Predicting Acute Kidney Injury at Hospital Re-entry Using High-dimensional Electronic Health Record Data

Acute Kidney Injury (AKI), a sudden decline in kidney function, is associated with increased mortality, morbidity, length of stay, and hospital cost. Since AKI is sometimes preventable, there is great interest in prediction. Most existing studies consider all patients and therefore restrict to features available in the first hours of hospitalization. Here, the focus is instead on rehospitalized patients, a cohort in which rich longitudinal features from prior hospitalizations can be analyzed. Our objective is to provide a risk score directly at hospital re-entry. Gradient boosting, penalized logistic regression (with and without stability selection), and a recurrent neural network are trained on two years of adult inpatient EHR data (3,387 attributes for 34,505 patients who generated 90,013 training samples with 5,618 cases and 84,395 controls). Predictions are internally evaluated with 50 iterations of 5-fold grouped cross-validation with special emphasis on calibration, an analysis of which is performed at the patient as well as hospitalization level. Error is assessed with respect to diagnosis, race, age, gender, AKI identification method, and hospital utilization. In an additional experiment, the regularization penalty is severely increased to induce parsimony and interpretability. Predictors identified for rehospitalized patients are also reported with a special analysis of medications that might be modifiable risk factors. Insights from this study might be used to construct a predictive tool for AKI in rehospitalized patients. An accurate estimate of AKI risk at hospital entry might serve as a prior for an admitting provider or another predictive algorithm.Comment: In revisio

Properties of Healthcare Teaming Networks as a Function of Network Construction Algorithms

Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other. Most healthcare service network models have been constructed from patient claims data, using billing claims to link patients with providers. The data sets can be quite large, making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks. To address this issue, we compared the properties of healthcare networks constructed using different algorithms and the 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We found that each algorithm produced networks with substantially different topological properties. Provider networks adhered to a power law, and organization networks to a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and greatly altered measures of vertex prominence such as the betweenness centrality. We identified patterns in the distance patients travel between network providers, and most strikingly between providers in the Northeast United States and Florida. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications for selecting the algorithm best suited to the type of analysis to be performed.Comment: With links to comprehensive, high resolution figures and networks via figshare.co

Attitudes towards terminal sedation: an empirical survey among experts in the field of medical ethics

BACKGROUND: "Terminal sedation" regarded as the use of sedation in (pre-)terminal patients with treatment-refractory symptoms is controversially discussed not only within palliative medicine. While supporters consider terminal sedation as an indispensable palliative medical treatment option, opponents disapprove of it as "slow euthanasia". Against this background, we interviewed medical ethics experts by questionnaire on the term and the moral acceptance of terminal sedation in order to find out how they think about this topic. We were especially interested in whether experts with a professional medical and nursing background think differently about the topic than experts without this background. METHODS: The survey was carried out by questionnaire; beside the provided answering options free text comments were possible. As test persons we chose the 477 members of the German Academy for Ethics in Medicine, an interdisciplinary society for medical ethics. RESULTS: 281 completed questionnaires were returned (response rate = 59%). The majority of persons without medical background regarded "terminal sedation" as an intentional elimination of consciousness until the patient's death occurs; persons with a medical background generally had a broader understanding of the term, including light or intermittent forms of sedation. 98% of the respondents regarded terminal sedation in dying patients with treatment-refractory physical symptoms as acceptable. Situations in which the dying process has not yet started, in which untreatable mental symptoms are the indication for terminal sedation or in which life-sustaining measures are withdrawn during sedation were evaluated as morally difficult. CONCLUSION: The survey reveals a great need for research and discussion on the medical indication as well as on the moral evaluation of terminal sedation. Prerequisite for this is a more precise terminology which describes the circumstances of the sedation

Impact of an Interactive On-line Tool on Therapeutic Decision-Making for Patients with Advanced Non-Small-Cell Lung Cancer

Background:Treatment guidelines provide recommendations but cannot account for the wide variability in patient-tumor characteristics in individual patients. We developed an on-line interactive decision tool to provide expert recommendations for specific patient scenarios in the first-line and maintenance settings for advanced non–small-cell lung cancer. We sought to determine how providing expert feedback would influence clinical decision-making.Method:Five lung cancer experts selected treatment for 96 different patient cases based on patient and/or tumor-specific features. These data were used to develop an on-line decision tool. Participant physicians entered variables for their patient scenario with treatment choices, and then received expert treatment recommendations for that scenario. To determine the impact on decision-making, users were asked whether the expert feedback impacted their original plan.Results:A total of 442 individual physicians, of which 88% were from outside the United States, entered 653 cases, with report on impact in 389 cases. Expert feedback affected treatment choice in 73% of cases (23% changed and 50% confirmed decisions). For cases with epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) fusion, all experts selected targeted therapy whereas 51% and 58% of participants did not. Greater variability was seen between experts and participants for cases involving EGFR or ALK wild-type tumors. Participants were 2.5-fold more likely to change to expert recommended therapy for ALK fusions than for EGFR mutations (p = 0.017).Conclusion:This online tool for treatment decision-making resulted in a positive influence on clinician's decisions. This approach offers opportunities for improving quality of care and meets an educational need in application of new therapeutic paradigms

