Which Multicenter Randomized Controlled Trials in Critical Care Medicine Have Shown Reduced Mortality? A Systematic Review:

INCEPT: The Intensive Care Platform Trial-Design and protocol

BACKGROUND

Adult intensive care unit (ICU) patients receive many interventions, but few are supported by high-certainty evidence. Randomised clinical trials (RCTs) are essential for trustworthy comparisons of intervention effects, but conventional RCTs are costly, cumbersome, inflexible, and often turn out inconclusive. Adaptive platform trials may mitigate these issues and have higher probabilities of obtaining conclusive results faster and at lower costs per participant.

METHODS

The Intensive Care Platform Trial (INCEPT) is an investigator-initiated, pragmatic, randomised, embedded, multifactorial, international, adaptive platform trial including adults acutely admitted to ICUs. INCEPT will assess comparable groups of interventions (primarily commonly used interventions with clinical uncertainty and practice variation) nested in domains. Interventions may be either open-label or masked. New domains will continuously be added to the platform. INCEPT assesses multiple core outcomes selected following substantial stakeholder involvement: mortality, days alive without life support/out of hospital/free of delirium, health-related quality of life, cognitive function, and safety outcomes. Each domain will use one of these core outcomes as the primary outcome. INCEPT primarily uses Bayesian statistical methods with neutral, minimally informative or sceptical priors, adjustment for important prognostic baseline variables, and calculation of absolute and relative differences in the intention-to-treat populations. Domains and intervention arms may be stopped for superiority/inferiority, practical equivalence, or futility according to pre-specified adaptation rules evaluated using statistical simulation or at pre-specified maximum sample sizes. Domains may use response-adaptive randomisation, meaning that more participants will be allocated to interventions with higher probabilities of being superior.

CONCLUSIONS

INCEPT provides an efficient, pragmatic, and flexible platform for comparing the effects of many interventions used in adult ICU patients. The adaptive design enables the trial to use accumulating data to improve the treatment of future participants. INCEPT will provide high-certainty, conclusive evidence for many interventions, directly inform clinical practice, and thus improve patient-important outcomes.

Heterogeneity of treatment effect: the case for individualising oxygen therapy in critically ill patients

Oxygen therapy is ubiquitous in critical illness but oxygenation targets to guide therapy remain controversial despite several large randomised controlled trials (RCTs). Findings from RCTs evaluating different approaches to oxygen therapy in critical illness present a confused picture for several reasons. Differences in both oxygen target measures (e.g. oxygen saturation or partial pressure) and the numerical thresholds used to define lower and higher targets complicate comparisons between trials. The duration of and adherence to oxygenation targets is also variable with consequent substantial variation in both the dose and the dose separation. Finally, heterogeneity of treatment effects (HTE) may also be a significant factor. HTE is defined as non-random variation in the benefit or harm of a treatment, in which the variation is associated with or attributable to patient characteristics. This narrative review aims to make the case that such heterogeneity is likely in relation to oxygen therapy for critically ill patients and that this has significant implications for the design and interpretation of trials of oxygen therapy in this context. HTE for oxygen therapy amongst critically ill patients may explain the contrasting results from different clinical trials of oxygen therapy. Individualised oxygen therapy may overcome this challenge, and future studies should incorporate ways to evaluate this approach.

Translating PK-PD principles into improved methodology for clinical trials which compare intermittent with prolonged infusion of beta-lactam antibiotics

Based on the fact that beta-lactam antibiotics demonstrate time-dependent killing, different dosing strategies have been implemented to increase the time that free (f) (unbound) antibiotic concentrations remain above the Minimal Inhibitory Concentration (MIC), including prolonged and continuous infusion. Multiple studies have been performed that compared continuous with traditional intermittent infusion to improve outcomes in patients with severe sepsis and/or septic shock. These studies have yielded inconsistent results for patients as measured by clinical response to treatment and mortality due to heterogeneity of included patients, pathogens, dosing strategies and the absence of Therapeutic Drug Monitoring (TDM). The MERCY and BLING III studies failed to show a difference in mortality between patients randomized to receive continuous and intermittent infusion of beta-lactam antibiotics.
 A deeper understanding of pharmacokinetic (PK) and pharmacodynamic (PD) mechanisms that occur in critically ill patients should guide us in dose optimization and improvement in methodology for future clinical trials.

Distinct immune profiles and clinical outcomes in sepsis subphenotypes based on temperature trajectories

PURPOSE

Sepsis is a heterogeneous syndrome. Identification of sepsis subphenotypes with distinct immune profiles could lead to targeted therapies. This study investigates the immune profiles of patients with sepsis following distinct body temperature patterns (i.e., temperature trajectory subphenotypes).

METHODS

Hospitalized patients from four hospitals between 2018 and 2022 with suspicion of infection were included. A previously validated temperature trajectory algorithm was used to classify study patients into temperature trajectory subphenotypes. Microbiological profiles, clinical outcomes, and levels of 31 biomarkers were compared between these subphenotypes.

RESULTS

The 3576 study patients were classified into four temperature trajectory subphenotypes: hyperthermic slow resolvers (N = 563, 16%), hyperthermic fast resolvers (N = 805, 23%), normothermic (N = 1693, 47%), hypothermic (N = 515, 14%). The mortality rate was significantly different between subphenotypes, with the highest rate in hypothermics (14.2%), followed by hyperthermic slow resolvers 6%, normothermic 5.5%, and lowest in hyperthermic fast resolvers 3.6% (p < 0.001). After multiple testing correction for the 31 biomarkers tested, 20 biomarkers remained significantly different between temperature trajectories: angiopoietin-1 (Ang-1), C-reactive protein (CRP), feline McDonough sarcoma-like tyrosine kinase 3 ligand (Flt-3l), granulocyte colony stimulating factor (G-CSF), granulocyte-macrophage colony stimulating factor (GM-CSF), interleukin (IL)-15, IL-1 receptor antagonist (RA), IL-2, IL-6, IL-7, interferon gamma-induced protein 10 (IP-10), monocyte chemoattractant protein-1 (MCP-1), human macrophage inflammatory protein 3 alpha (MIP-3a), neutrophil gelatinase-associated lipocalin (NGAL), pentraxin-3, thrombomodulin, tissue factor, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), and vascular cellular adhesion molecule-1 (vCAM-1).The hyperthermic fast and slow resolvers had the highest levels of most pro- and anti-inflammatory cytokines. Hypothermics had suppressed levels of most cytokines but the highest levels of several coagulation markers (Ang-1, thrombomodulin, tissue factor).

CONCLUSION

Sepsis subphenotypes identified using the universally available measurement of body temperature had distinct immune profiles. Hypothermic patients, who had the highest mortality rate, also had the lowest levels of most pro- and anti-inflammatory cytokines.

Comparative evaluation of early treatment with ceftolozane/tazobactam versus ceftazidime/avibactam for non-COVID-19 patients with pneumonia due to multidrug-resistant Pseudomonas aeruginosa

BACKGROUND

Ceftolozane/tazobactam and ceftazidime/avibactam are commonly used in patients with MDR-Pseudomonas aeruginosa (PSA) pneumonia (PNA). This study compared outcomes between non-COVID-19 hospitalized patients with MDR-PSA PNA who received ceftolozane/tazobactam or ceftazidime/avibactam.

