Prospective observational study of emergent endotracheal intubation practice in the intensive care unit and emergency department of an Australian regional tertiary hospital

Objective: The present study aimed to describe the characteristics and outcomes of intubation occurring in the ICU and ED of an Australian tertiary teaching hospital. Methods: This was a prospective observational study of intubation practice across the Geelong Hospital over a 6 month period from 1 August 2012 to 31 January 2013. Data were entered by the intubating team through an online data collection form. Results: There were 119 patients intubated and 134 attempts at intubation in the ED and ICU over a 6 month period. The first-pass success rate was 104/119 (87.4%), and all but a single patient was intubated by the second attempt. Propofol, fentanyl, midazolam and suxamethonium were the most common drugs used in rapid sequence induction. AEs were reported in 44/134 (32.8%) of intubation attempts, with transient hypoxia and hypotension being the most common. A significant adverse outcome, namely aspiration pneumonitis, occurred in one patient. There were no peri-intubation deaths. Conclusion: The majority of airways are managed by ICU and ED consultants and trainees, with success rates and AE rates comparable with other published studies. © 2014 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Heteroscedasticity robust panel unit root tests

This article proposes new unit root tests for panels where the errors may be not only serial and/or crosscorrelated,but also unconditionally heteroscedastic. Despite their generality, the test statistics are shown tobe very simple to implement, requiring only minimal corrections and still the limiting distributions underthe null hypothesis are completely free from nuisance parameters. Monte Carlo evidence is also providedto suggest that the new tests perform well in small samples, also when compared to some of the existingtests. Supplementary materials for this article are available online.

On the choice of test for a unit root when the errors are conditionally heteroskedastic

It is well known that in the context of the classical regression model with heteroskedastic errors, while ordinary least squares (OLS) is not efficient, the weighted least squares (WLS) and quasi-maximum likelihood (QML) estimators that utilize the information contained in the heteroskedasticity are. In the context of unit root testing with conditional heteroskedasticity, while intuition suggests that a similar result should apply, the relative performance of the tests associated with the OLS, WLS and QML estimators is not well understood. In particular, while QML has been shown to be able to generate more powerful tests than OLS, not much is known regarding the relative performance of the WLS-based test. By providing an in-depth comparison of the tests, the current paper fills this gap in the literature.

Evaluation of a filmed clinical scenario as a teaching resource for an introductory pharmacology unit for undergraduate health students: A pilot study.

BACKGROUND: Simulation is frequently being used as a learning and teaching resource for both undergraduate and postgraduate students, however reporting of the effectiveness of simulation particularly within the pharmacology context is scant. OBJECTIVES: The aim of this pilot study was to evaluate a filmed simulated pharmacological clinical scenario as a teaching resource in an undergraduate pharmacological unit. DESIGN: Pilot cross-sectional quantitative survey. SETTING: An Australian university. PARTICIPANTS: 32 undergraduate students completing a healthcare degree including nursing, midwifery, clinical science, health science, naturopathy, and osteopathy. METHODS: As a part of an undergraduate online pharmacology unit, students were required to watch a filmed simulated pharmacological clinical scenario. To evaluate student learning, a measurement instrument developed from Bloom's cognitive domains (knowledge, comprehension, application, analysis, synthesis and evaluation) was employed to assess pharmacological knowledge conceptualisation and knowledge application within the following fields: medication errors; medication adverse effects; medication interactions; and, general pharmacology. RESULTS: The majority of participants were enrolled in an undergraduate nursing or midwifery programme (72%). Results demonstrated that the majority of nursing and midwifery students (56.52%) found the teaching resource complementary or more useful compared to a lecture although less so compared to a tutorial. Students' self-assessment of learning according to Bloom's cognitive domains indicated that the filmed scenario was a valuable learning tool. Analysis of variance indicated that health science students reported higher levels of learning compared to midwifery and nursing. CONCLUSION: Students' self-report of the learning benefits of a filmed simulated clinical scenario as a teaching resource suggest enhanced critical thinking skills and knowledge conceptualisation regarding pharmacology, in addition to being useful and complementary to other teaching and learning methods.

