Network Analysis Subtleties in ICU Structures and Outcomes.
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ABSTRACT:
SUBMITTER: Chen Y
PROVIDER: S-EPMC7706157 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
Publications
Network Analysis Subtleties in ICU Structures and Outcomes.
Chen You Y Yan Chao C Patel Mayur B MB
American journal of respiratory and critical care medicine 20201201 11
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Project description: Not available
| S-EPMC7706162 | biostudies-literature
Project description:Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/.
| S-EPMC4987928 | biostudies-literature
Project description:BackgroundHealth care organizations (HCOs) adopt strategies (eg. physical distancing) to protect clinicians and patients in intensive care units (ICUs) during the COVID-19 pandemic. Many care activities physically performed before the COVID-19 pandemic have transitioned to virtual systems during the pandemic. These transitions can interfere with collaboration structures in the ICU, which may impact clinical outcomes. Understanding the differences can help HCOs identify challenges when transitioning physical collaboration to the virtual setting in the post-COVID-19 era.ObjectiveThis study aims to leverage network analysis to determine the changes in neonatal ICU (NICU) collaboration structures from the pre- to the intra-COVID-19 era.MethodsIn this retrospective study, we applied network analysis to the utilization of electronic health records (EHRs) of 712 critically ill neonates (pre-COVID-19, n=386; intra-COVID-19, n=326, excluding those with COVID-19) admitted to the NICU of Vanderbilt University Medical Center between September 1, 2019, and June 30, 2020, to assess collaboration between clinicians. We characterized pre-COVID-19 as the period of September-December 2019 and intra-COVID-19 as the period of March-June 2020. These 2 groups were compared using patients' clinical characteristics, including age, sex, race, length of stay (LOS), and discharge dispositions. We leveraged the clinicians' actions committed to the patients' EHRs to measure clinician-clinician connections. We characterized a collaboration relationship (tie) between 2 clinicians as actioning EHRs of the same patient within the same day. On defining collaboration relationship, we built pre- and intra-COVID-19 networks. We used 3 sociometric measurements, including eigenvector centrality, eccentricity, and betweenness, to quantify a clinician's leadership, collaboration difficulty, and broad skill sets in a network, respectively. We assessed the extent to which the eigenvector centrality, eccentricity, and betweenness of clinicians in the 2 networks are statistically different, using Mann-Whitney U tests (95% CI).ResultsCollaboration difficulty increased from the pre- to intra-COVID-19 periods (median eccentricity: 3 vs 4; P<.001). Nurses had reduced leadership (median eigenvector centrality: 0.183 vs 0.087; P<.001), and neonatologists with broader skill sets cared for more patients in the NICU structure during the pandemic (median betweenness centrality: 0.0001 vs 0.005; P<.001). The pre- and intra-COVID-19 patient groups shared similar distributions in sex (~0 difference), race (4% difference in White, and 3% difference in African American), LOS (interquartile range difference in 1.5 days), and discharge dispositions (~0 difference in home, 2% difference in expired, and 2% difference in others). There were no significant differences in the patient demographics and outcomes between the 2 groups.ConclusionsManagement of NICU-admitted patients typically requires multidisciplinary care teams. Understanding collaboration structures can provide fine-grained evidence to potentially refine or optimize existing teamwork in the NICU.
| S-EPMC8530253 | biostudies-literature
Project description: Not available
| S-EPMC8318639 | biostudies-literature
Project description:In a living organism, tens of thousands of genes are expressed and interact with each other to achieve necessary cellular functions. Gene regulatory networks contain information on regulatory mechanisms and the functions of gene expressions. Thus, incorporating network structures, discerned either through biological experiments or statistical estimations, could potentially increase the selection and estimation accuracy of genes associated with a phenotype of interest. Here, we considered a gene selection problem using gene expression data and the graphical structures found in gene networks. Because gene expression measurements are intermediate phenotypes between a trait and its associated genes, we adopted an instrumental variable regression approach. We treated genetic variants as instrumental variables to address the endogeneity issue. We proposed a two-step estimation procedure. In the first step, we applied the LASSO algorithm to estimate the effects of genetic variants on gene expression measurements. In the second step, the projected expression measurements obtained from the first step were treated as input variables. A graph-constrained regularization method was adopted to improve the efficiency of gene selection and estimation. We theoretically showed the selection consistency of the estimation method and derived the L∞ bound of the estimates. Simulation and real data analyses were conducted to demonstrate the effectiveness of our method and to compare it with its counterparts.