METHODS

The study included non-COVID-19 adult hospitalized patients with MDR-PSA PNA in the PINC AI Healthcare Database (2016-22) who received ceftolozane/tazobactam or ceftazidime/avibactam within 3 days of index culture for ≥2 days. Outcomes were mortality, recurrent MDR-PSA PNA, discharge destination, post-index culture day length of stay (LOS) and costs (in US dollars, USD), and hospital readmission.

RESULTS

The final sample included 197 patients (117 ceftolozane/tazobactam, 80 ceftazidime/avibactam). No significant differences were observed in mortality and post-index culture LOS and costs between groups. In the multivariable analyses, patients who received ceftolozane/tazobactam versus ceftazidime/avibactam had lower recurrent MDR-PSA PNA (7.9% versus 18.0%, P = 0.03) and 60 day PNA-related readmissions (11.1% versus 28.5%, P = 0.03) and were more likely to be discharged home (25.8% versus 9.8%, P = 0.03). Compared with ceftazidime/avibactam patients, ceftolozane/tazobactam patients had lower adjusted median total antibiotic costs (5052 USD versus 8099 USD, P = 0.003) and lower adjusted median comparator (ceftolozane/tazobactam or ceftazidime/avibactam) antibiotic costs (3938 USD versus 6441 USD, P = 0.005). In the desirability of outcome ranking (DOOR) analysis, a ceftolozane/tazobactam-treated patient was more likely to have a more favourable outcome than a ceftazidime/avibactam-treated patient [DOOR probability: 59.6% (95% CI: 52.5%-66.8%)].

CONCLUSIONS

Early treatment with ceftolozane/tazobactam may offer some clinical and cost benefits over ceftazidime/avibactam in patients with MDR-PSA PNA. Further large-scale studies are necessary to comprehensively understand the outcomes associated with these treatments for MDR-PSA PNA.

Personalized ventilation adjustment in ARDS: A systematic review and meta-analysis of image, driving pressure, transpulmonary pressure, and mechanical power

BACKGROUND

Acute Respiratory Distress Syndrome (ARDS) necessitates personalized treatment strategies due to its heterogeneity, aiming to mitigate Ventilator-Induced Lung Injury (VILI). Advanced monitoring techniques, including imaging, driving pressure, transpulmonary pressure, and mechanical power, present potential avenues for tailored interventions.

OBJECTIVE

To review some of the most important techniques for achieving greater personalization of mechanical ventilation in ARDS patients as evaluated in randomized clinical trials, by analyzing their effect on three clinically relevant aspects: mortality, ventilator-free days, and gas exchange.

METHODS

Following PRISMA guidelines, we conducted a systematic review and meta-analysis of Randomized Clinical Trials (RCTs) involving adult ARDS patients undergoing personalized ventilation adjustments. Outcomes were mortality (primary end-point), ventilator-free days, and oxygenation improvement.

RESULTS

Among 493 identified studies, 13 RCTs (n = 1255) met inclusion criteria. No personalized ventilation strategy demonstrated superior outcomes compared to traditional protocols. Meta-analysis revealed no significant reduction in mortality with image-guided (RR 0.88, 95 % CI 0.70-1.11), driving pressure-guided (RR 0.61, 95 % CI 0.29-1.30), or transpulmonary pressure-guided (RR 0.85, 95 % CI 0.58-1.24) strategies. Ventilator-free days and oxygenation outcomes showed no significant differences.

CONCLUSION

Our study does not support the superiority of personalized ventilation techniques over traditional protocols in ARDS patients. Further research is needed to standardize ventilation strategies and determine their impact on mechanical ventilation outcomes.

Heterogeneity, Bayesian thinking, and phenotyping in critical care: A primer

PURPOSE

To familiarize clinicians with the emerging concepts in critical care research of Bayesian thinking and personalized medicine through phenotyping and explain their clinical relevance by highlighting how they address the issues of frequent negative trials and heterogeneity of treatment effect.

SUMMARY

The past decades have seen many negative (effect-neutral) critical care trials of promising interventions, culminating in calls to improve the field's research through adopting Bayesian thinking and increasing personalization of critical care medicine through phenotyping. Bayesian analyses add interpretive power for clinicians as they summarize treatment effects based on probabilities of benefit or harm, contrasting with conventional frequentist statistics that either affirm or reject a null hypothesis. Critical care trials are beginning to include prospective Bayesian analyses, and many trials have undergone reanalysis with Bayesian methods. Phenotyping seeks to identify treatable traits to target interventions to patients expected to derive benefit. Phenotyping and subphenotyping have gained prominence in the most syndromic and heterogenous critical care disease states, acute respiratory distress syndrome and sepsis. Grouping of patients has been informative across a spectrum of clinically observable physiological parameters, biomarkers, and genomic data. Bayesian thinking and phenotyping are emerging as elements of adaptive clinical trials and predictive enrichment, paving the way for a new era of high-quality evidence. These concepts share a common goal, sifting through the noise of heterogeneity in critical care to increase the value of existing and future research.

CONCLUSION

The future of critical care medicine will inevitably involve modification of statistical methods through Bayesian analyses and targeted therapeutics via phenotyping. Clinicians must be familiar with these systems that support recommendations to improve decision-making in the gray areas of critical care practice.

Enhancing Patient Selection in Sepsis Clinical Trials Design Through an AI Enrichment Strategy: Algorithm Development and Validation

BACKGROUND

Sepsis is a heterogeneous syndrome, and enrollment of more homogeneous patients is essential to improve the efficiency of clinical trials. Artificial intelligence (AI) has facilitated the identification of homogeneous subgroups, but how to estimate the uncertainty of the model outputs when applying AI to clinical decision-making remains unknown.

OBJECTIVE

We aimed to design an AI-based model for purposeful patient enrollment, ensuring that a patient with sepsis recruited into a trial would still be persistently ill by the time the proposed therapy could impact patient outcome. We also expected that the model could provide interpretable factors and estimate the uncertainty of the model outputs at a customized confidence level.

METHODS

In this retrospective study, 9135 patients with sepsis requiring vasopressor treatment within 24 hours after sepsis onset were enrolled from Beth Israel Deaconess Medical Center. This cohort was used for model development, and 10-fold cross-validation with 50 repeats was used for internal validation. In total, 3743 patients with sepsis from the eICU Collaborative Research Database were used as the external validation cohort. All included patients with sepsis were stratified based on disease progression trajectories: rapid death, recovery, and persistent ill. A total of 148 variables were selected for predicting the 3 trajectories. Four machine learning algorithms with 3 different setups were used. We estimated the uncertainty of the model outputs using conformal prediction (CP). The Shapley Additive Explanations method was used to explain the model.

RESULTS

The multiclass gradient boosting machine was identified as the best-performing model with good discrimination and calibration performance in both validation cohorts. The mean area under the receiver operating characteristic curve with SD was 0.906 (0.018) for rapid death, 0.843 (0.008) for recovery, and 0.807 (0.010) for persistent ill in the internal validation cohort. In the external validation cohort, the mean area under the receiver operating characteristic curve (SD) was 0.878 (0.003) for rapid death, 0.764 (0.008) for recovery, and 0.696 (0.007) for persistent ill. The maximum norepinephrine equivalence, total urine output, Acute Physiology Score III, mean systolic blood pressure, and the coefficient of variation of oxygen saturation contributed the most. Compared to the model without CP, using the model with CP at a mixed confidence approach reduced overall prediction errors by 27.6% (n=62) and 30.7% (n=412) in the internal and external validation cohorts, respectively, as well as enabled the identification of more potentially persistent ill patients.

