Glucose evaluation and management in the ICU (GEM-ICU): Protocol for a bi-centre cohort study.

INTRODUCTION: Hyperglycaemia is common in intensive care unit (ICU) patients. Glycaemic monitoring and effective glycaemic control with insulin are crucial in the ICU to improve patient outcomes. However, glycaemic control and insulin use vary between ICU patients and hypo- and hyperglycaemia occurs. Therefore, we aim to provide contemporary data on glycaemic control and management, and associated outcomes, in adult ICU patients. We hypothesise that the occurrence of hypoglycaemia in acutely admitted ICU patients is lower than that of hyperglycaemia. METHODS: We will conduct a bi-centre cohort study of 300 acutely admitted adult ICU patients. Routine data will be collected retrospectively at baseline (ICU admission) and daily during ICU stay up to a maximum of 30 days. The primary outcome will be the number of patients with hypoglycaemia during their ICU stay. Secondary outcomes will be occurrence of severe hypoglycaemia, occurrence of hyperglycaemia, time below blood glucose target range, time above target range, all-cause mortality at Day 30, number of days alive without life support at Day 30 and number of days alive and out of hospital at Day 30. Process outcomes include the number of in-ICU days, glucose measurements (number of measurements and method) and use of insulin (including route of administration and dosage). All statistical analyses will be descriptive. CONCLUSIONS: This cohort study will provide a contemporary overview of glucose evaluation and management practices in adult ICU patients and, thus, highlight potential areas for improvement through future clinical trials in this area.

A systematic review of pharmacogenetic testing to guide antipsychotic treatment.

Pharmacogenomics could optimize antipsychotic treatment by preventing adverse drug reactions, improving treatment efficacy or relieving the cost burden on the healthcare system. Here we conducted a systematic review to investigate whether pharmacogenetic testing in individuals undergoing antipsychotic treatment influences clinical or economic outcomes. On 12 January 2024, we searched MEDLINE, EMBASE, PsycINFO and Cochrane Centrale Register of Controlled Trials. The results were summarized using a narrative approach and summary tables. In total, 13 studies were eligible for inclusion in the systematic review. The current evidence base is either in favor of pharmacogenetics-guided prescribing or showed no difference between pharmacogenetics and treatment as usual for clinical and economic outcomes. In the future, we require randomized controlled trials with sufficient sample sizes that provide recommendations for patients who take antipsychotics based on a broad, multigene panel, with consistent and comparable clinical outcomes.

Empirical meropenem versus piperacillin/tazobactam for adult patients with sepsis (EMPRESS) trial: Protocol.

BACKGROUND: Piperacillin/tazobactam may be associated with less favourable outcomes than carbapenems in patients with severe bacterial infections, but the certainty of evidence is low. METHODS: The Empirical Meropenem versus Piperacillin/Tazobactam for Adult Patients with Sepsis (EMPRESS) trial is an investigator-initiated, international, parallel-group, randomised, open-label, adaptive clinical trial with an integrated feasibility phase. We will randomise adult, critically ill patients with sepsis to empirical treatment with meropenem or piperacillin/tazobactam for up to 30 days. The primary outcome is 30-day all-cause mortality. The secondary outcomes are serious adverse reactions within 30 days; isolation precautions due to resistant bacteria within 30 days; days alive without life support and days alive and out of hospital within 30 and 90 days; 90- and 180-day all-cause mortality and 180-day health-related quality of life. EMPRESS will use Bayesian statistical models with weak to somewhat sceptical neutral priors. Adaptive analyses will be conducted after follow-up of the primary outcome for the first 400 participants concludes and after every 300 subsequent participants, with adaptive stopping for superiority/inferiority and practical equivalence (absolute risk difference <2.5%-points) and response-adaptive randomisation. The expected sample sizes in scenarios with no, small or large differences are 5189, 5859 and 2570 participants, with maximum 14,000 participants and ≥99% probability of conclusiveness across all scenarios. CONCLUSIONS: EMPRESS will compare the effects of empirical meropenem against piperacillin/tazobactam in adult, critically ill patients with sepsis. Due to the pragmatic, adaptive design with high probability of conclusiveness, the trial results are expected to directly inform clinical practice.