| S-EPMC6810723 | biostudies-literature
Project description:The outcomes of informal caregivers of survivors of critical illness likely depend on patient characteristics, which may change over time. To date, few studies have examined patient-specific predictors of post-ICU informal caregiver burden, and none has tested whether predictors vary after hospital discharge.We designed a prospective, longitudinal observational study, enrolling 48 patient-caregiver dyads from four ICUs in a university hospital. Informal caregiver depression symptoms were measured with the Center for Epidemiologic Studies Depression scale. Lifestyle disruption was measured with the Activity Restriction Scale. Linear regression models were built to test for patient- and caregiver-specific predictors of depression symptoms and lifestyle disruption 2, 6, and 12 months after ICU admission.Patients had a mean (SD) age of 52.5 (19.7) years, 67% were men, median (interquartile range) Acute Physiology and Chronic Health Evaluation score was 52 (38.5, 65). The caregivers had a mean (SD) age of 52.8 (12.8) years, 91.2% were women, and 48% were spouses. Predictors of caregiver depression symptoms were patient gender (men) at 2 and 12 months and tracheostomy at 12 months. Predictors of lifestyle disruption were patient education (more common among high school graduates) and patient gender (men) at 2 months, and tracheostomy, functional dependency, and patient gender (men) at 12 months.The determinants of post-ICU informal caregiver burden likely depend on characteristics of the patient as well as the caregiver and may vary over time. Further research is necessary to better understand the longitudinal determinants of burden in order to develop more effective caregiver interventions.
| S-EPMC2803119 | biostudies-other
Project description:BackgroundWe investigated the effect of delirium burden in mechanically ventilated patients, beginning in the ICU and continuing throughout hospitalization, on functional neurologic outcomes up to 2.5 years following critical illness.MethodsProspective cohort study of enrolling 178 consecutive mechanically ventilated adult medical and surgical ICU patients between October 2013 and May 2016. Altogether, patients were assessed daily for delirium 2941days using the Confusion Assessment Method for the ICU (CAM-ICU). Hospitalization delirium burden (DB) was quantified as number of hospital days with delirium divided by total days at risk. Survival status up to 2.5 years and neurologic outcomes using the Glasgow Outcome Scale were recorded at discharge 3, 6, and 12 months post-discharge.ResultsOf 178 patients, 19 (10.7%) were excluded from outcome analyses due to persistent coma. Among the remaining 159, 123 (77.4%) experienced delirium. DB was independently associated with >4-fold increased mortality at 2.5 years following ICU admission (adjusted hazard ratio [aHR], 4.77; 95% CI, 2.10-10.83; P < .001), and worse neurologic outcome at discharge (adjusted odds ratio [aOR], 0.02; 0.01-0.09; P < .001), 3 (aOR, 0.11; 0.04-0.31; P < .001), 6 (aOR, 0.10; 0.04-0.29; P < .001), and 12 months (aOR, 0.19; 0.07-0.52; P = .001). DB in the ICU alone was not associated with mortality (HR, 1.79; 0.93-3.44; P = .082) and predicted neurologic outcome less strongly than entire hospital stay DB. Similarly, the number of delirium days in the ICU and for whole hospitalization were not associated with mortality (HR, 1.00; 0.93-1.08; P = .917 and HR, 0.98; 0.94-1.03, P = .535) nor with neurological outcomes, except for the association between ICU delirium days and neurological outcome at discharge (OR, 0.90; 0.81-0.99, P = .038).ConclusionsDelirium burden throughout hospitalization independently predicts long term neurologic outcomes and death up to 2.5 years after critical illness, and is more predictive than delirium burden in the ICU alone and number of delirium days.
