Intravenous Vitamin C in Adults with Sepsis in the Intensive Care Unit.

BACKGROUND: Studies that have evaluated the use of intravenous vitamin C in adults with sepsis who were receiving vasopressor therapy in the intensive care unit (ICU) have shown mixed results with respect to the risk of death and organ dysfunction. METHODS: In this randomized, placebo-controlled trial, we assigned adults who had been in the ICU for no longer than 24 hours, who had proven or suspected infection as the main diagnosis, and who were receiving a vasopressor to receive an infusion of either vitamin C (at a dose of 50 mg per kilogram of body weight) or matched placebo administered every 6 hours for up to 96 hours. The primary outcome was a composite of death or persistent organ dysfunction (defined by the use of vasopressors, invasive mechanical ventilation, or new renal-replacement therapy) on day 28. RESULTS: A total of 872 patients underwent randomization (435 to the vitamin C group and 437 to the control group). The primary outcome occurred in 191 of 429 patients (44.5%) in the vitamin C group and in 167 of 434 patients (38.5%) in the control group (risk ratio, 1.21; 95% confidence interval [CI], 1.04 to 1.40; P = 0.01). At 28 days, death had occurred in 152 of 429 patients (35.4%) in the vitamin C group and in 137 of 434 patients (31.6%) in the placebo group (risk ratio, 1.17; 95% CI, 0.98 to 1.40) and persistent organ dysfunction in 39 of 429 patients (9.1%) and 30 of 434 patients (6.9%), respectively (risk ratio, 1.30; 95% CI, 0.83 to 2.05). Findings were similar in the two groups regarding organ-dysfunction scores, biomarkers, 6-month survival, health-related quality of life, stage 3 acute kidney injury, and hypoglycemic episodes. In the vitamin C group, one patient had a severe hypoglycemic episode and another had a serious anaphylaxis event. CONCLUSIONS: In adults with sepsis receiving vasopressor therapy in the ICU, those who received intravenous vitamin C had a higher risk of death or persistent organ dysfunction at 28 days than those who received placebo. (Funded by the Lotte and John Hecht Memorial Foundation; LOVIT ClinicalTrials.gov number, NCT03680274.).

Resumption of Cardiac Activity after Withdrawal of Life-Sustaining Measures.

BACKGROUND: The minimum duration of pulselessness required before organ donation after circulatory determination of death has not been well studied. METHODS: We conducted a prospective observational study of the incidence and timing of resumption of cardiac electrical and pulsatile activity in adults who died after planned withdrawal of life-sustaining measures in 20 intensive care units in three countries. Patients were intended to be monitored for 30 minutes after determination of death. Clinicians at the bedside reported resumption of cardiac activity prospectively. Continuous blood-pressure and electrocardiographic (ECG) waveforms were recorded and reviewed retrospectively to confirm bedside observations and to determine whether there were additional instances of resumption of cardiac activity. RESULTS: A total of 1999 patients were screened, and 631 were included in the study. Clinically reported resumption of cardiac activity, respiratory movement, or both that was confirmed by waveform analysis occurred in 5 patients (1%). Retrospective analysis of ECG and blood-pressure waveforms from 480 patients identified 67 instances (14%) with resumption of cardiac activity after a period of pulselessness, including the 5 reported by bedside clinicians. The longest duration after pulselessness before resumption of cardiac activity was 4 minutes 20 seconds. The last QRS complex coincided with the last arterial pulse in 19% of the patients. CONCLUSIONS: After withdrawal of life-sustaining measures, transient resumption of at least one cycle of cardiac activity after pulselessness occurred in 14% of patients according to retrospective analysis of waveforms; only 1% of such resumptions were identified at the bedside. These events occurred within 4 minutes 20 seconds after a period of pulselessness. (Funded by the Canadian Institutes for Health Research and others.).

Cerebral autoregulation-based mean arterial pressure targets and delirium in critically ill adults without brain injury: a retrospective cohort study.