Effects of restrictive fluid therapy on the time to resolution of hyperlactatemia in ICU patients with septic shock. A secondary post hoc analysis of the CLASSIC randomized trial.

PURPOSE: The aim of this study was to examine the effects of intravenous (IV) fluid restriction on time to resolution of hyperlactatemia in septic shock. Hyperlactatemia in sepsis is associated with worse outcome. Sepsis guidelines suggest targeting lactate clearance to guide fluid therapy despite the complexity of hyperlactatemia and the potential harm of fluid overload. METHODS: We conducted a post hoc analysis of serial plasma lactate concentrations in a sub-cohort of 777 patients from the international multicenter clinical CLASSIC trial (restriction of intravenous fluids in intensive care unit (ICU) patients with septic shock). Adult ICU patients with septic shock had been randomized to restrictive (n = 385) or standard (n = 392) intravenous fluid therapy. The primary outcome, time to resolution of hyperlactatemia, was analyzed with a competing-risks regression model. Death and discharge were competing outcomes, and administrative censoring was imposed 72 h after randomization if hyperlactatemia persisted. The regression analysis was adjusted for the same stratification variables and covariates as in the original CLASSIC trial analysis. RESULTS: The hazard ratios (HRs) for the cumulative probability of resolution of hyperlactatemia, in the restrictive vs the standard group, in the unadjusted analysis, with time split, were 0.94 (confidence interval (CI) 0.78-1.14) at day 1 and 1.21 (0.89-1.65) at day 2-3. The adjusted analyses were consistent with the unadjusted results. CONCLUSION: In this post hoc retrospective analysis of a multicenter randomized controlled trial (RCT), a restrictive intravenous fluid strategy did not seem to affect the time to resolution of hyperlactatemia in adult ICU patients with septic shock.

Effects of IV fluid restriction according to site-specific intensity of standard fluid treatment-protocol.

BACKGROUND: Variation in usual practice in fluid trials assessing lower versus higher volumes may affect overall comparisons. To address this, we will evaluate the effects of heterogeneity in treatment intensity in the Conservative versus Liberal Approach to Fluid Therapy of Septic Shock in Intensive Care trial. This will reflect the effects of differences in site-specific intensities of standard fluid treatment due to local practice preferences while considering participant characteristics. METHODS: We will assess the effects of heterogeneity in treatment intensity across one primary (all-cause mortality) and three secondary outcomes (serious adverse events or reactions, days alive without life support and days alive out of hospital) after 90 days. We will classify sites based on the site-specific intensity of standard fluid treatment, defined as the mean differences in observed versus predicted intravenous fluid volumes in the first 24 h in the standard-fluid group while accounting for differences in participant characteristics. Predictions will be made using a machine learning model including 22 baseline predictors using the extreme gradient boosting algorithm. Subsequently, sites will be grouped into fluid treatment intensity subgroups containing at least 100 participants each. Subgroups differences will be assessed using hierarchical Bayesian regression models with weakly informative priors. We will present the full posterior distributions of relative (risk ratios and ratios of means) and absolute differences (risk differences and mean differences) in each subgroup. DISCUSSION: This study will provide data on the effects of heterogeneity in treatment intensity while accounting for patient characteristics in critically ill adult patients with septic shock. REGISTRATIONS: The European Clinical Trials Database (EudraCT): 2018-000404-42, ClinicalTrials. gov: NCT03668236.

Effects of sceptical priors on the performance of adaptive clinical trials with binary outcomes.

