Interoperable and explainable machine learning models to predict morbidity and mortality in acute neurological injury in the pediatric intensive care unit: secondary analysis of the TOPICC study

BackgroundAcute neurological injury is a leading cause of permanent disability and death in the pediatric intensive care unit (PICU). No predictive model has been validated for critically ill children with acute neurological injury.ObjectivesWe hypothesized that PICU patients with concern for acute neurological injury are at higher risk for morbidity and mortality, and advanced analytics would derive robust, explainable subgroup models.MethodsWe performed a secondary subgroup analysis of the Trichotomous Outcomes in Pediatric Critical Care (TOPICC) study (2011–2013), predicting mortality and morbidity from admission physiology (lab values and vital signs in 6 h surrounding admission). We analyzed patients with suspected acute neurological injury using standard machine learning algorithms. Feature importance was analyzed using SHapley Additive exPlanations (SHAP). We created a Fast Healthcare Interoperability Resources (FHIR) application to demonstrate potential for interoperability using pragmatic data.Results1,860 patients had suspected acute neurological injury at PICU admission, with higher morbidity (8.2 vs. 3.4%) and mortality (6.2 vs. 1.9%) than those without similar concern. The ensemble regressor (containing Random Forest, Gradient Boosting, and Support Vector Machine learners) produced the best model, with Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.91 [95% CI (0.88, 0.94)] and Average Precision (AP) of 0.59 [0.51, 0.69] for mortality, and decreased performance predicting simultaneous mortality and morbidity (0.83 [0.80, 0.86] and 0.59 [0.51, 0.64]); at a set specificity of 0.995, positive predictive value (PPV) was 0.79 for mortality, and 0.88 for mortality and morbidity. By comparison, for mortality, the TOPICC logistic regression had AUROC of 0.90 [0.84, 0.93], but substantially inferior AP of 0.49 [0.35, 0.56] and PPV of 0.60 at specificity 0.995. Feature importance analysis showed that pupillary non-reactivity, Glasgow Coma Scale, and temperature were the most contributory vital signs, and acidosis and coagulopathy the most important laboratory values. The FHIR application provided a simulated demonstration of real-time health record query and model deployment.ConclusionsPICU patients with suspected acute neurological injury have higher mortality and morbidity. Our machine learning approach independently identified previously-known causes of secondary brain injury. Advanced modeling achieves improved positive predictive value in this important population compared to published models, providing a stepping stone in the path to deploying explainable models as interoperable bedside decision-support tools

A High-Resolution Airborne Color-Infrared Camera Water Mask for the NASA ABoVE Campaign

The airborne AirSWOT instrument suite, consisting of an interferometric Ka-band synthetic aperture radar and color-infrared (CIR) camera, was deployed to northern North America in July and August 2017 as part of the NASA Arctic-Boreal Vulnerability Experiment (ABoVE). We present validated, open (i.e., vegetation-free) surface water masks produced from high-resolution (1 m), co-registered AirSWOT CIR imagery using a semi-automated, object-based water classification. The imagery and resulting high-resolution water masks are available as open-access datasets and support interpretation of AirSWOT radar and other coincident ABoVE image products, including LVIS, UAVSAR, AIRMOSS, AVIRIS-NG, and CFIS. These synergies offer promising potential for multi-sensor analysis of Arctic-Boreal surface water bodies. In total, 3167 km2 of open surface water were mapped from 23,380 km2 of flight lines spanning 23 degrees of latitude and broad environmental gradients. Detected water body sizes range from 0.00004 km2 (40 m2) to 15 km2. Power-law extrapolations are commonly used to estimate the abundance of small lakes from coarser resolution imagery, and our mapped water bodies followed power-law distributions, but only for water bodies greater than 0.34 (±0.13) km2 in area. For water bodies exceeding this size threshold, the coefficients of power-law fits vary for different Arctic-Boreal physiographic terrains (wetland, prairie pothole, lowland river valley, thermokarst, and Canadian Shield). Thus, direct mapping using high-resolution imagery remains the most accurate way to estimate the abundance of small surface water bodies. We conclude that empirical scaling relationships, useful for estimating total trace gas exchange and aquatic habitats on Arctic-Boreal landscapes, are uniquely enabled by high-resolution AirSWOT-like mappings and automated detection methods such as those developed here

Impact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

Obesity and metabolic syndrome results from a complex interaction between genetic and environmetal factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator lean (L) strain. To enrich for adipose tissue obesity genes a ˝snap-shot˝ pooled-sample transcriptome comparison of key fat depots and non adipose tissue (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue.A number of novel obesity candidate genes were also identified (Thbs1, Ppp1rd, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred rolesin fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a dictinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathaways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity

Effect of Convalescent Plasma on Organ Support-Free Days in Critically Ill Patients With COVID-19: A Randomized Clinical Trial