PURPOSE: Cerebral autoregulation (CA) is a mechanism that acts to maintain consistent cerebral perfusion across a range of blood pressures, and impaired CA is associated with delirium. Individualized CA-derived blood pressure targets are poorly characterized in critically ill patients and the association with intensive care unit (ICU) delirium is unknown. Our objectives were to characterize optimal mean arterial pressure (MAPopt) ranges in critically ill adults without brain injury and determine whether deviations from these targets contribute to ICU delirium. METHODS: We performed a retrospective cohort analysis of patients with shock of any etiology and/or respiratory failure requiring invasive mechanical ventilation, without a neurologic admitting diagnosis. Patients were screened daily for delirium. Cerebral oximetry and mean arterial pressure data were captured for the first 24 hr from enrolment. RESULTS: Forty-two patients with invasive blood pressure monitoring data were analyzed. Optimal mean arterial pressure targets ranged from 55 to 100 mm Hg. Optimal mean arterial pressure values were not significantly different based on history of hypertension or delirium status, and delirium was not associated with deviations from MAPopt. Nevertheless, the majority (69%) of blood pressure targets exceeded the current 65 mm Hg Surviving Sepsis guidelines. CONCLUSION: We observed that MAPopt targets across patients were highly variable, but did not observe an association with the incidence of delirium. Studies designed to evaluate the impact on neurologic outcomes are needed to understand the association with individualized mean arterial pressure targets in the ICU. STUDY REGISTRATION: ClinicalTrials.gov (NCT02344043); first submitted 22 January 2015.

RéSUMé: OBJECTIF: L'autorégulation cérébrale (AC) est un mécanisme qui agit pour maintenir une perfusion cérébrale constante pour une gamme de tensions artérielles, et une altération de l'AC est associée au delirium. Les cibles de tension artérielle individualisées dérivées de l'AC sont mal caractérisées chez les patient·es gravement malades et l'association avec le delirium à l'unité de soins intensifs (USI) est inconnue. Nos objectifs étaient de caractériser la tension artérielle moyenne optimale (TAMopt) chez les adultes gravement malades sans lésion cérébrale et de déterminer si les écarts par rapport à ces cibles contribuaient au delirium à l'USI. MéTHODE: Nous avons réalisé une analyse de cohorte rétrospective de patient·es présentant un choc de toute étiologie et/ou une insuffisance respiratoire nécessitant une ventilation mécanique invasive, et n'ayant pas reçu de diagnostic d'atteinte neurologique à l'admission. Les patients ont été dépistés quotidiennement pour le delirium. Les données d'oxymétrie cérébrale et de tension artérielle moyenne ont été saisies pendant les 24 premières heures suivant le recrutement. RéSULTATS: Quarante-deux patient·es pour qui des données de monitorage invasif de la tension artérielle étaient disponibles ont été analysé·es. Les cibles optimales de tension artérielle moyenne variaient de 55 à 100 mm Hg. Les valeurs optimales de tension artérielle moyenne n'étaient pas significativement différentes en fonction des antécédents d'hypertension ou de delirium, et le delirium n'était pas associé à des écarts par rapport à la TAMopt. Néanmoins, la majorité (69 %) des cibles de tension artérielle dépassaient celle de 65 mm Hg préconisée par les lignes directrices Surviving Sepsis. CONCLUSION: Nous avons observé que les cibles de TAMopt étaient très variables chez les patient·es, mais nous n'avons pas observé d'association avec l'incidence de delirium. Des études conçues pour évaluer l'impact sur les issues neurologiques sont nécessaires pour comprendre l'association avec les cibles de tension artérielle moyenne individualisées à l'USI. ENREGISTREMENT DE L'éTUDE: ClinicalTrials.gov (NCT02344043); soumis pour la première fois le 22 janvier 2015.

COVID-19 and the Genetics of Inflammation.

