Nebulized Furosemide for Pulmonary Inflammation in Intubated Patients With COVID-19: A Phase 2 Randomized Controlled Double-Blind Study.

OBJECTIVES: Respiratory failure secondary to COVID-19 is associated with morbidity and mortality. Current anti-inflammatory therapies are effective but are given systemically and have significant side effects. Furosemide has anti-inflammatory properties, can be administered by inhalation, and is inexpensive. We investigated the efficacy of nebulized furosemide as an adjunctive therapy for COVID-19 respiratory failure. DESIGN: A double-blind, randomized, placebo-controlled trial. SETTING: Multicenter ICU study. PATIENTS: Adults requiring invasive mechanical ventilation secondary to COVID-19. INTERVENTION: Patients were randomized within 48 hours of intubation to receive inhaled furosemide or placebo until day 28, death, or liberation from mechanical ventilation. MEASUREMENTS AND MAIN RESULTS: The study was stopped early due to waning incidence of COVID-19; 39 patients were available for analysis with mean ± sd age of 70.5 (10.8) years, Acute Physiology and Chronic Health Evaluation II 26.1 (7.8) and Fio2 60.0% (21.9). Baseline characteristics were similar between the groups. For the primary outcome of change in Pao2/Fio2 ratio between day 1 and day 6, it was +31.4 (83.5) in the furosemide arm versus +20.1 (92.8) in the control (p = 0.58). For secondary outcomes, furosemide versus control: 60-day mortality was 48% versus 71% (p = 0.20), hospital stay was 25.6 (21.9) versus 27.4 (25.0) days, p = 0.94 and VFD was 6.0 (9.1) versus 3.1 (7.1), p value of equals to 0.28. A post hoc analysis of the hierarchical composite outcome, alive and ventilator-free favored furosemide. There were no adverse events. CONCLUSIONS: In this trial of inhaled furosemide for COVID-19 respiratory failure, differences in Pao2/Fio2 ratio to day 6 and other clinical outcomes were not significantly different, although the trial was underpowered due to early termination. Given the favorable profile of inhaled furosemide, further study is warranted in disease states where acute pulmonary inflammation contributes to the underlying pathophysiology.

Using a targeted metabolomics approach to explore differences in ARDS associated with COVID-19 compared to ARDS caused by H1N1 influenza and bacterial pneumonia.

RATIONALE: Acute respiratory distress syndrome (ARDS) is a life-threatening critical care syndrome commonly associated with infections such as COVID-19, influenza, and bacterial pneumonia. Ongoing research aims to improve our understanding of ARDS, including its molecular mechanisms, individualized treatment options, and potential interventions to reduce inflammation and promote lung repair. OBJECTIVE: To map and compare metabolic phenotypes of different infectious causes of ARDS to better understand the metabolic pathways involved in the underlying pathogenesis. METHODS: We analyzed metabolic phenotypes of 3 ARDS cohorts caused by COVID-19, H1N1 influenza, and bacterial pneumonia compared to non-ARDS COVID-19-infected patients and ICU-ventilated controls. Targeted metabolomics was performed on plasma samples from a total of 150 patients using quantitative LC-MS/MS and DI-MS/MS analytical platforms. RESULTS: Distinct metabolic phenotypes were detected between different infectious causes of ARDS. There were metabolomics differences between ARDSs associated with COVID-19 and H1N1, which include metabolic pathways involving taurine and hypotaurine, pyruvate, TCA cycle metabolites, lysine, and glycerophospholipids. ARDSs associated with bacterial pneumonia and COVID-19 differed in the metabolism of D-glutamine and D-glutamate, arginine, proline, histidine, and pyruvate. The metabolic profile of COVID-19 ARDS (C19/A) patients admitted to the ICU differed from COVID-19 pneumonia (C19/P) patients who were not admitted to the ICU in metabolisms of phenylalanine, tryptophan, lysine, and tyrosine. Metabolomics analysis revealed significant differences between C19/A, H1N1/A, and PNA/A vs ICU-ventilated controls, reflecting potentially different disease mechanisms. CONCLUSION: Different metabolic phenotypes characterize ARDS associated with different viral and bacterial infections.

Ceragenin-coated endotracheal tubes for the reduction of ventilator-associated pneumonia: a prospective, longitudinal, cross-over, interrupted time, implementation study protocol (CEASE VAP study).

