete and ClinicalTrials.gov. A preliminary search of these databases was performed from their inception to 30 August 2022. The risk of bias and random errors will be assessed using the revised Cochrane risk-of-bias tool for randomised clinical trials and the Newcastle-Ottawa Scale for case–control and cohort studies. If a sufficient number of comparable studies are identified, we will perform a meta-analysis applying random effects model. We will investigate heterogeneity using a combination of visual inspection of the funnel plot as well as the Egger’s test.Ethics and dissemination No ethics approval is required for this study since no original data will be collected. The findings will be disseminated through peer-reviewed publication and conference presentation.PROSPERO registration number CRD42022348181.

Abstract Background Intravenous fluids are often used in the treatment of sepsis. The better strategy regarding fluid volume is debated, but preliminary data in patients with septic shock or sepsis-related hypotension favor restrictive fluid administration. We describe the protocol and statistical analysis plan for the Restrictive Fluid Administration vs. Standard of Care in Emergency Department Sepsis Patients (REFACED Sepsis)—a multicenter, randomized clinical proof-of-concept trial. The aim of the REFACED Sepsis trial is to test if a restrictive intravenous fluid protocol in emergency department patients with sepsis without shock is feasible and decreases the intravenous fluid volume administered in comparison to standard care. Methods This is an investigator-initiated, multicenter, randomized, parallel-group, open-labeled, feasibility trial investigating volumes of crystalloid fluid within 24 h in 124 patients with sepsis without shock enrolled at three emergency departments in the Central Denmark Region. Patients are allocated to two different intravenous fluid regimens: a restrictive approach using four trigger criteria for fluid administration vs. standard care. The primary, feasibility outcome is total intravenous, crystalloid fluid volume within 24 h, and key secondary outcomes include protocol violations, total fluids (intravenous and oral) within 24 h, and serious adverse reactions and suspected unexpected serious adverse reactions. Status: The trial started in November 2021, and the last patient is anticipated to be included in January 2022. Discussion Sepsis is very common in emergency department patients and fluid administration is very frequently administered in these patients. However, the evidence to guide fluid administration is very sparse. This feasibility trial will be the foundation for a potential future large-scale trial investigating restrictive vs. standard fluid administration in patients with sepsis. Trial registration EudraCT number: 2021-000224-35 (date: 2021 May 03), ClinicalTrials.gov number: NCT05076435 (date: 2021 October 13), Committee on Health Research Ethics – Central Denmark Region: 1-10-72-163-21 (date: 2021 June 28).

Abstract In a recent paper, Chen et al. report the findings of a systematic review with meta-analysis concerning conservative versus conventional oxygen therapy for critically ill patients. We wish to commend the authors for their interest in the matter. However, the authors appear to misquote findings, fail to report results for all specified analyses, do not identify all relevant trials, have post hoc changed the eligibility criteria, and have seemingly switched directions of effects in analyses of secondary outcomes. These issues have led to incorrect conclusions concerning the effects of targeted oxygen therapy in critically ill patients.

Background: Patients admitted to an intensive care unit (ICU) with active haematological malignancy and hypoxaemic respiratory failure have a high mortality. Oxygen supplementation is essential, but limited information exists on the optimum oxygenation targets in these patients. Methods: This subgroup analysis was specified before completion of the Handling Oxygenation Targets in the ICU (HOT-ICU) trial. The trial investigated the effects of a lower (8 kPa) vs a higher (12 kPa) arterial oxygenation target and was stratified for active haematological malignancy, chronic obstructive pulmonary disease, and site. We here report the primary outcome (90-day mortality) and selected secondary outcomes in the subgroup of patients with active haematological malignancy. Results: The HOT-ICU trial included 168 patients with active haematological malignancy; 82 were randomly allocated to an arterial oxygenation target of 8 kPa, and 86 to 12 kPa. At 90 days, 53/81 patients (65%) in the lower-oxygenation group and 47/86 patients (55%) in the higher-oxygenation group had died: adjusted relative risk 1.22 (95% confidence interval 0.95–1.56); at 1 year, the numbers were 58/81 (72%) vs 56/86 (65%): adjusted relative risk 1.11 (95% confidence interval 0.90–1.36). No statistically significant differences were found for any secondary outcomes. Conclusion: In ICU patients with active haematological malignancies and hypoxaemic respiratory failure, we found a high mortality at 90 days and 1 year. Our results did not preclude clinically relevant benefits or harms of a lower oxygenation target in patients with active haematological malignancy. A randomised trial may, therefore, be worthwhile for these patients. Clinical trial registration: NCT03174002.

