Contemporary strategies to improve clinical trial design for critical care research: insights from the First Critical Care Clinical Trialists Workshop

Intensive care unit acquired weakness and physical rehabilitation in the ICU

Approximately half of critically ill adults experience intensive care unit acquired weakness (ICUAW). Patients who develop ICUAW may have negative outcomes, including longer duration of mechanical ventilation, greater length of stay, and worse mobility, physical functioning, quality of life, and mortality. Early physical rehabilitation interventions have potential for improving ICUAW; however, randomized trials show inconsistent findings on the efficacy of these interventions. This review summarizes the latest evidence on the definition, diagnosis, epidemiology, pathophysiology, risks factors, implications, and management of ICUAW. It specifically highlights research gaps and challenges, with considerations for future research for physical rehabilitation interventions.

Prioritizing attributes of approaches to analyzing patient-centered outcomes that are truncated due to death in critical care clinical trials: a Delphi study

BACKGROUND

A key challenge for many critical care clinical trials is that some patients will die before their outcome is fully measured. This is referred to as "truncation due to death" and must be accounted for in both the treatment effect definition (i.e. the estimand), as well as the statistical analysis approach. It is unknown which analytic approaches to this challenge are most relevant to stakeholders.

METHODS

Using a modified Delphi process, we sought to identify critical attributes of analytic methods used to account for truncation due to death in critical care clinical trials. The Delphi panel included stakeholders with diverse professional or personal experience in critical care-focused clinical trials. The research team generated an initial list of attributes and associated definitions. The attribute list and definitions were refined through two Delphi rounds. Panelists ranked and scored attributes and provided open-ended rationales for responses. A consensus threshold was set as ≥ 70% of respondents rating an attribute as "Critical" (i.e., score ≥ 7 on a 9-point Likert scale) and ≤ 15% of respondents rating the measure as "Not Important" (i.e., a score of ≤ 3).

RESULTS

Thirty-one (91%) of 34 invited individuals participated in one or both rounds. The response rate was 82% in Round 1 and 85% in Round 2. Participants included eight (26%) personal experience experts and 26 (84%) professional experience experts. After two Delphi rounds, four attributes met the criteria for consensus: accuracy (the approach will identify effects if they exist, but will not if they do not), interpretability (the approach enables a straightforward interpretation of the intervention's effect), clinical relevance (the approach can directly inform patient care), and patient-centeredness (the approach is relevant to patients and/or their families). Attributes that did not meet the consensus threshold included sensitivity, comparability, familiarity, mechanistic plausibility, and statistical simplicity.

CONCLUSIONS

We found that methods used to account for truncation due to death in the treatment effect definition and statistical approach in critical care trials should meet at least four defined criteria: accuracy, interpretability, clinical relevance, and patient-centeredness. Future work is needed to derive objective criteria to quantify how well existing estimands and analytic approaches encompass these attributes.

Composite Primary Outcomes Reported in Studies of Critical Care: A Scoping Review

OBJECTIVE

Composite primary outcomes (CPO) (incorporating both mortality and non-mortality outcomes) offer several advantages over mortality as an outcome for critical care research. Our objective was to explore and map the literature to report on CPO evaluated in critical care research.

DATA SOURCES

PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, Scopus, and Cochrane Library from January 2000 to January 2024.

STUDY SELECTION

All studies (both non-randomized controlled trial [RCT] and RCT) conducted in ICUs treating adult patients (18 yr old or older) that described CPOs and their definitions, were included for mapping, reporting, and analyzing CPOs without any restrictions.

DATA EXTRACTION

Independent double-screening of abstracts/full texts and data extraction was performed using a pilot-tested extraction template. The data collected included characteristics of CPO, definitions, trends, and death handling techniques used while reporting the CPO.

DATA SYNTHESIS

Seventeen CPOs were extracted from 71 studies, predominantly reported in the setting of pharmaceutical studies (48/71, 67.6%), used RCT methodology (60/71, 84.5%), and were mostly single-center studies (55/71, 77.5%). Ventilator-free days were the most commonly reported CPO (29/71, 40.8%) with marked variability in the definition used and death handling (0 d in 33 studies and -1 d in 7 studies). The most common statistical paradigm used was frequentist (63/71, 88.7%) and the study follow-up time was 90 days with 28 studies using this timeline (28/71, 39.4%). Narrative synthesis highlighted the variability in defining CPO.

CONCLUSIONS

CPOs are an emerging set of outcomes increasingly reported in critical care research. There was significant heterogeneity in definitions used, follow-up times, and reporting trends.

Bayesian Reanalyses of the Trials TOMAHAWK and COACT

BACKGROUND

The timing of coronary angiography in patients with successfully resuscitated out-of-hospital cardiac arrest and missing ST-segment elevations on the electrocardiogram has been investigated in 2 large randomized controlled trials, TOMAHAWK (Angiography After Out-of-Hospital Cardiac Arrest Without ST-Segment Elevation) and COACT (Coronary Angiography After Cardiac Arrest Trial). Both trials found neutral results for immediate vs delayed/selective coronary angiography on short-term all-cause mortality. The TOMAHAWK trial showed a tendency towards harm with immediate coronary angiography, though not statistically significant with traditional frequentist methods. Probabilistic analyses of both trials may enable greater clinical understanding of the trial findings.

OBJECTIVES

The purpose of this study was to perform reanalyses of both trials within a Bayesian framework.

METHODS

Post hoc analyses of both multicenter randomized controlled trials were performed in both cohorts separately and combined. The primary endpoint, 30-day all-cause mortality, was analyzed using Bayesian logistic regression. A spectrum of priors included "flat," "neutral," "optimistic," and "pessimistic" priors based on assumptions made when designing both trials.

RESULTS

In the TOMAHAWK trial, immediate coronary angiography showed a very high posterior probability of increased mortality between 90% and 97% across all priors. The ORs across all priors were directed towards harm. Similarly, COACT showed odds ratios ranging from 0.98 to 1.11 for the 30-day mortality endpoint. When combining both trials, immediate coronary angiography showed a high probability of increased mortality between 83% and 95%, again with ORs across all priors indicating a direction towards harm.

CONCLUSIONS

Bayesian reanalyses showed a very high probability of increased 30-day mortality risk with immediate compared with delayed/selective coronary angiography in the TOMAHAWK trial and combined trial cohort. These findings may shift the current understanding of both trials from a "neutral" towards a likely "harmful" effect of immediate coronary angiography after successfully resuscitated out-of-hospital cardiac arrest without ST-segment elevations. Therefore, adoption of a delayed strategy of coronary angiography might be preferred in clinical practice until the results of the DISCO (Direct or Subacute Coronary Angiography in Out-of-Hospital Cardiac Arrest) trial become available.

