Precision medicine for all? Challenges and opportunities for a precision medicine approach to critical illness

Impact of different intravenous bolus rates on fluid and electrolyte balance and mortality in critically ill patients

The effect of intravenous bolus rates on patient outcomes is a complex and crucial aspect of critical care. Fluid challenges are commonly used in critically ill patients to manage their hemodynamic status, but there is limited information available on the specifics of when, how much, and at what rate fluids should be administered during these challenges. The aim of this review is to thoroughly examine the relationship between intravenous bolus rates, fluid-electrolyte balance, and mortality and to analyze key research findings and methodologies to understand these complex dynamics better. Fluid challenges are commonly employed in managing hemodynamic status in this population, yet there is limited information on the optimal timing, volume, and rate of fluid administration. Utilizing a narrative review approach, the analysis identified nine relevant studies that investigate these variables. The findings underscore the importance of a precise and individualized approach in clinical settings, highlighting the need to tailor intravenous bolus rates to each patient's specific needs to maximize outcomes. This review provides valuable insights that can inform and optimize clinical practices in critical care, emphasizing the necessity of meticulous and exact strategies in fluid administration.

Toward Precision in Critical Care Research: Methods for Observational and Interventional Studies

Critical care trials evaluate the effect of interventions in patients with diverse personal histories and causes of illness, often under the umbrella of heterogeneous clinical syndromes, such as sepsis or acute respiratory distress syndrome. Given this variation, it is reasonable to expect that the effect of treatment on outcomes may differ for individuals with variable characteristics. However, in randomized controlled trials, efficacy is typically assessed by the average treatment effect (ATE), which quantifies the average effect of the intervention on the outcome in the study population. Importantly, the ATE may hide variations of the treatment's effect on a clinical outcome across levels of patient characteristics, which may erroneously lead to the conclusion that an intervention does not work overall when it may in fact benefit certain patients. In this review, we describe methodological approaches for assessing heterogeneity of treatment effect (HTE), including expert-derived subgrouping, data-driven subgrouping, baseline risk modeling, treatment effect modeling, and individual treatment rule estimation. Next, we outline how insights from HTE analyses can be incorporated into the design of clinical trials. Finally, we propose a research agenda for advancing the field and bringing HTE approaches to the bedside.

The need for a change in medical research thinking. Eco-systemic research frames are better suited to explore patterned disease behaviors

Many practicing physicians struggle to properly evaluate clinical research studies - they either simply do not know them, regard the reported findings as 'truth' since they were reported in a 'reputable' journal and blindly implement these interventions, or they disregard them as having little pragmatic impact or relevance to their daily clinical work. Three aspects for the latter are highlighted: study populations rarely reflect their practice population, the absolute average benefits on specific outcomes in most controlled studies, while statistically significant, are so small that they are pragmatically irrelevant, and overall mortality between the intervention and control groups are unaffected. These observations underscore the need to rethink our research approaches in the clinical context - moving from the predominant reductionist to an eco-systemic research approach will lead to knowledge better suited to clinical decision-making for an individual patient as it takes into account the complex interplay of multi-level variables that impact health outcomes in the real-world setting.

Bridging the clinical-research gap: Harnessing an electronic data capture, integration, and visualization platform to systematically assess prospective patient-reported outcomes in mitochondrial medicine

PURPOSE

Optimizing individualized clinical care in heterogeneous rare disorders, such as primary mitochondrial disease (PMD), will require gaining more comprehensive and objective understanding of the patient experience by longitudinally tracking quantifiable patient-specific outcomes and integrating subjective data with clinical data to monitor disease progression and targeted therapeutic effects.

METHODS

Electronic surveys of patient (and caregiver) reported outcome (PRO) measures were administered in REDCap within clinical domains commonly impaired in patients with PMD in the context of their ongoing routine care, including quality of life, fatigue, and functional performance. Descriptive statistics, group comparisons, and inter-measure correlations were used to evaluate system feasibility, utility of PRO results, and consistency across outcome measure domains. Real-time tracking and visualization of longitudinal individual-level and cohort-level data were facilitated by a customized data integration and visualization system, MMFP-Tableau.

RESULTS

An efficient PRO electronic capture and analysis system was successfully implemented within a clinically and genetically heterogeneous rare disease clinical population spanning all ages. Preliminary data analyses demonstrated the flexibility of this approach for a range of PROs, as well as the value of selected PRO scales to objectively capture qualitative functional impairment in four key clinical domains. High inter-measure reliability and correlation were observed. Between-group analyses revealed that adults with PMD reported significantly worse quality of life and greater fatigue than did affected children, while PMD patients with nuclear gene disorders reported lower functioning relative to those with an mtDNA gene disorder in several clinical domains.

CONCLUSION

Incorporation of routine electronic data collection, integration, visualization, and analysis of relevant PROs for rare disease patients seen in the clinical setting was demonstrated to be feasible, providing prospective and quantitative data on key clinical domains relevant to the patient experience. Further work is needed to validate specific PROs in diverse PMD patients and cohorts, and to formally evaluate the clinical impact and utility of harnessing integrated data systems to objectively track and integrate quantifiable PROs in the context of rare disease patient clinical care.

Identification and validation of sepsis subphenotypes using time-series data

Purpose

The recognition of sepsis as a heterogeneous syndrome necessitates identifying distinct subphenotypes to select targeted treatment.

Methods

Patients with sepsis from the MIMIC-IV database (2008-2019) were randomly divided into a development cohort (80%) and an internal validation cohort (20%). Patients with sepsis from the ICU database of Peking University People's Hospital (2008-2022) were included in the external validation cohort. Time-series k-means clustering analysis and dynamic time warping was performed to develop and validate sepsis subphenotypes by analyzing the trends of 21 vital signs and laboratory indicators within 24 h after sepsis onset. Inflammatory biomarkers were compared in the ICU database of Peking University People's Hospital, whereas treatment heterogeneity was compared in the MIMIC-IV database.

Findings

Three sub-phenotypes were identified in the development cohort. Type A patients (N = 2525, 47%) exhibited stable vital signs and fair organ function, type B (N = 1552, 29%) was exhibited an obvious inflammatory response and stable organ function, and type C (N = 1251, 24%) exhibited severely impaired organ function with a deteriorating tendency. Type C demonstrated the highest mortality rate (33%) and levels of inflammatory biomarkers, followed by type B (24%), whereas type A exhibited the lowest mortality rate (11%) and levels of inflammatory biomarkers. These subphenotypes were confirmed in both the internal and external cohorts, demonstrating similar features and comparable mortality rates. In type C patients, survivors had significantly lower fluid intake within 24 h after sepsis onset (median 2891 mL, interquartile range (IQR) 1530-5470 mL) than that in non-survivors (median 4342 mL, IQR 2189-7305 mL). For types B and C, survivors showed a higher proportion of indwelling central venous catheters (p < 0.05).

Conclusion

Three novel phenotypes of patients with sepsis were identified and validated using time-series data, revealing significant heterogeneity in inflammatory biomarkers, treatments, and consistency across cohorts.

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

BACKGROUND

Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.

METHODS

Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.

RESULTS

Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.