Abstract The COVID-19 pandemic has put massive strains on hospitals, and tools to guide hospital planners in resource allocation during the ebbs and flows of the pandemic are urgently needed. We investigate whether machine learning (ML) can be used for predictions of intensive care requirements a fixed number of days into the future. Retrospective design where health Records from 42,526 SARS-CoV-2 positive patients in Denmark was extracted. Random Forest (RF) models were trained to predict risk of ICU admission and use of mechanical ventilation after n days (n = 1, 2, …, 15). An extended analysis was provided for n = 5 and n = 10. Models predicted n-day risk of ICU admission with an area under the receiver operator characteristic curve (ROC-AUC) between 0.981 and 0.995, and n-day risk of use of ventilation with an ROC-AUC between 0.982 and 0.997. The corresponding n-day forecasting models predicted the needed ICU capacity with a coefficient of determination (R2) between 0.334 and 0.989 and use of ventilation with an R2 between 0.446 and 0.973. The forecasting models performed worst, when forecasting many days into the future (for large n). For n = 5, ICU capacity was predicted with ROC-AUC 0.990 and R2 0.928, and use of ventilator was predicted with ROC-AUC 0.994 and R2 0.854. Random Forest-based modelling can be used for accurate n-day forecasting predictions of ICU resource requirements, when n is not too large.

Abstract Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics—Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.

Introduction The 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 analysis This 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 dissemination Under 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.

Abstract Objectives Primary objective: To estimate the effect of corticosteroids compared with usual care or placebo on mortality up to 28 days after randomization. Secondary objectives: To examine whether the effect of corticosteroids compared with usual care or placebo on mortality up to 28 days after randomization varies between subgroups related to treatment characteristics, disease severity at the time of randomization, patient characteristics, or risk of bias. To examine the effect of corticosteroids compared with usual care or placebo on serious adverse events. Study design Prospective meta-analysis of randomized controlled trials. Both placebo-controlled and open-label trials are eligible. Participants Hospitalised, critically ill patients with suspected or confirmed COVID-19. Intervention and comparator Intervention groups will have received therapeutic doses of a steroid (dexamethasone, hydrocortisone or methylprednisolone) with IV or oral administration immediately after randomization. The comparator groups will have received standard of care or usual care or placebo. Main outcome All-cause mortality up to 28 days after randomization. Search methods Systematic searching of clinicaltrials.gov , EudraCT, the WHO ISRCTN registry, and the Chinese clinical trials registry. Additionally, research and WHO networks will be asked for relevant trials. Risk of bias assessments These will be based on the Cochrane RoB 2 tool, and will use structured information provided by the trial investigators on a form designed for this prospective meta-analysis. Summary of findings We will use GRADE to assess the certainty of the evidence. Statistical analyses Trial investigators will provide data on the numbers of participants who did and did not experience each outcome according to intervention group, overall and in specified subgroups. We will conduct fixed-effect (primary analysis) and random-effects (Paule-Mandel estimate of heterogeneity and Hartung-Knapp adjustment) meta-analyses. We will quantify inconsistency in effects between trials using I2 statistics. Evidence for subgroup effects will be quantified by ratios of odds ratios comparing effects in the subgroups, and corresponding interaction p-values. Comparisons between subgroups defined by trial characteristics will be made using random-effects meta-regression. Comparisons between subgroups defined by patient characteristics will be made by estimating trial-specific ratios of odds ratios comparing intervention effects between subgroups then combining these using random-effects meta-analysis. Steroid interventions will be classified as high or low dose according to whether the dose is greater or less than or equal to 400 mg hydrocortisone per day or equivalent. We will use network meta-analysis methods to make comparisons between the effects of high and low dose steroid interventions (because one trial randomized participants to both low and high dose steroid arms). PROSPERO registration number CRD42020197242 Full protocol The full protocol for this prospective meta-analysis is attached as an additional file, accessible from the Trials website (Additional file 1). To expedite dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol for the systematic review.