CONCLUSIONS

The implementation of our model has the potential to reduce heterogeneity and enroll more homogeneous patients in sepsis clinical trials. The use of CP for estimating the uncertainty of the model outputs allows for a more comprehensive understanding of the model's reliability and assists in making informed decisions based on the predicted outcomes.

Emergent Management of Hypoxic-Ischemic Brain Injury

OBJECTIVE

This article outlines interventions used to improve outcomes for patients with hypoxic-ischemic brain injury after cardiac arrest.

LATEST DEVELOPMENTS

Emergent management of patients after cardiac arrest requires prevention and treatment of primary and secondary brain injury. Primary brain injury is minimized by excellent initial resuscitative efforts. Secondary brain injury prevention requires the detection and correction of many pathophysiologic processes that may develop in the hours to days after the initial arrest. Key physiologic parameters important to secondary brain injury prevention include optimization of mean arterial pressure, cerebral perfusion, oxygenation and ventilation, intracranial pressure, temperature, and cortical hyperexcitability. This article outlines recent data regarding the treatment and prevention of secondary brain injury. Different patients likely benefit from different treatment strategies, so an individualized approach to treatment and prevention of secondary brain injury is advisable. Clinicians must use multimodal sources of data to prognosticate outcomes after cardiac arrest while recognizing that all prognostic tools have shortcomings.

ESSENTIAL POINTS

Neurologists should be involved in the postarrest care of patients with hypoxic-ischemic brain injury to improve their outcomes. Postarrest care requires nuanced and patient-centered approaches to the prevention and treatment of primary and secondary brain injury and neuroprognostication.

Composite outcome measures in high-impact critical care randomised controlled trials: a systematic review

BACKGROUND

The use of composite outcome measures (COM) in clinical trials is increasing. Whilst their use is associated with benefits, several limitations have been highlighted and there is limited literature exploring their use within critical care. The primary aim of this study was to evaluate the use of COM in high-impact critical care trials, and compare study parameters (including sample size, statistical significance, and consistency of effect estimates) in trials using composite versus non-composite outcomes.

METHODS

A systematic review of 16 high-impact journals was conducted. Randomised controlled trials published between 2012 and 2022 reporting a patient important outcome and involving critical care patients, were included.

RESULTS

8271 trials were screened, and 194 included. 39.1% of all trials used a COM and this increased over time. Of those using a COM, only 52.6% explicitly described the outcome as composite. The median number of components was 2 (IQR 2-3). Trials using a COM recruited fewer participants (409 (198.8-851.5) vs 584 (300-1566, p = 0.004), and their use was not associated with increased rates of statistical significance (19.7% vs 17.8%, p = 0.380). Predicted effect sizes were overestimated in all but 6 trials. For studies using a COM the effect estimates were consistent across all components in 43.4% of trials. 93% of COM included components that were not patient important.

CONCLUSIONS

COM are increasingly used in critical care trials; however effect estimates are frequently inconsistent across COM components confounding outcome interpretations. The use of COM was associated with smaller sample sizes, and no increased likelihood of statistically significant results. Many of the limitations inherent to the use of COM are relevant to critical care research.

Development and External Validation of Models to Predict Persistent Hypoxemic Respiratory Failure for Clinical Trial Enrichment

OBJECTIVES

Improving the efficiency of clinical trials in acute hypoxemic respiratory failure (HRF) depends on enrichment strategies that minimize enrollment of patients who quickly resolve with existing care and focus on patients at high risk for persistent HRF. We aimed to develop parsimonious models predicting risk of persistent HRF using routine data from ICU admission and select research immune biomarkers.

DESIGN

Prospective cohorts for derivation ( n = 630) and external validation ( n = 511).

SETTING

Medical and surgical ICUs at two U.S. medical centers.

PATIENTS

Adults with acute HRF defined as new invasive mechanical ventilation (IMV) and hypoxemia on the first calendar day after ICU admission.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We evaluated discrimination, calibration, and practical utility of models predicting persistent HRF risk (defined as ongoing IMV and hypoxemia on the third calendar day after admission): 1) a clinical model with least absolute shrinkage and selection operator (LASSO) selecting Pa o2 /F io2 , vasopressors, mean arterial pressure, bicarbonate, and acute respiratory distress syndrome as predictors; 2) a model adding interleukin-6 (IL-6) to clinical predictors; and 3) a comparator model with Pa o2 /F io2 alone, representing an existing strategy for enrichment. Forty-nine percent and 69% of patients had persistent HRF in derivation and validation sets, respectively. In validation, both LASSO (area under the receiver operating characteristic curve, 0.68; 95% CI, 0.64-0.73) and LASSO + IL-6 (0.71; 95% CI, 0.66-0.76) models had better discrimination than Pa o2 /F io2 (0.64; 95% CI, 0.59-0.69). Both models underestimated risk in lower risk deciles, but exhibited better calibration at relevant risk thresholds. Evaluating practical utility, both LASSO and LASSO + IL-6 models exhibited greater net benefit in decision curve analysis, and greater sample size savings in enrichment analysis, compared with Pa o2 /F io2 . The added utility of LASSO + IL-6 model over LASSO was modest.

CONCLUSIONS

Parsimonious, interpretable models that predict persistent HRF may improve enrichment of trials testing HRF-targeted therapies and warrant future validation.

Claudin-2 upregulation enhances intestinal permeability, immune activation, dysbiosis, and mortality in sepsis

Intestinal epithelial expression of the tight junction protein claudin-2, which forms paracellular cation and water channels, is precisely regulated during development and in disease. Here, we show that small intestinal epithelial claudin-2 expression is selectively upregulated in septic patients. Similar changes occurred in septic mice, where claudin-2 upregulation coincided with increased flux across the paracellular pore pathway. In order to define the significance of these changes, sepsis was induced in claudin-2 knockout (KO) and wild-type (WT) mice. Sepsis-induced increases in pore pathway permeability were prevented by claudin-2 KO. Moreover, claudin-2 deletion reduced interleukin-17 production and T cell activation and limited intestinal damage. These effects were associated with reduced numbers of neutrophils, macrophages, dendritic cells, and bacteria within the peritoneal fluid of septic claudin-2 KO mice. Most strikingly, claudin-2 deletion dramatically enhanced survival in sepsis. Finally, the microbial changes induced by sepsis were less pathogenic in claudin-2 KO mice as survival of healthy WT mice injected with cecal slurry collected from WT mice 24 h after sepsis was far worse than that of healthy WT mice injected with cecal slurry collected from claudin-2 KO mice 24 h after sepsis. Claudin-2 upregulation and increased pore pathway permeability are, therefore, key intermediates that contribute to development of dysbiosis, intestinal damage, inflammation, ineffective pathogen control, and increased mortality in sepsis. The striking impact of claudin-2 deletion on progression of the lethal cascade activated during sepsis suggests that claudin-2 may be an attractive therapeutic target in septic 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.