CONCLUSIONS

During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Sepsis-associated acute kidney injury: recent advances in enrichment strategies, sub-phenotyping and clinical trials

Acute kidney injury (AKI) often complicates sepsis and is associated with high morbidity and mortality. In recent years, several important clinical trials have improved our understanding of sepsis-associated AKI (SA-AKI) and impacted clinical care. Advances in sub-phenotyping of sepsis and AKI and clinical trial design offer unprecedented opportunities to fill gaps in knowledge and generate better evidence for improving the outcome of critically ill patients with SA-AKI. In this manuscript, we review the recent literature of clinical trials in sepsis with focus on studies that explore SA-AKI as a primary or secondary outcome. We discuss lessons learned and potential opportunities to improve the design of clinical trials and generate actionable evidence in future research. We specifically discuss the role of enrichment strategies to target populations that are most likely to derive benefit and the importance of patient-centered clinical trial endpoints and appropriate trial designs with the aim to provide guidance in designing future trials.

Advances and Challenges in Sepsis Management: Modern Tools and Future Directions

Sepsis, a critical condition marked by systemic inflammation, profoundly impacts both innate and adaptive immunity, often resulting in lymphopenia. This immune alteration can spare regulatory T cells (Tregs) but significantly affects other lymphocyte subsets, leading to diminished effector functions, altered cytokine profiles, and metabolic changes. The complexity of sepsis stems not only from its pathophysiology but also from the heterogeneity of patient responses, posing significant challenges in developing universally effective therapies. This review emphasizes the importance of phenotyping in sepsis to enhance patient-specific diagnostic and therapeutic strategies. Phenotyping immune cells, which categorizes patients based on clinical and immunological characteristics, is pivotal for tailoring treatment approaches. Flow cytometry emerges as a crucial tool in this endeavor, offering rapid, low cost and detailed analysis of immune cell populations and their functional states. Indeed, this technology facilitates the understanding of immune dysfunctions in sepsis and contributes to the identification of novel biomarkers. Our review underscores the potential of integrating flow cytometry with omics data, machine learning and clinical observations to refine sepsis management, highlighting the shift towards personalized medicine in critical care. This approach could lead to more precise interventions, improving outcomes in this heterogeneously affected patient population.

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.

Relationship of Age And Mobility Levels During Physical Rehabilitation With Clinical Outcomes in Critical Illness

Objective

To determine whether age, mobility level, and change in mobility level across the first 3 physical rehabilitation sessions associate with clinical outcomes of patients who are critically ill.

Design

Retrospective, observational cohort study.

Setting

Medical Intensive Care Unit (MICU).

Participants

Hospitalized adults (n = 132) who received 3 or more, consecutive rehabilitation sessions in the MICU.

Interventions

Not applicable.

Measurements and Main Results

Sample included 132 patients with 60 (45%) classified as younger (18-59 years) and 72 (55%) as older (60+ years). The most common diagnosis was sepsis/septicemia (32.6%). Older relative to younger patients had a significantly slower rate of improvement in ICU Mobility Scale (IMS) scores across rehabilitation sessions (mean slope coefficient 0.3 vs 0.6 points, P<.001), were less likely to be discharged to home (30.6% vs 55.0%, P=.005), and were more likely to die within 12 months (41.7% vs 25.0%, P=.046). Covariate-adjusted models indicated greater early improvement in IMS scores were associated with discharge home (P=.005). Longer time to first rehabilitation session, lower initial IMS scores, and slower improvement in IMS scores were associated with increased ICU days (all P<.03).

Conclusion

Older age and not achieving the mobility milestone of sitting at edge of bed or limited progression of mobility across sessions is associated with poor patient outcomes. Our findings suggest that age and mobility level contribute to outcome prognostication, and can aide in clinical phenotyping and rehabilitative service allocation.

The Potential of Meta-Proteomics and Artificial Intelligence to Establish the Next Generation of Probiotics for Personalized Healthcare

The symbiosis of probiotic bacteria with humans has rendered various health benefits while providing nutrition and a suitable environment for their survival. However, the probiotics must survive unfavorable gut conditions to exert beneficial effects. The intrinsic resistance of probiotics to survive harsh conditions results from a myriad of proteins. Interaction of microbial proteins with the host is indispensable for modulating the gut microbiome, such as interaction with cell receptors and protective action against pathogens. The complex interplay of proteins should be unraveled by utilizing metaproteomic strategies. The contribution of probiotics to health is now widely accepted. However, due to the inconsistency of generalized probiotics, contemporary research toward precision probiotics has gained momentum for customized treatment. This review explores the application of metaproteomics and AI/ML algorithms in resolving multiomics data analysis and in silico prediction of microbial features for screening specific beneficial probiotic organisms. Implementing these integrative strategies could augment the potential of precision probiotics for personalized healthcare.

Machine learning model identification and prediction of patients' need for ICU admission: A systematic review

BACKGROUND

The emergency department (ED) triage process serves as a crucial first step for patients seeking acute care, This initial assessment holds crucial implications for patient survival and prognosis. In this study, a systematic review of the existing literature was performed to investigate the performance of machine learning (ML) models in recognizing and predicting the need for intensive care among ED patients.

METHODS

Four prominent databases (PubMed, Embase, Cochrane Library and Web of Science) were searched for relevant literature published up to April 28, 2023. The Prediction model study Risk of Bias Assessment Tool (PROBAST) was employed to evaluate the risk of bias and feasibility of prediction models.

RESULTS

In ten studies, the main algorithms used were Gradient Boostin, Logistic Regressio, Neural Network, Support Vector Machines, Random Forest. The performance of each model was as follows: Gradient Boosting had a sensitivity range of 0.3 to 0.96, specificity range of 0.6 to 0.99, accuracy range of 0.37 to 0.99, precision range of 0.3 to 0.96, and AUC value range of 0.68 to 0.93; Logistic Regression had a sensitivity range of 0.46 to 0.97, specificity range of 0.28 to 0.99, accuracy range of 0.66 to 0.97, precision range of 0.27 to 0.63, and AUC value range of 0.72 to 0.97; Neural Networks had a sensitivity range of 0.45 to 0.96, specificity range of 0.58 to 0.99, accuracy range of 0.36 to 0.97, precision range of 0.27 to 0.96, and AUC value range of 0.67 to 0.91; Support Vector Machines had a sensitivity range of 0.49 to 0.83, specificity range of 0.94 to 0.98, accuracy range of 0.33 to 0.97, precision range of 0.53 to 0.94, and AUC values were not reported; Random Forests had a sensitivity range of 0.75 to 0.91, specificity range of 0.77 to 0.94, accuracy range of 0.35 to 0.77, precision range of 0.36 to 0.94, and AUC value of 0.83.

CONCLUSION

ML models have demonstrated good performance in identifying and predicting critically ill patients in ED triage. However, because of the limited number of studies on each model, further high-quality prospective research is needed to validate these findings.

Optimizing Vasopressin Use and Initiation Timing in Septic Shock: A Narrative Review

TOPIC IMPORTANCE

This review discusses the rationale for vasopressin use, summarizes the results of clinical trials evaluating vasopressin, and focuses on the timing of vasopressin initiation to provide clinicians guidance for optimal adjunctive vasopressin initiation in patients with septic shock.

REVIEW FINDINGS

Patients with septic shock require vasoactive agents to restore adequate tissue perfusion. After norepinephrine, vasopressin is the suggested second-line adjunctive agent in patients with persistent inadequate mean arterial pressure. Vasopressin use in practice is heterogeneous likely because of inconsistent clinical trial findings, the lack of specific recommendations for when it should be used, and the high drug acquisition cost. Despite these limitations, vasopressin has demonstrated price inelastic demand, and its use in the United States has continued to increase. However, questions remain regarding optimal vasopressin use in patients with septic shock, particularly regarding patient selection and the timing of vasopressin initiation.