Enhancing sepsis biomarker development: key considerations from public and private perspectives

Implementation of biomarkers in sepsis and septic shock in emergency situations, remains highly challenging. This viewpoint arose from a public-private 3-day workshop aiming to facilitate the transition of sepsis biomarkers into clinical practice. The authors consist of international academic researchers and clinician-scientists and industry experts who gathered (i) to identify current obstacles impeding biomarker research in sepsis, (ii) to outline the important milestones of the critical path of biomarker development and (iii) to discuss novel avenues in biomarker discovery and implementation. To define more appropriately the potential place of biomarkers in sepsis, a better understanding of sepsis pathophysiology is mandatory, in particular the sepsis patient's trajectory from the early inflammatory onset to the late persisting immunosuppression phase. This time-varying host response urges to develop time-resolved test to characterize persistence of immunological dysfunctions. Furthermore, age-related difference has to be considered between adult and paediatric septic patients. In this context, numerous barriers to biomarker adoption in practice, such as lack of consensus about diagnostic performances, the absence of strict recommendations for sepsis biomarker development, cost and resources implications, methodological validation challenges or limited awareness and education have been identified. Biomarker-guided interventions for sepsis to identify patients that would benefit more from therapy, such as sTREM-1-guided Nangibotide treatment or Adrenomedullin-guided Enibarcimab treatment, appear promising but require further evaluation. Artificial intelligence also has great potential in the sepsis biomarker discovery field through capability to analyse high volume complex data and identify complex multiparametric patient endotypes or trajectories. To conclude, biomarker development in sepsis requires (i) a comprehensive and multidisciplinary approach employing the most advanced analytical tools, (ii) the creation of a platform that collaboratively merges scientific and commercial needs and (iii) the support of an expedited regulatory approval process.

Critical Illness Outside the Intensive Care Unit: Research Challenges in Emergency and Prehospital Settings

Patients with acute critical illness require prompt interventions, yet high-quality evidence supporting many investigations and treatments is lacking. Clinical research in this setting is challenging due to the need for immediate treatment and the inability of patients to provide informed consent. Attempts to obtain consent from surrogate decision-makers can be intrusive and lead to unacceptable delays to treatment. These problems may be overcome by pragmatic approaches to study design and the use of supervised waivers of consent, which is ethical and appropriate in situations where there is high risk of poor outcome and a paucity of proven effective treatment.

Personalizing renal replacement therapy initiation in the intensive care unit: a reinforcement learning-based strategy with external validation on the AKIKI randomized controlled trials

OBJECTIVE

The timely initiation of renal replacement therapy (RRT) for acute kidney injury (AKI) requires sequential decision-making tailored to individuals' evolving characteristics. To learn and validate optimal strategies for RRT initiation, we used reinforcement learning on clinical data from routine care and randomized controlled trials.

MATERIALS AND METHODS

We used the MIMIC-III database for development and AKIKI trials for validation. Participants were adult ICU patients with severe AKI receiving mechanical ventilation or catecholamine infusion. We used a doubly robust estimator to learn when to start RRT after the occurrence of severe AKI for three days in a row. We developed a "crude strategy" maximizing the population-level hospital-free days at day 60 (HFD60) and a "stringent strategy" recommending RRT when there is significant evidence of benefit for an individual. For validation, we evaluated the causal effects of implementing our learned strategies versus following current best practices on HFD60.

RESULTS

We included 3748 patients in the development set and 1068 in the validation set. Through external validation, the crude and stringent strategies yielded an average difference of 13.7 [95% CI -5.3 to 35.7] and 14.9 [95% CI -3.2 to 39.2] HFD60, respectively, compared to current best practices. The stringent strategy led to initiating RRT within 3 days in 14% of patients versus 38% under best practices.

DISCUSSION

Implementing our strategies could improve the average number of days that ICU patients spend alive and outside the hospital while sparing RRT for many.

CONCLUSION

We developed and validated a practical and interpretable dynamic decision support system for RRT initiation in the ICU.

Effects of duration of follow-up and lag in data collection on the performance of adaptive clinical trials

Different combined outcome-data lags (follow-up durations plus data-collection lags) may affect the performance of adaptive clinical trial designs. We assessed the influence of different outcome-data lags (0-105 days) on the performance of various multi-stage, adaptive trial designs (2/4 arms, with/without a common control, fixed/response-adaptive randomisation) with undesirable binary outcomes according to different inclusion rates (3.33/6.67/10 patients/day) under scenarios with no, small, and large differences. Simulations were conducted under a Bayesian framework, with constant stopping thresholds for superiority/inferiority calibrated to keep type-1 error rates at approximately 5%. We assessed multiple performance metrics, including mean sample sizes, event counts/probabilities, probabilities of conclusiveness, root mean squared errors (RMSEs) of the estimated effect in the selected arms, and RMSEs between the analyses at the time of stopping and the final analyses including data from all randomised patients. Performance metrics generally deteriorated when the proportions of randomised patients with available data were smaller due to longer outcome-data lags or faster inclusion, that is, mean sample sizes, event counts/probabilities, and RMSEs were larger, while the probabilities of conclusiveness were lower. Performance metric impairments with outcome-data lags ≤45 days were relatively smaller compared to those occurring with ≥60 days of lag. For most metrics, the effects of different outcome-data lags and lower proportions of randomised patients with available data were larger than those of different design choices, for example, the use of fixed versus response-adaptive randomisation. Increased outcome-data lag substantially affected the performance of adaptive trial designs. Trialists should consider the effects of outcome-data lags when planning adaptive trials.

Association between urea trajectory and protein dose in critically ill adults: a secondary exploratory analysis of the effort protein trial (RE-EFFORT)

BACKGROUND

Delivering higher doses of protein to mechanically ventilated critically ill patients did not improve patient outcomes and may have caused harm. Longitudinal urea measurements could provide additional information about the treatment effect of higher protein doses. We hypothesised that higher urea values over time could explain the potential harmful treatment effects of higher doses of protein.

METHODS

We conducted a reanalysis of a randomised controlled trial of higher protein doses in critical illness (EFFORT Protein). We applied Bayesian joint models to estimate the strength of association of urea with 30-day survival and understand the treatment effect of higher protein doses.

RESULTS

Of the 1301 patients included in EFFORT Protein, 1277 were included in this analysis. There were 344 deaths at 30 days post-randomisation. By day 6, median urea was 2.1 mmol/L higher in the high protein group (95% CI 1.1-3.2), increasing to 3.0 mmol/L (95% CI 1.3-4.7) by day 12. A twofold rise in urea was associated with an increased risk of death at 30 days (hazard ratio 1.34, 95% credible interval 1.21-1.48), following adjustment of baseline characteristics including age, illness severity, renal replacement therapy, and presence of AKI. This association persisted over the duration of 30-day follow-up and in models adjusting for evolution of organ failure over time.

CONCLUSIONS

The increased risk of death in patients randomised to a higher protein dose in the EFFORT Protein trial was estimated to be mediated by increased urea cycle activity, of which serum urea is a biological signature. Serum urea should be taken into consideration when initiating and continuing protein delivery in critically ill patients.

CLINICALTRIALS

gov Identifier: NCT03160547 (2017-05-17).

Real-world causal evidence for planned predictive enrichment in critical care trials: A scoping review

BACKGROUND

Randomised clinical trials in critical care are prone to inconclusiveness due, in part, to undue optimism about effect sizes and suboptimal accounting for heterogeneous treatment effects. Although causal evidence from rich real-world critical care can help overcome these challenges by informing predictive enrichment, no overview exists.

METHODS

We conducted a scoping review, systematically searching 10 general and speciality journals for reports published on or after 1 January 2018, of randomised clinical trials enrolling adult critically ill patients. We collected trial metadata on 22 variables including recruitment period, intervention type and early stopping (including reasons) as well as data on the use of causal evidence from secondary data for planned predictive enrichment.

