Comparison of spontaneous with controlled mode of ventilation in tonsillectomy

Methods: This randomized study compares spontaneous versus controlled ventilation in 60 ASA I and II patients undergoing tonsillectomy as regards haemodynamic stability, recovery characteristics, intra- and immediate postoperative complications and surgical impressions.Results: The patients in the balanced anaesthesia (B) group showed less haemodynamic variability compared to baseline after tracheal intubation, mouth gag application and removal and incision. Two patients had dysrhythmias in the B group compared to six in the spontaneous breathing (S) group. Six patients in the S group had a rise in endtidal carbon dioxide concentration above 7.8 kPa (60 mmHg). Recovery scores were higher in the B group at 10 and 20 min into recovery. The surgical impression of bleeding and jaw relaxation was similar with both groups. The incidence of postoperative nausea and vomiting and agitation was higher in the S group but did not achieve statistical significance.CONCLUSION: Use of balanced anaesthesia offered more haemodynamic stability and a rapid recovery

Caterpillars and fungal pathogens: two co-occurring parasites of an ant-plant mutualism

In mutualisms, each interacting species obtains resources from its partner that it would obtain less efficiently if alone, and so derives a net fitness benefit. In exchange for shelter (domatia) and food, mutualistic plant-ants protect their host myrmecophytes from herbivores, encroaching vines and fungal pathogens. Although selective filters enable myrmecophytes to host those ant species most favorable to their fitness, some insects can by-pass these filters, exploiting the rewards supplied whilst providing nothing in return. This is the case in French Guiana for Cecropia obtusa (Cecropiaceae) as Pseudocabima guianalis caterpillars (Lepidoptera, Pyralidae) can colonize saplings before the installation of their mutualistic Azteca ants. The caterpillars shelter in the domatia and feed on food bodies (FBs) whose production increases as a result. They delay colonization by ants by weaving a silk shield above the youngest trichilium, where the FBs are produced, blocking access to them. This probable temporal priority effect also allows female moths to lay new eggs on trees that already shelter caterpillars, and so to occupy the niche longer and exploit Cecropia resources before colonization by ants. However, once incipient ant colonies are able to develop, they prevent further colonization by the caterpillars. Although no higher herbivory rates were noted, these caterpillars are ineffective in protecting their host trees from a pathogenic fungus, Fusarium moniliforme (Deuteromycetes), that develops on the trichilium in the absence of mutualistic ants. Therefore, the Cecropia treelets can be parasitized by two often overlooked species: the caterpillars that shelter in the domatia and feed on FBs, delaying colonization by mutualistic ants, and the fungal pathogen that develops on old trichilia. The cost of greater FB production plus the presence of the pathogenic fungus likely affect tree growth

A prospective registry of emergency department patients admitted with infection

<p>Abstract</p> <p>Background</p> <p>Patients with infections account for a significant proportion of Emergency Department (ED) workload, with many hospital patients admitted with severe sepsis initially investigated and resuscitated in the ED. The aim of this registry is to systematically collect quality observational clinical and microbiological data regarding emergency patients admitted with infection, in order to explore in detail the microbiological profile of these patients, and to provide the foundation for a significant programme of prospective observational studies and further clinical research.</p> <p>Methods/design</p> <p>ED patients admitted with infection will be identified through daily review of the computerised database of ED admissions, and clinical information such as site of infection, physiological status in the ED, and components of management abstracted from patients' charts. This information will be supplemented by further data regarding results of investigations, microbiological isolates, and length of stay (LOS) from hospital electronic databases. Outcome measures will be hospital and intensive care unit (ICU) LOS, and mortality endpoints derived from a national death registry.</p> <p>Discussion</p> <p>This database will provide substantial insights into the characteristics, microbiological profile, and outcomes of emergency patients admitted with infections. It will become the nidus for a programme of research into compliance with evidence-based guidelines, optimisation of empiric antimicrobial regimens, validation of clinical decision rules and identification of outcome determinants. The detailed observational data obtained will provide a solid baseline to inform the design of further controlled trials planned to optimise treatment and outcomes for emergency patients admitted with infections.</p

Global quantitative indices reflecting provider process-of-care: data-base derivation

Background: Controversy has attended the relationship between risk-adjusted mortality and process-of-care. There would be advantage in the establishment, at the data-base level, of global quantitative indices subsuming the diversity of process-of-care. Methods: A retrospective, cohort study of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 1993-2003, at the level of geographic and ICU-level descriptors (n = 35), for both hospital survivors and non-survivors. Process-of-care indices were established by analysis of: (i) the smoothed time-hazard curve of individual patient discharge and determined by pharmaco-kinetic methods as area under the hazard-curve (AUC), reflecting the integrated experience of the discharge process, and time-to-peak-hazard (TMAX, in days), reflecting the time to maximum rate of hospital discharge; and (ii) individual patient ability to optimize output (as length-of-stay) for recorded data-base physiological inputs; estimated as a technical production-efficiency (TE, scaled [0,(maximum)1]), via the econometric technique of stochastic frontier analysis. For each descriptor, multivariate correlation-relationships between indices and summed mortality probability were determined. Results: The data-set consisted of 223129 patients from 99 ICUs with mean (SD) age and APACHE III score of 59.2(18.9) years and 52.7(30.6) respectively; 41.7% were female and 45.7% were mechanically ventilated within the first 24 hours post-admission. For survivors, AUC was maximal in rural and for-profit ICUs, whereas TMAX (≥ 7.8 days) and TE (≥ 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (≥ 4.2 days) and TE (≥ 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysisof- variance, P ≤ 0.0001). Total explained variance, for survivors (0.89) and non-survivors (0.89), was maximized by combinations of indices demonstrating a low correlation with mortality probability. Conclusions: Global indices reflecting process of care may be formally established at the level of national patient databases. These indices appear orthogonal to mortality outcome.John L Moran, Patricia J Solomon and the Adult Database Management Committee (ADMC) of the Australian and New Zealand Intensive Care Society (ANZICS