SUMMARY

Experimental studies evaluating the initiation timing of vasopressin in patients with septic shock are limited, and recent observational studies have revealed an association between vasopressin initiation at lower norepinephrine-equivalent doses or lower lactate concentrations and lower mortality.

Precision fluid and vasoactive drug therapy for critically ill patients

There are several clinical practice guidelines concerning the use of fluid and vasoactive drug therapies in critically ill adult patients, but the recommendations in these guidelines are often based on low-quality evidence. Further, some were compiled prior to the publication of landmark clinical trials, particularly in the comparison of balanced crystalloid and normal saline. An important consideration in the treatment of critically ill patients is the application of precision medicine to provide the most effective care to groups of patients most likely to benefit from the therapy. Although not currently widely integrated into these practice guidelines, the utility of precision medicine in critical illness is a recognized research priority for fluid and vasoactive therapy management. The purpose of this narrative review was to illustrate the evaluation and challenges of providing precision fluid and vasoactive therapies to adult critically ill patients. The review includes a discussion of important investigations published after the release of currently available clinical practice guidelines to provide insight into how recommendations and research priorities may change future guidelines and bedside care for critically ill patients.

Biomarker Enrichment in Sepsis-Associated Acute Kidney Injury: Finding High-Risk Patients in the Intensive Care Unit

BACKGROUND

Sepsis-associated acute kidney injury (AKI) is a leading comorbidity in admissions to the intensive care unit. While a gold standard definition exists, it remains imperfect and does not allow for the timely identification of patients in the setting of critical illness. This review will discuss the use of biochemical and electronic biomarkers to allow for prognostic and predictive enrichment of patients with sepsis-associated AKI over and above the use of serum creatinine and urine output.

SUMMARY

Current data suggest that several biomarkers are capable of identifying patients with sepsis at risk for the development of severe AKI and other associated morbidity. This review discusses these data and these biomarkers in the setting of sub-phenotyping and endotyping sepsis-associated AKI. While not all these tests are widely available and some require further validation, in the near future we anticipate several new tools to help nephrologists and other providers better care for patients with sepsis-associated AKI.

KEY MESSAGES

Predictive and prognostic enrichment using both traditional biomarkers and novel biomarkers in the setting of sepsis can identify subsets of patients with either similar outcomes or similar pathophysiology, respectively. Novel biomarkers can identify kidney injury in patients without consensus definition AKI (e.g., changes in creatinine or urine output) and can predict other adverse outcomes (e.g., severe consensus definition AKI, inpatient mortality). Finally, emerging artificial intelligence and machine learning-derived risk models are able to predict sepsis-associated AKI in critically ill patients using advanced learning techniques and several laboratory and vital sign measurements.

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.

Continuous time recurrent neural networks: Overview and benchmarking at forecasting blood glucose in the intensive care unit

OBJECTIVE

Blood glucose measurements in the intensive care unit (ICU) are typically made at irregular intervals. This presents a challenge in choice of forecasting model. This article gives an overview of continuous time autoregressive recurrent neural networks (CTRNNs) and evaluates how they compare to autoregressive gradient boosted trees (GBT) in forecasting blood glucose in the ICU.

METHODS

Continuous time autoregressive recurrent neural networks (CTRNNs) are a deep learning model that account for irregular observations through incorporating continuous evolution of the hidden states between observations. This is achieved using a neural ordinary differential equation (ODE) or neural flow layer. In this manuscript, we give an overview of these models, including the varying architectures that have been proposed to account for issues such as ongoing medical interventions. Further, we demonstrate the application of these models to probabilistic forecasting of blood glucose in a critical care setting using electronic medical record and simulated data and compare with GBT and linear models.

RESULTS

The experiments confirm that addition of a neural ODE or neural flow layer generally improves the performance of autoregressive recurrent neural networks in the irregular measurement setting. However, several CTRNN architecture are outperformed by a GBT model (Catboost), with only a long short-term memory (LSTM) and neural ODE based architecture (ODE-LSTM) achieving comparable performance on probabilistic forecasting metrics such as the continuous ranked probability score (ODE-LSTM: 0.118 ± 0.001; Catboost: 0.118 ± 0.001), ignorance score (0.152 ± 0.008; 0.149 ± 0.002) and interval score (175 ± 1; 176 ± 1).

CONCLUSION

The application of deep learning methods for forecasting in situations with irregularly measured time series such as blood glucose shows promise. However, appropriate benchmarking by methods such as GBT approaches (plus feature transformation) are key in highlighting whether novel methodologies are truly state of the art in tabular data settings.

How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials

Large volumes of data are collected on critically ill patients, and using data science to extract information from the electronic medical record (EMR) and to inform the design of clinical trials represents a new opportunity in critical care research. Using improved methods of phenotyping critical illnesses, subject identification and enrollment, and targeted treatment group assignment alongside newer trial designs such as adaptive platform trials can increase efficiency while lowering costs. Some tools such as the EMR to automate data collection are already in use. Refinement of data science approaches in critical illness research will allow for better clinical trials and, ultimately, improved patient outcomes.

Open-inhaler versus single-inhaler triple therapy (long-acting muscarinic antagonist, inhaled corticosteroid, and long-acting β2-agonist) in asthma patients: a narrative review

OBJECTIVE

To review the evidence for the use of open-inhaler (inhaled corticosteroid [ICS] plus long-acting β2-agonist [LABA] with separate add-on long-acting muscarinic antagonist [LAMA]) versus single-inhaler triple therapy (ICS/LABA/LAMA combination) and the merits of add-on LAMA to ICS/LABA in patients with uncontrolled asthma.

DATA SOURCES

Original research articles were identified from PubMed using the search term "triple therapy asthma." Information was also retrieved from the ClinicalTrials.gov website.

STUDY SELECTIONS

Articles detailing the use of add-on LAMA to ICS plus LABA (open-inhaler triple therapy), and closed triple therapy compared with ICS plus LABA dual therapy, addressing patient symptoms, exacerbations, and health-related quality of life.

RESULTS

Open-inhaler triple therapy was associated with a significantly reduced incidence of hospitalizations and emergency department visits and a decrease in ICS dose, oral corticosteroids use, and antibiotics use. Exacerbations and acute respiratory events were also reduced. Single-inhaler triple therapy showed a greater improvement in lung function, asthma control, and health status and was noninferior to open-inhaler triple therapy for Asthma Quality of Life Questionnaire scores. Single-inhaler triple therapy may also lead to improved therapy adherence.

CONCLUSION

Add-on LAMA to ICS plus LABA (open- or single-inhaler triple therapy) improves the response in patients who remain symptomatic and provides a reasonable alternative to ICS dose escalation in treatment-refractory patients.

Clinical Sepsis Phenotypes in Critically Ill Patients

Sepsis, defined as the life-threatening dysregulated host response to an infection leading to organ dysfunction, is considered as one of the leading causes of mortality worldwide, especially in intensive care units (ICU). Moreover, sepsis remains an enigmatic clinical syndrome, with complex pathophysiology incompletely understood and a great heterogeneity both in terms of clinical expression, patient response to currently available therapeutic interventions and outcomes. This heterogeneity proves to be a major obstacle in our quest to deliver improved treatment in septic critical care patients; thus, identification of clinical phenotypes is absolutely necessary. Although this might be seen as an extremely difficult task, nowadays, artificial intelligence and machine learning techniques can be recruited to quantify similarities between individuals within sepsis population and differentiate them into distinct phenotypes regarding not only temperature, hemodynamics or type of organ dysfunction, but also fluid status/responsiveness, trajectories in ICU and outcome. Hopefully, we will eventually manage to determine both the subgroup of septic patients that will benefit from a therapeutic intervention and the correct timing of applying the intervention during the disease process.