RESULTS

We screened 9020 records and included 316 unique RCTs with a total of 268,563 randomised participants. One hundred seventy-three (55%) trials tested drug interventions, 101 (32%) management strategies and 42 (13%) devices. The median duration of enrolment was 2.2 (IQR: 1.3-3.4) years, and 83% of trials randomised less than 1000 participants. Thirty-six trials (11%) were restricted to COVID-19 patients. Of the 55 (17%) trials that stopped early, 23 (42%) used predefined rules; futility, slow enrolment and safety concerns were the commonest stopping reasons. None of the included RCTs had used causal evidence from secondary data for planned predictive enrichment.

CONCLUSION

Work is needed to harness the rich multiverse of critical care data and establish its utility in critical care RCTs. Such work will likely need to leverage methodology from interventional and analytical epidemiology as well as data science.

Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity

PURPOSE

Various studies have analyzed sepsis subtypes, yet the reproducibility of such results remains unclear. This study aimed to determine the reproducibility of sepsis subtypes across multiple cohorts.

METHODS

The study examined 63,547 sepsis patients from six distinct cohorts who had similar sepsis-related characteristics (vital signs, lactate, sequential organ failure assessment score, bilirubin, serum, urine output, and Glasgow coma scale). Identical cluster analysis techniques were used, employing 27 clustering schemes, and normalized mutual information (NMI), a metric ranging from 0 to 1 with higher values indicating better concordance, was employed to quantify the clustering solutions' reproducibility. Principal component analysis (PCA) was utilized to obtain the disease axis, and its uniformity across cohorts was evaluated through patterns of feature loading and correlation.

RESULTS

The reproducibility of sepsis clustering subtypes across the various studies was modest (median NMI ranging from 0.08 to 0.54). The top-down transfer learning method (model trained on cohorts with greater severity was transferred to cohorts with lower severity score) had a higher NMI value than the bottom-up approach (median [Q1, Q3]: 0.64 [0.49, 0.78] vs. 0.23 [0.2, 0.31], p < 0.001). The reproducibility was greater when the transfer solution was performed within United States (US) cohorts. The PCA analysis revealed that the correlation pattern between variables was consistent across all cohorts, and the first two disease axes were the "shock axis" and "systemic inflammatory response syndrome (SIRS) axis."

CONCLUSIONS

Cluster analysis of sepsis patients across various cohorts showed modest reproducibility. Sepsis heterogeneity is better characterized through continuous disease axes that coexist to varying degrees within the same individual instead of mutually exclusive subtypes.

Association between days alive without life support/out of hospital and health-related quality of life

BACKGROUND

Trials in critically ill patients increasingly focus on days alive without life support (DAWOLS) or days alive out of hospital (DAOOH) and health-related quality of life (HRQoL). DAWOLS and DAOOH convey more information than mortality and are simpler and faster to collect than HRQoL. However, whether these outcomes are associated with HRQoL is uncertain. We thus aimed to assess the associations between DAWOLS and DAOOH and long-term HRQoL.

METHODS

Secondary analysis of the COVID STEROID 2 trial including adults with COVID-19 and severe hypoxaemia and the Handling Oxygenation Targets in the Intensive Care Unit (HOT-ICU) trial including adult intensive care unit patients with acute hypoxaemic respiratory failure. Associations between DAWOLS and DAOOH at day 28 and 90 and long-term HRQoL (after 6 or 12 months) using the EuroQol 5-dimension 5-level survey (EQ VAS and EQ-5D-5L index values) were assessed using flexible models and evaluated using measures of fit and prediction adequacy in both datasets (comprising internal performance and external validation), non-parametric correlation coefficients and graphical presentations.

RESULTS

We found no strong associations between DAWOLS or DAOOH and HRQoL in survivors at HRQoL-follow-up (615 and 1476 patients, respectively). There was substantial variability in outcomes, and predictions from the best fitted models were poor both internally and externally in the other trial dataset, which also showed inadequate calibration. Moderate associations were found when including non-survivors, although predictions remained uncertain and calibration inadequate.

CONCLUSION

DAWOLS and DAOOH were poorly associated with HRQoL in adult survivors of severe or critical illness included in the COVID STEROID 2 and HOT-ICU trials.

Biomarker-Based Risk Stratification in Pediatric Sepsis From a Low-Middle Income Country

OBJECTIVES

Most biomarker studies of sepsis originate from high-income countries, whereas mortality risk is higher in low- and middle-income countries. The second version of the Pediatric Sepsis Biomarker Risk Model (PERSEVERE-II) has been validated in multiple North American PICUs for prognosis. Given differences in epidemiology, we assessed the performance of PERSEVERE-II in septic children from Pakistan, a low-middle income country. Due to uncertainty regarding how well PERSEVERE-II would perform, we also assessed the utility of other select biomarkers reflecting endotheliopathy, coagulopathy, and lung injury.

DESIGN

Prospective cohort study.

SETTING

PICU in Aga Khan University Hospital in Karachi, Pakistan.

PATIENTS

Children (< 18 yr old) meeting pediatric modifications of adult Sepsis-3 criteria between November 2020 and February 2022 were eligible.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Plasma was collected within 24 hours of admission and biomarkers quantified. The area under the receiver operating characteristic curve for PERSEVERE-II to discriminate 28-day mortality was determined. Additional biomarkers were compared between survivors and nonsurvivors and between subjects with and without acute respiratory distress syndrome. In 86 subjects (20 nonsurvivors, 23%), PERSEVERE-II discriminated mortality (area under the receiver operating characteristic curve, 0.83; 95% CI, 0.72-0.94) and stratified the cohort into low-, medium-, and high-risk of mortality. Biomarkers reflecting endotheliopathy (angiopoietin 2, intracellular adhesion molecule 1) increased across worsening risk strata. Angiopoietin 2, soluble thrombomodulin, and plasminogen activator inhibitor 1 were higher in nonsurvivors, and soluble receptor for advanced glycation end-products and surfactant protein D were higher in children meeting acute respiratory distress syndrome criteria.

CONCLUSIONS

PERSEVERE-II performs well in septic children from Aga Khan University Hospital, representing the first validation of PERSEVERE-II in a low-middle income country. Patients possessed a biomarker profile comparable to that of sepsis from high-income countries, suggesting that biomarker-based enrichment strategies may be effective in this setting.

Trend in Clinical Trial Participation During COVID-19: A Secondary Analysis of the I-SPY COVID Clinical Trial

To analyze the temporal trend in enrollment rates in a COVID-19 platform trial during the first three waves of the pandemic in the United States.

DESIGN

Secondary analysis of data from the I-SPY COVID randomized controlled trial (RCT).

SETTING

Thirty-one hospitals throughout the United States.

PATIENTS

Patients who were approached, either directly or via a legally authorized representative, for consent and enrollment into the I-SPY COVID RCT.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Among 1,338 patients approached for the I-SPY COVID trial from July 30, 2020, to February 17, 2022, the number of patients who enrolled (n = 1,063) versus declined participation (n = 275) was used to calculate monthly enrollment rates. Overall, demographic and baseline clinical characteristics were similar between those who enrolled versus declined. Enrollment rates fluctuated over the course of the COVID-19 pandemic, but there were no significant trends over time (Mann-Kendall test, p = 0.21). Enrollment rates were also comparable between vaccinated and unvaccinated patients. In multivariable logistic regression analysis, age, sex, region of residence, COVID-19 severity of illness, and vaccination status were not significantly associated with the decision to decline consent.