BACKGROUND: Critically ill patients are at high risk of acquiring ventilator-associated pneumonia (VAP), which occurs in approximately 20% of mechanically ventilated patients. VAP results either from aspiration of pathogen-contaminated oropharyngeal secretions or contaminated biofilms that form on endotracheal tubes (ETTs) after intubation. VAP results in increased duration of mechanical ventilation, increased intensive care unit and hospital length of stay, increased risk of death and increased healthcare costs. Because of its impact on patient outcomes and the healthcare system, VAP is regarded as an important patient safety issue and there is an urgent need for better evidence on the efficacy of prevention strategies. Modified ETTs that reduce aspiration of oropharyngeal secretions with subglottic secretion drainage or reduce the occurrence of biofilm with a coating of ceragenins (CSAs) are available for clinical use in Canada. In this implementation study, we will evaluate the efficacy of these two types of Health Canada-licensed ETTs on the occurrence of VAP, and impact on patient-centred outcomes. METHODS: In this ongoing, pragmatic, prospective, longitudinal, interrupted time, cross-over implementation study, we will compare the efficacy of a CSA-coated ETT (CeraShield N8 Pharma) with an ETT with subglottic secretion drainage (Taper Guard, Covidien). The study periods consist of four alternating time periods of 11 or 12 weeks or a total of 23 weeks for each ETT. All patients intubated with the study ETT in each time period will be included in an intention-to-treat analysis. Outcomes will include VAP incidence, mortality and health services utilisation including antibiotic use and length of stay. ETHICS AND DISSEMINATION: This study has been approved by the Health Sciences Research Ethics Board at Queen's University. The results of this study will be actively disseminated through manuscript publication and conference presentations. TRIAL REGISTRATION NUMBER: NCT05761613.

Proteomic Evolution from Acute to Post-COVID-19 Conditions.

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

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.

Neurological Impairment in Critically Ill Patients on Dialysis: Research Letter for the INCOGNITO-AKI Feasibility Study.

Background: Acute kidney injury (AKI) resulting in kidney replacement therapy is rising among critically ill adults. Long-term kidney replacement therapy and critical illness are independently linked to acute and prolonged cognitive impairment, and structural brain pathology. Poor regional cerebral oxygenation (rSO2) may be a contributing factor. Objective: To assess the feasibility of testing the association between intradialytic rSO2 and acute and long-term neurological outcomes. Design: Longitudinal observational study. Setting and Participants: We enrolled patients initiating continuous kidney replacement therapy or intermittent hemodialysis in the Kingston Health Sciences Centre (KHSC) Intensive Care Unit (ICU). Measurements and Methods: rSO2 was monitored during the first 72 hours of continuous kidney replacement therapy or throughout each intermittent hemodialysis session. We measured acute neurological impairment by daily delirium screening and long-term neurocognitive outcomes using the Kinarm robot, Repeatable Battery for the Assessment of Neuropsychological Status, and brain magnetic resonance imaging. Results: Of 484 ICU patients, 26 met the screening criteria. Two declined, and 13 met at least one exclusion criteria. Eleven patients were enrolled. Eight died in ICU, one died 2 months after discharge, and one declined follow-up. Data capture rates were high: rSO2/vitals (91.3%), and delirium screening and demographics (100%). Longitudinal testing was completed in 50% (1 of 2) of survivors. Limitations: Enrollment was low due to a variety of factors, limiting our ability to evaluate long-term outcomes. Conclusion: rSO2 and delirium data collection is feasible in critically ill patients undergoing kidney replacement therapy; high mortality limits follow-up.