It is unclear how sceptical priors impact adaptive trials. We assessed the influence of priors expressing a spectrum of scepticism on the performance of several Bayesian, multi-stage, adaptive clinical trial designs using binary outcomes under different clinical scenarios. Simulations were conducted using fixed stopping rules and stopping rules calibrated to keep type 1 error rates at approximately 5%. We assessed total sample sizes, event rates, event counts, probabilities of conclusiveness and selecting the best arm, root mean squared errors (RMSEs) of the estimated treatment effect in the selected arms, and ideal design percentages (IDPs; which combines arm selection probabilities, power, and consequences of selecting inferior arms), with RMSEs and IDPs estimated in conclusive trials only and after selecting the control arm in inconclusive trials. Using fixed stopping rules, increasingly sceptical priors led to larger sample sizes, more events, higher IDPs in simulations ending in superiority, and lower RMSEs, lower probabilities of conclusiveness/selecting the best arm, and lower IDPs when selecting controls in inconclusive simulations. With calibrated stopping rules, the effects of increased scepticism on sample sizes and event counts were attenuated, and increased scepticism increased the probabilities of conclusiveness/selecting the best arm and IDPs when selecting controls in inconclusive simulations without substantially increasing sample sizes. Results from trial designs with gentle adaptation and non-informative priors resembled those from designs with more aggressive adaptation using weakly-to-moderately sceptical priors. In conclusion, the use of somewhat sceptical priors in adaptive trial designs with binary outcomes seems reasonable when considering multiple performance metrics simultaneously.

The vagus nerve mediates the physiological but not pharmacological effects of PYY3-36 on food intake.

Peptide YY (PYY3-36) is a post-prandially released gut hormone with potent appetite-reducing activity, the mechanism of action of which is not fully understood. Unravelling how this system physiologically regulates food intake may help unlock its therapeutic potential, whilst minimising unwanted effects. Here we demonstrate that germline and post-natal targeted knockdown of the PYY3-36 preferring receptor (neuropeptide Y (NPY) Y2 receptor (Y2R)) in the afferent vagus nerve is required for the appetite inhibitory effects of physiologically-released PYY3-36, but not peripherally administered pharmacological doses. Post-natal knockdown of the Y2R results in a transient body weight phenotype that is not evident in the germline model. Loss of vagal Y2R signalling also results in altered meal patterning associated with accelerated gastric emptying. These results are important for the design of PYY-based anti-obesity agents.

Position Paper on the Reporting of Norepinephrine Formulations in Critical Care from the Society of Critical Care Medicine and European Society of Intensive Care Medicine Joint Task Force.

OBJECTIVES: To provide guidance on the reporting of norepinephrine formulation labeling, reporting in publications, and use in clinical practice. DESIGN: Review and task force position statements with necessary guidance. SETTING: A series of group conference calls were conducted from August 2023 to October 2023, along with a review of the available evidence and scope of the problem. SUBJECTS: A task force of multinational and multidisciplinary critical care experts assembled by the Society of Critical Care Medicine and the European Society of Intensive Care Medicine. INTERVENTIONS: The implications of a variation in norepinephrine labeled as conjugated salt (i.e., bitartrate or tartrate) or base drug in terms of effective concentration of norepinephrine were examined, and guidance was provided. MEASUREMENTS AND MAIN RESULTS: There were significant implications for clinical care, dose calculations for enrollment in clinical trials, and results of datasets reporting maximal norepinephrine equivalents. These differences were especially important in the setting of collaborative efforts across countries with reported differences. CONCLUSIONS: A joint task force position statement was created outlining the scope of norepinephrine-dose formulation variations, and implications for research, patient safety, and clinical care. The task force advocated for a uniform norepinephrine-base formulation for global use, and offered advice aimed at appropriate stakeholders.

Use of inotropic agents in advanced heart failure: pros and cons.

