The eICU Collaborative Research Database, a freely available multi-center database for critical care research

Critical care patients are monitored closely through the course of their illness. As a result of this monitoring, large amounts of data are routinely collected for these patients. Philips Healthcare has developed a telehealth system, the eICU Program, which leverages these data to support management of critically ill patients. Here we describe the eICU Collaborative Research Database, a multi-center intensive care unit (ICU)database with high granularity data for over 200,000 admissions to ICUs monitored by eICU Programs across the United States. The database is deidentified, and includes vital sign measurements, care plan documentation, severity of illness measures, diagnosis information, treatment information, and more. Data are publicly available after registration, including completion of a training course in research with human subjects and signing of a data use agreement mandating responsible handling of the data and adhering to the principle of collaborative research. The freely available nature of the data will support a number of applications including the development of machine learning algorithms, decision support tools, and clinical research

Datathons and Software to Promote Reproducible Research

Background: Datathons facilitate collaboration between clinicians, statisticians, and data scientists in order to answer important clinical questions. Previous datathons have resulted in numerous publications of interest to the critical care community and serve as a viable model for interdisciplinary collaboration. Objective: We report on an open-source software called Chatto that was created by members of our group, in the context of the second international Critical Care Datathon, held in September 2015. Methods: Datathon participants formed teams to discuss potential research questions and the methods required to address them. They were provided with the Chatto suite of tools to facilitate their teamwork. Each multidisciplinary team spent the next 2 days with clinicians working alongside data scientists to write code, extract and analyze data, and reformulate their queries in real time as needed. All projects were then presented on the last day of the datathon to a panel of judges that consisted of clinicians and scientists. Results: Use of Chatto was particularly effective in the datathon setting, enabling teams to reduce the time spent configuring their research environments to just a few minutes—a process that would normally take hours to days. Chatto continued to serve as a useful research tool after the conclusion of the datathon. Conclusions: This suite of tools fulfills two purposes: (1) facilitation of interdisciplinary teamwork through archiving and version control of datasets, analytical code, and team discussions, and (2) advancement of research reproducibility by functioning postpublication as an online environment in which independent investigators can rerun or modify analyses with relative ease. With the introduction of Chatto, we hope to solve a variety of challenges presented by collaborative data mining projects while improving research reproducibility

The association between the neutrophil-to-lymphocyte ratio and mortality in critical illness: an observational cohort study

Introduction The neutrophil-to-lymphocyte ratio (NLR) is a biological marker that has been shown to be associated with outcomes in patients with a number of different malignancies. The objective of this study was to assess the relationship between NLR and mortality in a population of adult critically ill patients. Methods We performed an observational cohort study of unselected intensive care unit (ICU) patients based on records in a large clinical database. We computed individual patient NLR and categorized patients by quartile of this ratio. The association of NLR quartiles and 28-day mortality was assessed using multivariable logistic regression. Secondary outcomes included mortality in the ICU, in-hospital mortality and 1-year mortality. An a priori subgroup analysis of patients with versus without sepsis was performed to assess any differences in the relationship between the NLR and outcomes in these cohorts. Results A total of 5,056 patients were included. Their 28-day mortality rate was 19%. The median age of the cohort was 65 years, and 47% were female. The median NLR for the entire cohort was 8.9 (interquartile range, 4.99 to 16.21). Following multivariable adjustments, there was a stepwise increase in mortality with increasing quartiles of NLR (first quartile: reference category; second quartile odds ratio (OR) = 1.32; 95% confidence interval (CI), 1.03 to 1.71; third quartile OR = 1.43; 95% CI, 1.12 to 1.83; 4th quartile OR = 1.71; 95% CI, 1.35 to 2.16). A similar stepwise relationship was identified in the subgroup of patients who presented without sepsis. The NLR was not associated with 28-day mortality in patients with sepsis. Increasing quartile of NLR was statistically significantly associated with secondary outcome. Conclusion The NLR is associated with outcomes in unselected critically ill patients. In patients with sepsis, there was no statistically significant relationship between NLR and mortality. Further investigation is required to increase understanding of the pathophysiology of this relationship and to validate these findings with data collected prospectively.National Institutes of Health (U.S.) (Grant R01 EB017205-01A1

Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

With growing concerns that big data will only augment the problem of unreliable research, the Laboratory of Computational Physiology at the Massachusetts Institute of Technology organized the Critical Data Conference in January 2014. Thought leaders from academia, government, and industry across disciplines--including clinical medicine, computer science, public health, informatics, biomedical research, health technology, statistics, and epidemiology--gathered and discussed the pitfalls and challenges of big data in health care. The key message from the conference is that the value of large amounts of data hinges on the ability of researchers to share data, methodologies, and findings in an open setting. If empirical value is to be from the analysis of retrospective data, groups must continuously work together on similar problems to create more effective peer review. This will lead to improvement in methodology and quality, with each iteration of analysis resulting in more reliability