Designing acute kidney injury clinical trials

Acute kidney injury (AKI) is a common clinical condition with various causes and is associated with increased mortality. Despite advances in supportive care, AKI increases not only the risk of premature death compared with the general population but also the risk of developing chronic kidney disease and progressing towards kidney failure. Currently, no specific therapy exists for preventing or treating AKI other than mitigating further injury and supportive care. To address this unmet need, novel therapeutic interventions targeting the underlying pathophysiology must be developed. New and well-designed clinical trials with appropriate end points must be subsequently designed and implemented to test the efficacy of such new interventions. Herein, we discuss predictive and prognostic enrichment strategies for patient selection, as well as primary and secondary end points that can be used in different clinical trial designs (specifically, prevention and treatment trials) to evaluate novel interventions and improve the outcomes of patients at a high risk of AKI or with established AKI.

Effect of protocol-based family visitation on physiological indicators in ICU patients: a randomized controlled trial

BACKGROUND

Intensive care unit (ICU) patients often experience significant physiological stress. This study evaluated the effect of a defined family visitation protocol on physiological responses in the ICU.

METHODS

A randomized, block-randomized clinical trial was conducted on 78 ICU patients at Imam Reza Hospital between February 8, 2017, and August 8, 2017. The intervention group received protocol-based visits, and the control group continued with standard visitation. Block randomization was utilized for group assignments. The primary outcome was the measurement of physiological signs using designated monitoring devices. Data were analyzed using SPSS version 22, employing independent t-tests, Mann-Whitney U test, repeated measures analysis, and Friedman's test.

RESULTS

The results showed no significant differences in systolic blood pressure, diastolic blood pressure, mean arterial pressure, respiratory rate, and arterial blood oxygen levels between the two groups. However, heart rate in the intervention group was significantly lower in three stages before, during, and after the meaningful visiting (P = 0.008).

CONCLUSION

Protocol-based scheduled family visits in the ICU may reduce physiological stress, as evidenced by a decrease in patients' heart rate. Implementing tailored visitation protocols sensitive to patient preferences and clinical contexts is advisable, suggesting the integration of family visits into standard care practices for enhanced patient outcomes.

TRIAL REGISTRATION

IRCT20161229031654N2; 25/01/2018; Iranian Registry of Clinical Trials ( https://en.irct.ir ).

Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.

Sepsis and acute respiratory failure in patients with cancer: how can we improve care and outcomes even further?

PURPOSE OF REVIEW

Care and outcomes of critically ill patients with cancer have improved over the past decade. This selective review will discuss recent updates in sepsis and acute respiratory failure among patients with cancer, with particular focus on important opportunities to improve outcomes further through attention to phenotyping, predictive analytics, and improved outcome measures.

RECENT FINDINGS

The prevalence of cancer diagnoses in intensive care units (ICUs) is nontrivial and increasing. Sepsis and acute respiratory failure remain the most common critical illness syndromes affecting these patients, although other complications are also frequent. Recent research in oncologic sepsis has described outcome variation - including ICU, hospital, and 28-day mortality - across different types of cancer (e.g., solid vs. hematologic malignancies) and different sepsis definitions (e.g., Sepsis-3 vs. prior definitions). Research in acute respiratory failure in oncology patients has highlighted continued uncertainty in the value of diagnostic bronchoscopy for some patients and in the optimal respiratory support strategy. For both of these syndromes, specific challenges include multifactorial heterogeneity (e.g. in etiology and/or underlying cancer), delayed recognition of clinical deterioration, and complex outcomes measurement.

SUMMARY

Improving outcomes in oncologic critical care requires attention to the heterogeneity of cancer diagnoses, timely recognition and management of critical illness, and defining appropriate ICU outcomes.

Haloperidol for the treatment of delirium in critically ill patients: an updated systematic review with meta-analysis and trial sequential analysis

BACKGROUND

Haloperidol is frequently used in critically ill patients with delirium, but evidence for its effects has been sparse and inconclusive. By including recent trials, we updated a systematic review assessing effects of haloperidol on mortality and serious adverse events in critically ill patients with delirium.

METHODS

This is an updated systematic review with meta-analysis and trial sequential analysis of randomised clinical trials investigating haloperidol versus placebo or any comparator in critically ill patients with delirium. We adhered to the Cochrane handbook, the PRISMA guidelines and the grading of recommendations assessment, development and evaluation statements. The primary outcomes were all-cause mortality and proportion of patients with one or more serious adverse events or reactions (SAEs/SARs). Secondary outcomes were days alive without delirium or coma, delirium severity, cognitive function and health-related quality of life.

RESULTS

We included 11 RCTs with 15 comparisons (n = 2200); five were placebo-controlled. The relative risk for mortality with haloperidol versus placebo was 0.89; 96.7% CI 0.77 to 1.03; I2 = 0% (moderate-certainty evidence) and for proportion of patients experiencing SAEs/SARs 0.94; 96.7% CI 0.81 to 1.10; I2 = 18% (low-certainty evidence). We found no difference in days alive without delirium or coma (moderate-certainty evidence). We found sparse data for other secondary outcomes and other comparators than placebo.

CONCLUSIONS

Haloperidol may reduce mortality and likely result in little to no change in the occurrence of SAEs/SARs compared with placebo in critically ill patients with delirium. However, the results were not statistically significant and more trial data are needed to provide higher certainty for the effects of haloperidol in these patients.

TRIAL REGISTRATION

CRD42017081133, date of registration 28 November 2017.

State of the art post-cardiac arrest care: evolution and future of post cardiac arrest care

Out-of-hospital cardiac arrest is a leading cause of mortality. In the pre-hospital setting, bystander response with cardiopulmonary resuscitation and the use of publicly available automated external defibrillators have been associated with improved survival. Early in-hospital treatment still focuses on emergency coronary angiography for selected patients. For patients remaining comatose, temperature control to avoid fever is still recommended, but former hypothermic targets have been abandoned. For patients without spontaneous awakening, the use of a multimodal prognostication model is key. After discharge, follow-up with screening for cognitive and emotional disabilities is recommended. There has been an incredible evolution of research on cardiac arrest. Two decades ago, the largest trials include a few hundred patients. Today, undergoing studies are planning to include 10-20 times as many patients, with improved methodology. This article describes the evolution and perspectives for the future in post-cardiac arrest care.

Distinct host-response signatures in circulatory shock: a narrative review

Circulatory shock is defined syndromically as hypotension associated with tissue hypoperfusion and often subcategorized according to hemodynamic profile (e.g., distributive, cardiogenic, hypovolemic) and etiology (e.g., infection, myocardial infarction, trauma, among others). These shock subgroups are generally considered homogeneous entities in research and clinical practice. This current definition fails to consider the complex pathophysiology of shock and the influence of patient heterogeneity. Recent translational evidence highlights previously under-appreciated heterogeneity regarding the underlying pathways with distinct host-response patterns in circulatory shock syndromes. This heterogeneity may confound the interpretation of trial results as a given treatment may preferentially impact distinct subgroups. Re-analyzing results of major 'neutral' treatment trials from the perspective of biological mechanisms (i.e., host-response signatures) may reveal treatment effects in subgroups of patients that share treatable traits (i.e., specific biological signatures that portend a predictable response to a given treatment). In this review, we discuss the emerging literature suggesting the existence of distinct biomarker-based host-response patterns of circulatory shock syndrome independent of etiology or hemodynamic profile. We further review responses to newly prescribed treatments in the intensive care unit designed to personalize treatments (biomarker-driven or endotype-driven patient selection in support of future clinical trials).

Temporal trends in postoperative and ventilator-associated pneumonia in the United States

OBJECTIVE

To determine change in rates of postoperative pneumonia and ventilator-associated pneumonia among patients hospitalized in the United States during 2009-2019.