BACKGROUND: Use of inotropic agents in advanced heart failure (HF) has over time been evaluated in several randomized, controlled clinical trials (RCTs). However, the evidence for both efficacy and safety is conflicting. SUMMARY: In this narrative review, the evidence for and role of inotropes in advanced HF are outlined. Readers are provided with a comprehensive overview of key-findings from 23 important RCTs comparing orally or intravenously administered inotropes. Clinically relevant pros and cons of inotropic regimens are summarized to guide the clinician in the management of advanced HF patients in different settings (e.g., out-patient, in-patient, and intensive care unit). Finally, future perspectives and potential new agents are discussed. KEY MESSAGES: Long-term use of inotropes in advanced HF is controversial and should only be considered in selected patients (e.g., as palliative or bridging strategy). However, short-term use continues to play a large role in hospitalized patients with cardiogenic shock or severe decompensated acute HF.

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.

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.

Health-related quality of life trajectories in critical illness: Protocol for a Monte Carlo simulation study.

BACKGROUND: Health-related quality of life (HRQoL) is a patient-centred outcome increasingly used as a secondary outcome in critical care research. It may cover several important dimensions of clinical status in intensive care unit (ICU) patients that arguably elude other more easily quantified outcomes such as mortality. Poor associations with harder outcomes, conflicting data on HRQoL in critically ill compared to the background population, and paradoxical effects on HRQoL and mortality complicate the current operationalisation in critical care trials. This protocol outlines a simulation study that will gauge if the areas under the HRQoL trajectories could be a viable alternative. METHODS: We will gauge the behaviour of the proposed HRQoL operationalisation through Monte Carlo simulations, under clinical scenarios that reflect a broad critical care population eligible for inclusion in a large pragmatic trial. We will simulate 15,360 clinical scenarios based on a full factorial design with the following seven simulation parameters: number of patients per arm, relative mortality reduction in the interventional arm, acceleration of HRQoL improvement in the interventional arm, the relative improvement in final HRQoL in the interventional arm, dampening effect of mortality on HRQoL values at discharge from the ICU, proportion of so-called mortality benefiters in the interventional arm and mortality trajectory shape. For each clinical scenario, we will simulate 100,000 two-arm trials with 1:1 randomisation. HRQoL will be sampled fortnightly after ICU discharge. Outcomes will include HRQoL in survivors and all patients at the end of follow-up; mean areas under the HRQoL trajectories in both arms; and mean difference between areas under the HRQoL trajectories and single-sampled HRQoLs at the end of follow-up. DISCUSSION: In the outlined simulation study, we aim to assess whether the area under the HRQoL trajectory curve could be a candidate for reconciling the seemingly paradoxical effects on improved mortality and reduced HRQoL while remaining sensitive to early or accelerated improvement in patient outcomes. The resultant insights will inform subsequent methodological work on prudent collection and statistical analysis of such data from real critically ill patients.

Restrictive versus standard IV fluid therapy in adult ICU patients with septic shock-Bayesian analyses of the CLASSIC trial.

BACKGROUND: The CLASSIC trial assessed the effects of restrictive versus standard intravenous (IV) fluid therapy in adult intensive care unit (ICU) patients with septic shock. This pre-planned study provides a probabilistic interpretation and evaluates heterogeneity in treatment effects (HTE). METHODS: We analysed mortality, serious adverse events (SAEs), serious adverse reactions (SARs) and days alive without life-support within 90 days using Bayesian models with weakly informative priors. HTE on mortality was assessed according to five baseline variables: disease severity, vasopressor dose, lactate levels, creatinine values and IV fluid volumes given before randomisation. RESULTS: The absolute difference in mortality was 0.2%-points (95% credible interval: -5.0 to 5.4; 47% posterior probability of benefit [risk difference <0.0%-points]) with restrictive IV fluid. The posterior probabilities of benefits with restrictive IV fluid were 72% for SAEs, 52% for SARs and 61% for days alive without life-support. The posterior probabilities of no clinically important differences (absolute risk difference ≤2%-points) between the groups were 56% for mortality, 49% for SAEs, 90% for SARs and 38% for days alive without life-support. There was 97% probability of HTE for previous IV fluid volumes analysed continuously, that is, potentially relatively lower mortality of restrictive IV fluids with higher previous IV fluids. No substantial evidence of HTE was found in the other analyses. CONCLUSION: We could not rule out clinically important effects of restrictive IV fluid therapy on mortality, SAEs or days alive without life-support, but substantial effects on SARs were unlikely. IV fluids given before randomisation might interact with IV fluid strategy.