Looking ahead in early-phase trial design to improve the drug development process: examples in oncology

BACKGROUND

Clinical trial design must consider the specific resource constraints and overall goals of the drug development process (DDP); for example, in designing a phase I trial to evaluate the safety of a drug and recommend a dose for a subsequent phase II trial. Here, we focus on design considerations that involve the sequence of clinical trials, from early phase I to late phase III, that constitute the DDP.

METHODS

We discuss how stylized simulation models of clinical trials in an oncology DDP can quantify important relationships between early-phase trial designs and their consequences for the remaining phases of development. Simulations for three illustrative settings are presented, using stylized models of the DDP that mimic trial designs and decisions, such as the potential discontinuation of the DDP.

RESULTS

We describe: (1) the relationship between a phase II single-arm trial sample size and the likelihood of a positive result in a subsequent phase III confirmatory trial; (2) the impact of a phase I dose-finding design on the likelihood that the DDP will produce evidence of a safe and effective therapy; and (3) the impact of a phase II enrichment trial design on the operating characteristics of a subsequent phase III confirmatory trial.

CONCLUSIONS

Stylized models of the DDP can support key decisions, such as the sample size, in the design of early-phase trials. Simulation models can be used to estimate performance metrics of the DDP under realistic scenarios; for example, the duration and the total number of patients enrolled. These estimates complement the evaluation of the operating characteristics of early-phase trial design, such as power or accuracy in selecting safe and effective dose levels.

[Individualized treatment in anesthesiology and intensive care medicine]

BACKGROUND

Individualized medicine uses data on biological characteristics of individual patients in order to tailor treatment planning to their unique constitution. With respect to the practice of anesthesiology and intensive care medicine, it bears the potential to systematize the often complex medical care of critically ill patients and to improve outcomes.

OBJECTIVE

The aim of this narrative review is to provide an overview of the possible applications of the principles of individualized medicine in anesthesiology and intensive care medicine.

MATERIAL AND METHODS

Based on a search in MEDLINE, CENTRAL and Google Scholar, the results of previous studies and systematic reviews are narratively synthesized and the implications for the scientific and clinical practice are presented.

RESULTS AND DISCUSSION

There are possibilities for individualization and an increase in precision of patient care in most if not all problems in anesthesiology and symptoms in intensive medical care. Even now, all practicing physicians can initiate measures to individualize treatment at different timepoints throughout the course of treatment. Individualized medicine can supplement and be integrated into protocols. Plans for future applications of individualized medicine interventions should consider the feasibility in a real-world setting. Clinical studies should contain process evaluations in order to create ideal preconditions for a successful implementation. Quality management, audits and feedback should become a standard procedure to ensure sustainability. In the long run, individualization of care, especially in the critically ill, should be enshrined in guidelines and become an integral part of clinical practice.

Pediatric Critical Care in the Twenty-first Century and Beyond

Pediatric critical care addresses prevention, diagnosis, and treatment of organ dysfunction in the setting of increasingly complex patients, therapies, and environments. Soon burgeoning data science will enable all aspects of intensive care: driving facilitated diagnostics, empowering a learning health-care environment, promoting continuous advancement of care, and informing the continuum of critical care outside the intensive care unit preceding and following critical illness/injury. Although novel technology will progressively objectify personalized critical care, humanism, practiced at the bedside, defines the essence of pediatric critical care now and in the future.

Physiological and clinical variables identify ARDS classes and therapeutic heterogeneity to glucocorticoids: a retrospective study

OBJECTIVE

We aimed to identify new classes in acute respiratory distress syndrome (ARDS) using physiological and clinical variables and to explore heterogeneity in the effects of glucocorticoid therapy between classes.

METHODS

Using the Medical Information Mart for Intensive Care-IV database, we identified patients with ARDS. Potential profile analysis was used to identify classes with physiological and clinical data as delineating variables. Baseline characteristics and clinical outcomes were compared between classes. The effect of glucocorticoid treatment was explored by stratifying by class and glucocorticoid treatment.

RESULTS

From 2008 to 2019, 1104 patients with ARDS were enrolled in the study. The 2-class potential analysis model had the best fit (P < 0.0001), with 78% of patients falling into class 1 and 22% into class 2. Additional classes did not improve the model fit. Patients in class 2 had higher anion gap, lactate, creatinine, and glucose levels and lower residual base, blood pressure, and bicarbonate compared with class 1. In-hospital mortality and 28-day mortality were significantly higher among patients in class 2 than those in class 1 (P < 0.001). Heterogeneity of glucocorticoid treatment was observed, stratified by class and treatment, with no significant effect in class 1 (P = 0.496), increased mortality in class 2 (P = 0.001), and a significant interaction (P = 0.0381). In class 2, 28-day survival was significantly lower with glucocorticoid treatment compared with no hormone treatment (P = 0.001).

CONCLUSION

We used clinical and physiological variables to identify two classes of non-COVID-19-associated ARDS with different baseline characteristics and clinical outcomes. The response to glucocorticoid therapy varied among different classes of patients.

Heterogeneous Treatment Effects of Therapeutic-Dose Heparin in Patients Hospitalized for COVID-19

IMPORTANCE

Randomized clinical trials (RCTs) of therapeutic-dose heparin in patients hospitalized with COVID-19 produced conflicting results, possibly due to heterogeneity of treatment effect (HTE) across individuals. Better understanding of HTE could facilitate individualized clinical decision-making.

OBJECTIVE

To evaluate HTE of therapeutic-dose heparin for patients hospitalized for COVID-19 and to compare approaches to assessing HTE.

DESIGN, SETTING, AND PARTICIPANTS

Exploratory analysis of a multiplatform adaptive RCT of therapeutic-dose heparin vs usual care pharmacologic thromboprophylaxis in 3320 patients hospitalized for COVID-19 enrolled in North America, South America, Europe, Asia, and Australia between April 2020 and January 2021. Heterogeneity of treatment effect was assessed 3 ways: using (1) conventional subgroup analyses of baseline characteristics, (2) a multivariable outcome prediction model (risk-based approach), and (3) a multivariable causal forest model (effect-based approach). Analyses primarily used bayesian statistics, consistent with the original trial.

EXPOSURES

Participants were randomized to therapeutic-dose heparin or usual care pharmacologic thromboprophylaxis.

MAIN OUTCOMES AND MEASURES

Organ support-free days, assigning a value of -1 to those who died in the hospital and the number of days free of cardiovascular or respiratory organ support up to day 21 for those who survived to hospital discharge; and hospital survival.