OBJECTIVE: Interindividual variability in the clinical progression of COVID-19 may be explained by host genetics. Emerging literature supports a potential inherited predisposition to severe forms of COVID-19. Demographic and inflammatory characteristics of COVID-19 suggest that acquired hematologic mutations leading to clonal hematopoiesis (CH) may further increase vulnerability to adverse sequelae. This review summarizes the available literature examining genetic predispositions to severe COVID-19 and describes how these findings could eventually be used to improve its clinical management. DATA SOURCES: A PubMed literature search was performed. STUDY SELECTION: Studies examining the significance of inherited genetic variation or acquired CH mutations in severe COVID-19 were selected for inclusion. DATA EXTRACTION: Relevant genetic association data and aspects of study design were qualitatively assessed and narratively synthesized. DATA SYNTHESIS: Genetic variants affecting inflammatory responses may increase susceptibility to severe COVID-19. Genome-wide association studies and candidate gene approaches have identified a list of inherited mutations, which likely alter cytokine and interferon secretion, and lung-specific mechanisms of immunity in COVID-19. The potential role of CH in COVID-19 is more uncertain at present; however, the available evidence suggests that the various types of acquired mutations and their differential influence on immune cell function must be carefully considered. CONCLUSIONS: The current literature supports the hypothesis that host genetic factors affect vulnerability to severe COVID-19. Further research is required to confirm the full scope of relevant variants and the causal mechanisms underlying these associations. Clinical approaches, which consider the genetic basis of interindividual variability in COVID-19 and potentially other causes of critical illness, could optimize hospital resource allocation, predict responsiveness to treatment, identify more efficacious drug targets, and ultimately improve outcomes.

The Reviewer Academy of the Society of Critical Care Medicine: Key Principles and Strategic Plan.

The Society of Critical Care Medicine (SCCM) Reviewer Academy seeks to train and establish a community of trusted, reliable, and skilled peer reviewers with diverse backgrounds and interests to promote high-quality reviews for each of the SCCM journals. Goals of the Academy include building accessible resources to highlight qualities of excellent manuscript reviews; educating and mentoring a diverse group of healthcare professionals; and establishing and upholding standards for insightful and informative reviews. This manuscript will map the mission of the Reviewer Academy with a succinct summary of the importance of peer review, process of reviewing a manuscript, and the expected ethical standards of reviewers. We will equip readers to target concise, thoughtful feedback as peer reviewers, advance their understanding of the editorial process and inspire readers to integrate medical journalism into diverse professional careers.

Informed consent practices in clinical research: present and future.

Clinical research must balance the need for ambitious recruitment with protecting participants' autonomy; a requirement of which is informed consent. Despite efforts to improve the informed consent process, participants are seldom provided sufficient information regarding research, hindering their ability to make informed decisions. These issues are particularly pervasive among patients experiencing acute illness or neurological impairment, both of which may impede their capacity to provide consent. There is a critical need to understand the components, requirements, and methods of obtaining true informed consent to achieve the vast numbers required for meaningful research. This paper provides a comprehensive review of the tenets underlying informed consent in research, including the assessment of capacity to consent, considerations for patients unable to consent, when to seek consent from substitute decision-makers, and consent under special circumstances. Various methods for obtaining informed consent are addressed, along with strategies for balancing recruitment and consent.

Bayes' Theorem in Neurocritical Care: Principles and Practice.

Patients with critical neurological illness are diverse. As a result of the heterogeneity of this patient population, standardized approaches to patient management might not confer benefit. A precision medicine approach to neurocritical care is therefore urgently needed to improve our understanding of neurocritical illness and the care provided to this vulnerable cohort. Research designs and approaches based on Bayesian models have the potential to meet this need, as they are specifically designed to evolve with emerging evidence. This adaptability provides a benefit over the popular frequentist statistical approach, as it provides a way of adjusting hypotheses and trial procedures to maximize efficacy. This review summarizes the current state of knowledge on Bayes' theorem, and its potential applications to the field of neurocritical care. We review the basic principles underlying Bayes' theorem, compare the use of Bayesian versus frequentist statistics in medicine, and discuss the relevance of Bayesian statistics to the field of neuroscience and to clinical research. Finally, we explore the potential benefits of employing Bayesian methods within the field of neurocritical care as a steppingstone toward implementing precision medicine approaches to improve patient outcomes for complex, heterogeneous disorders.

Characterizing the Patients, Hospitals, and Data Quality of the eICU Collaborative Research Database.