DESIGN

Retrospective cohort study.

PATIENTS

Patients hospitalized for major surgical procedures, acute myocardial infarction, heart failure, and pneumonia.

METHODS

We conducted a retrospective review of data from the Medicare Patient Safety Monitoring System, a chart-abstraction-derived database including 21 adverse-event measures among patients hospitalized in the United States. Changes in observed and risk-adjusted rates of postoperative pneumonia and ventilator-associated pneumonia were derived.

RESULTS

Among 58,618 patients undergoing major surgical procedures between 2009 and 2019, the observed rate of postoperative pneumonia from 2009-2011 was 1.9% and decreased to 1.3% during 2017-2019. The adjusted annual risk each year, compared to the prior year, was 0.94 (95% CI, 0.92-0.96). Among 4,007 patients hospitalized for any of these 4 conditions at risk for ventilator-associated pneumonia during 2009-2019, we did not detect a significant change in observed or adjusted rates. Observed rates clustered around 10%, and adjusted annual risk compared to the prior year was 0.99 (95% CI, 0.95-1.02).

CONCLUSIONS

During 2009-2019, the rate of postoperative pneumonia decreased statistically and clinically significantly in among patients hospitalized for major surgical procedures in the United States, but rates of ventilator-associated pneumonia among patients hospitalized for major surgical procedures, acute myocardial infarction, heart failure, and pneumonia did not change.

Cancer and sepsis

Sepsis is one of the leading causes of death worldwide. While mortality is high regardless of inciting infection or comorbidities, mortality in patients with cancer and sepsis is significantly higher than mortality in patients with sepsis without cancer. Cancer patients are also significantly more likely to develop sepsis than the general population. The mechanisms underlying increased mortality in cancer and sepsis patients are multifactorial. Cancer treatment alters the host immune response and can increase susceptibility to infection. Preclinical data also suggests that cancer, in and of itself, increases mortality from sepsis with dysregulation of the adaptive immune system playing a key role. Further, preclinical data demonstrate that sepsis can alter subsequent tumor growth while tumoral immunity impacts survival from sepsis. Checkpoint inhibition is a well-accepted treatment for many types of cancer, and there is increasing evidence suggesting this may be a useful strategy in sepsis as well. However, preclinical studies of checkpoint inhibition in cancer and sepsis demonstrate results that could not have been predicted by examining either variable in isolation. As sepsis management transitions from a 'one size fits all' model to a more individualized approach, understanding the mechanistic impact of cancer on outcomes from sepsis represents an important strategy towards delivering on the promise of precision medicine in the intensive care unit.

Propofol and survival: an updated meta-analysis of randomized clinical trials

BACKGROUND

Propofol is one of the most widely used hypnotic agents in the world. Nonetheless, propofol might have detrimental effects on clinically relevant outcomes, possibly due to inhibition of other interventions' organ protective properties. We performed a systematic review and meta-analysis of randomized controlled trials to evaluate if propofol reduced survival compared to any other hypnotic agent in any clinical setting.

METHODS

We searched eligible studies in PubMed, Google Scholar, and the Cochrane Register of Clinical Trials. The following inclusion criteria were used: random treatment allocation and comparison between propofol and any comparator in any clinical setting. The primary outcome was mortality at the longest follow-up available. We conducted a fixed-effects meta-analysis for the risk ratio (RR). Using this RR and 95% confidence interval, we estimated the probability of any harm (RR > 1) through Bayesian statistics. We registered this systematic review and meta-analysis in PROSPERO International Prospective Register of Systematic Reviews (CRD42022323143).

RESULTS

We identified 252 randomized trials comprising 30,757 patients. Mortality was higher in the propofol group than in the comparator group (760/14,754 [5.2%] vs. 682/16,003 [4.3%]; RR = 1.10; 95% confidence interval, 1.01-1.20; p = 0.03; I2 = 0%; number needed to harm = 235), corresponding to a 98.4% probability of any increase in mortality. A statistically significant mortality increase in the propofol group was confirmed in subgroups of cardiac surgery, adult patients, volatile agent as comparator, large studies, and studies with low mortality in the comparator arm.

CONCLUSIONS

Propofol may reduce survival in perioperative and critically ill patients. This needs careful assessment of the risk versus benefit of propofol compared to other agents while planning for large, pragmatic multicentric randomized controlled trials to provide a definitive answer.

MYOSIN LIGHT CHAIN KINASE DELETION WORSENS LUNG PERMEABILITY AND INCREASES MORTALITY IN PNEUMONIA-INDUCED SEPSIS

ABSTRACT

Increased epithelial permeability in sepsis is mediated via disruptions in tight junctions, which are closely associated with the perijunctional actin-myosin ring. Genetic deletion of myosin light chain kinase (MLCK) reverses sepsis-induced intestinal hyperpermeability and improves survival in a murine model of intra-abdominal sepsis. In an attempt to determine the generalizability of these findings, this study measured the impact of MLCK deletion on survival and potential associated mechanisms following pneumonia-induced sepsis. MLCK -/- and wild-type mice underwent intratracheal injection of Pseudomonas aeruginosa . Unexpectedly, survival was significantly worse in MLCK -/- mice than wild-type mice. This was associated with increased permeability to Evans blue dye in bronchoalveolar lavage fluid but not in tissue homogenate, suggesting increased alveolar epithelial leak. In addition, bacterial burden was increased in bronchoalveolar lavage fluid. Cytokine array using whole-lung homogenate demonstrated increases in multiple proinflammatory and anti-inflammatory cytokines in knockout mice. These local pulmonary changes were associated with systemic inflammation with increased serum levels of IL-6 and IL-10 and a marked increase in bacteremia in MLCK -/- mice. Increased numbers of both bulk and memory CD4 + T cells were identified in the spleens of knockout mice, with increased early and late activation. These results demonstrate that genetic deletion of MLCK unexpectedly increases mortality in pulmonary sepsis, associated with worsened alveolar epithelial leak and both local and systemic inflammation. This suggests that caution is required in targeting MLCK for therapeutic gain in sepsis.

Haloperidol vs. placebo for the treatment of delirium in ICU patients: a pre-planned, secondary Bayesian analysis of the AID–ICU trial

PURPOSE

The AID-ICU trial was a randomised, blinded, placebo-controlled trial investigating effects of haloperidol versus placebo in acutely admitted, adult patients admitted in intensive care unit (ICU) with delirium. This pre-planned Bayesian analysis facilitates probabilistic interpretation of the AID-ICU trial results.

METHODS

We used adjusted Bayesian linear and logistic regression models with weakly informative priors to analyse all primary and secondary outcomes reported up to day 90, and with sensitivity analyses using other priors. The probabilities for any benefit/harm, clinically important benefit/harm, and no clinically important differences with haloperidol treatment according to pre-defined thresholds are presented for all outcomes.

RESULTS

The mean difference for days alive and out of hospital to day 90 (primary outcome) was 2.9 days (95% credible interval (CrI) - 1.1 to 6.9) with probabilities of 92% for any benefit and 82% for clinically important benefit. The risk difference for mortality was - 6.8 percentage points (95% CrI - 12.8 to - 0.8) with probabilities of 99% for any benefit and 94% for clinically important benefit. The adjusted risk difference for serious adverse reactions was 0.3 percentage points (95% CrI - 1.3 to 1.9) with 98% probability of no clinically important difference. Results were consistent across sensitivity analyses using different priors, with more than 83% probability of benefit and less than 17% probability of harm with haloperidol treatment.