RESULTS

Baseline demographic characteristics were similar between patients randomized to therapeutic-dose heparin or usual care (median age, 60 years; 38% female; 32% known non-White race; 45% Hispanic). In the overall multiplatform RCT population, therapeutic-dose heparin was not associated with an increase in organ support-free days (median value for the posterior distribution of the OR, 1.05; 95% credible interval, 0.91-1.22). In conventional subgroup analyses, the effect of therapeutic-dose heparin on organ support-free days differed between patients requiring organ support at baseline or not (median OR, 0.85 vs 1.30; posterior probability of difference in OR, 99.8%), between females and males (median OR, 0.87 vs 1.16; posterior probability of difference in OR, 96.4%), and between patients with lower body mass index (BMI <30) vs higher BMI groups (BMI ≥30; posterior probability of difference in ORs >90% for all comparisons). In risk-based analysis, patients at lowest risk of poor outcome had the highest propensity for benefit from heparin (lowest risk decile: posterior probability of OR >1, 92%) while those at highest risk were most likely to be harmed (highest risk decile: posterior probability of OR <1, 87%). In effect-based analysis, a subset of patients identified at high risk of harm (P = .05 for difference in treatment effect) tended to have high BMI and were more likely to require organ support at baseline.

CONCLUSIONS AND RELEVANCE

Among patients hospitalized for COVID-19, the effect of therapeutic-dose heparin was heterogeneous. In all 3 approaches to assessing HTE, heparin was more likely to be beneficial in those who were less severely ill at presentation or had lower BMI and more likely to be harmful in sicker patients and those with higher BMI. The findings illustrate the importance of considering HTE in the design and analysis of RCTs.

TRIAL REGISTRATION

ClinicalTrials.gov Identifiers: NCT02735707, NCT04505774, NCT04359277, NCT04372589.

The double sides of NLRP3 inflammasome activation in sepsis

Sepsis is defined as a life-threatening organ dysfunction induced by a dysregulated host immune response to infection. Immune response induced by sepsis is complex and dynamic. It is schematically described as an early dysregulated systemic inflammatory response leading to organ failures and early deaths, followed by the development of persistent immune alterations affecting both the innate and adaptive immune responses associated with increased risk of secondary infections, viral reactivations, and late mortality. In this review, we will focus on the role of NACHT, leucin-rich repeat and pyrin-containing protein 3 (NLRP3) inflammasome in the pathophysiology of sepsis. NLRP3 inflammasome is a multiproteic intracellular complex activated by infectious pathogens through a two-step process resulting in the release of the pro-inflammatory cytokines IL-1β and IL-18 and the formation of membrane pores by gasdermin D, inducing a pro-inflammatory form of cell death called pyroptosis. The role of NLRP3 inflammasome in the pathophysiology of sepsis can be ambivalent. Indeed, although it might protect against sepsis when moderately activated after initial infection, excessive NLRP3 inflammasome activation can induce dysregulated inflammation leading to multiple organ failure and death during the acute phase of the disease. Moreover, this activation might become exhausted and contribute to post-septic immunosuppression, driving impaired functions of innate and adaptive immune cells. Targeting the NLRP3 inflammasome could thus be an attractive option in sepsis either through IL-1β and IL-18 antagonists or through inhibition of NLRP3 inflammasome pathway downstream components. Available treatments and results of first clinical trials will be discussed.

A smart paper-based electrochemical sensor for reliable detection of iron ions in serum

The fast-growing healthcare demand for user-friendly and affordable analytical tools is driving the efforts to develop reliable platforms for the customization of therapy based on individual health conditions. In this overall scenario, we developed a paper-based electrochemical sensor for the quantification of iron ions in serum as a cost-effective sensing tool for the correct supplement administration. In detail, the working electrode of the screen-printed device has been modified with a nanocomposite constituted of carbon black and gold nanoparticles with a drop-casting procedure. Square wave voltammetry has been adopted as an electrochemical technique. This sensor was further modified with Nafion for iron quantification in serum after sample treatment with trifluoroacetic acid. Under optimized conditions, iron ions have been detected with a LOD down to 0.05 mg/L and a linearity up to 10 mg/L in standard solution. The obtained results have been compared with reference methods namely commercial colorimetric assay and atomic absorption spectroscopy, obtaining a good correlation within the experimental errors. These results demonstrated the suitability of the developed paper-based sensor for future applications in precision medicine of iron-deficiency diseases.

THE EUROPEAN SHOCK SOCIETY MEETS THE IMMUNOSEP CONSORTIUM FOR PERSONALIZED SEPSIS TREATMENT

ABSTRACT

The unacceptable high mortality of severe infections and sepsis led over the years to understand the need for adjunctive immunotherapy to modulate the dysregulated host response of the host. However, not all patients should receive the same type of treatment. The immune function may largely differ from one patient to the other. The principles of precision medicine require that some biomarker is used to capture the immune function of the host and guide the best candidate therapy. This is the approach of the ImmunoSep randomized clinical trial (NCT04990232) where patients are allocated to treatment with anakinra or recombinant interferon gamma tailored to immune signs of macrophage activation-like syndrome and immunoparalysis respectively. ImmunoSep is a first-in-class paradigm of precision medicine for sepsis. Other approaches need to consider classification by sepsis endotypes, targeting T cell and application of stem cells. Basic principle for any trial to be successful is the delivery of appropriate antimicrobial therapy as standard-of-care taking into consideration not just the likelihood for resistant pathogens but also the pharmacokinetic/pharmacodynamic mode of action of the administered antimicrobial.

Sepsis-associated acute kidney injury: consensus report of the 28th Acute Disease Quality Initiative workgroup

Sepsis-associated acute kidney injury (SA-AKI) is common in critically ill patients and is strongly associated with adverse outcomes, including an increased risk of chronic kidney disease, cardiovascular events and death. The pathophysiology of SA-AKI remains elusive, although microcirculatory dysfunction, cellular metabolic reprogramming and dysregulated inflammatory responses have been implicated in preclinical studies. SA-AKI is best defined as the occurrence of AKI within 7 days of sepsis onset (diagnosed according to Kidney Disease Improving Global Outcome criteria and Sepsis 3 criteria, respectively). Improving outcomes in SA-AKI is challenging, as patients can present with either clinical or subclinical AKI. Early identification of patients at risk of AKI, or at risk of progressing to severe and/or persistent AKI, is crucial to the timely initiation of adequate supportive measures, including limiting further insults to the kidney. Accordingly, the discovery of biomarkers associated with AKI that can aid in early diagnosis is an area of intensive investigation. Additionally, high-quality evidence on best-practice care of patients with AKI, sepsis and SA-AKI has continued to accrue. Although specific therapeutic options are limited, several clinical trials have evaluated the use of care bundles and extracorporeal techniques as potential therapeutic approaches. Here we provide graded recommendations for managing SA-AKI and highlight priorities for future research.

Biomarkers as Prognostic Predictors and Therapeutic Guide in Critically Ill Patients: Clinical Evidence

A biomarker is a molecule that can be measured in a biological sample in an objective, systematic, and precise way, whose levels indicate whether a process is normal or pathological. Knowing the most important biomarkers and their characteristics is the key to precision medicine in intensive and perioperative care. Biomarkers can be used to diagnose, in assessment of disease severity, to stratify risk, to predict and guide clinical decisions, and to guide treatments and response to them. In this review, we will analyze what characteristics a biomarker should have and how to ensure its usefulness, and we will review the biomarkers that in our opinion can make their knowledge more useful to the reader in their clinical practice, with a future perspective. These biomarkers, in our opinion, are lactate, C-Reactive Protein, Troponins T and I, Brain Natriuretic Peptides, Procalcitonin, MR-ProAdrenomedullin and BioAdrenomedullin, Neutrophil/lymphocyte ratio and lymphopenia, Proenkephalin, NefroCheck, Neutrophil gelatinase-associated lipocalin (NGAL), Interleukin 6, Urokinase-type soluble plasminogen activator receptor (suPAR), Presepsin, Pancreatic Stone Protein (PSP), and Dipeptidyl peptidase 3 (DPP3). Finally, we propose an approach to the perioperative evaluation of high-risk patients and critically ill patients in the Intensive Care Unit (ICU) based on biomarkers.