A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

The penetration of intermittent renewable energy sources (IRESs) into power grids has increased in the last decade. Integration of wind farms and solar systems as the major IRESs have significantly boosted the level of uncertainty in operation of power systems. This paper proposes a comprehensive computational framework for quantification and integration of uncertainties in distributed power systems (DPSs) with IRESs. Different sources of uncertainties in DPSs such as electrical load, wind and solar power forecasts and generator outages are covered by the proposed framework. Load forecast uncertainty is assumed to follow a normal distribution. Wind and solar forecast are implemented by a list of prediction intervals (PIs) ranging from 5% to 95%. Their uncertainties are further represented as scenarios using a scenario generation method. Generator outage uncertainty is modeled as discrete scenarios. The integrated uncertainties are further incorporated into a stochastic security-constrained unit commitment (SCUC) problem and a heuristic genetic algorithm is utilized to solve this stochastic SCUC problem. To demonstrate the effectiveness of the proposed method, five deterministic and four stochastic case studies are implemented. Generation costs as well as different reserve strategies are discussed from the perspectives of system economics and reliability. Comparative results indicate that the planned generation costs and reserves are different from the realized ones. The stochastic models show better robustness than deterministic ones. Power systems run a higher level of risk during peak load hours.

Restorative care for palliative patients: a retrospective clinical audit of outcomes for patients admitted to an inpatient palliative care unit

BACKGROUND: Restorative care in palliative care is a subset of rehabilitation that aims to improve quality of life through restoration or maintenance of physical functions. Outcomes for restorative care programmes delivered by palliative care units have not adequately been assessed. OBJECTIVES: The objectives are to examine the outcomes of a restorative care programme in an inpatient palliative care unit, including discharge destination, performance status changes and length of stay. METHODS: Retrospective clinical audit of consecutive patients admitted to Calvary Health Care Bethlehem in Melbourne, Australia, principally for restorative care from July 2010 to December 2011. RESULTS: 79 admissions met inclusion criteria. Mean age was 76.5 years (SD=11.14) and 43 (54%) were men. 75 (95%) patients had a malignant diagnosis; of these, the majority had lung cancer (24%). 16 patients (20%) were discharged home, 51 (65%) died and 12 (15%) were transferred. Of the patients discharged home, only 6 (38% of those discharged home) improved their performance status. Those discharged home had a significantly shorter length of stay (17 days compared to 39 days; p<0.05). Patients discharged home also had significantly better Australia-modified Karnofsky Performance Status (AKPS) and Resource Utilisation Groups-Activities of Daily Living (RUG-ADL) scores on admission than others (both p<0.05). CONCLUSIONS: The majority of patients referred for restorative care died during admission, with only a minority discharged home. Patients discharged most commonly experienced maintenance and not improvement in performance status. A successful discharge home following restorative care was associated with a shorter length of stay. Implications and recommendations for successful restorative care will be discussed.

Student reflections in a first year public health and health promotion unit

While reflective practice has been used extensively in nursing and teaching education over many years, the introduction of reflective practice into other disciplines is more recent. This paper provides an overview of the use of reflective practice as an assessment task in a first year, first trimester, undergraduate health promotion and public health unit. Reflective practice is included in this unit as a way for students to deal with challenges that arise during learning. This study used a coding scheme to determine the level of reflection of student journals, as well as a qualitative approach of thematic analysis to investigate themes within the student’s reflective journals. Findings of this study suggest a low level of student reflection, however; thematic analysis results in rich data that describe student aspirations for future careers.

A note on the use of the LLC panel unit root test

One of the single most cited studies within the field of nonstationary panel data analysis is that of LLC (Levin et al. in J Econom 98:1 - 24, 2002), in which the authors propose a test for a common unit root in the panel. Using both theoretical arguments and simulation evidence, we show that this test can be misleading unless it is based on the same bandwidth selection rule used by LLC. © Springer-Verlag 2008.

New tools for understanding the local asymptotic power of panel unit root tests

Abstract Motivated by the previously documented discrepancy between actual and predicted power, the present paper provides new tools for analyzing the local asymptotic power of panel unit root tests. These tools are appropriate in general when considering panel data with a dominant autoregressive root of the form ^ρi=1+^ciN-^κT-^τ, where i=1,...,N indexes the cross-sectional units, T is the number of time periods and ^ci is a random local-to-unity parameter. A limit theory for the sample moments of such panel data is developed and is shown to involve infinite-order series expansions in the moments of ^ci, in which existing theories can be seen as mere first-order approximations. The new theory is applied to study the asymptotic local power functions of some known test statistics for a unit root. These functions can be expressed in terms of the expansions in the moments of ^ci, and include existing local power functions as special cases. Monte Carlo evidence is provided to suggest that the new results go a long way toward bridging the gap between actual and predicted power.

