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Background:
COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.
Objective:
The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points.
Methods:
We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.
Results:
Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction.
Conclusions:
We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.
We report on simultaneous broadband observations of the TeV-emitting blazar Markarian 501 between 2013 April 1 and August 10, including the first detailed characterization of the synchrotron peak with Swift and NuSTAR. During the campaign, the nearby BL Lac object was observed in both a quiescent and an elevated state. The broadband campaign includes observations with NuSTAR, MAGIC, VERITAS, the Fermi Large Area Telescope, Swift X-ray Telescope and UV Optical Telescope, various ground-based optical instruments, including the GASP-WEBT program, as well as radio observations by OVRO, Metsahovi, and the F-Gamma consortium. Some of the MAGIC observations were affected by a sand layer from the Saharan desert, and had to be corrected using event-by-event corrections derived with a Light Detection and Ranging (LIDAR) facility. This is the first time that LIDAR information is used to produce a physics result with Cherenkov Telescope data taken during adverse atmospheric conditions, and hence sets a precedent for the current and future ground-based gamma-ray instruments. The NuSTAR instrument provides unprecedented sensitivity in hard X-rays, showing the source to display a spectral energy distribution (SED) between 3 and 79 keV consistent with a log-parabolic spectrum and hard X-ray variability on hour timescales. None (of the four extended NuSTAR observations) show evidence of the onset of inverse-Compton emission at hard X-ray energies. We apply a single-zone equilibrium synchrotron self-Compton (SSC) model to five simultaneous broadband SEDs. We find that the SSC model can reproduce the observed broadband states through a decrease in the magnetic field strength coinciding with an increase in the luminosity and hardness of the relativistic leptons responsible for the high-energy emission.
Phe2vec
(2021)
Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning and assess its effectiveness against standard rule-based algorithms from Phenotype KnowledgeBase (PheKB). Phe2vec is based on pre-computing embeddings of medical concepts and patients' clinical history. Disease phenotypes are then derived from a seed concept and its neighbors in the embedding space. Patients are linked to a disease if their embedded representation is close to the disease phenotype. Comparing Phe2vec and PheKB cohorts head-to-head using chart review, Phe2vec performed on par or better in nine out of ten diseases. Differently from other approaches, it can scale to any condition and was validated against widely adopted expert-based standards. Phe2vec aims to optimize clinical informatics research by augmenting current frameworks to characterize patients by condition and derive reliable disease cohorts.
The role that climate and environmental history may have played in influencing human evolution has been the focus of considerable interest and controversy among paleoanthropologists for decades. Prior attempts to understand the environmental history side of this equation have centered around the study of outcrop sediments and fossils adjacent to where fossil hominins (ancestors or close relatives of modern humans) are found, or from the study of deep sea drill cores. However, outcrop sediments are often highly weathered and thus are unsuitable for some types of paleoclimatic records, and deep sea core records come from long distances away from the actual fossil and stone tool remains. The Hominin Sites and Paleolakes Drilling Project (HSPDP) was developed to address these issues. The project has focused its efforts on the eastern African Rift Valley, where much of the evidence for early hominins has been recovered. We have collected about 2 km of sediment drill core from six basins in Kenya and Ethiopia, in lake deposits immediately adjacent to important fossil hominin and archaeological sites. Collectively these cores cover in time many of the key transitions and critical intervals in human evolutionary history over the last 4 Ma, such as the earliest stone tools, the origin of our own genus Homo, and the earliest anatomically modern Homo sapiens. Here we document the initial field, physical property, and core description results of the 2012-2014 HSPDP coring campaign.
The role that climate and environmental history may have played in influencing human evolution has been the focus of considerable interest and controversy among paleoanthropologists for decades. Prior attempts to understand the environmental history side of this equation have centered around the study of outcrop sediments and fossils adjacent to where fossil hominins (ancestors or close relatives of modern humans) are found, or from the study of deep sea drill cores. However, outcrop sediments are often highly weathered and thus are unsuitable for some types of paleoclimatic records, and deep sea core records come from long distances away from the actual fossil and stone tool remains. The Hominin Sites and Paleolakes Drilling Project (HSPDP) was developed to address these issues. The project has focused its efforts on the eastern African Rift Valley, where much of the evidence for early hominins has been recovered. We have collected about 2 km of sediment drill core from six basins in Kenya and Ethiopia, in lake deposits immediately adjacent to important fossil hominin and archaeological sites. Collectively these cores cover in time many of the key transitions and critical intervals in human evolutionary history over the last 4 Ma, such as the earliest stone tools, the origin of our own genus Homo, and the earliest anatomically modern Homo sapiens. Here we document the initial field, physical property, and core description results of the 2012-2014 HSPDP coring campaign.