Derivation and Validation of Vasoactive Inotrope Score Trajectory Groups in Critically Ill Children With Shock

OBJECTIVES

To determine whether there are clinically relevant and reproducible Vasoactive Inotrope Score (VIS) trajectories in children with shock during the acute phase of critical illness.

DESIGN

Retrospective, observational cohort study.

SETTING

Two tertiary, academic PICUs.

PATIENTS

Children (< 18 yr old) who required vasoactive infusions within 24 hours of admission to the PICU. Those admitted post cardiac surgery were excluded.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

An hourly VIS was calculated for the first 72 hours after initiation of vasoactives. Group-based trajectory modeling (GBTM) was applied to a derivation set (75% of encounters) and compared with the trajectories in a validation set (25% of encounters) using the same variables. The primary outcome was in-hospital mortality, and the secondary outcome was multiple organ dysfunction syndrome (MODS) on day 7. A total of 1,828 patients met inclusion criteria, and 309 (16.9%) died. GBTM identified four subgroups that were reproducible in the validation set: "Mild, fast resolving shock" ( n = 853 [47%]; mortality 9%), "Moderate, slow resolving shock" ( n = 422 [23%]; mortality 15%), "Moderate, prolonged shock" ( n = 312 [17%]; mortality 21%), and "Severe, prolonged shock" ( n = 241 [13%]; mortality 40%). There was a significant difference in mortality, MODS on day 7, and suspected infection ( p < 0.001) across groups. The "Mild, fast resolving shock" and "Severe, prolonged shock" groups were identifiable within the first 24 hours. The "Moderate, slow resolving" and "Moderate, prolonged shock" groups were indistinguishable in the first 24 hours after initiation of vasoactives but differed in in-hospital mortality and MODS on day 7. Hydrocortisone administration was independently associated with poor outcomes in the "Mild, fast resolving shock" group.

CONCLUSIONS

We uncovered four distinct and reproducible VIS trajectory groups that were associated with different risk factors, response to therapy, and outcomes in children with shock. Characterizing VIS trajectory groups in the acute phase of critical illness may enable better prognostication and more targeted management.

Advances in the Staging and Phenotyping of Cardiogenic Shock: Part 1 of 2

Cardiogenic shock (CS) is a heterogeneous syndrome reflecting a broad spectrum of shock severity, diverse etiologies, variable cardiac function, different hemodynamic trajectories, and concomitant organ dysfunction. These factors influence the clinical presentation, management, response to therapy, and outcomes of CS patients, necessitating a tailored approach to care. To better understand the variability inherent to CS populations, recent algorithms for staging the severity of CS have been described and validated. This paper is part 1 of a 2-part state-of-the-art review. In this first article, we consider the context for clinical staging and stratification in CS with a focus on established severity staging systems for CS and their use for risk stratification and clinical care. We describe the use of staging for predicting outcomes in populations with or at risk for CS, including risk modifiers that provide more nuanced risk stratification, and highlight how these approaches may allow individualized care.

A Standardized Multimodal Neurological Monitoring Protocol-Guided Cerebral Protection Therapy for Venoarterial Extracorporeal Membrane Oxygenation Supported Patients

Background

The main objective of this study was to investigate the role of a multimodal neurological monitoring (MNM)-guided protocol in the precision identification of neural impairment and long-term neurological outcomes in venoarterial extracorporeal membrane oxygenation (VA-ECMO) supported patients.

Methods

We performed a cohort study that examined adult patients who underwent VA-ECMO support in our center between February 2010 and April 2021. These patients were retrospectively assigned to the “with MNM group” and the “without MNM group” based on the presence or absence of MNM-guided precision management. The differences in ECMO-related characteristics, evaluation indicators (precision, sensitivity, and specificity) of the MNM-guided protocol, and the long-term outcomes of the surviving patients were measured and compared between the two groups.

Results

A total of 63 patients with VA-ECMO support were retrospectively assigned to the without MNM group (n = 35) and the with MNM group (n = 28). The incidence of neural impairment in the without MNM group was significantly higher than that in the with MNM group (82.1 vs. 54.3%, P = 0.020). The MNM group exhibited older median ages [52.5 (39.5, 65.3) vs. 31 (26.5, 48.0), P = 0.008], a higher success rate of ECMO weaning (92.8 vs. 71.4%, P = 0.047), and a lower median duration of building ECMO [40.0 (35.0, 52.0) vs. 58.0 (48.0, 76.0), P = 0.025] and median ECMO duration days [5.0 (4.0, 6.2) vs. 7.0 (5.0, 10.5), P = 0.018] than the group without MNM. The MNM-guided protocol exhibited a higher precision rate (82.1 vs. 60.0%), sensitivity (95.7 vs. 78.9%), and specificity (83.3 vs. 37.5%) in identifying neural impairment in VA-ECMO support patients. There were significant differences in the long-term outcomes of survivors at 1, 3 and 6 months after discharge between the two groups (P < 0.05). However, the results showed no significant differences in ICU length of stay (LOS), hospital LOS, survival to discharge, or 28-day mortality between the two groups (P > 0.05).

Conclusion

The MNM-guided protocol is conducive to guiding intensivists in the improvement of cerebral protection therapy for ECMO-supported patients to detect and treat potential neurologic impairment promptly, and then improving long-term neurological outcomes after discharge.

Research in Pediatric Intensive Care

Many important clinical questions remain unanswered in the practice of pediatric intensive care due to the lack of high-quality evidence. Although challenges exist in conducting research in pediatric intensive care units, identification of research priorities, interdisciplinary collaborations, innovative trial designs, and the use of common datasets and outcome measures helps to bring new knowledge to our field. The topic of "Research in PICUs" is extremely broad; therefore, this review focuses on a few common themes receiving increased attention in the literature, including research agendas, core outcome sets, precision medicine, and novel clinical trial strategies.

Redefining critical illness

Research and practice in critical care medicine have long been defined by syndromes, which, despite being clinically recognizable entities, are, in fact, loose amalgams of heterogeneous states that may respond differently to therapy. Mounting translational evidence-supported by research on respiratory failure due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-suggests that the current syndrome-based framework of critical illness should be reconsidered. Here we discuss recent findings from basic science and clinical research in critical care and explore how these might inform a new conceptual model of critical illness. De-emphasizing syndromes, we focus on the underlying biological changes that underpin critical illness states and that may be amenable to treatment. We hypothesize that such an approach will accelerate critical care research, leading to a richer understanding of the pathobiology of critical illness and of the key determinants of patient outcomes. This, in turn, will support the design of more effective clinical trials and inform a more precise and more effective practice at the bedside.

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.