CONCLUSIONS

We found high probabilities of benefits and low probabilities of harm with haloperidol treatment compared with placebo in acutely admitted, adult ICU patients with delirium for the primary and most secondary outcomes.

The Impact of the Society of Critical Care Medicine's Flagship Journal: Critical Care Medicine: Reflections of Critical Care Pioneers

On the 50th anniversary of the Society of Critical Care Medicine's journal Critical Care Medicine, critical care pioneers reflect on the importance of the journal to their careers and to the development of the field of adult and pediatric critical care.

Multicentre randomised trials in anaesthesia: an analysis using Bayesian metrics

Are the results of randomised trials reliable and are p values and confidence intervals the best way of quantifying efficacy? Low power is common in medical research, which reduces the probability of obtaining a 'significant result' and declaring the intervention had an effect. Metrics derived from Bayesian methods may provide an insight into trial data unavailable from p values and confidence intervals. We did a structured review of multicentre trials in anaesthesia that were published in the New England Journal of Medicine, The Lancet, Journal of the American Medical Association, British Journal of Anaesthesia and Anesthesiology between February 2011 and November 2021. We documented whether trials declared a non-zero effect by an intervention on the primary outcome. We documented the expected and observed effect sizes. We calculated a Bayes factor from the published trial data indicating the probability of the data under the null hypothesis of zero effect relative to the alternative hypothesis of a non-zero effect. We used the Bayes factor to calculate the post-test probability of zero effect for the intervention (having assumed 50% belief in zero effect before the trial). We contacted all authors to estimate the costs of running the trials. The median (IQR [range]) hypothesised and observed absolute effect sizes were 7% (3-13% [0-25%]) vs. 2% (1-7% [0-24%]), respectively. Non-zero effects were declared for 12/56 outcomes (21%). The Bayes factor favouring a zero effect relative to a non-zero effect for these 12 trials was 0.000001-1.9, with post-test zero effect probabilities for the intervention of 0.0001-65%. The other 44 trials did not declare non-zero effects, with Bayes factors favouring zero effect of 1-688, and post-test probabilities of zero effect of 53-99%. The median (IQR [range]) study costs reported by 20 corresponding authors in US$ were $1,425,669 ($514,766-$2,526,807 [$120,758-$24,763,921]). We think that inadequate power and mortality as an outcome are why few trials declared non-zero effects. Bayes factors and post-test probabilities provide a useful insight into trial results, particularly when p values approximate the significance threshold.

Personalized medicine using omics approaches in acute respiratory distress syndrome to identify biological phenotypes

In the last decade, research on acute respiratory distress syndrome (ARDS) has made considerable progress. However, ARDS remains a leading cause of mortality in the intensive care unit. ARDS presents distinct subphenotypes with different clinical and biological features. The pathophysiologic mechanisms of ARDS may contribute to the biological variability and partially explain why some pharmacologic therapies for ARDS have failed to improve patient outcomes. Therefore, identifying ARDS variability and heterogeneity might be a key strategy for finding effective treatments. Research involving studies on biomarkers and genomic, metabolomic, and proteomic technologies is increasing. These new approaches, which are dedicated to the identification and quantitative analysis of components from biological matrixes, may help differentiate between different types of damage and predict clinical outcome and risk. Omics technologies offer a new opportunity for the development of diagnostic tools and personalized therapy in ARDS. This narrative review assesses recent evidence regarding genomics, proteomics, and metabolomics in ARDS research.

Development and validation of novel sepsis subphenotypes using trajectories of vital signs

PURPOSE

Sepsis is a heterogeneous syndrome and identification of sub-phenotypes is essential. This study used trajectories of vital signs to develop and validate sub-phenotypes and investigated the interaction of sub-phenotypes with treatment using randomized controlled trial data.

METHODS

All patients with suspected infection admitted to four academic hospitals in Emory Healthcare between 2014-2017 (training cohort) and 2018-2019 (validation cohort) were included. Group-based trajectory modeling was applied to vital signs from the first 8 h of hospitalization to develop and validate vitals trajectory sub-phenotypes. The associations between sub-phenotypes and outcomes were evaluated in patients with sepsis. The interaction between sub-phenotype and treatment with balanced crystalloids versus saline was tested in a secondary analysis of SMART (Isotonic Solutions and Major Adverse Renal Events Trial).

RESULTS

There were 12,473 patients with suspected infection in training and 8256 patients in validation cohorts, and 4 vitals trajectory sub-phenotypes were found. Group A (N = 3483, 28%) were hyperthermic, tachycardic, tachypneic, and hypotensive. Group B (N = 1578, 13%) were hyperthermic, tachycardic, tachypneic (not as pronounced as Group A) and hypertensive. Groups C (N = 4044, 32%) and D (N = 3368, 27%) had lower temperatures, heart rates, and respiratory rates, with Group C normotensive and Group D hypotensive. In the 6,919 patients with sepsis, Groups A and B were younger while Groups C and D were older. Group A had the lowest prevalence of congestive heart failure, hypertension, diabetes mellitus, and chronic kidney disease, while Group B had the highest prevalence. Groups A and D had the highest vasopressor use (p < 0.001 for all analyses above). In logistic regression, 30-day mortality was significantly higher in Groups A and D (p < 0.001 and p = 0.03, respectively). In the SMART trial, sub-phenotype significantly modified treatment effect (p = 0.03). Group D had significantly lower odds of mortality with balanced crystalloids compared to saline (odds ratio (OR) 0.39, 95% confidence interval (CI) 0.23-0.67, p < 0.001).

CONCLUSION

Sepsis sub-phenotypes based on vital sign trajectory were consistent across cohorts, had distinct outcomes, and different responses to treatment with balanced crystalloids versus saline.

The End of “One Size Fits All” Sepsis Therapies: Toward an Individualized Approach

Sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to an infection, remains a major challenge for clinicians and trialists. Despite decades of research and multiple randomized clinical trials, a specific therapeutic for sepsis is not available. The evaluation of therapeutics targeting components of host response anomalies in patients with sepsis has been complicated by the inability to identify those in this very heterogeneous population who are more likely to benefit from a specific intervention. Additionally, multiple and diverse host response aberrations often co-exist in sepsis, and knowledge of which dysregulated biological organ system or pathway drives sepsis-induced pathology in an individual patient is limited, further complicating the development of effective therapies. Here, we discuss the drawbacks of previous attempts to develop sepsis therapeutics and delineate a future wherein interventions will be based on the host response profile of a patient.

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.

Agents intervening against delirium in the intensive care unit trial-Protocol for a secondary Bayesian analysis

BACKGROUND

Delirium is highly prevalent in the intensive care unit (ICU) and is associated with high morbidity and mortality. The antipsychotic haloperidol is the most frequently used agent to treat delirium although this is not supported by solid evidence. The agents intervening against delirium in the intensive care unit (AID-ICU) trial investigates the effects of haloperidol versus placebo for the treatment of delirium in adult ICU patients.

