Using Tactile Pressure Sensors to Measure Lateral Spreading Induced Earth Pressures Against a Large, Rigid Foundation

Two centrifuge tests were performed at the NEES facility at Rensselaer Polytechnic Institute (RPI) to observe lateral earth pressures mobilized against a rigid foundation element during liquefaction-induced lateral spreading, as part of a larger NEESR study aimed at developing novel approaches to mitigate the effects of seismically-induced ground failures on large, rigid foundation elements. Models were constructed in a laminar box to allow unimpeded downslope soil displacement, and the sand in the model was liquefied during the centrifuge test. Lateral pressures prior to, during, and after shaking and liquefaction were directly measured using a novel device: tactile pressure sensors. Prior to testing the production models, several 1g and centrifuge experiments were conducted to determine whether the tactile pressure sensors would accurately measure pressures. Using the tactile pressure sensor and configuration described in this paper, geostatic pressures measured prior to the shaking agreed well with the anticipated theoretical at-rest earth pressures. In this paper, we describe these initial tests, the challenges that were encountered, methods employed to overcome these challenges, and the production centrifuge tests

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illnessResearch in context

Summary: Background: Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification of genes associated with a persistent MODS trajectory may shed light on underlying biology and allow for accurate prediction of those at-risk. Methods: Secondary analyses of publicly available gene-expression datasets. Supervised machine learning (ML) was used to identify a parsimonious set of genes associated with a persistent MODS trajectory in a training set of pediatric septic shock. We optimized model parameters and tested risk-prediction capabilities in independent validation and test datasets, respectively. We compared model performance relative to an established gene-set predictive of sepsis mortality. Findings: Patients with a persistent MODS trajectory had 568 differentially expressed genes and characterized by a dysregulated innate immune response. Supervised ML identified 111 genes associated with the outcome of interest on repeated cross-validation, with an AUROC of 0.87 (95% CI: 0.85–0.88) in the training set. The optimized model, limited to 20 genes, achieved AUROCs ranging from 0.74 to 0.79 in the validation and test sets to predict those with persistent MODS, regardless of host age and cause of organ dysfunction. Our classifier demonstrated reproducibility in identifying those with persistent MODS in comparison with a published gene-set predictive of sepsis mortality. Interpretation: We demonstrate the utility of supervised ML driven identification of the genes associated with persistent MODS. Pending validation in enriched cohorts with a high burden of organ dysfunction, such an approach may inform targeted delivery of interventions among at-risk patients. Funding: H.R.W.′s NIH R35GM126943 award supported the work detailed in this manuscript. Upon his death, the award was transferred to M.N.A. M.R.A., N.S.P, and R.K were supported by NIH R21GM151703. R.K. was supported by R01GM139967

Risk factors for mortality in pediatric postsurgical versus medical severe sepsis

Background: Sepsis is a leading cause of morbidity and mortality after surgery. Most studies regarding sepsis do not differentiate between patients who have had recent surgery and those without. Few data exist regarding the risk factors for poor outcomes in pediatric postsurgical sepsis. Our hypothesis is pediatric postsurgical, and medical patients with severe sepsis have unique risk factors for mortality. Methods: Data were extracted from a secondary analysis of an international point prevalence study of pediatric severe sepsis. Sites included 128 pediatric intensive care units from 26 countries. Pediatric patients with severe sepsis were categorized into those who had recent surgery (postsurgical sepsis) versus those that did not (medical sepsis) before sepsis onset. Multivariable logistic regression models were used to determine risk factors for mortality. Results: A total of 556 patients were included: 138 with postsurgical and 418 with medical sepsis. In postsurgical sepsis, older age, admission from the hospital ward, multiple organ dysfunction syndrome at sepsis recognition, and cardiovascular and respiratory comorbidities were independent risk factors for death. In medical sepsis, resource-limited region, hospital-acquired infection, multiple organ dysfunction syndrome at sepsis recognition, higher Pediatric Index of Mortality-3 score, and malignancy were independent risk factors for death. Conclusions: Pediatric patients with postsurgical sepsis had different risk factors for mortality compared with medical sepsis. This included a higher mortality risk in postsurgical patients presenting to the intensive care unit from the hospital ward. These data suggest an opportunity to develop and test early warning systems specific to pediatric sepsis in the postsurgical population

Pediatric Organ Dysfunction Information Update Mandate (PODIUM) Contemporary Organ Dysfunction Criteria: Executive Summary.

Prior criteria for organ dysfunction in critically ill children were based mainly on expert opinion. We convened the Pediatric Organ Dysfunction Information Update Mandate (PODIUM) expert panel to summarize data characterizing single and multiple organ dysfunction and to derive contemporary criteria for pediatric organ dysfunction. The panel was composed of 88 members representing 47 institutions and 7 countries. We conducted systematic reviews of the literature to derive evidence-based criteria for single organ dysfunction for neurologic, cardiovascular, respiratory, gastrointestinal, acute liver, renal, hematologic, coagulation, endocrine, endothelial, and immune system dysfunction. We searched PubMed and Embase from January 1992 to January 2020. Study identification was accomplished using a combination of medical subject headings terms and keywords related to concepts of pediatric organ dysfunction. Electronic searches were performed by medical librarians. Studies were eligible for inclusion if the authors reported original data collected in critically ill children; evaluated performance characteristics of scoring tools or clinical assessments for organ dysfunction; and assessed a patient-centered, clinically meaningful outcome. Data were abstracted from each included study into an electronic data extraction form. Risk of bias was assessed using the Quality in Prognosis Studies tool. Consensus was achieved for a final set of 43 criteria for pediatric organ dysfunction through iterative voting and discussion. Although the PODIUM criteria for organ dysfunction were limited by available evidence and will require validation, they provide a contemporary foundation for researchers to identify and study single and multiple organ dysfunction in critically ill children

A Core Outcome Measurement Set for Pediatric Critical Care

Objectives: To identify a PICU Core Outcome Measurement Set (PICU COMS), a set of measures that can be used to evaluate the PICU Core Outcome Set (PICU COS) domains in PICU patients and their families. Design: A modified Delphi consensus process. Setting: Four webinars attended by PICU physicians and nurses, pediatric surgeons, rehabilitation physicians, and scientists with expertise in PICU clinical care or research (n = 35). Attendees were from eight countries and convened from the Pediatric Acute Lung Injury and Sepsis Investigators Pediatric Outcomes STudies after PICU Investigators and the Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network PICU COS Investigators. Subjects: Measures to assess outcome domains of the PICU COS are as follows: cognitive, emotional, overall (including health-related quality of life), physical, and family health. Measures evaluating social health were also considered. Interventions: None. Measurements and Main Results: Measures were classified as general or additional based on generalizability across PICU populations, feasibility, and relevance to specific COS domains. Measures with high consensus, defined as 80% agreement for inclusion, were selected for the PICU COMS. Among 140 candidate measures, 24 were delineated as general (broadly applicable) and, of these, 10 achieved consensus for inclusion in the COMS (7 patient-oriented and 3 family-oriented). Six of the seven patient measures were applicable to the broadest range of patients, diagnoses, and developmental abilities. All were validated in pediatric populations and have normative pediatric data. Twenty additional measures focusing on specific populations or in-depth evaluation of a COS subdomain also met consensus for inclusion as COMS additional measures. Conclusions: The PICU COMS delineates measures to evaluate domains in the PICU COS and facilitates comparability across future research studies to characterize PICU survivorship and enable interventional studies to target long-term outcomes after critical illness.</p