CONCLUSIONS

In this secondary analysis of the I-SPY COVID clinical trial, there was no significant association between the enrollment rate and time period or vaccination status among all eligible patients approached for clinical trial participation. Additional studies are needed to better understand whether the COVID-19 pandemic has altered clinical trial participation and to develop strategies for encouraging participation in future COVID-19 and critical care clinical trials.

Mortality As a Measure of Treatment Effect in Clinical Trials Recruiting Critically Ill Patients

OBJECTIVES

All-cause mortality is a common measure of treatment effect in ICU-based randomized clinical trials (RCTs). We sought to understand the performance characteristics of a mortality endpoint by evaluating its temporal course, responsiveness to differential treatment effects, and impact when used as an outcome measure in trials of acute illness.

DATA SOURCES

We searched OVID Medline for RCTs published from 1990 to 2018.

STUDY SELECTION

We reviewed RCTs that had randomized greater than or equal to 100 patients, were published in one of five high-impact general medical or eight critical care journals, and reported mortality at two or more distinct time points. We excluded trials recruiting pediatric or neonatal patients and cluster RCTs.

DATA EXTRACTION

Mortality by randomization group was recorded from the article or estimated from survival curves. Trial impact was assessed by inclusion of results in clinical practice guidelines.

DATA SYNTHESIS

From 2,592 potentially eligible trials, we included 343 RCTs (228,784 adult patients). While one third of all deaths by 180 days had occurred by day 7, the risk difference between study arms continued to increase until day 60 (p = 0.01) and possibly day 90 (p = 0.07) and remained stable thereafter. The number of deaths at ICU discharge approximated those at 28-30 days (95% [interquartile range [IQR], 86-106%]), and deaths at hospital discharge approximated those at 60 days (99% [IQR, 94-104%]). Only 13 of 43 interventions (30.2%) showing a mortality benefit have been adopted into widespread clinical practice.

CONCLUSIONS

Our findings provide a conceptual framework for choosing a time horizon and interpreting mortality outcome in trials of acute illness. Differential mortality effects persist for 60 to 90 days following recruitment. Location-based measures approximate time-based measures for trials conducted outside the United States. The documentation of a mortality reduction has had a modest impact on practice.

Effect of non-invasive ventilation after extubation in critically ill patients with obesity in France: a multicentre, unblinded, pragmatic randomised clinical trial

BACKGROUND

Non-invasive ventilation (NIV) and oxygen therapy (high-flow nasal oxygen [HFNO] or standard oxygen) following extubation have never been compared in critically ill patients with obesity. We aimed to compare NIV (alternating with HFNO or standard oxygen) and oxygen therapy (HFNO or standard oxygen) following extubation of critically ill patients with obesity.

METHODS

In this multicentre, parallel group, pragmatic randomised controlled trial, conducted in 39 intensive care units in France, critically ill patients with obesity undergoing extubation were randomly assigned (1:1) to either the NIV group or the oxygen therapy group. Two randomisations were performed: first, randomisation to either NIV or oxygen therapy, and second, randomisation to either HFNO or standard oxygen (also 1:1), which was nested within the first randomisation. Blinding of the randomisation was not possible, but the statistician was masked to group assignment. The primary outcome was treatment failure within 3 days after extubation, a composite of reintubation for mechanical ventilation, switch to the other study treatment, or premature discontinuation of study treatment. The primary outcome was analysed by intention to treat. Effect of medical and surgical status was assessed. The reintubation within 3 days was analysed by intention to treat and after a post-hoc crossover analysis. This study is registered with ClinicalTrials.gov, number NCT04014920.

FINDINGS

From Oct 2, 2019, to July 17, 2021, of the 1650 screened patients, 981 were enrolled. Treatment failure occurred in 66 (13·5%) of 490 patients in the NIV group and in 130 (26·5%) of 491 patients in the oxygen-therapy group (relative risk 0·43; 95% CI 0·31-0·60, p<0·0001). Medical or surgical status did not modify the effect of NIV group on the treatment-failure rate. Reintubation within 3 days after extubation was similar in the non-invasive ventilation group and in the oxygen therapy group in the intention-to-treat analysis (48 (10%) of 490 patients and 59 (12%) of 491 patients, p=0·26) and lower in the NIV group than in the oxygen-therapy group in the post-hoc cross-over (51 (9%) of 560 patients and 56 (13%) of 421 patients, p=0·037) analysis. No severe adverse events were reported.

INTERPRETATION

Among critically ill adults with obesity undergoing extubation, the use of NIV was effective to reduce treatment-failure within 3 days. Our results are relevant to clinical practice, supporting the use of NIV after extubation of critically ill patients with obesity. However, most of the difference in the primary outcome was due to patients in the oxygen therapy group switching to NIV, and more evidence is needed to conclude that an NIV strategy leads to improved patient-centred outcomes.

FUNDING

French Ministry of Health.

A Bayesian Interpretation of a Pediatric Cardiac Arrest Trial (THAPCA-OH)

BACKGROUND: Pediatric out-of-hospital cardiac arrest results in high morbidity and mortality. Currently, there are no recommended therapies beyond supportive care. The THAPCA-OH (Therapeutic Hypothermia after Pediatric Cardiac Arrest Out-of-Hospital) trial compared hypothermia (33.0°C) with normothermia (36.8°C) in 295 children. Good neurobehavioral outcome and survival at 1 year were higher in the hypothermia group (20 vs. 12% and 38 vs. 29%, respectively). These differences did not meet the planned statistical threshold of P75% for all informative prior integrations with the THAPCA-OH results, except those with the most pessimistic priors. CONCLUSIONS: There is a high probability that hypothermia provides a modest benefit in neurobehavioral outcome and survival at 1 year. (ClinicalTrials.gov number, NCT00878644.)

Pragmatic platform trials to improve the outcome of patients with acute kidney injury

PURPOSE OF REVIEW

There is an important need for improved diagnostic strategies and treatment among patients with acute kidney injury (AKI). Classical randomized clinical trials have generated relevant results in AKI but are associated with shortcomings, such as high costs and sometimes lack of generalizability. In this minireview, we discuss the value and limits of pragmatic trials and platform trials for AKI research.

RECENT FINDINGS

The implementation of pragmatic and platform trials in critical care settings has generated relevant clinical evidence impacting clinical practice. Pragmatic and platform designs have recently been applied to patients at risk of AKI and represent a crucial opportunity to advance our understanding of optimized treatment and strategies in patients at risk of AKI or presenting with AKI. Trials embedded in electronic health records can facilitate patient enrollment and data collection. Platform trials have allowed for a more efficient study design. Although both pragmatic and platform trials have several advantages, they also come with the challenges and shortcomings discussed in this review.

SUMMARY

Pragmatic and platform trials can provide clinical answers in 'real-life' settings, facilitate a significant sample size enrollment at a limited cost, and provide results that can have a faster implementation in clinical practice.

Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead

Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.