Contexte: L'insuffisance rénale aiguë (IRA) menant à une thérapie de remplacement rénal est en augmentation chez les adultes aux soins intensifs. Un séjour aux soins intensifs et la thérapie de remplacement rénal à long terme sont indépendamment liés à des déficits cognitifs aigus et prolongés ainsi qu'à des pathologies structurelles du cerveau. La faible saturation régionale du cerveau en oxygène (rSO2) pourrait être un facteur contributif. Objectif: Évaluer la possibilité de tester l'association entre la rSO2 intradialytique et les résultats neurologiques aigus et chroniques. Type d'étude: Étude observationnelle longitudinale. Cadre et sujets de l'étude: Nous avons recruté des patients qui entamaient une thérapie de remplacement rénal en continu ou une hémodialyse intermittente à l'unité des soins intensifs (USI) du Kingston Health Sciences Centre (KHSC). Mesures et méthodologie: La rSO2 a été surveillée pendant les 72 premières heures de thérapie de remplacement rénal en continu, ou tout au long de chaque séance d'hémodialyse intermittente. Nous avons mesuré les déficits neurologiques aigus par un dépistage quotidien du délirium et les atteintes neurocognitives à long terme à l'aide du robot Kinarm, de la Repeatable Battery for the Assessment of Neuropsychological Status et de l'imagerie par résonance magnétique cérébrale. Résultats: Sur les 484 patients hospitalisés à l'USI, 26 répondaient aux critères de sélection. Deux ont refusé de participer à l'étude et treize satisfaisaient à au moins un critère d'exclusion. Onze patients ont été inclus à l'étude. Huit patients sont décédés à l'USI, un est décédé deux mois après sa sortie de l'hôpital et un a refusé le suivi. Les taux de saisie des données étaient élevés: rSO2 et paramètres vitaux (91,3 %), dépistage du délirium et démographie (100 %). Des tests longitudinaux ont été effectués chez 50 % (1 de 2) des survivants. Limites: Le taux d'inscription était faible en raison de divers facteurs, ce qui a limité notre capacité à évaluer les résultats à long terme. Conclusion: Il est possible de collecter des données sur la rSO2 et le délirium chez les patients de soins intensifs qui suivent une thérapie de remplacement rénal; un taux de mortalité élevé a limité le suivi. Trial Registration: clinicaltrials.gov, registration number NCT04722939.

Outcomes and characteristics of patients hospitalized for COVID-19 in British Columbia, Ontario and Quebec during the Omicron wave.

BACKGROUND: Omicron is the current predominant variant of concern of SARS-CoV-2. We hypothesized that vaccination alters outcomes of patients hospitalized with COVID-19 during the Omicron wave and that these patients have different characteristics and outcomes than in previous waves. METHODS: This is a substudy of the Host Response Mediators in Coronavirus (COVID-19) Infection (ARBs CORONA I) trial, which included adults admitted to hospital with acute COVID-19 up to July 2022 from 9 hospitals in British Columbia, Ontario and Quebec. We excluded emergency department visits without hospital admission, readmissions and admissions for another reason. Using adjusted regression analysis, we compared mortality and organ dysfunction between vaccinated (≥ 2 doses) and unvaccinated patients during the Omicron wave, as well as between all patients in the Omicron and first 3 waves of the COVID-19 pandemic. RESULTS: During the Omicron wave, 28-day mortality was significantly lower in vaccinated (n = 19/237) than unvaccinated hospitalized patients (n = 12/127) (adjusted odds ratio [OR] 0.36, 95% confidence interval [CI] 0.15-0.89); vaccinated patients had lower risk of admission to the intensive care unit, invasive ventilation and acute respiratory distress syndrome and shorter hospital length of stay. Patients hospitalized during the Omicron wave had more comorbidities than in previous waves, and lower 28-day mortality than in waves 1 and 2 (adjusted OR 0.38, 95% CI 0.24-0.59; and 0.42, 95% CI 0.26-0.65) but not wave 3 (adjusted OR 0.81, 95% CI 0.43-1.51) and had less organ dysfunction than in the first 2 waves. INTERPRETATION: Patients who were at least double vaccinated had lower mortality than unvaccinated patients hospitalized during the Omicron wave. Patients hospitalized during the Omicron wave had more chronic disease and lower mortality than in the first 2 waves, but not wave 3. Changes in vaccination, treatments and predominant SARS-CoV-2 variant may have decreased mortality in patients hospitalized during the Omicron wave.

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.

Establishing the role of the FES tyrosine kinase in the pathogenesis, pathophysiology, and severity of sepsis and its outcomes.