METHODS

This protocol describes the secondary, pre-planned Bayesian analyses of the primary and secondary outcomes up to day 90 of the AID-ICU trial. We will use Bayesian linear regression models for all count outcomes and Bayesian logistic regression models for all dichotomous outcomes. We will adjust for stratification variables (site and delirium subtype) and use weakly informative priors supplemented with sensitivity analyses using sceptical priors. We will present results as absolute differences (mean differences and risk differences) and relative differences (ratios of means and relative risks). Posteriors will be summarised using median values as point estimates and percentile-based 95% credibility intervals. Probabilities of any benefit/harm, clinically important benefit/harm and clinically unimportant differences will be presented for all outcomes.

DISCUSSION

The results of this secondary, pre-planned Bayesian analysis will complement the primary frequentist analysis of the AID-ICU trial and facilitate a nuanced and probabilistic interpretation of the trial results.

Precision Care in Cardiac Arrest: ICECAP (PRECICECAP) Study Protocol and Informatics Approach

BACKGROUND

Most trials in critical care have been neutral, in part because between-patient heterogeneity means not all patients respond identically to the same treatment. The Precision Care in Cardiac Arrest: Influence of Cooling duration on Efficacy in Cardiac Arrest Patients (PRECICECAP) study will apply machine learning to high-resolution, multimodality data collected from patients resuscitated from out-of-hospital cardiac arrest. We aim to discover novel biomarker signatures to predict the optimal duration of therapeutic hypothermia and 90-day functional outcomes. In parallel, we are developing a freely available software platform for standardized curation of intensive care unit-acquired data for machine learning applications.

METHODS

The Influence of Cooling duration on Efficacy in Cardiac Arrest Patients (ICECAP) study is a response-adaptive, dose-finding trial testing different durations of therapeutic hypothermia. Twelve ICECAP sites will collect data for PRECICECAP from multiple modalities routinely used after out-of-hospital cardiac arrest, including ICECAP case report forms, detailed medication data, cardiopulmonary and electroencephalographic waveforms, and digital imaging and communications in medicine files (DICOMs). We partnered with Moberg Analytics to develop a freely available software platform to allow high-resolution critical care data to be used efficiently and effectively. We will use an autoencoder neural network to create low-dimensional representations of all raw waveforms and derivative features, censored at rewarming to ensure clinical usability to guide optimal duration of hypothermia. We will also consider simple features that are historically considered to be important. Finally, we will create a supervised deep learning neural network algorithm to directly predict 90-day functional outcome from large sets of novel features.

RESULTS

PRECICECAP is currently enrolling and will be completed in late 2025.

CONCLUSIONS

Cardiac arrest is a heterogeneous disease that causes substantial morbidity and mortality. PRECICECAP will advance the overarching goal of titrating personalized neurocritical care on the basis of robust measures of individual need and treatment responsiveness. The software platform we develop will be broadly applicable to hospital-based research after acute illness or injury.

Health-related quality-of-life and health-utility reporting in critical care

Mortality is a well-established patient-important outcome in critical care studies. In contrast, morbidity is less uniformly reported (given the myriad of critical care illnesses and complications of each) but may have a common end-impact on a patient’s functional capacity and health-related quality-of-life (HRQoL). Survival with a poor quality-of-life may not be acceptable depending on individual patient values and preferences. Hence, as mortality decreases within critical care, it becomes increasingly important to measure intensive care unit (ICU) survivor HRQoL. HRQoL measurements with a preference-based scoring algorithm can be converted into health utilities on a scale anchored at 0 (representing death) and 1 (representing full health). They can be combined with survival to calculate quality-adjusted life-years (QALY), which are one of the most widely used methods of combining morbidity and mortality into a composite outcome. Although QALYs have been use for health-technology assessment decision-making, an emerging and novel role would be to inform clinical decision-making for patients, families and healthcare providers about what expected HRQoL may be during and after ICU care. Critical care randomized control trials (RCTs) have not routinely measured or reported HRQoL (until more recently), likely due to incapacity of some patients to participate in patient-reported outcome measures. Further differences in HRQoL measurement tools can lead to non-comparable values. To this end, we propose the validation of a gold-standard HRQoL tool in critical care, specifically the EQ-5D-5L. Both combined health-utility and mortality (disaggregated) and QALYs (aggregated) can be reported, with disaggregation allowing for determination of which components are the main drivers of the QALY outcome. Increased use of HRQoL, health-utility, and QALYs in critical care RCTs has the potential to: (1) Increase the likelihood of finding important effects if they exist; (2) improve research efficiency; and (3) help inform optimal management of critically ill patients allowing for decision-making about their HRQoL, in additional to traditional health-technology assessments.

Validation of Messenger Ribonucleic Acid Markers Differentiating Among Human Acute Respiratory Distress Syndrome Subgroups in an Ovine Model of Acute Respiratory Distress Syndrome Phenotypes

Background

The discovery of biological subphenotypes in acute respiratory distress syndrome (ARDS) might offer a new approach to ARDS in general and possibly targeted treatment, but little is known about the underlying biology yet. To validate our recently described ovine ARDS phenotypes model, we compared a subset of messenger ribonucleic acid (mRNA) markers in leukocytes as reported before to display differential expression between human ARDS subphenotypes to the expression in lung tissue in our ovine ARDS phenotypes model (phenotype 1 (Ph1): hypoinflammatory; phenotype 2 (Ph2): hyperinflammatory).

Methods

We studied 23 anesthetized sheep on mechanical ventilation with observation times between 6 and 24 h. They were randomly allocated to the two phenotypes (n = 14 to Ph1 and n = 9 to Ph2). At study end, lung tissue was harvested and preserved in RNAlater. After tissue homogenization in TRIzol, total RNA was extracted and custom capture and reporter probes designed by NanoString Technologies were used to measure the expression of 14 genes of interest and the 6 housekeeping genes on a nCounter SPRINT profiler.

Results

Among the 14 mRNA markers, in all animals over all time points, 13 markers showed the same trend in ovine Ph2/Ph1 as previously reported in the MARS cohort: matrix metalloproteinase 8, olfactomedin 4, resistin, G protein-coupled receptor 84, lipocalin 2, ankyrin repeat domain 22, CD177 molecule, and transcobalamin 1 expression was higher in Ph2 and membrane metalloendopeptidase, adhesion G protein-coupled receptor E3, transforming growth factor beta induced, histidine ammonia-lyase, and sulfatase 2 expression was higher in Ph1. These expression patterns could be found when different sources of mRNA – such as blood leukocytes and lung tissue – were compared.

Conclusion

In human and ovine ARDS subgroups, similar activated pathways might be involved (e.g., oxidative phosphorylation, NF-κB pathway) that result in specific phenotypes.

Blood Purification Studies in the ICU: What Endpoints Should We Use?

The potential for treatment of the critically ill using blood purification techniques has been discussed for several decades. However, since the first attempts at applying extracorporeal techniques to patients with sepsis were described, there has been considerable hesitancy towards the widespread adoption of such methods, given the lack of mortality benefit observed and indeed the paucity of randomized controlled studies. However, this is not unique so far as studies on the critically ill are concerned where there is a dearth of studies providing a positive finding to influence clinical practice. Consequently, as well as targeted patient selection, it is perhaps time to consider endpoints other than mortality in studies on the critically ill, particularly in blood purification studies where, to-date, such heterogeneous groups of patients have been studied.

Association of Sequential Organ Failure Assessment (SOFA) components with mortality

BACKGROUND

Sequential Organ Failure Assessment (SOFA) is a practical method to describe and quantify the presence and severity of organ system dysfunctions and failures. Some proposals suggest that SOFA could be employed as an endpoint in trials. To justify this, all SOFA component scores should reflect organ dysfunctions of comparable severity. We aimed to investigate whether the associations of different SOFA components with in-hospital mortality are comparable.

