Continuous infusion of ticarcillin-clavulanate for home treatment of serious infections : clinical efficacy, safety, pharmacokinetics and pharmacodynamics

Continuous infusion (CI) ticarcillin–clavulanate is a potential therapeutic improvement over conventional intermittent dosing because the major pharmacodynamic (PD) predictor of efficacy of β-lactams is the time that free drug levels exceed the MIC. This study incorporated a 6-year retrospective arm evaluating efficacy and safety of CI ticarcillin–clavulanate in the home treatment of serious infections and a prospective arm additionally evaluating pharmacokinetics (PK) and PD. In the prospective arm, steady-state serum ticarcillin and clavulanate levels and MIC testing of significant pathogens were performed. One hundred and twelve patients (median age, 56 years) were treated with a CI dose of 9.3–12.4 g/day and mean CI duration of 18.0 days. Infections treated included osteomyelitis (50 patients), septic arthritis (6), cellulitis (17), pulmonary infections (12), febrile neutropenia (7), vascular infections (7), intra-abdominal infections (2), and Gram-negative endocarditis (2); 91/112 (81%) of patients were cured, 14 (13%) had partial response and 7 (6%) failed therapy. Nine patients had PICC line complications and five patients had drug adverse events. Eighteen patients had prospective PK/PD assessment although only four patients had sufficient data for a full PK/PD evaluation (both serum steady-state drug levels and ticarcillin and clavulanate MICs from a bacteriological isolate), as this was difficult to obtain in home-based patients, particularly as serum clavulanate levels were found to deteriorate rapidly on storage. Three of four patients with matched PK/PD assessment had free drug levels exceeding the MIC of the pathogen. Home CI of ticarcillin–clavulanate is a safe, effective, convenient and practical therapy and is a therapeutic advance over traditional intermittent dosing when used in the home setting.

Discharge planning in the emergency department : a comprehensive approach

Discharge planning has become increasingly important, with current trends toward shorter hospital stays, increased health care costs, and more community-based health services. Effective discharge planning ensures the safety and ongoing care for patients,1 and it also benefits health care providers and organizations. It results in shorter hospital stays, fewer readmissions, higher access rates to post-hospitalization services, greater patient satisfaction with the discharge, and improved quality of life and continuity of care.[2] and [3] All acute care patients and their caregivers require some degree of preparation for discharge home—education about their health status, risks, and treatment; help setting health goals and maintaining a good level of self-care; information about community resources; and follow-up appointments and referrals to appropriate community health providers. Inadequate preparation exposes the patient to unnecessary risks of recurrence or complications of the acute complaint, neglect of nonacute comorbidities, mismanagement and side effects of medication, disruption of family and social life, emotional distress, and financial loss.[2], [3] and [4] The result may be re-presentation to the emergency department. It is noteworthy that up to 18% of ED presentations are revisits within 72 hours of the original visit5; many of these are considered preventable.6 It is a primary responsibility of nurses to ensure that patients return to the community adequately prepared and with appropriate support in place. Up to 65% of ED patients are discharged home from the emergency department,7 and the characteristics of the emergency department and its patient population make the provision of a high standard of discharge planning uniquely difficult. In addition, discharge planning is neglected in contemporary emergency nursing—there are no monographs devoted to the subject, and there is little published research. In this article 3 issues are explored: the importance of emergency nurses’ participation in the discharge-planning process, impediments to their participation; and strategies to improve discharge planning in the emergency department.

Aetiology of Hip dislocation

Written by the surgeons of the Exeter Hip Team and their colleagues from around the world, this book describes 40 years of innovation and development with cemented hip replacement. Topics covered include the basic science behind successful cemented hip replacement, modern surgical techniques and recent advances. There is also extensive coverage of the revision techniques developed at Exeter and elsewhere, focussing on femoral and acetabular impaction grafting. Each chapter is a self-contained article with an emphasis, where appropriate, on practical techniques and surgical tips, supported by line drawings and intra-operative photographs.

The use of cement in hip arthroplasty

Written by the surgeons of the Exeter Hip Team and their colleagues from around the world, this book describes 40 years of innovation and development with cemented hip replacement. Topics covered include the basic science behind successful cemented hip replacement, modern surgical techniques and recent advances. There is also extensive coverage of the revision techniques developed at Exeter and elsewhere, focussing on femoral and acetabular impaction grafting. Each chapter is a self-contained article with an emphasis, where appropriate, on practical techniques and surgical tips, supported by line drawings and intra-operative photographs.