| S-EPMC8638853 | biostudies-literature
Project description:Hinge motions are important for molecular recognition, and knowledge of their location can guide the sampling of protein conformations for docking. Predicting domains and intervening hinges is also important for identifying structurally self-determinate units and anticipating the influence of mutations on protein flexibility and stability. Here we present StoneHinge, a novel approach for predicting hinges between domains using input from two complementary analyses of noncovalent bond networks: StoneHingeP, which identifies domain-hinge-domain signatures in ProFlex constraint counting results, and StoneHingeD, which does the same for DomDecomp Gaussian network analyses. Predictions for the two methods are compared to hinges defined in the literature and by visual inspection of interpolated motions between conformations in a series of proteins. For StoneHingeP, all the predicted hinges agree with hinge sites reported in the literature or observed visually, although some predictions include extra residues. Furthermore, no hinges are predicted in six hinge-free proteins. On the other hand, StoneHingeD tends to overpredict the number of hinges, while accurately pinpointing hinge locations. By determining the consensus of their results, StoneHinge improves the specificity, predicting 11 of 13 hinges found both visually and in the literature for nine different open protein structures, and making no false-positive predictions. By comparison, a popular hinge detection method that requires knowledge of both the open and closed conformations finds 10 of the 13 known hinges, while predicting four additional, false hinges.
| S-EPMC2708048 | biostudies-literature
Project description:Observed associations between fluid balance and septic shock outcomes are likely confounded by initial mortality risk. We conducted a risk-stratified analysis of the association between post-ICU admission fluid balance and pediatric septic shock outcomes.Retrospective analysis of an ongoing multicenter pediatric septic shock clinical and biological database.Seventeen PICUs in the United States.Three hundred and seventeen children with septic shock.None.We stratified subjects into three mortality risk categories (low, intermediate, and high) using a validated biomarker-based stratification tool. Within each category, we assessed three fluid balance variables: total fluid intake/kg/d during the first 24 hours, percent positive fluid balance during the first 24 hours, and cumulative percent positive fluid balance up to 7 days. We used logistic regression to estimate the effect of fluid balance on the odds of 28-day mortality, and on complicated course, which we defined as either death within 28 days or persistence of two or more organ failures at 7 days. There were 40 deaths, and 91 subjects had a complicated course. Increased cumulative percent positive fluid balance was associated with mortality in the low-risk cohort (n = 204; odds ratio, 1.035; 95% CI, 1.004-1.066) but not in the intermediate- and high-risk cohorts. No other associations with mortality were observed. Fluid intake, percent positive fluid balance in the first 24 hours, and cumulative percent positive fluid balance were all associated with increased odds of a complicated course in the low-risk cohort but not in the intermediate- and high-risk cohorts.When stratified for mortality risk, increased fluid intake and positive fluid balance after ICU admission are associated with worse outcomes in pediatric septic shock patients with a low initial mortality risk but not in patients at moderate or high mortality risk.
| S-EPMC3947064 | biostudies-literature
Project description:BackgroundConflicting data exist regarding sex-specific outcomes after cardiac arrest. This study investigates sex disparities in the provision of critical care and outcomes of in-hospital (IHCA) and out-of-hospital cardiac arrest (OHCA) patients.MethodsAnalysis of adult cardiac arrest patients admitted to certified Swiss intensive care units (ICUs) (01/2008-12/2022) using the nationwide prospective ICU registry. The primary outcome was ICU mortality, with secondary outcomes including ICU admission probability and advanced treatment provision.ResultsAmong 41,733 individuals (34.9% women), 21,692 patients (30.6% women) were admitted to ICUs (16,571 OHCA patients/5121 IHCA patients). Women were less likely to be admitted to the ICU than men (incidence rate ratio 0.82 [95% CI 0.80-0.85] and had a higher ICU mortality (41.8% vs 36.2%; p < 0.001). Mortality differences were more pronounced in OHCA patients (unadjusted HR: 1.35 [95% CI 1.28-1.43]; adjusted HR: 1.19 [95% CI 1.12-1.25]). In IHCA patients, mortality differences were less pronounced (unadjusted HR: 1.14 [95% CI 1.04-1.25]) and vanished after adjustment for confounders: adjusted HR: 1.03 [95% CI 0.94-1.13]). Women after cardiac arrest were older, more severely ill, and received fewer interventions before (44.7% vs 54.0%; p < 0.001) and during ICU stay. A subgroup analysis of 11,202 patients revealed that treatment limitations were more frequent in women (46.7% vs 38.7%; p < 0.001). However, these limitations were associated with an increased risk of death in both sexes.ConclusionsThis study highlights sex disparities in short-term mortality and ICU resource allocation among cardiac arrest patients, with women potentially facing disadvantages, in particular after OHCA. The limitations of ICU registry data, particularly the lack of detailed cardiac arrest-specific and comorbidity information, restrict definitive conclusions. Future research should prioritize prospective studies with more granular data to better understand and address these disparities.
| S-EPMC11756088 | biostudies-literature