OBJECTIVES: The eICU Collaborative Research Database is a publicly available repository of granular data from more than 200,000 ICU admissions. The quantity and variety of its entries hold promise for observational critical care research. We sought to understand better the data available within this resource to guide its future use. DESIGN: We conducted a descriptive analysis of the eICU Collaborative Research Database, including patient, practitioner, and hospital characteristics. We investigated the completeness of demographic and hospital data, as well as those values required to calculate an Acute Physiology and Chronic Health Evaluation score. We also assessed the rates of ventilation, intubation, and dialysis, and looked for potential errors in the vital sign data. SETTING: American ICUs that participated in the Philips Healthcare eICU program between 2014 and 2015. PATIENTS: A total of 139,367 individuals who were admitted to one of the 335 participating ICUs between 2014 and 2015. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Most encounters were from small- and medium-sized hospitals, and managed by nonintensivists. The median ICU length of stay was 1.57 days (interquartile range, 0.82-2.97 d). The median Acute Physiology and Chronic Health Evaluation IV-predicted ICU mortality was 2.2%, with an observed mortality of 5.4%. Rates of ventilation (20-33%), intubation (15-24%), and dialysis (3-5%) varied according to the query method used. Most vital sign readings fell into realistic ranges, with manually curated data less likely to contain implausible results than automatically entered data. CONCLUSIONS: Data in the eICU Collaborative Research Database are for the most part complete and plausible. Some ambiguity exists in determining which encounters are associated with various interventions, most notably mechanical ventilation. Caution is warranted in extrapolating findings from the eICU Collaborative Research Database to larger ICUs with higher acuity.

Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals.

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of "modifiable risk factors", measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.

Insights Into a "Negative" ICU Trial Derived From Gene Expression Profiling.

OBJECTIVES: Randomized controlled trials in the ICU often fail to show differences in endpoints between groups. We sought to explore reasons for this at a molecular level by analyzing transcriptomic data from a recent negative trial. Our objectives were to determine if randomization successfully balanced transcriptomic features between groups, to assess transcriptomic heterogeneity among the study subjects included, and to determine if the study drug had any effect at the gene expression level. DESIGN: Bioinformatics analysis of transcriptomic and clinical data collected in the course of a randomized controlled trial. SETTING: Tertiary academic mixed medical-surgical ICU. PATIENTS: Adult, critically ill patients expected to require invasive mechanical ventilation more than 48 hours. INTERVENTIONS: Lactoferrin or placebo delivered enterally and via an oral swab for up to 28 days. MEASUREMENTS AND MAIN RESULTS: We found no major imbalances in transcriptomic features between groups. Unsupervised analysis did not reveal distinct clusters among patients at the time of enrollment. There were marked differences in gene expression between early and later time points. Patients in the lactoferrin group showed changes in the expression of genes associated with immune pathways known to be associated with lactoferrin. CONCLUSIONS: In this clinical trial, transcriptomic data provided a useful complement to clinical data, suggesting that the reasons for the negative result were less likely related to the biological efficacy of the study drug, and may instead have been related to poor sensitivity of the clinical outcomes. In larger studies, transcriptomics may also prove useful in predicting response to treatment.

Prevention of Nosocomial Infections in Critically Ill Patients With Lactoferrin: A Randomized, Double-Blind, Placebo-Controlled Study.