METHODS

We performed a study based on nationwide register data on adult patients admitted to 26 Finnish intensive care units (ICUs) during 2012-2015. We determined the SOFA score as the maximum score in the first 24 hours after ICU admission. We defined organ failure (OF) as an organ-specific SOFA score of three or higher. We evaluated the association of different SOFA component scores with mortality.

RESULTS

Our study population comprised 63,756 ICU patients. Overall hospital mortality was 10.7%. In-hospital mortality was 22.5% for patients with respiratory failure, 34.8% for those with coagulation failure, 40.1% for those with hepatic failure, 14.9% for those with cardiovascular failure, 26.9% for those with neurologic failure and 34.6% for the patients with renal failure. Among patients with comparable total SOFA scores, the risk of death was lower in patients with cardiovascular OF compared with patients with other OFs.

CONCLUSIONS

All SOFA components are associated with mortality, but their weights are not comparable. High scores of other organ systems mean a higher risk of death than high cardiovascular scores. The scoring of cardiovascular dysfunction needs to be updated.

Higher versus lower oxygenation targets in COVID-19 patients with severe hypoxaemia (HOT-COVID) trial: Protocol for a secondary Bayesian analysis

BACKGROUND

Respiratory failure is the main cause of mortality and morbidity among ICU patients with coronavirus disease 2019 (COVID-19). In these patients, supplemental oxygen therapy is essential, but there is limited evidence the optimal target. To address this, the ongoing handling oxygenation targets in COVID-19 (HOT-COVID) trial was initiated to investigate the effect of a lower oxygenation target (partial pressure of arterial oxygen (PaO₂ ) of 8 kPa) versus a higher oxygenation target (PaO₂ of 12 kPa) in the ICU on clinical outcome in patients with COVID-19 and hypoxaemia.

METHODS

The HOT-COVID is planned to enrol 780 patients. This paper presents the protocol and statistical analysis plan for the conduct of a secondary Bayesian analysis of the primary outcome of HOT-COVID being days alive without life-support at 90 days and the secondary outcome 90-day all-cause mortality. Furthermore, both outcomes will be investigated for the presence heterogeneity of treatment effects based on four baseline parameters being sequential organ failure assessment score, PaO₂ /fraction of inspired oxygen ratio, highest dose of norepinephrine during the 24 h before randomisation, and plasma concentration of lactate at randomisation.

CONCLUSION

The results of this pre-planned secondary Bayesian analysis will complement the primary frequentist analysis of the HOT-COVID trial and may facilitate a more nuanced interpretation of the trial results.

Probiotics: Should We Use Them Proactively in Critical Illness?

Soni KD. Probiotics: Should We Use Them Proactively in Critical Illness? Indian J Crit Care Med 2022;26(3):266–267.

Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field

BACKGROUND

We aimed to determine the post-hoc power of randomized controlled trials (RCTs) in critical care, and describe the implications for long-term positive (PPV) and negative predictive value (NPV) of statistically significant and non-significant findings respectively in the research field.

METHODS

We reviewed three cohorts of RCTs. "Adult-RCTs" were 216 multicenter RCTs with a mortality outcome from a published systematic review. "Pediatric-RCTs" were 120 RCTs with a mortality outcome, obtained by search of picutrials.net. "Consecutive-RCTs" were 90 recent RCTs obtained by screening publications in 6 journals. Post-hoc power for each study was calculated at α 0.05 and 0.005, for measures of small, medium, and large effect-size, using G*Power software. Long-run expected PPV and NPV of critical care research field findings were then calculated.

RESULTS

With α 0.05, post-hoc power for small effect-size was very low in all RCT-cohorts (eg, median 24% in Adult-RCTs). For medium effect-size, post-hoc power was low, except for Adult-RCTs (eg, median 9% in Pediatric-RCTs). For large effect-size, post-hoc power for non-human-animal Consecutive-RCTs was low (median 32%). With α 0.005, post-hoc power was even lower. The corollary was that both PPV and NPV were poor for small effect-size, unless α 0.005 was used. Even with α 0.005, with realistic (vs. optimistic) prior probability of the alternative hypothesis, the PPV was low (eg, in Adult-RCTs 57.1% vs. 92.3%). Adding mild bias (0.1) reduced the PPV even further. For medium effect-size both PPV and NPV were better; nevertheless, with α 0.05 and realistic prior probability of the alternative hypothesis the PPV was poor, and with α 0.005 and mild bias (0.1) the PPV was very low (eg, Adult-RCTs median 44.1%).

CONCLUSIONS

To improve the predictive value of findings in the critical care research field, RCTs should be designed to have 80% power for realistic effect-size at α 0.005.

Renal microvascular endothelial cell responses in sepsis-induced acute kidney injury

Microvascular endothelial cells in the kidney have been a neglected cell type in sepsis-induced acute kidney injury (sepsis-AKI) research; yet, they offer tremendous potential as pharmacological targets. As endothelial cells in distinct cortical microvascular segments are highly heterogeneous, this Review focuses on endothelial cells in their anatomical niche. In animal models of sepsis-AKI, reduced glomerular blood flow has been attributed to inhibition of endothelial nitric oxide synthase activation in arterioles and glomeruli, whereas decreased cortex peritubular capillary perfusion is associated with epithelial redox stress. Elevated systemic levels of vascular endothelial growth factor, reduced levels of circulating sphingosine 1-phosphate and loss of components of the glycocalyx from glomerular endothelial cells lead to increased microvascular permeability. Although coagulation disbalance occurs in all microvascular segments, the molecules involved differ between segments. Induction of the expression of adhesion molecules and leukocyte recruitment also occurs in a heterogeneous manner. Evidence of similar endothelial cell responses has been found in kidney and blood samples from patients with sepsis. Comprehensive studies are needed to investigate the relationships between segment-specific changes in the microvasculature and kidney function loss in sepsis-AKI. The application of omics technologies to kidney tissues from animals and patients will be key in identifying these relationships and in developing novel therapeutics for sepsis.

Levosimendan in intensive care and emergency medicine: literature update and expert recommendations for optimal efficacy and safety

The inodilator levosimendan, in clinical use for over two decades, has been the subject of extensive clinical and experimental evaluation in various clinical settings beyond its principal indication in the management of acutely decompensated chronic heart failure. Critical care and emergency medicine applications for levosimendan have included postoperative settings, septic shock, and cardiogenic shock. As the experience in these areas continues to expand, an international task force of experts from 15 countries (Austria, Belgium, China, Croatia, Finland, France, Germany, Greece, Hungary, Italy, the Netherlands, Spain, Sweden, Switzerland, and the USA) reviewed and appraised the latest additions to the database of levosimendan use in critical care, considering all the clinical studies, meta-analyses, and guidelines published from September 2019 to November 2021. Overall, the authors of this opinion paper give levosimendan a "should be considered" recommendation in critical care and emergency medicine settings, with different levels of evidence in postoperative settings, septic shock, weaning from mechanical ventilation, weaning from veno-arterial extracorporeal membrane oxygenation, cardiogenic shock, and Takotsubo syndrome, in all cases when an inodilator is needed to restore acute severely reduced left or right ventricular ejection fraction and overall haemodynamic balance, and also in the presence of renal dysfunction/failure.