Abstract Background It is unclear whether influenza infection and associated co-infection are associated with patient-important outcomes in critically ill immunocompromised patients with acute respiratory failure. Methods Preplanned secondary analysis of EFRAIM, a prospective cohort study of 68 hospitals in 16 countries. We included 1611 patients aged 18 years or older with non-AIDS-related immunocompromise, who were admitted to the ICU with acute hypoxemic respiratory failure. The main exposure of interest was influenza infection status. The primary outcome of interest was all-cause hospital mortality, and secondary outcomes ICU length of stay (LOS) and 90-day mortality. Results Influenza infection status was categorized into four groups: patients with influenza alone (n = 95, 5.8%), patients with influenza plus pulmonary co-infection (n = 58, 3.6%), patients with non-influenza pulmonary infection (n = 820, 50.9%), and patients without pulmonary infection (n = 638, 39.6%). Influenza infection status was associated with a requirement for intubation and with LOS in ICU (P

Abstract Background Acute kidney injury (AKI) occurs in up to 50% of all critically ill patients and hemodynamic abnormalities are assumed to contribute, but their nature and share is still unclear. We explored the associations between hemodynamic variables, including cardiac index and right ventricular function, and the occurrence of AKI in critically ill patients. Methods In this prospective cohort study, we included all patients acutely admitted to an intensive care unit (ICU). Within 24 h after ICU admission clinical and hemodynamic variables were registered including ultrasonographic measurements of cardiac index and right ventricular function, assessed using tricuspid annular plane systolic excursion (TAPSE) and right ventricular systolic excursion (RV S’). Maximum AKI stage was assessed according to the KDIGO criteria during the first 72 h after admission. Multivariable logistic regression modeling was used including both known predictors and univariable significant predictors of AKI. Secondary outcomes were days alive outside ICU and 90-day mortality. Results A total of 622 patients were included, of which 338 patients (54%) had at least AKI stage 1 within 72 h after ICU admission. In the final multivariate model higher age (OR 1.01, 95% CI 1.00–1.03, for each year), higher weight (OR 1.03 CI 1.02–1.04, for each kg), higher APACHE IV score (OR 1.02, CI 1.01–1.03, per point), lower mean arterial pressure (OR 1.02, CI 1.01–1.03, for each mmHg decrease) and lower TAPSE (OR 1.05, CI 1.02–1.09 per millimeter decrease) were all independent predictors for AKI in the final multivariate logistic regression model. Sepsis, cardiac index, RV S’ and use of vasopressors were not significantly associated with AKI in our data. AKI patients had fewer days alive outside of ICU, and their mortality rate was significantly higher than those without AKI. Conclusions In our cohort of acutely admitted ICU patients, the incidence of AKI was 54%. Hemodynamic variables were significantly different between patients with and without AKI. A worse right ventricle function was associated with AKI in the final model, whereas cardiac index was not.

Objectives:. To explore the association between antibiotic combination therapy and in-hospital mortality in patients with septic shock in two tertiary ICUs in different countries. Design:. Retrospective observational study. Setting:. ICUs of two tertiary hospitals, Royal Brisbane and Women’s Hospital, Brisbane, QLD, Australia, and Rigshospitalet, Copenhagen, Denmark. Patients:. Adult patients with antibiotic treatment greater than or equal to 72 hours and vasopressor therapy greater than or equal to 24 hours. Intervention:. Combination versus mono antibiotic therapy. Measurements and Main Results:. Combination antibiotic therapy was defined as receiving two or more antibiotics from different classes, started within 12 hours of each other and with an overlapping duration of greater than or equal to 12 hours. Bivariate and multiple logistic regression analysis were performed comparing combination antibiotic therapy versus antibiotic monotherapy on in-hospital mortality. The analysis was adjusted for age, gender, centre, Acute Physiology and Chronic Health Evaluation II score, and chronic health evaluation. In total, 1,667 patients were included with 953 (57%) receiving combination therapy. Patients given combination therapy were older (60 ± 16 vs 56 ± 18), more likely admitted to Rigshospitalet (58% vs 16%), and had a higher Acute Physiology and Chronic Health Evaluation II score (26 ± 8 vs 23 ± 8). Combination therapy was associated with an increased mortality in univariate analysis (odds ratio = 1.33; 95% CI, 1.07–1.66); however, there was no significant association in the adjusted analysis (odds ratio = 0.88; 95% CI, 0.68–1.15). Conclusions:. In this retrospective study, no association was found between use of combination therapy and in-hospital mortality. The large differences between centers probably reflect local traditions and lack of definitive evidence.