HESS J1943+213
(2018)
HESS J1943+213 is a very high energy (VHE; > 100 GeV) gamma-ray source in the direction of the Galactic plane. Studies exploring the classification of the source are converging toward its identification as an extreme synchrotron BL Lac object. Here we present 38 hr of VERITAS observations of HESS J1943+213 taken over 2 yr. The source is detected with a significance of similar to 20 standard deviations, showing a remarkably stable flux and spectrum in VHE gamma-rays. Multifrequency Very Long Baseline Array (VLBA) observations of the source confirm the extended, jet-like structure previously found in the 1.6 GHz band with the European VLBI Network and detect this component in the 4.6 and 7.3 GHz bands. The radio spectral indices of the core and the jet and the level of polarization derived from the VLBA observations are in a range typical for blazars. Data from VERITAS, Fermi-LAT, Swift-XRT, the FLWO 48 ' telescope, and archival infrared and hard X-ray observations are used to construct and model the spectral energy distribution (SED) of the source with a synchrotron self-Compton model. The well-measured gamma-ray peak of the SED with VERITAS and Fermi-LAT provides constraining upper limits on the source redshift. Possible contribution of secondary gamma-rays from ultra-high-energy cosmic-ray-initiated electromagnetic cascades to the gamma-ray emission is explored, finding that only a segment of the VHE spectrum can be accommodated with this process. A variability search is performed across X-ray and gamma-ray bands. No statistically significant flux or spectral variability is detected.
The Galactic Center ridge has been observed extensively in the past by both GeV and TeV gamma-ray instruments revealing a wealth of structure, including a diffuse component and the point sources G0.9+0.1 (a composite supernova remnant) and Sgr A* (believed to be associated with the supermassive black hole located at the center of our Galaxy). Previous very high energy (VHE) gamma-ray observations with the H.E.S.S.. experiment have also detected an extended TeV gamma-ray component along the Galactic plane in the >300 GeV gamma-ray regime. Here we report on observations of the Galactic Center ridge from 2010 to 2014 by the VERITAS telescope array in the >2 TeV energy range. From these observations we (1) provide improved measurements of the differential energy spectrum for Sgr A* in the >2 TeV gamma-ray regime, (2) provide a detection in the >2 TeV gamma-ray emission from the composite SNR G0.9+0.1 and an improved determination of its multi-TeV gamma-ray energy spectrum, and. (3) report on the detection of VER J1746-289, a localized enhancement of >2 TeV gamma-ray emission along the Galactic plane.
We present a new measurement of the energy spectrum of iron nuclei in cosmic rays from 20 TeV to 500 TeV; The measurement makes use of a template-based analysis method, which, for the first time, is applied to the energy reconstruction of iron-induced air showers recorded by the VERITAS array of imaging atmospheric Cherenkov telescopes. The event selection makes use of the direct Cherenkov light which is emitted by charged particles before the first interaction, as well as other parameters related to the shape of the recorded air shower images. The measured spectrum is well described by a power law dF/dE = f(0) center dot (E/E-0)(-gamma) over the full energy range, with gamma = 2.82 +/- 0.30(stat)(-0.27)(+0.24)(syst) and f(0) = (4.82 +/- 0.98(stat)(-2.70)(+2.12)(syst)) x 10(-7) m(-2) s(-1) TeV-1 sr(-1) at E-0 = 50 TeV, with no indication of a cutoff or spectral break. The measured differential flux is compatible with previous results, with improved statistical uncertainty at the highest energies.
Cosmic-ray electrons and positrons (CREs) at GeV-TeV energies are a unique probe of our local Galactic neighborhood. CREs lose energy rapidly via synchrotron radiation and inverse-Compton scattering processes while propagating within the Galaxy, and these losses limit their propagation distance. For electrons with TeV energies, the limit is on the order of a kiloparsec. Within that distance, there are only a few known astrophysical objects capable of accelerating electrons to such high energies. It is also possible that the CREs are the products of the annihilation or decay of heavy dark matter (DM) particles. VERITAS, an array of imaging air Cherenkov telescopes in southern Arizona, is primarily utilized for gamma-ray astronomy but also simultaneously collects CREs during all observations. We describe our methods of identifying CREs in VERITAS data and present an energy spectrum, extending from 300 GeV to 5 TeV, obtained from approximately 300 hours of observations. A single power-law fit is ruled out in VERITAS data. We find that the spectrum of CREs is consistent with a broken power law, with a break energy at 710 +/- 40(stat) +/- 140(syst) GeV.