NPRL: Nightly Profile Representation Learning for Early Sepsis Onset Prediction in ICU Trauma Patients

Sepsis is a syndrome that develops in response to the presence of infection. It is characterized by severe organ dysfunction and is one of the leading causes of mortality in Intensive Care Units (ICUs) worldwide. These complications can be reduced through early application of antibiotics, hence the ability to anticipate the onset of sepsis early is crucial to the survival and well-being of patients. Current machine learning algorithms deployed inside medical infrastructures have demonstrated poor performance and are insufficient for anticipating sepsis onset early. In recent years, deep learning methodologies have been proposed to predict sepsis, but some fail to capture the time of onset (e.g., classifying patients' entire visits as developing sepsis or not) and others are unrealistic to be deployed into medical facilities (e.g., creating training instances using a fixed time to onset where the time of onset needs to be known apriori). Therefore, in this paper, we first propose a novel but realistic prediction framework that predicts each morning whether sepsis onset will occur within the next 24 hours with the help of most recent data collected at night, when patient-provider ratios are higher due to cross-coverage resulting in limited observation to each patient. However, as we increase the prediction rate into daily, the number of negative instances will increase while that of positive ones remain the same. Thereafter, we have a severe class imbalance problem, making a machine learning model hard to capture rare sepsis cases. To address this problem, we propose to do nightly profile representation learning (NPRL) for each patient. We prove that NPRL can theoretically alleviate the rare event problem. Our empirical study using data from a level-1 trauma center further demonstrates the effectiveness of our proposal

A Candidate Brightest Proto-Cluster Galaxy at z = 3.03

We report the discovery of a very bright (m_R = 22.2) Lyman break galaxy at z = 3.03 that appears to be a massive system in a late stage of merging. Deep imaging reveals multiple peaks in the brightness profile with angular separations of ~0.''8 (~25 h^-1 kpc comoving). In addition, high signal-to-noise ratio rest-frame UV spectroscopy shows evidence for ~5 components based on stellar photospheric and ISM absorption lines with a velocity dispersion of sigma ~460 km s^-1 for the three strongest components. Both the dynamics and high luminosity, as well as our analysis of a LCDM numerical simulation, suggest a very massive system with halo mass M ~ 10^13 M_solar. The simulation finds that all halos at z = 3 of this mass contain sub-halos in agreement with the properties of these observed components and that such systems typically evolve into M ~ 10^14 M_solar halos in groups and clusters by z = 0. This discovery provides a rare opportunity to study the properties and individual components of z ~ 3 systems that are likely to be the progenitors to brightest cluster galaxies.Comment: 14 pages, 3 figures, submitted to ApJ Letter

Disordered loops in the two-dimensional antiferromagnetic spin-fermion model

The spin-fermion model has long been used to describe the quantum-critical behavior of 2d electron systems near an antiferromagnetic (AFM) instability. Recently, the standard procedure to integrate out the fermions to obtain an effective action for spin waves has been questioned in the clean case. We show that in the presence of disorder, the single fermion loops display two crossover scales: upon lowering the energy, the singularities of the clean fermionic loops are first cut off, but below a second scale new singularities arise that lead again to marginal scaling. In addition, impurity lines between different fermion loops generate new relevant couplings which dominate at low energies. We outline a non-linear sigma model formulation of the single-loop problem, which allows to control the higher singularities and provides an effective model in terms of low-energy diffusive as well as spin modes.Comment: 22 pages, 8 figure

Multi-Subset Approach to Early Sepsis Prediction

Sepsis is a life-threatening organ malfunction caused by the host's inability to fight infection, which can lead to death without proper and immediate treatment. Therefore, early diagnosis and medical treatment of sepsis in critically ill populations at high risk for sepsis and sepsis-associated mortality are vital to providing the patient with rapid therapy. Studies show that advancing sepsis detection by 6 hours leads to earlier administration of antibiotics, which is associated with improved mortality. However, clinical scores like Sequential Organ Failure Assessment (SOFA) are not applicable for early prediction, while machine learning algorithms can help capture the progressing pattern for early prediction. Therefore, we aim to develop a machine learning algorithm that predicts sepsis onset 6 hours before it is suspected clinically. Although some machine learning algorithms have been applied to sepsis prediction, many of them did not consider the fact that six hours is not a small gap. To overcome this big gap challenge, we explore a multi-subset approach in which the likelihood of sepsis occurring earlier than 6 hours is output from a previous subset and feed to the target subset as additional features. Moreover, we use the hourly sampled data like vital signs in an observation window to derive a temporal change trend to further assist, which however is often ignored by previous studies. Our empirical study shows that both the multi-subset approach to alleviating the 6-hour gap and the added temporal trend features can help improve the performance of sepsis-related early prediction

Using Emotional Freedom Techniques (EFT) to Treat PTSD in Veterans: A Review of the Evidence, Survey of Practitioners, and Proposed Clinical Guidelines

Abstract BACKGROUND: High prevalence rates of posttraumatic stress disorder (PTSD) in active military and veterans present a treatment challenge. Many PTSD studies have demonstrated the efficacy and safety of Emotional Freedom Techniques (EFT). OBJECTIVES: To develop clinical best practice guidelines for the use of EFT to treat PTSD, on the basis of the published literature, practitioner experience, and typical case histories. METHODS: We surveyed 448 EFT practitioners to gather information on their experiences with PTSD treatment. This included their demographic profiles, prior training, professional settings, use of assessments, and PTSD treatment practices. We used their responses, with the research evidence base, to formulate clinical guidelines applying the "stepped care" treatment model used by the United Kingdom's National Institute for Health and Clinical Excellence. RESULTS: Most practitioners (63%) reported that even complex PTSD can be remediated in 10 or fewer EFT sessions. Some 65% of practitioners found that more than 60% of PTSD clients are fully rehabilitated, and 89% stated that less than 10% of clients make little or no progress. Practitioners combined EFT with a wide variety of other approaches, especially cognitive therapy. Practitioner responses, evidence from the literature, and the results of a meta-analysis were aggregated into a proposed clinical guideline. CONCLUSION: We recommend a stepped care model, with 5 EFT therapy sessions for subclinical PTSD and 10 sessions for clinical PTSD, in addition to group therapy, online self-help resources, and social support. Clients who fail to respond should be referred for appropriate further care