Summary: Background: Many mortality prediction models have been developed for patients in intensive care units (ICUs); most are based on data available at ICU admission. We investigated whether machine learning methods using analyses of time-series data improved mortality prognostication for patients in the ICU by providing real-time predictions of 90-day mortality. In addition, we examined to what extent such a dynamic model could be made interpretable by quantifying and visualising the features that drive the predictions at different timepoints. Methods: Based on the Simplified Acute Physiology Score (SAPS) III variables, we trained a machine learning model on longitudinal data from patients admitted to four ICUs in the Capital Region, Denmark, between 2011 and 2016. We included all patients older than 16 years of age, with an ICU stay lasting more than 1 h, and who had a Danish civil registration number to enable 90-day follow-up. We leveraged static data and physiological time-series data from electronic health records and the Danish National Patient Registry. A recurrent neural network was trained with a temporal resolution of 1 h. The model was internally validated using the holdout method with 20% of the training dataset and externally validated using previously unseen data from a fifth hospital in Denmark. Its performance was assessed with the Matthews correlation coefficient (MCC) and area under the receiver operating characteristic curve (AUROC) as metrics, using bootstrapping with 1000 samples with replacement to construct 95% CIs. A Shapley additive explanations algorithm was applied to the prediction model to obtain explanations of the features that drive patient-specific predictions, and the contributions of each of the 44 features in the model were analysed and compared with the variables in the original SAPS III model. Findings: From a dataset containing 15 615 ICU admissions of 12 616 patients, we included 14 190 admissions of 11 492 patients in our analysis. Overall, 90-day mortality was 33·1% (3802 patients). The deep learning model showed a predictive performance on the holdout testing dataset that improved over the timecourse of an ICU stay: MCC 0·29 (95% CI 0·25–0·33) and AUROC 0·73 (0·71–0·74) at admission, 0·43 (0·40–0·47) and 0·82 (0·80–0·84) after 24 h, 0·50 (0·46–0·53) and 0·85 (0·84–0·87) after 72 h, and 0·57 (0·54–0·60) and 0·88 (0·87–0·89) at the time of discharge. The model exhibited good calibration properties. These results were validated in an external validation cohort of 5827 patients with 6748 admissions: MCC 0·29 (95% CI 0·27–0·32) and AUROC 0·75 (0·73–0·76) at admission, 0·41 (0·39–0·44) and 0·80 (0·79–0·81) after 24 h, 0·46 (0·43–0·48) and 0·82 (0·81–0·83) after 72 h, and 0·47 (0·44–0·49) and 0·83 (0·82–0·84) at the time of discharge. Interpretation: The prediction of 90-day mortality improved with 1-h sampling intervals during the ICU stay. The dynamic risk prediction can also be explained for an individual patient, visualising the features contributing to the prediction at any point in time. This explanation allows the clinician to determine whether there are elements in the current patient state and care that are potentially actionable, thus making the model suitable for further validation as a clinical tool. Funding: Novo Nordisk Foundation and the Innovation Fund Denmark.

