Finding the Right Distribution for Highly Skewed Zero-inflated Clinical Data

Discrete, highly skewed distributions with excess numbers of zeros often result in biased estimates and misleading inferences if the zeros are not properly addressed. A clinical example of children with electrophysiologic disorders in which many of the children are treated without surgery is provided. The purpose of the current study was to identify the optimal modeling strategy for highly skewed, zeroinflated data often observed in the clinical setting by: (a) simulating skewed, zero-inflated count data; (b) fitting simulated data with Poisson, Negative Binomial, Zero-Inflated Poisson (ZIP) and Zero-inflated Negative Binomial (ZINB) models; and, (c) applying the aforementioned models to actual, highlyskewed, clinical data of children with an EP disorder. The ZIP model was observed to be the optimal model based on traditional fit statistics as well as estimates of bias, mean-squared error, and coverage. &nbsp

Low frequency view of GRB 190114C reveals time varying shock micro-physics

We present radio and optical afterglow observations of the TeV-bright long gamma-ray burst 190114C at a redshift of z = 0.425, which was detected by the Major Atmospheric Gamma Imaging Cherenkov telescope. Our observations with Atacama Large Millimeter/submillitmeter Array, Australia Telescope Compact Array, and upgraded Giant Metre-wave Radio Telescope were obtained by our low frequency observing campaign and range from ∼1 to ∼140 d after the burst and the optical observations were done with three optical telescopes spanning up to ∼25 d after the burst. Long-term radio/mm observations reveal the complex nature of the afterglow, which does not follow the spectral and temporal closure relations expected from the standard afterglow model. We find that the microphysical parameters of the external forward shock, representing the share of shock-created energy in the non-thermal electron population and magnetic field, are evolving with time. The inferred kinetic energy in the blast-wave depends strongly on the assumed ambient medium density profile, with a constant density medium demanding almost an order of magnitude higher energy than in the prompt emission, while a stellar wind-driven medium requires approximately the same amount energy as in prompt emission

Low frequency view of GRB 190114C reveals time varying shock micro-physics

We present radio and optical afterglow observations of the TeV-bright long gamma-ray burst 190114C at a redshift of z = 0.425, which was detected by the Major Atmospheric Gamma Imaging Cherenkov telescope. Our observations with Atacama Large Millimeter/submillitmeter Array, Australia Telescope Compact Array, and upgraded Giant Metre-wave Radio Telescope were obtained by our low frequency observing campaign and range from ∼1 to ∼140 d after the burst and the optical observations were done with three optical telescopes spanning up to ∼25 d after the burst. Long-term radio/mm observations reveal the complex nature of the afterglow, which does not follow the spectral and temporal closure relations expected from the standard afterglow model. We find that the microphysical parameters of the external forward shock, representing the share of shock-created energy in the non-thermal electron population and magnetic field, are evolving with time. The inferred kinetic energy in the blast-wave depends strongly on the assumed ambient medium density profile, with a constant density medium demanding almost an order of magnitude higher energy than in the prompt emission, while a stellar wind-driven medium requires approximately the same amount energy as in prompt emission

Low frequency view of GRB 190114C reveals time varying shock micro-physics

We present radio and optical afterglow observations of the TeV-bright long Gamma Ray Burst (GRB) 190114C at a redshift of $z=0.425$, which was detected by the MAGIC telescope. Our observations with ALMA, ATCA, and uGMRT were obtained by our low frequency observing campaign and range from $\sim1$ to $\sim140$ days after the burst and the optical observations were done with three optical telescopes spanning up to $\sim25$ days after the burst. Long term radio/mm observations reveal the complex nature of the afterglow, which does not follow the spectral and temporal closure relations expected from the standard afterglow model. We find that the microphysical parameters of the external forward shock, representing the share of shock-created energy in the non-thermal electron population and magnetic field, are evolving with time. The inferred kinetic energy in the blast-wave depends strongly on the assumed ambient medium density profile, with a constant density medium demanding almost an order of magnitude higher energy than in the prompt emission, while a stellar wind-driven medium requires approximately the same amount energy as in prompt emission.Comment: MNRAS, in press, expanded after referee report, 19 pages, 15 figures, 6 table

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Glycemic Excursions in Type 1 Diabetes in Pregnancy: A Semiparametric Statistical Approach to Identify Sensitive Time Points during Gestation

Aim. To examine the gestational glycemic profile and identify specific times during pregnancy that variability in glucose levels, measured by change in velocity and acceleration/deceleration of blood glucose fluctuations, is associated with delivery of a large-for-gestational-age (LGA) baby, in women with type 1 diabetes. Methods. Retrospective analysis of capillary blood glucose levels measured multiple times daily throughout gestation in women with type 1 diabetes was performed using semiparametric mixed models. Results. Velocity and acceleration/deceleration in glucose levels varied across gestation regardless of delivery outcome. Compared to women delivering LGA babies, those delivering babies appropriate for gestational age exhibited significantly smaller rates of change and less variation in glucose levels between 180 days of gestation and birth. Conclusions. Use of innovative statistical methods enabled detection of gestational intervals in which blood glucose fluctuation parameters might influence the likelihood of delivering LGA baby in mothers with type 1 diabetes. Understanding dynamics and being able to visualize gestational changes in blood glucose are a potentially useful tool to assist care providers in determining the optimal timing to initiate continuous glucose monitoring