Are We Making Progress in Medical Education?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75582/1/j.1525-1497.2006.00446.x.pd

Observed Binary Fraction Sets Limits on the Extent of Collisional Grinding in the Kuiper Belt

The size distribution in the cold classical Kuiper belt can be approximated by two idealized power laws: one with steep slope for radii R>R* and one with shallow slope for R<R*, where R*~25-50 km. Previous works suggested that the SFD roll-over at R* can be the result of extensive collisional grinding in the Kuiper belt that led to the catastrophic disruption of most bodies with R<R*. Here we use a new code to test the effect of collisions in the Kuiper belt. We find that the observed roll-over could indeed be explained by collisional grinding provided that the initial mass in large bodies was much larger than the one in the present Kuiper belt, and was dynamically depleted. In addition to the size distribution changes, our code also tracks the effects of collisions on binary systems. We find that it is generally easier to dissolve wide binary systems, such as the ones existing in the cold Kuiper belt today, than to catastrophically disrupt objects with R~R*. Thus, the binary survival sets important limits on the extent of collisional grinding in the Kuiper belt. We find that the extensive collisional grinding required to produce the SFD roll-over at R* would imply a strong gradient of the binary fraction with R and separation, because it is generally easier to dissolve binaries with small components and/or those with wide orbits. The expected binary fraction for R<R* is <0.1. The present observational data do not show such a gradient. Instead, they suggest a large binary fraction of ~0.4 for R=30-40 km. This may indicate that the roll-over was not produced by disruptive collisions, but is instead a fossil remnant of the KBO formation process.Comment: The Astronomical Journal, in pres

A randomized trial to determine the impact on compliance of a psychophysical peripheral cue based on the Elaboration Likelihood Model

Objective: Non-compliance in clinical studies is a significant issue, but causes remain unclear. Utilizing the Elaboration Likelihood Model of persuasion, this study assessed the psychophysical peripheral cue ‘Interactive Voice Response System (IVRS) call frequency’ on compliance. Methods: 71 participants were randomized to once daily (OD), twice daily (BID) or three times daily (TID) call schedules over two weeks. Participants completed 30-item cognitive function tests at each call. Compliance was defined as proportion of expected calls within a narrow window (± 30 min around scheduled time), and within a relaxed window (− 30 min to + 4 h). Data were analyzed by ANOVA and pairwise comparisons adjusted by the Bonferroni correction. Results: There was a relationship between call frequency and compliance. Bonferroni adjusted pairwise comparisons showed significantly higher compliance (p = 0.03) for the BID (51.0%) than TID (30.3%) for the narrow window; for the extended window, compliance was higher (p = 0.04) with OD (59.5%), than TID (38.4%). Conclusion: The IVRS psychophysical peripheral cue call frequency supported the ELM as a route to persuasion. The results also support OD strategy for optimal compliance. Models suggest specific indicators to enhance compliance with medication dosing and electronic patient diaries to improve health outcomes and data integrity respectively

Formation of Kuiper Belt Binaries by Gravitational Collapse

A large fraction of 100-km-class low-inclination objects in the classical Kuiper Belt (KB) are binaries with comparable mass and wide separation of components. A favored model for their formation was capture during the coagulation growth of bodies in the early KB. Instead, recent studies suggested that large objects can rapidly form in the protoplanetary disks when swarms of locally concentrated solids collapse under their own gravity. Here we examine the possibility that KB binaries formed during gravitational collapse when the excess of angular momentum prevented the agglomeration of available mass into a solitary object. We find that this new mechanism provides a robust path toward the formation of KB binaries with observed properties, and can explain wide systems such as 2001 QW322 and multiples such as (47171) 1999 TC36. Notably, the gravitational collapse is capable of producing 100% binary fraction for a wide range of the swarm's initial angular momentum values. The binary components have similar masses (80% have the secondary-over-primary radius ratio >0.7) and their separation ranges from ~1,000 to ~100,000 km. The binary orbits have eccentricities from e=0 to ~1, with the majority having e<0.6. The binary orbit inclinations with respect to the initial angular momentum of the swarm range from i=0 to ~90 deg, with most cases having i<50 deg. Our binary formation mechanism implies that the primary and secondary components in each binary pair should have identical bulk composition, which is consistent with the current photometric data. We discuss the applicability of our results to the Pluto-Charon, Orcus-Vanth, (617) Patroclus-Menoetius and (90) Antiope binary systems.Comment: Astronomical Journal, in pres

An Impossibility Theorem for Base Rate Tracking and Equalised Odds

There is a theorem that shows that it is impossible for an algorithm to jointly satisfy the statistical fairness criteria of Calibration and Equalised Odds non-trivially. But what about the recently advocated alternative to Calibration, Base Rate Tracking? Here, we show that Base Rate Tracking is strictly weaker than Calibration, and then take up the question of whether it is possible to jointly satisfy Base Rate Tracking and Equalised Odds in non-trivial scenarios. We show that it is not, thereby establishing an even more general impossibility theorem