The Exeter Hip. 40 Years of Innovation in Total Hip Arthroplasty

* Propoerties and use of acrylic cement * Design and biomechaniscs of a cemented hip replacement * The science of loosening, lysis and wear * Preparation of patients for surgery * Potential complications and their avoidance * Modern primary surgical techniques and new developments * Complex primary hip replacement and specialist techniques * Outcomes of cemented hip replacement * Principles of revision hip replacement * Basic science of bone grafting in revision surgery * Femoral acetabular impaction bone grafting techniques * Results of revision with bone graft and cement

Fusionless scoliosis correction using shape memory alloy staples

Severe spinal deformity in young children is a formidable challenge for optimal treatment. Standard interventions for adolescents, such as spinal deformity correction and fusion, may not be appropriate for young patients with considerable growth remaining. Alternative surgical options that provide deformity correction and protect the growth remaining in the spine are needed to treat this group of patients 1, 2. One such method is the use of shape memory alloy staples. We report our experience to date using video-assisted thoracoscopic insertion of shape memory alloy staples. A retrospective review was conducted of 13 patients with scoliosis, aged 7 to 13 years, who underwent video-assisted thoracoscopic insertion of shape memory staples. In our experience, video-assisted thoracoscopic insertion of shape memory alloy staples is a safe procedure with no complications noted. It is a reliable method of providing curve stability, however the follow up results to date indicate that the effectiveness of the procedure is greater in younger patients.

Ethics and public health

Note: see later edition of this work at http://eprints.qut.edu.au/47632/ This chapter introduces you to the basic ethical principles that underpin public health practice. The themes to be considered in this chapter include: the characteristics of ‘ethics’, the justification for reflecting on ethics and values, the foundations of public health ethics, whether and how we can incorporate ethics and values into our practice and the nature of some of the potential ethical complications of public health practice.

Self-efficacy, outcome expectations and self-care behaviour in people with type 2 diabetes in Taiwan

Aims. To explore differences in self-care behaviour according to demographic and illness characteristics; and relationships among self-care behaviour and demographic and illness characteristics, efficacy expectations and outcome expectations of people with type 2 diabetes in Taiwan. Background. Most people with diabetes do not control their disease appropriately in Taiwan. Enhanced self-efficacy towards managing diseases can be an effective way of improving disease control as proposed by the self-efficacy model which provides a useful framework for understanding adherence to self-care behaviours. Design and methods. The sample comprised 145 patients with type 2 diabetes aged 30 years or more from diabetes outpatient clinics in Taipei. Data were collected using a self-administered questionnaire for this study. One-way anova, t-tests, Pearson product moment correlation and hierarchical regression were analysed for the study. Results. Significant differences were found: between self-care behaviour and complications (t = −2·52, p < 0·01) and patient education (t = −1·96, p < 0·05). Self-care behaviour was significantly and positively correlated with duration of diabetes (r = 0·36, p < 0·01), efficacy expectations (r = 0·54, p < 0·01) and outcome expectations (r = 0·44, p < 0·01). A total of 39·1% of variance in self-care behaviour can be explained by duration of diabetes, efficacy expectations and outcome expectations. Conclusions. Findings support the use of the self-efficacy model as a framework for understanding adherence to self-care behaviour. Relevance to clinical practice. Using self-efficacy theory when designing patient education interventions for people with type 2 diabetes will enhance self-management routines and assist in reducing major complications in the future.

Does quality of life among breast cancer survivors one year after diagnosis differ depending on urban and non-urban residence? A comparative study

Background: This study examined the quality of life (QOL), measured by the Functional Assessment of Cancer Therapy (FACT) questionnaire, among urban (n=277) and non-urban (n=323) breast cancer survivors and women from the general population (n=1140) in Queensland, Australia. ---------- Methods: Population-based samples of breast cancer survivors aged <75 years who were 12 months post-diagnosis and similarly-aged women from the general population were recruited between 2002 and 2007. ---------- Results: Age-adjusted QOL among urban and non-urban breast cancer survivors was similar, although QOL related to breast cancer concerns was the weakest domain and was lower among non-urban survivors than their urban counterparts (36.8 versus 40.4, P<0.01). Irrespective of residence, breast cancer survivors, on average, reported comparable scores on most QOL scales as their general population peers, although physical well-being was significantly lower among non-urban survivors (versus the general population, P<0.01). Overall, around 20%-33% of survivors experienced lower QOL than peers without the disease. The odds of reporting QOL below normative levels were increased more than two-fold for those who experienced complications following surgery, reported upper-body problems, had higher perceived stress levels and/or a poor perception of handling stress (P<0.01 for all). ---------- Conclusions: Results can be used to identify subgroups of women at risk of low QOL and to inform components of tailored recovery interventions to optimize QOL for these women following cancer treatment.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.