Patient-Important Outcomes Other Than Mortality in Contemporary ICU Trials: A Scoping Review

OBJECTIVES

Randomized clinical trials (RCTs) conducted in adult ICU patients increasingly include patient-important outcomes other than mortality. This comes with challenges regarding outcome choices/definitions, handling of deceased patients and missing data in analyses, and choices of effect measures and statistical methods due to complex distributions. This scoping review aimed to characterize how these challenges are handled in relevant contemporary RCTs.

DATA SOURCES

We systematically searched 10 selected journals for RCTs conducted primarily in adult ICU patients published between 1 January 2018 and 5 May 2022 reporting at least one patient-important outcome other than mortality, including "days alive without"…-type outcomes, functional/cognitive/neurologic outcomes, health-related quality of life (HRQoL) outcomes, and ordinal/other outcomes.

STUDY SELECTION

Abstracts and full-texts were assessed independently and in duplicate by two reviewers.

DATA EXTRACTION

Data were extracted independently and in duplicate by two reviewers using predefined and pilot-tested extraction forms and subsequently categorized to facilitate analysis.

DATA SYNTHESIS

We included 687 outcomes from 167 RCTs, with 32% of RCTs using a patient-important outcome other than mortality as a (co-)primary outcome, most frequently "days alive without"…-type outcomes. Many different functional/cognitive/neurologic (103) and HRQoL (29) outcomes were reported. Handling of deceased patients varied, with analyses frequently restricted to survivors only for functional/cognitive/neurologic (62%) and HRQoL (89%) outcomes. Follow-up was generally longer and missing data proportions higher for functional/cognitive/neurologic and HRQoL outcomes. Most outcomes were analyzed using nonparametric tests (31%), linear regression/ t tests (27%), chi-square-like tests (12%), and proportional odds logistic regression (9%), often without presentation of actual treatment effects estimates (38%).

CONCLUSIONS

In this sample of RCTs, substantial variation in practice and suboptimal methodological choices were observed. This calls for increased focus on standardizing outcome choices and definitions, adequate handling of missing data and deceased patients in analyses, and use of statistical methods quantifying effect sizes.

Oxygen-Free Days as an Outcome Measure in Clinical Trials of Therapies for COVID-19 and Other Causes of New-Onset Hypoxemia

Mortality historically has been the primary outcome of choice for acute and critical care clinical trials. However, undue reliance on mortality can limit the scope of trials that can be performed. Large sample sizes are usually needed for trials powered for a mortality outcome, and focusing solely on mortality fails to recognize the importance that reducing morbidity can have on patients' lives. The COVID-19 pandemic has highlighted the need for rapid, efficient trials to rigorously evaluate new therapies for hospitalized patients with acute lung injury. Oxygen-free days (OFDs) is a novel outcome for clinical trials that is a composite of mortality and duration of new supplemental oxygen use. It is designed to characterize recovery from acute lung injury in populations with a high prevalence of new hypoxemia and supplemental oxygen use. In these populations, OFDs captures two patient-centered consequences of acute lung injury: mortality and hypoxemic lung dysfunction. Power to detect differences in OFDs typically is greater than that for other clinical trial outcomes, such as mortality and ventilator-free days. OFDs is the primary outcome for the Fourth Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV-4) Host Tissue platform, which evaluates novel therapies targeting the host response to COVID-19 among adults hospitalized with COVID-19 and new hypoxemia. This article outlines the rationale for use of OFDs as an outcome for clinical trials, proposes a standardized method for defining and analyzing OFDs, and provides a framework for sample size calculations using the OFD outcome.

Opportunities for improved clinical trial designs in acute respiratory distress syndrome

The acute respiratory distress syndrome (ARDS) is a common critical illness syndrome with high morbidity and mortality. There are no proven pharmacological therapies for ARDS. The current definition of ARDS is based on shared clinical characteristics but does not capture the heterogeneity in clinical risk factors, imaging characteristics, physiology, timing of onset and trajectory, and biology of the syndrome. There is increasing interest within the ARDS clinical trialist community to design clinical trials that reduce heterogeneity in the trial population. This effort must be balanced with ongoing work to craft an inclusive, global definition of ARDS, with important implications for trial design. Ultimately, the two aims-to design trials that are applicable to the diverse global ARDS population while also advancing opportunities to identify targetable traits-should coexist. In this Personal View, we recommend two primary strategies to improve future ARDS trials: the development of new methods to target treatable traits in clinical trial populations, and improvements in the representativeness of ARDS trials, with the inclusion of global populations. We emphasise that these two strategies are complementary. We also discuss how a proposed expansion of the definition of ARDS could affect the future of clinical trials.

Anticoagulation in hospitalized patients with COVID-19

Coronavirus disease-19 (COVID-19) includes a thromboinflammatory syndrome that may manifest with microvascular and macrovascular thrombosis. Patients with COVID-19 have a higher incidence of venous thromboembolism than other hospitalized patients. Three randomized control trials suggesting benefit of therapeutic heparin in hospitalized noncritically ill patients with COVID-19 have led to conditional guideline recommendations for this treatment. By contrast, prophylactic-dose heparin is recommended for critically ill patients. Unprecedented collaboration and rapidly funded research have improved care of hospitalized patients with COVID-19.

Systematic Review of the “Pragmatism” of Pragmatic Critical Care Trials

To assess the pragmatism of published critical care randomized controlled trials self-described as pragmatic using a validated tool.

Use of pragmatic and explanatory trial designs in acute care research: lessons from COVID-19

Unique challenges arise when conducting trials to evaluate therapies already in common clinical use, including difficulty enrolling patients owing to widespread open-label use of trial therapies and the need for large sample sizes to detect small but clinically meaningful treatment effects. Despite numerous successes in trials evaluating novel interventions such as vaccines, traditional explanatory trials have struggled to provide definitive answers to time-sensitive questions for acutely ill patients with COVID-19. Pragmatic trials, which can increase efficiency by allowing some or all trial procedures to be embedded into clinical care, are increasingly proposed as a means to evaluate therapies that are in common clinical use. In this Personal View, we use two concurrently conducted COVID-19 trials of hydroxychloroquine (the US ORCHID trial and the UK RECOVERY trial) to contrast the effects of explanatory and pragmatic trial designs on trial conduct, trial results, and the care of patients managed outside of clinical trials. In view of the potential advantages and disadvantages of explanatory and pragmatic trial designs, we make recommendations for their optimal use in the evaluation of therapies in the acute care setting.

Randomised clinical trials in critical care: past, present and future

Randomised clinical trials (RCTs) are the gold standard for providing unbiased evidence of intervention effects. Here, we provide an overview of the history of RCTs and discuss the major challenges and limitations of current critical care RCTs, including overly optimistic effect sizes; unnuanced conclusions based on dichotomization of results; limited focus on patient-centred outcomes other than mortality; lack of flexibility and ability to adapt, increasing the risk of inconclusive results and limiting knowledge gains before trial completion; and inefficiency due to lack of re-use of trial infrastructure. We discuss recent developments in critical care RCTs and novel methods that may provide solutions to some of these challenges, including a research programme approach (consecutive, complementary studies of multiple types rather than individual, independent studies), and novel design and analysis methods. These include standardization of trial protocols; alternative outcome choices and use of core outcome sets; increased acceptance of uncertainty, probabilistic interpretations and use of Bayesian statistics; novel approaches to assessing heterogeneity of treatment effects; adaptation and platform trials; and increased integration between clinical trials and clinical practice. We outline the advantages and discuss the potential methodological and practical disadvantages with these approaches. With this review, we aim to inform clinicians and researchers about conventional and novel RCTs, including the rationale for choosing one or the other methodological approach based on a thorough discussion of pros and cons. Importantly, the most central feature remains the randomisation, which provides unparalleled restriction of confounding compared to non-randomised designs by reducing confounding to chance.