The role of lumbar puncture in children with suspected central nervous system infection

BACKGROUND: The use of the lumbar puncture in the diagnosis of central nervous system infection in acutely ill children is controversial. Recommendations have been published but it is unclear whether they are being followed. METHODS: The medical case notes of 415 acute medical admissions in a children's hospital were examined to identify children with suspected central nervous system infection and suspected meningococcal septicaemia. We determined whether lumbar punctures were indicated or contraindicated, whether they had been performed, and whether the results contributed to the patients' management. RESULTS: Fifty-two children with suspected central nervous system infections, and 43 with suspected meningococcal septicaemia were identified. No lumbar punctures were performed in patients with contraindications, but only 25 (53%) of 47 children with suspected central nervous system infection and no contraindications received a lumbar puncture. Lumbar puncture findings contributed to the management in 18 (72%) of these patients, by identifying a causative organism or excluding bacterial meningitis. CONCLUSION: The recommendations for undertaking lumbar punctures in children with suspected central nervous system infection are not being followed because many children that should receive lumbar punctures are not getting them. When they are performed, lumbar puncture findings make a useful contribution to the patients' management

Paediatric meningitis in the conjugate vaccine era and a novel clinical decision model to predict bacterial aetiology

Objectives The aims of this study were to assess aetiology and clinical characteristics in childhood meningitis, and develop clinical decision rules to distinguish bacterial meningitis from other similar clinical syndromes. Methods Children aged <16 years hospitalised with suspected meningitis/encephalitis were included, and prospectively recruited at 31 UK hospitals. Meningitis was defined as identification of bacteria/viruses from cerebrospinal fluid (CSF) and/or a raised CSF white blood cell count. New clinical decision rules were developed to distinguish bacterial from viral meningitis and those of alternative aetiology. Results The cohort included 3002 children (median age 2·4 months); 1101/3002 (36·7%) had meningitis, including 180 bacterial, 423 viral and 280 with no pathogen identified. Enterovirus was the most common pathogen in those aged <6 months and 10–16 years, with Neisseria meningitidis and/or Streptococcus pneumoniae commonest at age 6 months to 9 years. The Bacterial Meningitis Score had a negative predictive value of 95·3%. We developed two clinical decision rules, that could be used either before (sensitivity 82%, specificity 71%) or after lumbar puncture (sensitivity 84%, specificity 93%), to determine risk of bacterial meningitis. Conclusions Bacterial meningitis comprised 6% of children with suspected meningitis/encephalitis. Our clinical decision rules provide potential novel approaches to assist with identifying children with bacterial meningitis. Funding This study was funded by the Meningitis Research Foundation, Pfizer and the NIHR Programme Grants for Applied Research

In the dedicated pursuit of dedicated capital: restoring an indigenous investment ethic to British capitalism

Tony Blair’s landslide electoral victory on May 1 (New Labour Day?) presents the party in power with a rare, perhaps even unprecedented, opportunity to revitalise and modernise Britain’s ailing and antiquated manufacturing economy.* If it is to do so, it must remain true to its long-standing (indeed, historic) commitment to restore an indigenous investment ethic to British capitalism. In this paper we argue that this in turn requires that the party reject the very neo-liberal orthodoxies which it offered to the electorate as evidence of its competence, moderation and ‘modernisation’, which is has internalised, and which it apparently now views as circumscribing the parameters of the politically and economically possible

Topographic steering of enhanced ice flow at the bottleneck between East and West Antarctica

Hypothesized drawdown of the East Antarctic Ice Sheet (EAIS) through the ‘bottleneck’ zone between East and West Antarctica would have significant impacts for a large proportion of the Antarctic Ice Sheet. Earth observation satellite orbits and a sparseness of radio-echo sounding (RES) data have restricted investigations of basal boundary controls on ice flow in this region until now. New airborne RES surveys reveal complex topography of high relief beneath the southernmost Weddell/Ross ice divide, with three subglacial troughs connecting interior Antarctica to the Foundation and Patuxent Ice Streams and Siple Coast ice streams. These troughs route enhanced ice flow through the interior of Antarctica but limit potential drawdown of the EAIS through the bottleneck zone. In a thinning or retreating scenario, these topographically-controlled corridors of enhanced flow could however drive ice divide migration, and increase mass discharge from interior West Antarctica to the Southern Ocean