Abstract Background Proton pump inhibitors are often used in critically ill patients to prevent gastrointestinal bleeding despite limited evidence for benefit. Patients with acute kidney injury requiring renal replacement therapy (RRT) are at high risk of gastrointestinal bleeding as (pre-)uremia induces coagulopathy through effects on platelets and coagulation cascades. No high-quality randomized clinical trials have previously assessed the benefits and harms of prophylactic proton pump inhibitor use in this high-risk population of adult critically ill patients. Methods/design Among the 3350 patients included in the Stress Ulcer Prophylaxis in the Intensive Care Unit (SUP-ICU) trial—an investigator-initiated international randomized clinical trial on prophylactic proton pump inhibitor versus placebo in acutely admitted adult ICU patients at risk of gastrointestinal bleeding—we will compare the benefits and harms of prophylactic use of proton pump inhibitor in patients in need of RRT versus those not requiring this treatment. We will determine the proportion of patients with clinically important bleeding, the proportion of patients with adverse events including pneumonia, Clostridium difficile enteritis, or acute myocardial ischemia in the ICU, as well as transfusion requirements. Moreover, 90 day and 365 day mortality post-randomization will be investigated. As a secondary analysis, we will examine the association between acute kidney injury and RRT during ICU stay and gastrointestinal bleeding. Discussion With the outlined predefined analysis, we will characterize the balance between the benefits and harms of stress ulcer prophylaxis in acutely admitted adult ICU patients in need of RRT, including the potential interaction of allocation to proton pump inhibitor versus placebo. Trial registration ClinicalTrials.gov, NCT02718261 . Registered on 14 March 2016.

Abstract Background Patients with malignant haematological disease and especially those who require intensive care have an increased risk of bleeding and thrombosis, but none of these data were obtained in ICU patients only. We assessed the incidence of bleeding and thrombotic complications, use of blood products and risk factors for bleeding in an adult population of ICU patients with haematological malignancies. Methods We screened all patients with acute leukaemia and myelodysplastic syndrome admitted to a university hospital ICU during 2008–2012. Bleeding in ICU was scored according to the WHO grading system, and risk factors were evaluated using unadjusted and adjusted analyses. Results In total, 116 of 129 ICU patients were included; their median length of stay was 7 (IQR 2–16) days. Of these, 66 patients (57%) had at least one bleeding episode in ICU; they bled for 3 (2–6) days and most often from lower and upper airways and upper GI tract. Thirty-nine (59%) of the 66 patients had severe or debilitating (WHO grade 3 or 4) bleeding. The median platelet count on the day of grade 3 or 4 bleeding was 23 × 109 per litre (IQR 13–39). Nine patients (8%) died in ICU following a bleeding episode; five of these had intra-cerebral haemorrhage. Platelet count on admission was associated with subsequent bleeding (adjusted odds ratio 1.18 (95% CI 1.03–1.35) for every 10 × 109 per litre drop in platelet count, p = 0.016). Eleven of the 116 patients (9%) developed a clinically significant thrombosis in ICU, which was the cause of death in four patients. The median platelet count was 20 × 109 per litre (15–48) at the time of thrombosis. The patients received a median of 6 units of red blood cells, 1 unit of fresh frozen plasma and 8 units of platelet concentrates in ICU. Conclusions Severe and debilitating bleeding complications were frequent in our ICU patients with haematological malignancies, but thrombosis also occurred in spite of low platelet counts. Platelet count on ICU admission was associated with subsequent bleeding.

Abstract Background Stress ulcer prophylaxis is considered standard of care in many critically ill patients in the intensive care unit (ICU). However, the quality of evidence supporting this has recently been questioned, and clinical equipoise exists. Whether there is overall benefit or harm of stress ulcer prophylaxis in adult hospitalised acutely ill patients is unknown. Accordingly, we aim to assess patient-important benefits and harms of stress ulcer prophylaxis versus placebo or no treatment in adult hospitalised acutely ill patients with high risk of gastrointestinal bleeding irrespective of hospital setting. Methods/design We will conduct a systematic review of randomised clinical trials with meta-analysis and trial sequential analysis and assess use of proton pump inhibitors (PPIs) or histamine-2-receptor antagonists (H2RAs) in any dose, formulation and duration. We will accept placebo or no prophylaxis as control interventions. The participants will be adult hospitalised acutely ill patients with high risk of gastrointestinal bleeding. We will systematically search the Cochrane Library, MEDLINE, EMBASE, Science Citation Index, BIOSIS and Epistemonikos for relevant literature. We will follow the recommendations by the Cochrane Collaboration and the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. The risk of systematic errors (bias) and random errors will be assessed, and the overall quality of evidence will be evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Discussion There is a need for a high-quality systematic review to summarise the benefits and harms of stress ulcer prophylaxis in hospitalised patients to inform practice and future research. Although stress ulcer prophylaxis is used worldwide, no firm evidence for benefit or harm as compared to placebo or no treatments has been established. Critical illness is a continuum not limited to the ICU setting, which is why it is important to assess the benefits and harms of stress ulcer prophylaxis in a wider perspective than exclusively in ICU patients. Systematic review registration PROSPERO CRD42017055676