Glycemic Excursions in Type 1 Diabetes in Pregnancy: A Semiparametric Statistical Approach to Identify Sensitive Time Points during Gestation

Aim. To examine the gestational glycemic profile and identify specific times during pregnancy that variability in glucose levels, measured by change in velocity and acceleration/deceleration of blood glucose fluctuations, is associated with delivery of a large-forgestational-age (LGA) baby, in women with type 1 diabetes. Methods. Retrospective analysis of capillary blood glucose levels measured multiple times daily throughout gestation in women with type 1 diabetes was performed using semiparametric mixed models. Results. Velocity and acceleration/deceleration in glucose levels varied across gestation regardless of delivery outcome. Compared to women delivering LGA babies, those delivering babies appropriate for gestational age exhibited significantly smaller rates of change and less variation in glucose levels between 180 days of gestation and birth. Conclusions. Use of innovative statistical methods enabled detection of gestational intervals in which blood glucose fluctuation parameters might influence the likelihood of delivering LGA baby in mothers with type 1 diabetes. Understanding dynamics and being able to visualize gestational changes in blood glucose are a potentially useful tool to assist care providers in determining the optimal timing to initiate continuous glucose monitoring

Diabetes management and glycemic control in youth with type 1 diabetes: test of a predictive model

The objective of this study was to test a comprehensive model of biologic (pubertal status), family (communication and conflict), and psychological influences (behavioral autonomy) on diabetes management and glycemic control in a sample of youth (N = 226) with type 1 diabetes recruited during late childhood/early adolescence (ages 9–11 years). The study design was a prospective, multisite, multi-method study involving prediction of diabetes management and glycemic control 1 year post-baseline. The primary outcome measures included diabetes management behaviors based on the Diabetes Self-Management Profile (DSMP) administered separately to mothers and youth and glycemic control measured by glycated hemoglobin (HbA1c) obtained by blood samples and analyzed by a central laboratory to ensure standardization. Our hypothesized predictive model received partial support based on structural equation modeling analyses. Family conflict predicted less adequate glycemic control 1 year later (p < 0.05). Higher conflict predicted less adequate diabetes management and less adequate glycemic control. More advanced pubertal status also predicted less adequate glycemic control, but behavioral autonomy did not. Family conflict is an important, potentially clinically significant influence on glycemic control that should be considered in primary and secondary prevention in the management of type 1 diabetes in youth

Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach

Background. Characterizing maternal glucose sampling over the course of the entire pregnancy is an important step toward improvement in prediction of adverse birth outcome, such as preterm birth, for women with type 1 diabetes mellitus (T1DM). Objectives. To characterize the relationship between the gestational glycemic profile and risk of preterm birth using a joint modeling approach. Methods. A joint model was developed to simultaneously characterize the relationship between a longitudinal outcome (daily blood glucose sampling) and an event process (preterm birth). A linear mixed effects model using natural cubic splines was fitted to predict the longitudinal submodel. Covariates included mother’s age at last menstrual period, age at diabetes onset, body mass index, hypertension, retinopathy, and nephropathy. Various association structures (value, value plus slope, and area under the curve) were examined before selecting the final joint model. We compared the joint modeling approach to the time-dependent Cox model (TDCM). Results. A total of 16,480 glucose readings over gestation (range: 50-260 days) with 32 women (28%) having preterm birth was included in the study. Mother’s age at last menstrual period and age at diabetes onset were statistically significant (beta = 1.29, 95% CI 1.10, 1.72; beta = 0.84, 95% CI 0.62, 0.98) for the longitudinal submodel, reflecting that older women tended to have higher mean blood glucose and those with later diabetes onset tended to have a lower mean blood glucose level. The presence of nephropathy was statistically significant in the event submodel (beta = 2.29, 95% CI 1.05, 4.48). Cumulative association parameterization provided the best joint model fit. The joint model provided better fit compared to the time-dependent Cox model (DIC JM=19,895; DIC TDCM=19,932). Conclusion. The joint model approach was able to simultaneously characterize the glycemic profile and assess the risk of preterm birth and provided additional insights and a better model fit compared to the time-dependent Cox model

Analysis of EMG patterns of control subjects and subjects with ACL deficiency during an unanticipated walking cut task

Purpose: The purpose of this study was to describe the muscle activation patterns of the vastus lateralis (VL), medial hamstrings (MH) and lateral hamstrings (LH) associated with subjects that were anterior cruciate ligament (ACL) deficient and controls. Methods: A total of 54 subjects participated in this study including 25 ACL deficient subjects subdivided into copers (n = 9) and non-copers (n = 16) using clinical criteria. Muscle activation patterns were recorded at 1000 Hz during an unanticipated side step cut task. The root mean square processed data (time constant 11 ms) were ensemble averaged from 20% of stance before heel strike to toe off. Using the first five harmonics of the Fourier Coefficients as features, muscle activation patterns were divided using a cluster analysis algorithm. Results: A majority (76-93%) of control subjects used three muscle activation patterns for each muscle. The coper group preferentially used a particular VL and MH activation pattern \u3e2 times more frequently than controls. The non-coper group also preferentially used a MH activation pattern \u3e2 times more frequently than controls and utilized a unique MH and LH activation pattern, distinct from the copers and controls. Conclusions: Specific muscle activation patterns distinguish subsets of subjects that are healthy and injured, suggesting possible patterns of muscle activation that contribute to coping status. © 2006 Elsevier B.V. All rights reserved