Importance: The evidence for benefit of convalescent plasma for critically ill patients with COVID-19 is inconclusive. Objective: To determine whether convalescent plasma would improve outcomes for critically ill adults with COVID-19. Design, Setting, and Participants: The ongoing Randomized, Embedded, Multifactorial, Adaptive Platform Trial for Community-Acquired Pneumonia (REMAP-CAP) enrolled and randomized 4763 adults with suspected or confirmed COVID-19 between March 9, 2020, and January 18, 2021, within at least 1 domain; 2011 critically ill adults were randomized to open-label interventions in the immunoglobulin domain at 129 sites in 4 countries. Follow-up ended on April 19, 2021. Interventions: The immunoglobulin domain randomized participants to receive 2 units of high-titer, ABO-compatible convalescent plasma (total volume of 550 mL ± 150 mL) within 48 hours of randomization (n = 1084) or no convalescent plasma (n = 916). Main Outcomes and Measures: The primary ordinal end point was organ support-free days (days alive and free of intensive care unit-based organ support) up to day 21 (range, -1 to 21 days; patients who died were assigned -1 day). The primary analysis was an adjusted bayesian cumulative logistic model. Superiority was defined as the posterior probability of an odds ratio (OR) greater than 1 (threshold for trial conclusion of superiority >99%). Futility was defined as the posterior probability of an OR less than 1.2 (threshold for trial conclusion of futility >95%). An OR greater than 1 represented improved survival, more organ support-free days, or both. The prespecified secondary outcomes included in-hospital survival; 28-day survival; 90-day survival; respiratory support-free days; cardiovascular support-free days; progression to invasive mechanical ventilation, extracorporeal mechanical oxygenation, or death; intensive care unit length of stay; hospital length of stay; World Health Organization ordinal scale score at day 14; venous thromboembolic events at 90 days; and serious adverse events. Results: Among the 2011 participants who were randomized (median age, 61 [IQR, 52 to 70] years and 645/1998 [32.3%] women), 1990 (99%) completed the trial. The convalescent plasma intervention was stopped after the prespecified criterion for futility was met. The median number of organ support-free days was 0 (IQR, -1 to 16) in the convalescent plasma group and 3 (IQR, -1 to 16) in the no convalescent plasma group. The in-hospital mortality rate was 37.3% (401/1075) for the convalescent plasma group and 38.4% (347/904) for the no convalescent plasma group and the median number of days alive and free of organ support was 14 (IQR, 3 to 18) and 14 (IQR, 7 to 18), respectively. The median-adjusted OR was 0.97 (95% credible interval, 0.83 to 1.15) and the posterior probability of futility (O

Reduction in Radiation Exposure in Cardiovascular CT Imaging

Advances of cardiac computed tomography angiography (CTA) have been developed for dose reduction, but their efficacy in clinical practice is largely unknown. This study was designed to evaluate radiation dose exposure and utilization of dose-saving strategies for contrast-enhanced cardiac CTA in daily practice

An upper limit to the photon fraction in cosmic rays above 10^19 eV from the Pierre Auger Observatory

An upper limit of 16% (at 95% c.l.) is derived for the photon fraction in cosmic rays with energies above 10^19 eV, based on observations of the depth of shower maximum performed with the hybrid detector of the Pierre Auger Observatory. This is the first such limit on photons obtained by observing the fluorescence light profile of air showers. This upper limit confirms and improves on previous results from the Haverah Park and AGASA surface arrays. Additional data recorded with the Auger surface detectors for a subset of the event sample, support the conclusion that a photon origin of the observed events is not favoured

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Identification of Post-cardiac Arrest Blood Pressure Thresholds Associated With Outcomes in Children: An ICU-Resuscitation Study

INTRODUCTION: Though early hypotension after pediatric in-hospital cardiac arrest (IHCA) is associated with inferior outcomes, ideal post-arrest blood pressure (BP) targets have not been established. We aimed to leverage prospectively collected BP data to explore the association of post-arrest BP thresholds with outcomes. We hypothesized that post-arrest systolic and diastolic BP thresholds would be higher than the currently recommended post-cardiopulmonary resuscitation BP targets and would be associated with higher rates of survival to hospital discharge. METHODS: We performed a secondary analysis of prospectively collected BP data from the first 24 h following return of circulation from index IHCA events enrolled in the ICU-RESUScitation trial (NCT02837497). The lowest documented systolic BP (SBP) and diastolic BP (DBP) were percentile-adjusted for age, height and sex. Receiver operator characteristic curves and cubic spline analyses controlling for illness category and presence of pre-arrest hypotension were generated exploring the association of lowest post-arrest SBP and DBP with survival to hospital discharge and survival to hospital discharge with favorable neurologic outcome (Pediatric Cerebral Performance Category of 1-3 or no change from baseline). Optimal cutoffs for post-arrest BP thresholds were based on analysis of receiver operator characteristic curves and spline curves. Logistic regression models accounting for illness category and pre-arrest hypotension examined the associations of these thresholds with outcomes. RESULTS: Among 693 index events with 0-6 h post-arrest BP data, identified thresholds were: SBP \u3e 10th percentile and DBP \u3e 50th percentile for age, sex and height. Fifty-one percent (n = 352) of subjects had lowest SBP above threshold and 50% (n = 346) had lowest DBP above threshold. SBP and DBP above thresholds were each associated with survival to hospital discharge (SBP: aRR 1.21 [95% CI 1.10, 1.33]; DBP: aRR 1.23 [1.12, 1.34]) and survival to hospital discharge with favorable neurologic outcome (SBP: aRR 1.22 [1.10, 1.35]; DBP: aRR 1.27 [1.15, 1.40]) (all p \u3c 0.001). CONCLUSIONS: Following pediatric IHCA, subjects had higher rates of survival to hospital discharge and survival to hospital discharge with favorable neurologic outcome when BP targets above a threshold of SBP \u3e 10th percentile for age and DBP \u3e 50th percentile for age during the first 6 h post-arrest