Health-related quality of life and days alive without life support or out of hospital: Protocol

BACKGROUND

Mortality is often the primary outcome in randomised clinical trials (RCTs) conducted in critically ill patients. Due to increased awareness on survivors after critical illness and outcomes other than mortality, health-related quality of life (HRQoL) and days alive without life support (DAWOLS) or days alive and out of hospital (DAAOOH) are increasingly being used. DAWOLS and DAAOOH convey more information than mortality, are easier to collect than HRQoL, and are usually assessed at earlier time points, which may be preferable in some situations. However, the associations between DAWOLS-DAAOOH and HRQoL are uncertain.

METHODS

We will assess associations between DAWOLS-DAAOOH at day 28 and 90 (independent variables/predictors) and HRQoL assessed using the EuroQol EQ-5D-5L questionnaire (EQ-VAS and EQ-5D-5L index values) at 6 or 12 months (dependent variables) in two RCTs: the COVID STEROID 2 RCT conducted in adult patients with COVID-19 and severe hypoxaemia and the Handling Oxygenation Targets in the Intensive Care Unit (HOT-ICU) RCT conducted in adult intensive care patients with acute hypoxaemic respiratory failure. We will describe associations using best-fitting fractional polynomial transformations separately in each dataset, with the resulting models presented and assessed in both datasets graphically and using measures of fit and prediction adequacy (i.e., internal performance and external validation). We will use multiple imputation if missingness exceeds 5%.

DISCUSSION

The outlined study will provide important knowledge on the associations between DAWOLS-DAAOOH and HRQoL in adult critically ill patients, which may help researchers and clinical trialists prioritise and select outcomes in future RCTs conducted in this population.

Effect of dexamethasone in patients with ARDS and COVID-19 (REMED trial)-study protocol for a prospective, multi-centre, open-label, parallel-group, randomized controlled trial

Background

Since December 2019, SARS-CoV-2 virus has infected millions of people worldwide. In patients with COVID-19 pneumonia in need of oxygen therapy or mechanical ventilation, dexamethasone 6 mg per day is currently recommended. However, the dose of 6 mg of dexamethasone is currently being reappraised and may miss important therapeutic potential or may prevent potential deleterious effects of higher doses of corticosteroids.

Methods

REMED is a prospective, open-label, randomised controlled trial testing the superiority of dexamethasone 20 mg (dexamethasone 20 mg on days 1–5, followed by dexamethasone 10 mg on days 6–10) vs 6 mg administered once daily intravenously for 10 days in adult patients with moderate or severe ARDS due to confirmed COVID-19. Three hundred participants will be enrolled and followed up for 360 days after randomization. Patients will be randomised in a 1:1 ratio into one of the two treatment arms. The following stratification factors will be applied: age, Charlson Comorbidity Index, CRP levels and trial centre. The primary endpoint is the number of ventilator-free days (VFDs) at 28 days after randomisation. The secondary endpoints are mortality from any cause at 60 days after randomisation; dynamics of the inflammatory marker, change in WHO Clinical Progression Scale at day 14; and adverse events related to corticosteroids and independence at 90 days after randomisation assessed by the Barthel Index. The long-term outcomes of this study are to assess long-term consequences on mortality and quality of life at 180 and 360 days. The study will be conducted in the intensive care units (ICUs) of ten university hospitals in the Czech Republic.

Discussion

We aim to compare two different doses of dexamethasone in patients with moderate to severe ARDS undergoing mechanical ventilation regarding efficacy and safety.

Trial registration

EudraCT No. 2020-005887-70. ClinicalTrials.gov NCT04663555. Registered on December 11, 2020

Efficacy and Safety of Intravenous Iron Therapy for Treating Anaemia in Critically ill Adults: A Rapid Systematic Review With Meta-Analysis

Our objective was to systematically evaluate the efficacy and safety of intravenous (IV) iron therapy for treating anaemia in critically ill adults (>16 years) admitted to intensive care or high dependency units. We excluded quasi-RCTs and other not truly randomised trials. We searched 7 electronic databases (including CENTRAL, MEDLINE, and Embase) using a pre-defined search strategy from inception to June 14, 2021. One reviewer screened, extracted, and analysed data, with verification by a second reviewer of all decisions. We used Cochrane risk of bias (ROB) 1 and GRADE to assess the certainty of the evidence. We reported 3 comparisons across 1198 patients, in 8 RCTs: (1) IV iron vs control (7 RCTs, 748 participants); our primary outcome (hemoglobin (Hb) concentration at 10 to 30 days) was reported in 7 of the 8 included trials. There was evidence of an effect (very-low certainty) in favour of IV iron over control in the main comparison only (6 RCTs, n = 528, mean difference (MD) 0.52g/dL [95%CI 0.23, 0.81], P = .0005). For the remaining outcomes there was no evidence of an effect in either direction (low certainty of evidence for Hb concentration at <10 days; very-low certainty of evidence for hospital duration, ICU duration, hospital readmission, infection, mortality; HRQoL outcomes were not GRADED). (2) IV iron + subcutaneous erythropoietin (EPO) vs control (2 RCTs, 104 participants); reported outcomes showed no evidence of effect in either direction, based on very-low certainty evidence (Hb concentration at 10-30 days, and <10 days, infection, mortality). (3) Hepcidin-guided treatment with IV iron or iron+ EPO vs standard care (1 RCT, 399 participants) reported evidence of an effect in favour of the intervention for 90-day mortality (low certainty of evidence), but no other group differences for the reported outcomes (low certainty evidence for Hb concentration at 10-30 days, hospital duration; HRQoL was not GRADED). The evidence across all comparisons was downgraded for high and unclear ROB for lack of blinding, incomplete outcome data, baseline imbalance, and imprecision around the estimate (wide CIs and small sample size). In conclusion, the current evidence continues to support further investigation into the role for iron therapy in increasing Hb in critically ill patients. Recent, small, trials have begun to focus on patient-centred outcomes but a large, well conducted, and adequately powered trial is needed to inform clinical practice.

A multivariate model for successful publication of intensive care medicine randomized controlled trials in the highest impact factor journals: the SCOTI score

Background

Critical care randomized controlled trials (RCTs) are often published in high-impact journals, whether general journals [the New England Journal of Medicine (NEJM), The Lancet, the Journal of the American Medical Association (JAMA)] or critical care journals [Intensive Care Medicine (ICM), the American Journal of Respiratory and Critical Care Medicine (AJRCCM), Critical Care Medicine (CCM)]. As rejection occurs in up to 97% of cases, it might be appropriate to assess pre-submission probability of being published. The objective of this study was to develop and internally validate a simplified score predicting whether an ongoing trial stands a chance of being published in high-impact general journals.