Endotypes and the Path to Precision in Moderate and Severe Traumatic Brain Injury

Heterogeneity is recognized as a major barrier in efforts to improve the care and outcomes of patients with traumatic brain injury (TBI). Even within the narrower stratum of moderate and severe TBI, current management approaches do not capture the complexity of this condition characterized by manifold clinical, anatomical, and pathophysiologic features. One approach to heterogeneity may be to resolve undifferentiated TBI populations into endotypes, subclasses that are distinguished by shared biological characteristics. The endotype paradigm has been explored in a range of medical domains, including psychiatry, oncology, immunology, and pulmonology. In intensive care, endotypes are being investigated for syndromes such as sepsis and acute respiratory distress syndrome. This review provides an overview of the endotype paradigm as well as some of its methods and use cases. A conceptual framework is proposed for endotype research in moderate and severe TBI, together with a scientific road map for endotype discovery and validation in this population.

Operationalizing the Exposome Using Passive Silicone Samplers

The exposome, which is defined as the cumulative effect of environmental exposures and corresponding biological responses, aims to provide a comprehensive measure for evaluating non-genetic causes of disease. Operationalization of the exposome for environmental health and precision medicine has been limited by the lack of a universal approach for characterizing complex exposures, particularly as they vary temporally and geographically. To overcome these challenges, passive sampling devices (PSDs) provide a key measurement strategy for deep exposome phenotyping, which aims to provide comprehensive chemical assessment using untargeted high-resolution mass spectrometry for exposome-wide association studies. To highlight the advantages of silicone PSDs, we review their use in population studies and evaluate the broad range of applications and chemical classes characterized using these samplers. We assess key aspects of incorporating PSDs within observational studies, including the need to preclean samplers prior to use to remove impurities that interfere with compound detection, analytical considerations, and cost. We close with strategies on how to incorporate measures of the external exposome using PSDs, and their advantages for reducing variability in exposure measures and providing a more thorough accounting of the exposome. Continued development and application of silicone PSDs will facilitate greater understanding of how environmental exposures drive disease risk, while providing a feasible strategy for incorporating untargeted, high-resolution characterization of the external exposome in human studies.

Vitamin therapy in sepsis

Vitamins are essential micronutrients with key roles in many biological pathways relevant to sepsis. Some of these relevant biological mechanisms include antioxidant and anti-inflammatory effects, protein and hormone synthesis, energy generation, and regulation of gene transcription. Moreover, relative vitamin deficiencies in plasma are common during sepsis and vitamin therapy has been associated with improved outcomes in some adult and pediatric studies. High-dose intravenous vitamin C has been the vitamin therapy most extensively studied in adult patients with sepsis and septic shock. This includes three randomized control trials (RCTs) as monotherapy with a total of 219 patients showing significant reduction in organ dysfunction and lower mortality when compared to placebo, and five RCTs as a combination therapy with thiamine and hydrocortisone with a total of 1134 patients showing no difference in clinical outcomes. Likewise, the evidence for the role of other vitamins in sepsis remains mixed. In this narrative review, we present the preclinical, clinical, and safety evidence of the most studied vitamins in sepsis, including vitamin C, thiamine (i.e., vitamin B₁), and vitamin D. We also present the relevant evidence of the other vitamins that have been studied in sepsis and critical illness in both children and adults, including vitamins A, B₂, B₆, B₁₂, and E. IMPACT: Vitamins are key effectors in many biological processes relevant to sepsis. We present the preclinical, clinical, and safety evidence of the most studied vitamins in pediatric sepsis. Designing response-adaptive platform trials may help fill in knowledge gaps regarding vitamin use for critical illness and association with clinical outcomes.

The Supportive Role of International Government Funds on the Progress of Sepsis Research During the Past Decade (2010-2019): A Narrative Review

This narrative review aimed to clarify the characteristics of international government support for sepsis research, trends in published literature on sepsis, and potential contributions of government-source grants to progress in sepsis research between fiscal years 2010 and 2019. The data in this study were collected from the National Institutes of Health (NIH, https://projectreporter.nih.gov/reporter.cfm/) of the United States of America (USA), National Natural Science Foundation of China (NSFC, https://isisn.nsfc.gov.cn/egrantweb/), and Japan Society for the Promotion of Science (JSPS, https://kaken.nii.ac.jp/). All sepsis-related projects approved by the NIH, NSFC, and JSPS were retrieved by searching the project titles, abstracts, and key words for “sepsis,” “septic shock,” or “sepsis inflammatory response syndrome” between 2010 and 2019. Representative sepsis-related studies published between Jan 2010 and Aug 2020 by the first/corresponding authors from these countries were obtained by searching the PubMed database using Medical Subject Heading terms for “sepsis” in representative journals, including Nature, Cell, Science, The Lancet, New England Journal of medicine (New Engl J Med), The Journal of American Medical Association (JAMA), Critical Care Medicine (CCM), Intensive Care Medicine (ICM), Chest, Annals of Emergency Medicine (Ann Emerg Med), and American Thoracic Society journals (ATS). The total/annual institutional budgets, major funding mechanisms and schemes, superior institutions and individual principal investigators, and published original research articles in the field of sepsis in the USA, China, and Japan during the past decade were investigated. The national supporting schemes of the NIH, NSFC, and JSPS were similar. Support from these institutions is quite important for the development of the field of “sepsis” which was acknowledged in 57–64% of original research articles published in CCM. For the future development of precision medicine in sepsis, more government funding support is necessary.

The immunology of sepsis

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to an infection. This recently implemented definition does not capture the heterogeneity or the underlying pathophysiology of the syndrome, which is characterized by concurrent unbalanced hyperinflammation and immune suppression. Here, we review current knowledge of aberrant immune responses during sepsis and recent initiatives to stratify patients with sepsis into subgroups that are more alike from a clinical and/or pathobiological perspective, which could be key for identification of patients who are more likely to benefit from specific immune interventions.

Revising Host Phenotypes of Sepsis Using Microbiology

Background: There is wide heterogeneity in sepsis in causative pathogens, host response, organ dysfunction, and outcomes. Clinical and biologic phenotypes of sepsis are proposed, but the role of pathogen data on sepsis classification is unknown. Methods: We conducted a secondary analysis of the Recombinant Human Activated Protein C (rhAPC) Worldwide Evaluation in Severe Sepsis (PROWESS) Study. We used latent class analysis (LCA) to identify sepsis phenotypes using, (i) only clinical variables ("host model") and, (ii) combining clinical with microbiology variables (e.g., site of infection, culture-derived pathogen type, and anti-microbial resistance characteristics, "host-pathogen model"). We describe clinical characteristics, serum biomarkers, and outcomes of host and host-pathogen models. We tested the treatment effects of rhAPC by phenotype using Kaplan-Meier curves. Results: Among 1,690 subjects with severe sepsis, latent class modeling derived a 4-class host model and a 4-class host-pathogen model. In the host model, alpha type (N = 327, 19%) was younger and had less shock; beta type (N=518, 31%) was older with more comorbidities; gamma type (N = 532, 32%) had more pulmonary dysfunction; delta type (N = 313, 19%) had more liver, renal and hematologic dysfunction and shock. After the addition of microbiologic variables, 772 (46%) patients changed phenotype membership, and the median probability of phenotype membership increased from 0.95 to 0.97 (P < 0.01). When microbiology data were added, the contribution of individual variables to phenotypes showed greater change for beta and gamma types. In beta type, the proportion of abdominal infections (from 20 to 40%) increased, while gamma type patients had an increased rate of lung infections (from 50 to 78%) with worsening pulmonary function. Markers of coagulation such as d-dimer and plasminogen activator inhibitor (PAI)-1 were greater in the beta type and lower in the gamma type. The 28 day mortality was significantly different for individual phenotypes in host and host-pathogen models (both P < 0.01). The treatment effect of rhAPC obviously changed in gamma type when microbiology data were added (P-values of log rank test changed from 0.047 to 0.780). Conclusions: Sepsis host phenotype assignment was significantly modified when microbiology data were added to clinical variables, increasing cluster cohesiveness and homogeneity.