OBJECTIVE: To obtain preliminary evidence for the efficacy of lactoferrin as a preventative measure for nosocomial infections and inform the conduct of a definitive study. DESIGN: Phase 2, multicenter, randomized, double-blind, placebo-controlled study. SETTING: Medical-surgical ICUs. PATIENTS: Adult, critically ill patients receiving invasive mechanical ventilation. INTERVENTIONS: Randomized, eligible, consenting patients expected to require invasive mechanical ventilation more than 48 hours received lactoferrin both enterally and via an oral swab or a placebo of sterile water for up to 28 days. MEASUREMENTS AND MAIN RESULTS: Of the 214 patients who were randomized, 212 received at least one dose of the intervention and were analyzed (107 lactoferrin and 105 placebo). Protocol adherence was 87.5%. Patients receiving lactoferrin were older (mean [SD], 66.3 [13.5] vs 62.5 [16.2] yr), had a higher Acute Physiology and Chronic Health Evaluation II score (26.8 [7.8] vs 23.5 [7.9]), and need for vasopressors (79% vs 70%). Antibiotic-free days (17.3 [9.0] vs 18.5 [7.1]; p = 0.91) and nosocomial infections (0.3 [0.7] vs 0.4 [0.6] per patient; p = 0.48) did not differ between lactoferrin and placebo groups, respectively. Clinical outcomes for lactoferrin versus placebo were as follows: ICU length of stay (14.5 [18.0] vs 15.0 [37.3] d; p = 0.82), hospital length of stay (25.0 [25.9] vs 28.1 [44.6] d; p = 0.57), hospital mortality (41.1% vs 30.5%; p = 0.11), and 90-day mortality (44.9% vs 32.4%; p = 0.06). Biomarker levels did not differ between the groups. CONCLUSIONS: Lactoferrin did not improve the primary outcome of antibiotic-free days, nor any of the secondary outcomes. Our data do not support the conduct of a larger phase 3 trial.

A path to precision in the ICU.

Precision medicine is increasingly touted as a groundbreaking new paradigm in biomedicine. In the ICU, the complexity and ambiguity of critical illness syndromes have been identified as fundamental justifications for the adoption of a precision approach to research and practice. Inherently protean diseases states such as sepsis and acute respiratory distress syndrome have manifestations that are physiologically and anatomically diffuse, and that fluctuate over short periods of time. This leads to considerable heterogeneity among patients, and conditions in which a "one size fits all" approach to therapy can lead to widely divergent results. Current ICU therapy can thus be seen as imprecise, with the potential to realize substantial gains from the adoption of precision medicine approaches. A number of challenges still face the development and adoption of precision critical care, a transition that may occur incrementally rather than wholesale. This article describes a few concrete approaches to addressing these challenges.First, novel clinical trial designs, including registry randomized controlled trials and platform trials, suggest ways in which conventional trials can be adapted to better accommodate the physiologic heterogeneity of critical illness. Second, beyond the "omics" technologies already synonymous with precision medicine, the data-rich environment of the ICU can generate complex physiologic signatures that could fuel precision-minded research and practice. Third, the role of computing infrastructure and modern informatics methods will be central to the pursuit of precision medicine in the ICU, necessitating close collaboration with data scientists. As work toward precision critical care continues, small proof-of-concept studies may prove useful in highlighting the potential of this approach.

Customization of a Severity of Illness Score Using Local Electronic Medical Record Data.

PURPOSE: Severity of illness (SOI) scores are traditionally based on archival data collected from a wide range of clinical settings. Mortality prediction using SOI scores tends to underperform when applied to contemporary cases or those that differ from the case-mix of the original derivation cohorts. We investigated the use of local clinical data captured from hospital electronic medical records (EMRs) to improve the predictive performance of traditional severity of illness scoring. METHODS: We conducted a retrospective analysis using data from the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database, which contains clinical data from the Beth Israel Deaconess Medical Center in Boston, Massachusetts. A total of 17 490 intensive care unit (ICU) admissions with complete data were included, from 4 different service types: medical ICU, surgical ICU, coronary care unit, and cardiac surgery recovery unit. We developed customized SOI scores trained on data from each service type, using the clinical variables employed in the Simplified Acute Physiology Score (SAPS). In-hospital, 30-day, and 2-year mortality predictions were compared with those obtained from using the original SAPS using the area under the receiver-operating characteristics curve (AUROC) as well as the area under the precision-recall curve (AUPRC). Test performance in different cohorts stratified by severity of organ injury was also evaluated. RESULTS: Most customized scores (30 of 39) significantly outperformed SAPS with respect to both AUROC and AUPRC. Enhancements over SAPS were greatest for patients undergoing cardiovascular surgery and for prediction of 2-year mortality. CONCLUSIONS: Custom models based on ICU-specific data provided better mortality prediction than traditional SAPS scoring using the same predictor variables. Our local data approach demonstrates the value of electronic data capture in the ICU, of secondary uses of EMR data, and of local customization of SOI scoring.