Do tobacco 21 laws work?

Tobacco 21 (T-21) laws raise the minimum legal purchasing age for all tobacco products to 21. This study is the first to examine the impact of statewide T21 laws on teenage and young adult cigarette and electronic cigarette (e-cigarette) use. Using survey data from the Behavioral Risk Factor Surveillance System (BRFSS) and a difference-in-differences approach, we find that statewide adoption of a T-21 law is associated with a 2-to-4 percentage-point decline in smoking participation among 18-to-20-year-olds. Supplemental analyses using the State Youth Risk Behavior Surveys (YRBS) show that frequent e-cigarette use among 18-year-olds also fell following the adoption of T21 laws, though this effect was partially because teens turned to informal social sources to obtain e-cigarettes (i.e., borrowing or bumming). Finally, we find that T-21 laws generate spillover effects, including (2) reductions in cigarette use among 16-to-17-year-olds, a group that relies heavily on informal social markets in high school, and (2) reductions in marijuana use and days of alcohol use among some teens.

Platform trials.

Platform trials focus on the perpetual testing of many interventions in a disease or a setting. These trials have lasting organizational, administrative, data, analytic, and operational frameworks making them highly efficient. The use of adaptation often increases the probabilities of allocating participants to better interventions and obtaining conclusive results. The COVID-19 pandemic showed the potential of platform trials as a fast and valid way to improved treatments. This review gives an overview of key concepts and elements using the Intensive Care Platform Trial (INCEPT) as an example.

A biocatalytic platform for asymmetric alkylation of α-keto acids by mining and engineering of methyltransferases.

Catalytic asymmetric α-alkylation of carbonyl compounds represents a long-standing challenge in synthetic organic chemistry. Herein, we advance a dual biocatalytic platform for the efficient asymmetric alkylation of α-keto acids. First, guided by our recently obtained crystal structures, we develop SgvMVAV as a general biocatalyst for the enantioselective methylation, ethylation, allylation and propargylation of a range of α-keto acids with total turnover numbers (TTNs) up to 4,600. Second, we mine a family of bacterial HMTs from Pseudomonas species sharing less than 50% sequence identities with known HMTs and evaluated their activities in SAM regeneration. Our best performing HMT from P. aeruginosa, PaHMT, displays the highest SAM regeneration efficiencies (TTN up to 7,700) among HMTs characterized to date. Together, the synergistic use of SgvMVAV and PaHMT affords a fully biocatalytic protocol for asymmetric methylation featuring a record turnover efficiency, providing a solution to the notorious problem of asymmetric alkylation.

Evaluating operational parameters of the careHPV, GeneXpert, AmpFire, and MA-6000 HPV systems for cervical precancer screening: Experience from Battor, Ghana.

In response to calls by the World Health Organization for cervical precancer screening services in low-resource settings to lean toward HPV DNA testing, a number of testing platforms have been made available. This study aimed to evaluate the operational parameters of four HPV testing systems in previous (careHPV) and current (GeneXpert, AmpFire, and MA-6000) use in a secondary healthcare setting in terms of 'appropriateness', ease of use, throughput, and diagnostic yield. This descriptive retrospective cohort analysis included 6056 women who presented to our facility between June 2016 and March 2022 for cervical precancer screening via HPV testing. A large majority of this cohort underwent AmpFire testing (55.8%), followed by careHPV (23.3%), MA-6000 (14.7%), and GeneXpert (6.1%). MA-6000 showed the highest hr-HPV positivity rate of 26.4% (95% CI, 23.6-29.5), followed by AmpFire (17.2%; 95% CI, 15.9-17.5). GeneXpert and careHPV showed similar hr-HPV positivity rates of 14.8% (95% CI, 11.3-18.8) and 14.8% (95% CI, 13.0-16.8), respectively. For the AmpFire and MA-6000 platforms, which utilize similar detection and reporting formats, we found a significant excess detection rate of 9.2% (95% CI, 6.1-12.4; p-value <0.0001) for MA-6000 compared to AmpFire. At the genotype level, MA-6000 also detected significantly higher rates of HPV 16 and other hr-HPV types (both p-values <0.001) than AmpFire; there was no difference in detection for HPV 18. Based on our experiences and preliminary analysis, we believe that the choice of HPV testing platform cannot be accomplished with a one-size-fits-all approach. Factors worth considering are the financial implications of platform acquisition, costs to clients, and throughput when screening programs are not sufficiently large. We describe our successes and challenges with the different platforms which we believe will be helpful to centers in low-income countries as they transition into using HPV DNA testing for cervical precancer screening.