Methods

A cohort of critical care RCTs published between 1999 and 2018 in the three highest impact medical journals (NEJM, The Lancet, JAMA) or the three highest impact critical care journals (ICM, AJRCCM, CCM) was split into two samples (derivation cohort, validation cohort) to develop and internally validate the simplified score. Primary outcome was journal of publication assessed as high-impact general journal (NEJM, The Lancet, JAMA) or critical care journal (ICM, AJRCCM, CCM).

Results

A total of 968 critical care RCTs were included in the predictive cohort and split into a derivation cohort (n = 510) and a validation cohort (n = 458). In the derivation cohort, the sample size (P value < 0.001), the number of centers involved (P value = 0.01), mortality as primary outcome (P value = 0.002) or a composite item including mortality as primary outcome (P value = 0.004), and topic [ventilation (P value < 0.001) or miscellaneous (P value < 0.001)] were independent factors predictive of publication in high-impact general journals, compared to high-impact critical care journals. The SCOTI score (Sample size, Centers, Outcome, Topic, and International score) was developed with an area under the ROC curve of 0.84 (95% Confidence Interval, 0.80–0.88) in validation by split sample.

Conclusions

The SCOTI score, developed and validated by split sample, accurately predicts the chances of a critical care RCT being published in high-impact general journals, compared to high-impact critical care journals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00954-x.

A systematic review and meta-analysis of enrollment into ARDS and sepsis trials published between 2009 and 2019 in major journals

BACKGROUND

Enrollment problems are common among randomized controlled trials conducted in the ICU. However, little is known about actual trial enrollment rates and influential factors. We set out to determine the overall enrollment rate in recent randomized controlled trials (RCTs) of patients with acute respiratory distress syndrome (ARDS), acute lung injury (ALI), or sepsis, and which factors influenced enrollment rate.

METHODS

We conducted a systematic review by searching Pubmed using predefined terms for ARDS/ALI and sepsis to identify individually RCTs published among the seven highest impact general medicine and seven highest impact critical care journals between 2009 and 2019. Cluster randomized trials were excluded. Data were extracted by two independent reviewers using an electronic database management system. We conducted a random-effects meta-analysis of the eligible trials for the primary outcome of enrollment rate by time and site.

RESULTS

Out of 457 articles identified, 94 trials met inclusion criteria. Trials most commonly evaluated pharmaceutical interventions (53%), were non-industry funded (78%), and required prospective informed consent (81%). The overall mean enrollment rate was 0.83 (95% confidence interval: 0.57-1.21) participants per month per site. Enrollment in ARDS/ALI and sepsis trials were 0.48 (95% CI 0.32-0.70) and 0.98 (95% CI 0.62-1.56) respectively. The enrollment rate was significantly higher for single-center trials (4.86; 95% CI 2.49-9.51) than multicenter trials (0.52; 95% CI 0.41-0.66). Of the 36 trials that enrolled < 95% of the target sample size, 8 (22%) reported slow enrollment as the reason.

CONCLUSIONS

In this systematic review and meta-analysis, recent ARDS/ALI and sepsis clinical trials had an overall enrollment rate of less than 1 participant per site per month. Novel approaches to improve critical care trial enrollment efficiency are needed to facilitate the translation of best evidence into practice.

Safety and tolerability of non-neutralizing adrenomedullin antibody adrecizumab (HAM8101) in septic shock patients: the AdrenOSS-2 phase 2a biomarker-guided trial

Purpose

Investigate safety and tolerability of adrecizumab, a humanized monoclonal adrenomedullin antibody, in septic shock patients with high adrenomedullin.

Methods

Phase-2a, double-blind, randomized, placebo-controlled biomarker-guided trial with a single infusion of adrecizumab (2 or 4 mg/kg b.w.) compared to placebo. Patients with adrenomedullin above 70 pg/mL, < 12 h of vasopressor start for septic shock were eligible. Randomization was 1:1:2. Primary safety (90-day mortality, treatment emergent adverse events (TEAE)) and tolerability (drug interruption, hemodynamics) endpoints were recorded. Efficacy endpoints included the Sepsis Support Index (SSI, reflecting ventilator- and shock-free days alive), change in Sequential-related Organ Failure Assessment (SOFA) and 28-day mortality.

Results

301 patients were enrolled (median time of 8.5 h after vasopressor start). Adrecizumab was well tolerated (one interruption, no hemodynamic alteration) with no differences in frequency and severity in TEAEs between treatment arms (TEAE of grade 3 or higher: 70.5% in the adrecizumab group and 71.1% in the placebo group) nor in 90-day mortality. Difference in change in SSI between adrecizumab and placebo was 0.72 (CI −1.93–0.49, p = 0.24). Among various secondary endpoints, delta SOFA score (defined as maximum versus minimum SOFA) was more pronounced in the adrecizumab combined group compared to placebo [difference at 0.76 (95% CI 0.18–1.35); p = 0.007]. 28-day mortality in the adrecizumab group was 23.9% and 27.7% in placebo with a hazard ratio of 0.84 (95% confidence interval 0.53–1.31, log-rank p = 0.44).

Conclusions

Overall, we successfully completed a randomized trial evaluating selecting patients for enrolment who had a disease-related biomarker. There were no overt signals of harm with using two doses of the adrenomedullin antibody adrecizumab; however, further randomized controlled trials are required to confirm efficacy and safety of this agent in septic shock patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06537-5.

Patient-important outcomes other than mortality in recent ICU trials: Protocol for a scoping review

BACKGROUND

Randomised clinical trials (RCTs) conducted in intensive care units (ICUs) frequently focus on all-cause mortality, but other patient-important outcomes are increasingly used and recommended. Their use, however, is not straightforward: choices and definitions, operationalisation of death, handling of missing data, choice of effect measures, and statistical analyses for these outcomes vary greatly.

METHODS

We will conduct a scoping review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. We will search 10 selected general and speciality journals for RCTs conducted in adult ICU patients from 2018 and onwards reporting at least 1 patient-important outcome other than mortality (including days alive without life support/days alive and out of hospital-type outcomes, health-related quality of life, functional/cognitive/neurological outcomes, and other general patient-important outcomes). We will summarise data on outcome measures and definitions, assessment time points, proportions and handling of death, proportions and handling of missing data, and effect measures and statistical methods used for analysis.

DISCUSSION

The outlined scoping review will provide an overview of choices, definitions and handling of patient-important outcomes other than mortality in contemporary RCTs conducted in adult ICU patients. This may guide discussions with patients and relatives, the design of future RCTs, and research on optimal outcome choices and handling.

Optimising clinical trials in acute myocardial infarction complicated by cardiogenic shock: a statement from the 2020 Critical Care Clinical Trialists Workshop

Acute myocardial infarction complicated by cardiogenic shock (AMICS) is a critical syndrome with a high risk of morbidity and mortality. Current management consists of coronary revascularisation, vasoactive drugs, and circulatory and ventilatory support, which are tailored to patients mainly on the basis of clinicians' experience rather than evidence-based recommendations. For many therapeutic interventions in AMICS, randomised clinical trials have not shown a meaningful survival benefit, and a disproportionately high rate of neutral and negative results has been reported. In this context, an accurate definition of the AMICS syndrome for appropriate patient selection and optimisation of study design are warranted to achieve meaningful results and pave the way for new, evidence-based therapeutic options. In this Position Paper, we provide a statement of priorities and recommendations agreed by a multidisciplinary group of experts at the Critical Care Clinical Trialists Workshop in February, 2020, for the optimisation and harmonisation of clinical trials in AMICS. Implementation of proposed criteria to define the AMICS population-moving beyond a cardio-centric definition to that of a systemic disease-and steps to improve the design of clinical trials could lead to improved outcomes for patients with this life-threatening syndrome.