Rethinking the univariate approach to panel unit root testing: using covariates to resolve the incidental trend problem

In an influential article, Hansen showed that covariate augmentation can lead to substantial power gains when compared to univariate tests. In this article, we ask if this result extends also to the panel data context? The answer turns out to be yes, which is maybe not that surprising. What is surprising, however, is the extent of the power gain, which is shown to more than outweigh the well-known power loss in the presence of incidental trends. That is, the covariates have an order effect on the neighborhood around unity for which local asymptotic power is negligible.

The effect of recursive detrending on panel unit root tests

This paper analyzes the properties of panel unit root tests based on recursively detrended data. The analysis is conducted while allowing for a (potentially) non-linear trend function, which represents a more general consideration than the current state of affairs with (at most) a linear trend. A new test statistic is proposed whose asymptotic behavior under the unit root null hypothesis, and the simplifying assumptions of a polynomial trend and iid errors are shown to be surprisingly simple. Indeed, the test statistic is not only asymptotically independent of the true trend polynomial, but also is in fact unique in that it is independent also of the degree of the fitted polynomial. However, this invariance property does not carry over to the local alternative, under which it is shown that local power is a decreasing function of the trend degree. But while power does decrease, the rate of shrinking of the local alternative is generally constant in the trend degree, which goes against the common belief that the rate of shrinking should be decreasing in the trend degree. The above results are based on simplifying assumptions. To compensate for this lack of generality, a second, robust, test statistic is proposed, whose validity does not require that the trend function is a polynomial or that the errors are iid.

On the importance of the first observation in GLS detrending in unit root testing

First-differencing is generally taken to imply the loss of one observation, the first, or at least that the effect of ignoring this observation is asymptotically negligible. However, this is not always true, as in the case of generalized least squares (GLS) detrending. In order to illustrate this, the current article considers as an example the use of GLS detrended data when testing for a unit root. The results show that the treatment of the first observation is absolutely crucial for test performance, and that ignorance causes test break-down.

The asymptotic distribution of the CADF unit root test in the presence of heterogeneous AR(p) errors

The CADF test of Pesaran (J Appl Econ 22:265–312, 2007) are among the most popular univariate tests for cross-section correlated panels around. Yet, the existing asymptotic analysis of this test statistic is limited to a model in which the errors are assumed to follow a simple AR(1) structure with homogenous autoregressive coefficients. One reason for this is that the model involves an intricate identification issue, as both the serial and cross-section correlation structures of the errors are unobserved. The purpose of the current paper is to tackle this issue and in so doing extend the existing analysis to the case of AR((Formula presented.)) errors with possibly heterogeneous coefficients.

A factor analytical method to interactive effects dynamic panel models with or without unit root

In a recent study, Bai (Fixed-Effects Dynamic Panel Models, A Factor Analytical Method. Econometrica 81, 285-314, 2013a) proposes a new factor analytic (FA) method to the estimation of dynamic panel data models, which has the unique and very useful property that it is completely bias-free. However, while certainly appealing, it is restricted to fixed effects models without a unit root. In many situations of practical relevance this is a rather restrictive consideration. The purpose of the current study is therefore to extend the FA approach to cover models with multiple interactive effects and a possible unit root.

Pooled panel unit root tests and the effect of past initialization

This paper analyzes the role of initialization when testing for a unit root in panel data, an issue that has received surprisingly little attention in the literature. In fact, most studies assume that the initial value is either zero or bounded. As a response to this, the current paper considers a model in which the initialization is in the past, which is shown to have several distinctive features that makes it attractive, even in comparison to the common time series practice of making the initial value a draw from its unconditional distribution under the stationary alternative. The results have implications not only for theory, but also for applied work. In particular, and in contrast to the time series case, in panels the effect of the initialization need not be negative but can actually lead to improved test performance.