Importance of heart failure duration for development of pulmonary hypertension in advanced heart failure.

BACKGROUND AND OBJECTIVES: Pulmonary vascular resistance (PVR) is critical when evaluating candidacy for advanced heart failure (HF) therapies, but risk factors for elevated PVR are not well studied. We hypothesized that HF duration would be associated with elevated PVR. METHODS: Danish single-center registry of consecutive in- and outpatients undergoing right heart catheterization as part of advanced HF work up. The relation between HF duration and PVR was estimated by regression analysis. Finally, the relation between PVR and long-term mortality was assessed by Cox proportional hazards regression and Kaplan-Meier analyses. RESULTS: A total of 549 patients (77% men, median age 54 (43-61) years, median HF duration 1.6 years (0.1-7.1)) were included. Univariate linear regression displayed an association between longer HF duration and increasing PVR (p = 0.014). PVR > 3 WU was present in 92 patients (17%) who were older (median p < 0.001) and had longer HF duration (p = 0.03). HF duration (per 1 year increase) did not predict PVR > 3 WU after adjustment for covariables (OR 1.00; p = 0.99). During a mean follow-up time of 4.5 years, there were 240 (44%) deaths. Increasing PVR was associated with elevated all-cause mortality risk (adjusted HR 1.24; p < 0.001). PVR > 3 WU was associated with higher mortality (adjusted HR 1.49; p = 0.027). CONCLUSION: Longer duration of HF was associated with higher PVR in patients with advanced HF, but this association disappeared in multivariate analyses. Longer HF duration per se likely does not cause elevated PVR and should not discourage evaluation for heart transplantation.

Use of days alive without life support and similar count outcomes in randomised clinical trials - an overview and comparison of methodological choices and analysis methods.

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.

Development of a dynamic prediction model for unplanned ICU admission and mortality in hospitalized patients.

Frequent assessment of the severity of illness for hospitalized patients is essential in clinical settings to prevent outcomes such as in-hospital mortality and unplanned admission to the intensive care unit (ICU). Classical severity scores have been developed typically using relatively few patient features. Recently, deep learning-based models demonstrated better individualized risk assessments compared to classic risk scores, thanks to the use of aggregated and more heterogeneous data sources for dynamic risk prediction. We investigated to what extent deep learning methods can capture patterns of longitudinal change in health status using time-stamped data from electronic health records. We developed a deep learning model based on embedded text from multiple data sources and recurrent neural networks to predict the risk of the composite outcome of unplanned ICU transfer and in-hospital death. The risk was assessed at regular intervals during the admission for different prediction windows. Input data included medical history, biochemical measurements, and clinical notes from a total of 852,620 patients admitted to non-intensive care units in 12 hospitals in Denmark's Capital Region and Region Zealand during 2011-2016 (with a total of 2,241,849 admissions). We subsequently explained the model using the Shapley algorithm, which provides the contribution of each feature to the model outcome. The best model used all data modalities with an assessment rate of 6 hours, a prediction window of 14 days and an area under the receiver operating characteristic curve of 0.898. The discrimination and calibration obtained with this model make it a viable clinical support tool to detect patients at higher risk of clinical deterioration, providing clinicians insights into both actionable and non-actionable patient features.