Protocol for a two-arm pragmatic stepped-wedge hybrid effectiveness-implementation trial evaluating Engagement and Collaborative Management to Proactively Advance Sepsis Survivorship (ENCOMPASS)

BACKGROUND

Sepsis survivors experience high morbidity and mortality, and healthcare systems lack effective strategies to address patient needs after hospital discharge. The Sepsis Transition and Recovery (STAR) program is a navigator-led, telehealth-based multicomponent strategy to provide proactive care coordination and monitoring of high-risk patients using evidence-driven, post-sepsis care tasks. The purpose of this study is to evaluate the effectiveness of STAR to improve outcomes for sepsis patients and to examine contextual factors that influence STAR implementation.

METHODS

This study uses a hybrid type I effectiveness-implementation design to concurrently test clinical effectiveness and gather implementation data. The effectiveness evaluation is a two-arm, pragmatic, stepped-wedge cluster randomized controlled trial at eight hospitals in North Carolina comparing clinical outcomes between sepsis survivors who receive Usual Care versus care delivered through STAR. Each hospital begins in a Usual Care control phase and transitions to STAR in a randomly assigned sequence (one every 4 months). During months that a hospital is allocated to Usual Care, all eligible patients will receive usual care. Once a hospital transitions to STAR, all eligible patients will receive STAR during their hospitalization and extending through 90 days from discharge. STAR includes centrally located nurse navigators using telephonic counseling and electronic health record-based support to facilitate best-practice post-sepsis care strategies including post-discharge review of medications, evaluation for new impairments or symptoms, monitoring existing comorbidities, and palliative care referral when appropriate. Adults admitted with suspected sepsis, defined by clinical criteria for infection and organ failure, are included. Planned enrollment is 4032 patients during a 36-month period. The primary effectiveness outcome is the composite of all-cause hospital readmission or mortality within 90 days of discharge. A mixed-methods implementation evaluation will be conducted before, during, and after STAR implementation.

DISCUSSION

This pragmatic evaluation will test the effectiveness of STAR to reduce combined hospital readmissions and mortality, while identifying key implementation factors. Results will provide practical information to advance understanding of how to integrate post-sepsis management across care settings and facilitate implementation, dissemination, and sustained utilization of best-practice post-sepsis management strategies in other heterogeneous healthcare delivery systems.

TRIAL REGISTRATION

NCT04495946 . Submitted July 7, 2020; Posted August 3, 2020.

Higher vs Lower Doses of Dexamethasone in Patients with COVID-19 and Severe Hypoxia (COVID STEROID 2) trial: Protocol for a secondary Bayesian analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) can lead to severe hypoxic respiratory failure and death. Corticosteroids decrease mortality in severely or critically ill patients with COVID-19. However, the optimal dose remains unresolved. The ongoing randomised COVID STEROID 2 trial investigates the effects of higher vs lower doses of dexamethasone (12 vs 6 mg intravenously daily for up to 10 days) in 1,000 adult patients with COVID-19 and severe hypoxia.

METHODS

This protocol outlines the rationale and statistical methods for a secondary, pre-planned Bayesian analysis of the primary outcome (days alive without life support at day 28) and all secondary outcomes registered up to day 90. We will use hurdle-negative binomial models to estimate the mean number of days alive without life support in each group and present results as mean differences and incidence rate ratios with 95% credibility intervals (CrIs). Additional count outcomes will be analysed similarly and binary outcomes will be analysed using logistic regression models with results presented as probabilities, relative risks and risk differences with 95% CrIs. We will present probabilities of any benefit/harm, clinically important benefit/harm and probabilities of effects smaller than pre-defined clinically minimally important differences for all outcomes analysed. Analyses will be adjusted for stratification variables and conducted using weakly informative priors supplemented by sensitivity analyses using sceptic priors.

DISCUSSION

This secondary, pre-planned Bayesian analysis will supplement the primary, conventional analysis and may help clinicians, researchers and policymakers interpret the results of the COVID STEROID 2 trial while avoiding arbitrarily dichotomised interpretations of the results.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT04509973; EudraCT: 2020-003363-25.

Using Bayesian Methods to Augment the Interpretation of Critical Care Trials. An Overview of Theory and Example Reanalysis of the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial

Most randomized trials are designed and analyzed using frequentist statistical approaches such as null hypothesis testing and P values. Conceptually, P values are cumbersome to understand, as they provide evidence of data incompatibility with a null hypothesis (e.g., no clinical benefit) and not direct evidence of the alternative hypothesis (e.g., clinical benefit). This counterintuitive framework may contribute to the misinterpretation that the absence of evidence is equal to evidence of absence and may cause the discounting of potentially informative data. Bayesian methods provide an alternative, probabilistic interpretation of data. The reanalysis of completed trials using Bayesian methods is becoming increasingly common, particularly for trials with effect estimates that appear clinically significant despite P values above the traditional threshold of 0.05. Statistical inference using Bayesian methods produces a distribution of effect sizes that would be compatible with observed trial data, interpreted in the context of prior assumptions about an intervention (called "priors"). These priors are chosen by investigators to reflect existing beliefs and past empirical evidence regarding the effect of an intervention. By calculating the likelihood of clinical benefit, a Bayesian reanalysis can augment the interpretation of a trial. However, if priors are not defined a priori, there is a legitimate concern that priors could be constructed in a manner that produces biased results. Therefore, some standardization of priors for Bayesian reanalysis of clinical trials may be desirable for the critical care community. In this Critical Care Perspective, we discuss both frequentist and Bayesian approaches to clinical trial analysis, introduce a framework that researchers can use to select priors for a Bayesian reanalysis, and demonstrate how to apply our proposal by conducting a novel Bayesian trial reanalysis.

Designing an ARDS trial for 2020 and beyond: focus on enrichment strategies

With the exception of a few successes in trials of supportive care, the majority of interventional clinical trials for acute respiratory distress syndrome (ARDS) have not led to new therapies. To improve the likelihood of benefit from clinical trial interventions in ARDS, clinical trial design must be improved. To optimize trial design, many factors need to be considered including the type of therapy to be tested, the type of trial (phase 2 or 3), how patients will be selected, primary and secondary end-points, and strategy for conduct of the trial, including potential newer trial designs such as platform or adaptive trials. Of these, optimization of patient selection is central to the likelihood of success and is particularly relevant in ARDS, which is a heterogeneous clinical syndrome, not a homogeneous disease. Recent advances including improved understanding of pathophysiologic mechanisms and better tools for outcome prediction in ARDS should facilitate both predictive and prognostic enrichment. This commentary focuses on new information and novel methods for prognostic and predictive enrichment that may be useful to optimize patient selection and increase the likelihood of positive clinical trials in ARDS.