11 C-Metomidate PET/CT is a useful adjunct for lateralization of primary aldosteronism in routine clinical practice.

OBJECTIVE: To describe clinical practice experience of 11 C-Metomidate PET/CT as an adjunct to adrenal vein sampling (AVS) in the lateralization of aldosterone-producing adenomas (APA) in primary aldosteronism (PA). CONTEXT: Accurate lateralization of APA in the setting of PA offers the potential for surgical cure and improved long-term cardiovascular outcomes. Challenges associated with AVS, the current gold standard lateralization modality, mean that only a small proportion of potentially eligible patients currently make it through to surgery. This has prompted consideration of alternative strategies for lateralization, including the application of novel molecular PET tracers such as 11 C-Metomidate. DESIGN: Clinical Service Evaluation/Retrospective audit. PATIENTS: Fifteen individuals with a confirmed diagnosis of PA, undergoing lateralization with 11 C-Metomidate PET/CT prior to final clinical decision on surgical vs medical management. MEASUREMENTS: All patients underwent screening aldosterone renin ratio (ARR), followed by confirmatory testing with the seated saline infusion test, according to Endocrine Society Clinical Practice Guidelines. Adrenal glands were imaged using dedicated adrenal CT. 11 C-Metomidate PET/CT was undertaken due to equivocal or failed AVS. Management outcomes were assessed by longitudinal measurement of blood pressure, ARR, number of hypertensive medications following adrenalectomy or institution of medical therapy. RESULTS: We describe the individual lateralization and clinical outcomes for 15 patients with PA. CONCLUSION: 11 C-Metomidate PET/CT in conjunction with adrenal CT and AVS provided useful information which aided clinical decision-making for PA within a multidisciplinary hypertension clinic

Modeling Wind Direction Distributions Using a Diagnostic Model in the Context of Probabilistic Fire Spread Prediction

With emerging research on the dynamics of extreme fire behavior, it is increasingly important for wind models, used in operational fire prediction, to accurately capture areas of complex flow across rugged terrain. Additionally, the emergence of ensemble and stochastic modeling frameworks has led to the discussion of uncertainty in fire prediction. To capture the uncertainty of modeled fire outputs, it is necessary to recast uncertain inputs in probabilistic terms. WindNinja is the diagnostic wind model currently being applied within a number of operational fire prediction frameworks across the world. For computational efficiency, allowing for real-time or faster than real-time prediction, the physical equations governing wind flow across a complex terrain are often simplified. The model has a number of well documented limitations, for instance, it is known to perform poorly on leeward slopes. First, this study is aimed at understanding these limitations in a probabilistic context, by comparing individual deterministic predictions to observed distributions of wind direction. Secondly, a novel application of the deterministic WindNinja model is presented in this study which is shown to enable prediction of wind direction distributions that capture some of the variability of complex wind flow. Recasting wind fields in terms of probability distributions enables a better understanding of variability across the landscape, and provides the probabilistic information required to capture uncertainty through ensemble or stochastic fire modeling. The comparisons detailed in this study indicate the potential for WindNinja to predict multi-modal wind direction distributions that represent complex wind behaviors, including re-circulation regions on leeward slopes. However, the limitations of using deterministic models within probabilistic frameworks are also highlighted. To enhance fire prediction and to better understand uncertainty, it is recommended that statistical approaches also be developed to complement existing physics-based deterministic wind models

Review-Electrode Kinetics and Electrolyte Stability in Vanadium Flow Batteries

Two aspects of vanadium flow batteries are reviewed: electrochemical kinetics on carbon electrodes and positive electrolyte stability. There is poor agreement between reported values of kinetic parameters; however, most authors report that kinetic rates are faster for VIV/VV than for VII/VIII. Cycling the electrode potential increases the rates of both reactions initially due to roughening but when no further roughening is observed, the VII/VIII and VIV/VV reactions are affected oppositely by the pretreatment potential. Anodic pretreatment activates the electrode for the VII/VIII reaction, and deactivates it for VIV/VV. Three states of the carbon surface are suggested: reduced and oxidized states R and O, respectively, both with low electrocatalytic activity, and an intermediate state M with higher activity. The role of surface functional groups and the mechanisms of electron transfer for the VII/VIII and VIV/VV reactions are still not well understood. The induction time for precipitation of V2O5 from positive electrolytes decreases with temperature, showing an Arrhenius-type dependence with an activation energy of 1.79 eV in agreement with DFT calculations based on a VO(OH)3 intermediate. It also decreases exponentially with increasing VV concentration and increases exponentially with increasing sulphate concentration. Both arsenate and phosphate are effective additives for improving thermal stability

Has the frequency of bleeding changed over time for patients presenting with an acute coronary syndrome? The Global Registry of Acute Coronary Events

AIMS: To determine whether changes in practice, over time, are associated with altered rates of major bleeding in acute coronary syndromes (ACS). METHODS AND RESULTS: Patients from the Global Registry of Acute Coronary Events were enrolled between 2000 and 2007. The main outcome measures were frequency of major bleeding, including haemorrhagic stroke, over time, after adjustment for patient characteristics, and impact of major bleeding on death and myocardial infarction. Of the 50 947 patients, 2.3% sustained a major bleed; almost half of these presented with ST-elevation ACS (44%, 513). Despite changes in antithrombotic therapy (increasing use of low molecular weight heparin, P < 0.0001), thienopyridines (P < 0.0001), and percutaneous coronary interventions (P < 0.0001), frequency of major bleeding for all ACS patients decreased (2.6 to 1.8%; P < 0.0001). Most decline was seen in ST-elevation ACS (2.9 to 2.1%, P = 0.02). The overall decline remained after adjustment for patient characteristics and treatments (P = 0.002, hazard ratio 0.94 per year, 95% confidence interval 0.91-0.98). Hospital characteristics were an independent predictor of bleeding (P < 0.0001). Patients who experienced major bleeding were at increased risk of death within 30 days from admission, even after adjustment for baseline variables. CONCLUSION: Despite increasing use of more intensive therapies, there was a decline in the rate of major bleeding associated with changes in clinical practice. However, individual hospital characteristics remain an important determinant of the frequency of major bleeding