A Research Agenda for Precision Medicine in Sepsis and Acute Respiratory Distress Syndrome: An Official American Thoracic Society Research Statement

Background: Precision medicine focuses on the identification of therapeutic strategies that are effective for a group of patients based on similar unifying characteristics. The recent success of precision medicine in non-critical care settings has resulted from the confluence of large clinical and biospecimen repositories, innovative bioinformatics, and novel trial designs. Similar advances for precision medicine in sepsis and in the acute respiratory distress syndrome (ARDS) are possible but will require further investigation and significant investment in infrastructure. Methods: This project was funded by the American Thoracic Society Board of Directors. A multidisciplinary and diverse working group reviewed the available literature, established a conceptual framework, and iteratively developed recommendations for the Precision Medicine Research Agenda for Sepsis and ARDS. Results: The following six priority recommendations were developed by the working group: 1) the creation of large richly phenotyped and harmonized knowledge networks of clinical, imaging, and multianalyte molecular data for sepsis and ARDS; 2) the implementation of novel trial designs, including adaptive designs, and embedding trial procedures in the electronic health record; 3) continued innovation in the data science and engineering methods required to identify heterogeneity of treatment effect; 4) further development of the tools necessary for the real-time application of precision medicine approaches; 5) work to ensure that precision medicine strategies are applicable and available to a broad range of patients varying across differing racial, ethnic, socioeconomic, and demographic groups; and 6) the securement and maintenance of adequate and sustainable funding for precision medicine efforts. Conclusions: Precision medicine approaches that incorporate variability in genomic, biologic, and environmental factors may provide a path forward for better individualizing the delivery of therapies and improving care for patients with sepsis and ARDS.

Rapid single-molecule digital detection of protein biomarkers for continuous monitoring of systemic immune disorders

Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. However, translating digital protein assays to acute clinical care has been challenging because it requires deployment of these assays with a rapid turnaround. Herein, we present a technology platform for ultrafast digital protein biomarker detection by using single-molecule counting of immune-complex formation events at an early, pre-equilibrium state. This method, which we term "pre-equilibrium digital enzyme-linked immunosorbent assay" (PEdELISA), can quantify a multiplexed panel of protein biomarkers in 10 µL of serum within an unprecedented assay incubation time of 15 to 300 seconds over a 104 dynamic range. PEdELISA allowed us to perform rapid monitoring of protein biomarkers in patients manifesting post-chimeric antigen receptor T-cell therapy cytokine release syndrome, with ∼30-minute sample-to-answer time and a sub-picograms per mL limit of detection. The rapid, sensitive, and low-input volume biomarker quantification enabled by PEdELISA is broadly applicable to timely monitoring of acute disease, potentially enabling more personalized treatment.

Methods and implementation of a pediatric asthma pharmacogenomic study in the emergency department setting

OBJECTIVES

The emergency department (ED) is a challenging setting to conduct pharmacogenomic studies and integrate that data into fast-paced and potentially life-saving treatment decisions. Therefore, our objective is to present the methods and feasibility of a pilot pharmacogenomic study set in the ED that measured pediatric bronchodilator response (BDR) during acute asthma exacerbations.

METHODS

This is an exploratory pilot study that collected buccal swabs for DNA and measured BDR during ED encounters for pediatric asthma exacerbations. We evaluated the study's feasibility with a qualitative analysis of ED provider surveys and quantitatively by the proportion of eligible patients enrolled.

RESULTS

We enrolled 59 out of 90 patients (65%) that were identified and considered eligible during a 5-month period (target enrollment 60 patients over 12 months). The median patient age was 7 years (interquartile range 4-9 years), 61% (N = 36) were male, and 92% (N = 54) were African American. Quality DNA collection was successful for all 59 patients. The ED provider survey response rate was 100%. Most ED providers reported that the study did not impact their workflow (98% of physicians, 88% of nurses, and 90% of respiratory therapists). ED providers did report difficulties with spirometry in the younger age group.

CONCLUSIONS

Pharmacogenomic studies can be conducted in the ED setting, and enroll a younger patient population with a high proportion of minority participants. By disseminating this study's methods and feasibility analysis, we aim to increase interest in pharmacogenomic studies set in the ED and aimed toward future ED-based pharmacogenomic decision-making.

Meeting the challenge: Health information technology's essential role in achieving precision medicine

Precision medicine can revolutionize health care by tailoring treatments to individual patient needs. Advancing precision medicine requires evidence development through research that combines needed data, including clinical data, at an unprecedented scale. Widespread adoption of health information technology (IT) has made digital clinical data broadly available. These data and information systems must evolve to support precision medicine research and delivery. Specifically, relevant health IT data, infrastructure, clinical integration, and policy needs must be addressed. This article outlines those needs and describes work the Office of the National Coordinator for Health Information Technology is leading to improve health IT through pilot projects and standards and policy development. The Office of the National Coordinator for Health Information Technology will build on these efforts and continue to coordinate with other key stakeholders to achieve the vision of precision medicine. Advancement of precision medicine will require ongoing, collaborative health IT policy and technical initiatives that advance discovery and transform healthcare delivery.

Morbidity and Mortality in Critically Ill Children. I. Pathophysiologies and Potential Therapeutic Solutions

OBJECTIVES

Developing effective therapies to reduce morbidity and mortality requires knowing the responsible pathophysiologies and the therapeutic advances that are likely to be impactful. Our objective was to determine at the individual patient level the important pathophysiological processes and needed therapeutic additions and advances that could prevent or ameliorate morbidities and mortalities.

DESIGN

Structured chart review by pediatric intensivists of PICU children discharged with significant new morbidity or mortality to determine the pathophysiologies responsible for poor outcomes and needed therapeutic advances.

SETTING

Multicenter study (eight sites) from the Collaborative Pediatric Critical Care Research Network of general and cardiac PICUs.

PATIENTS

First PICU admission of patients from December 2011 to April 2013.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Two-hundred ninety-two patients were randomly selected from 681 patients discharged with significant new morbidity or mortality. The median age was 2.4 years, 233 (79.8%) were in medical/surgical ICUs, 59 (20.2%) were in cardiac ICUs. Sixty-five (22.3%) were surgical admissions. The outcomes included 117 deaths and 175 significant new morbidities. The most common pathophysiologies contributing to the poor outcomes were impaired substrate delivery (n = 158, 54.1%) and inflammation (n = 104, 35.6%). There were no strong correlations between the pathophysiologies and no remarkable clusters among them. The most common therapeutic needs involved new drugs (n = 149, 51.0%), cell regeneration (n = 115, 39.4%), and immune and inflammatory modulation (n = 79, 27.1%). As with the pathophysiologies, there was a lack of strong correlations or meaningful clusters in the suggested therapeutic needs.

CONCLUSIONS

There was no single dominant pathophysiology or cluster of pathophysiologies responsible for poor pediatric critical care outcomes. Therapeutic needs often involved therapies that are not close to implementation such as cell regeneration, improved organ transplant, improved extracorporeal support and artificial organs, and improved drugs.