Abstract Background Intravenous administration of fluids is an essential part of critical care. While some fluid administration is likely beneficial, there is increasing observational evidence that the development of fluid overload is associated with increased mortality. There are no randomised trials to confirm this association in patients with acute kidney injury. We aim to perform a pilot trial to test the feasibility of forced fluid removal compared to standard care in patients with acute kidney injury and severe fluid overload, the FFAKI trial. Methods Then FFAKI trial is a pilot, multicentre, randomised clinical trial recruiting adult intensive care patients with acute kidney injury and fluid overload, defined as more than 10% of ideal bodyweight. Patients are randomised with concealed allocation to either standard care or forced fluid removal with a therapeutic target of negative net fluid balance ≥1 mL/kg/h. The safety of fluid removal is continually evaluated according to predefined criteria of hypoperfusion: lactate ≥4 mmol/L, mean arterial pressure

Abstract Objectives To investigate the effect of continuous infusion of the potential endothelial cytoprotective agent prostacyclin (Iloprost) 1 ng/kg/min vs. placebo for 72 hours on pulmonary endotheliopathy in mechanically ventilated COVID-19 patients. Trial design A multicenter, randomized (1:1, active: placebo), blinded, parallel group exploratory trial Participants Inclusion criteria are: Adult patients (>18 years); Confirmed COVID-19 infection; Need for mechanical interventions; Endothelial biomarker soluble thrombomodulin >4ng/ml. Exclusion criteria: Withdrawal from active therapy; Pregnancy (non-pregnancy confirmed by patient being postmenopausal (age 60 or above) or having a negative urine- or plasma-hCG); Known hypersensitivity to iloprost or to any of the other ingredients; Previously included in this trial or a prostacyclin trial within 30 days; Consent cannot be obtained; Life-threatening bleeding defined by the treating physician; Known severe heart failure (NYHA class IV); Suspected acute coronary syndrome The study is conducted at five intensive care units in the Capital Region of Denmark at Rigshospitalet, Herlev Hospital, Hvidovre Hospital, Bispebjerg Hospital, Nordsjællands Hospital. Intervention and comparator The patients are randomized to 72-hours continuous infusion of either prostacyclin (Iloprost/Ilomedin) at a dose of 1 ng/kg/min or Placebo (normal saline). Main outcomes Primary endpoint: Days alive without mechanical ventilation in the intensive care units within 28 days Randomisation The randomisation sequence is performed in permuted blocks of variable sizes stratified for trial site using centralised, concealed allocation. The randomisation sequence is generated 1:1 (active/placebo) using the online randomisation software ‘Sealed Envelope’ ( https://www.sealedenvelope.com/ ). Once generated the randomisation sequence is formatted and uploaded into Research Electronic Data Capture system (REDCap) to facilitate centralised, web-based allocation according to local written instruction. Blinding (masking) The following are blinded: all clinicians, patients, investigators, and those assessing the outcomes including the statisticians. Numbers to be randomised (sample size) Forty patients are planned to be randomized to each group, with a total sample size of 80 patients. Trial Status Protocol version 1.4 dated May 25, 2020. Recruitment is ongoing. The recruitment was started June 15, 2020 and the anticipated finish of recruitment is February 28, 2021 with 90 days follow up hereafter. Trial registration Trial registration at clinicaltrialregisters.eu; EudraCT no. 2020-001296-33 on 3 April 2020 and at ClinicalTrials.gov Identifier: NCT04420741 on 9 June 2020 Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1).In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Summary: Background: Intensive-care units (ICUs) treat the most critically ill patients, which is complicated by the heterogeneity of the diseases that they encounter. Severity scores based mainly on acute physiology measures collected at ICU admission are used to predict mortality, but are non-specific, and predictions for individual patients can be inaccurate. We investigated whether inclusion of long-term disease history before ICU admission improves mortality predictions. Methods: Registry data for long-term disease histories for more than 230 000 Danish ICU patients were used in a neural network to develop an ICU mortality prediction model. Long-term disease histories and acute physiology measures were aggregated to predict mortality risk for patients for whom both registry and ICU electronic patient record data were available. We compared mortality predictions with admission scores on the Simplified Acute Physiology Score (SAPS) II, the Acute Physiologic Assessment and Chronic Health Evaluation (APACHE) II, and the best available multimorbidity score, the Multimorbidity Index. An external validation set from an additional hospital was acquired after model construction to confirm the validity of our model. During initial model development data were split into a training set (85%) and an independent test set (15%), and a five-fold cross-validation was done during training to avoid overfitting. Neural networks were trained for datasets with disease history of 1 month, 3 months, 6 months, 1 year, 2·5 years, 5 years, 7·5 years, 10 years, and 23 years before ICU admission. Findings: Mortality predictions with a model based solely on disease history outperformed the Multimorbidity Index (Matthews correlation coefficient 0·265 vs 0·065), and performed similarly to SAPS II and APACHE II (Matthews correlation coefficient with disease history, age, and sex 0·326 vs 0·347 and 0·300 for SAPS II and APACHE II, respectively). Diagnoses up to 10 years before ICU admission affected current mortality prediction. Aggregation of previous disease history and acute physiology measures in a neural network yielded the most precise predictions of in-hospital mortality (Matthews correlation coefficient 0·391 for in-hospital mortality compared with 0·347 with SAPS II and 0·300 with APACHE II). These results for the aggregated model were validated in an external independent dataset of 1528 patients (Matthews correlation coefficient for prediction of in-hospital mortality 0·341). Interpretation: Longitudinal disease-spectrum-wide data available before ICU admission are useful for mortality prediction. Disease history can be used to differentiate mortality risk between patients with similar vital signs with more precision than SAPS II and APACHE II scores. Machine learning models can be deconvoluted to generate novel understandings of how ICU patient features from long-term and short-term events interact with each other. Explainable machine learning models are key in clinical settings, and our results emphasise how to progress towards the transformation of advanced models into actionable, transparent, and trustworthy clinical tools. Funding: Novo Nordisk Foundation and Innovation Fund Denmark.