Evaluating the effectiveness of a tailored multifaceted performance feedback intervention to improve the quality of care: protocol for a cluster randomized trial in intensive care

Contains fulltext : 95871.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: Feedback is potentially effective in improving the quality of care. However, merely sending reports is no guarantee that performance data are used as input for systematic quality improvement (QI). Therefore, we developed a multifaceted intervention tailored to prospectively analyzed barriers to using indicators: the Information Feedback on Quality Indicators (InFoQI) program. This program aims to promote the use of performance indicator data as input for local systematic QI. We will conduct a study to assess the impact of the InFoQI program on patient outcome and organizational process measures of care, and to gain insight into barriers and success factors that affected the program's impact. The study will be executed in the context of intensive care. This paper presents the study's protocol. METHODS/DESIGN: We will conduct a cluster randomized controlled trial with intensive care units (ICUs) in the Netherlands. We will include ICUs that submit indicator data to the Dutch National Intensive Care Evaluation (NICE) quality registry and that agree to allocate at least one intensivist and one ICU nurse for implementation of the intervention. Eligible ICUs (clusters) will be randomized to receive basic NICE registry feedback (control arm) or to participate in the InFoQI program (intervention arm). The InFoQI program consists of comprehensive feedback, establishing a local, multidisciplinary QI team, and educational outreach visits. The primary outcome measures will be length of ICU stay and the proportion of shifts with a bed occupancy rate above 80%. We will also conduct a process evaluation involving ICUs in the intervention arm to investigate their actual exposure to and experiences with the InFoQI program. DISCUSSION: The results of this study will inform those involved in providing ICU care on the feasibility of a tailored multifaceted performance feedback intervention and its ability to accelerate systematic and local quality improvement. Although our study will be conducted within the domain of intensive care, we believe our conclusions will be generalizable to other settings that have a quality registry including an indicator set available. TRIAL REGISTRATION: Current Controlled Trials ISRCTN50542146

Translocation of Threatened New Zealand Falcons to Vineyards Increases Nest Attendance, Brooding and Feeding Rates

Anthropogenic landscapes can be rich in resources, and may in some cases provide potential habitat for species whose natural habitat has declined. We used remote videography to assess whether reintroducing individuals of the threatened New Zealand falcon Falco novaeseelandiae into a highly modified agricultural habitat affected the feeding rates of breeding falcons or related breeding behavior such as nest attendance and brooding rates. Over 2,800 recording hours of footage were used to compare the behavior of falcons living in six natural nests (in unmanaged, hilly terrain between 4 km and 20 km from the nearest vineyard), with that of four breeding falcon pairs that had been transported into vineyards and nested within 500 m of the nearest vineyard. Falcons in vineyard nests had higher feeding rates, higher nest attendance, and higher brooding rates. As chick age increased, parents in vineyard nests fed chicks a greater amount of total prey and larger prey items on average than did parents in hill nests. Parents with larger broods brought in larger prey items and a greater total sum of prey biomass. Nevertheless, chicks in nests containing siblings received less daily biomass per individual than single chicks. Some of these results can be attributed to the supplementary feeding of falcons in vineyards. However, even after removing supplementary food from our analysis, falcons in vineyards still fed larger prey items to chicks than did parents in hill nests, suggesting that the anthropogenic habitat may be a viable source of quality food. Although agricultural regions globally are rarely associated with raptor conservation, these results suggest that translocating New Zealand falcons into vineyards has potential for the conservation of this species

Understanding the cluster randomised crossover design::a graphical illustraton of the components of variation and a sample size tutorial

Abstract Background In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or ‘cluster’ of individuals. Each cluster receives each intervention in a separate period of time, forming ‘cluster-periods’. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Methods Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society – Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). Results The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of the WPC or BPC can increase the required number of clusters. Conclusions By illustrating how the parameters required for sample size calculations arise from the CRXO design and by providing guidance on both how to choose values for the parameters and perform the sample size calculations, the implementation of the sample size formulae for CRXO trials may improve

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

for the ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS)BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. RESULTS The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag ₄₀ and 35% had autocorrelation through to lag ₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. CONCLUSIONS The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.John L Moran, Patricia J Solomo

The Worker Honeybee Fat Body Proteome Is Extensively Remodeled Preceding a Major Life-History Transition

Honeybee workers are essentially sterile female helpers that make up the majority of individuals in a colony. Workers display a marked change in physiology when they transition from in-nest tasks to foraging. Recent technological advances have made it possible to unravel the metabolic modifications associated with this transition. Previous studies have revealed extensive remodeling of brain, thorax, and hypopharyngeal gland biochemistry. However, data on changes in the abdomen is scarce. To narrow this gap we investigated the proteomic composition of abdominal tissue in the days typically preceding the onset of foraging in honeybee workers