Introduction: Sepsis is a result of initial over-activation of the immune system in response to an infection or trauma that results in reduced blood flow and life-threatening end-organ damage, followed by suppression of the immune system that prevents proper clearance of the infection or trauma. Because of this, therapies that not only limit the activation of the immune system early on, but also improve blood flow to crucial organs and reactivate the immune system in late-stage sepsis, may be effective treatments. The tyrosine kinase FES may fulfill this role. FES is present in immune cells and serves to limit immune system activation. We hypothesize that by enhancing FES in early sepsis and inhibiting its effects in late sepsis, the severity and outcome of septic illness can be improved. Methods and analysis: In vitro and in vivo modeling will be performed to determine the degree of inflammatory signaling, cytokine production, and neutrophil extracellular trap (NET) formation that occurs in wild-type (WT) and FES knockout (FES-/- ) mice. Clinically available treatments known to enhance or inhibit FES expression (lorlatinib and decitabine, respectively), will be used to explore the impact of early vs. late FES modulation on outcomes in WT mice. Bioinformatic analysis will be performed to examine FES expression levels in RNA transcriptomic data from sepsis patient cohorts, and correlate FES expression data with clinical outcomes (diagnosis of sepsis, illness severity, hospital length-of-stay). Ethics and dissemination: Ethics approval pending from the Queen's University Health Sciences & Affiliated Teaching Hospitals Research Ethics Board. Results will be disseminated through scientific publications and through lay summaries to patients and families.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

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.

A deep learning model for the classification of atrial fibrillation in critically ill patients.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia in the intensive care unit and is associated with increased morbidity and mortality. New-onset atrial fibrillation (NOAF) is often initially paroxysmal and fleeting, making it difficult to diagnose, and therefore difficult to understand the true burden of disease. Automated algorithms to detect AF in the ICU have been advocated as a means to better quantify its true burden. RESULTS: We used a publicly available 12-lead ECG dataset to train a deep learning model for the classification of AF. We then conducted an external independent validation of the model using continuous telemetry data from 984 critically ill patients collected in our institutional database. Performance metrics were stratified by signal quality, classified as either clean or noisy. The deep learning model was able to classify AF with an overall sensitivity of 84%, specificity of 89%, positive predictive value (PPV) of 55%, and negative predictive value of 97%. Performance was improved in clean data as compared to noisy data, most notably with respect to PPV and specificity. CONCLUSIONS: This model demonstrates that computational detection of AF is currently feasible and effective. This approach stands to improve the efficiency of retrospective and prospective research into AF in the ICU by automating AF detection, and enabling precise quantification of overall AF burden.

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.

Optimized Arterial Line Artifact Identification Algorithm Cleans High-Frequency Arterial Line Data With High Accuracy in Critically Ill Patients.

High-frequency data streams of vital signs may be used to generate individualized hemodynamic targets for critically ill patients. Central to this precision medicine approach to resuscitation is our ability to screen these data streams for errors and artifacts. However, there is no consensus on the best method for data cleaning. Our goal was to determine whether an error-checking algorithm developed for intraoperative use could be applied to high volumes of arterial line data in an ICU population. DESIGN: Multicenter observational study. SETTING: ICUs across Ontario, Canada. PATIENTS: Nested cohort of ICU patients with shock and/or respiratory failure requiring invasive mechanical ventilation. INTERVENTIONS: High-frequency blood pressure data was analyzed. Systolic, diastolic, and mean arterial pressure minute averages were calculated. For manual analysis, a trained researcher retrospectively reviewed mean arterial pressure data, removing values that were deemed nonphysiological. The algorithm was implemented and identified artifactual data. MEASUREMENTS AND MAIN RESULTS: Arterial line data was extracted from 15 patients. A trained researcher manually reviewed 40,798 minute-by-minute data points, then subsequently analyzed them with the algorithm. Manual review resulted in the identification of 119 artifacts (0.29%). The optimized algorithm identified 116 (97%) of these artifacts. Five hundred thirty-seven data points were erroneously removed or modified. Compared with manual review, the modified algorithm incorporating absolute thresholds of greater than 30 and less than 200 mm Hg had 97.5% sensitivity, 98.7% specificity, and a Matthew correlation coefficient of 0.41. CONCLUSIONS: The error-checking algorithm had high sensitivity and specificity in detecting arterial line blood pressure artifacts compared with manual data cleaning. Given the growing use of large datasets and machine learning in critical care research, methods to validate the quality of high-frequency data is important to optimize algorithm performance and prevent spurious associations based on artifactual data.