PURPOSE:Fluid resuscitation is a key intervention in patients with sepsis and circulatory impairment. The recommendations for continued fluid therapy in sepsis are vague, which may result in differences in clinical practice. We aimed to evaluate associations between hospital and patient characteristics and fluid resuscitation volumes in ICU patients with severe sepsis. METHODS:We explored the 6S trial database of ICU patients with severe sepsis needing fluid resuscitation randomised to hydroxyethyl starch 130/0.42 vs. Ringer's acetate. Our primary outcome measure was fluid resuscitation volume and secondary outcome total fluid input administered from 24 hours before randomisation until the end of day 3 post-randomisation. We performed multivariate analyses with hospital and patient baseline characteristics as covariates to assess associations with fluid volumes given. RESULTS:We included 654 patients who were in the ICU for 3 days and had fluid volumes available. Individual trial sites administered significantly different volumes of fluid resuscitation and total fluid input after adjusting for baseline variables (P

Severity scores including the Simplified Acute Physiology Score (SAPS) II and the Sequential Organ Failure Assessment (SOFA) score are used in intensive care units (ICUs) to assess disease severity, predict mortality and in research. We aimed to assess the predictive performance of SAPS II and the initial SOFA score for in-hospital and 90-day mortality in a contemporary international cohort.This was a post-hoc study of the Stress Ulcer Prophylaxis in the Intensive Care Unit (SUP-ICU) inception cohort study, which included acutely ill adults from ICUs across 11 countries (n = 1034). We compared the discrimination of SAPS II and initial SOFA scores, compared the discrimination of SAPS II in our cohort with the original cohort, assessed the calibration of SAPS II customised to our cohort, and compared the discrimination for 90-day mortality vs. in-hospital mortality for both scores. Discrimination was evaluated using areas under the receiver operating characteristics curves (AUROC). Calibration was evaluated using Hosmer-Lemeshow's goodness-of-fit Ĉ-statistic.AUROC for in-hospital mortality was 0.80 (95% confidence interval (CI) 0.77-0.83) for SAPS II and 0.73 (95% CI 0.69-0.76) for initial SOFA score (P

In a recent study we found no difference in the concentrations of luminal lactate in the rectum between nonsurvivors and survivors in early septic shock (