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.

Turning Around Talipes: Nursing Considerations

The management of congenital talipes equinovarus (TEV) has received much clinical and research attention within the disciplines of medicine and physiotherapy. However, few articles have been published about the role of the registered nurse in contributing to the optimum health and wellbeing of the child and family presenting for assessment and treatment of the condition. Much of the most intense treatment for TEV occurs in the first few weeks of the child’s life; a time of critical growth and development when the infant is both sensitive and vulnerable to the environment within which it is nurtured. This is also a crucial time for developing a secure attachment to the caregiver and nurses can assist parents in optimising their infant’s opportunities for a secure attachment relationship. This paper thus provides an overview of the medical and physiotherapy management of TEV and highlights the role nurses have in providing nursing care and psycho-social support to parents of infants with TEV, in areas such as the maintenance of skin integrity and circulation, providing effective pain relief, and optimising growth, development, and a secure attachment relationship. Congenital TEV or 'club foot' is one of the most common congenital orthopaedic anomalies of infants. In Queensland in 2000, in approximately 50,000 births, 244 infants were born with talipes; almost five infants per 1000 births. National statistics are not as specific, with coding providing only 'other lower limb' as the category that would encompass talipes; the 1997 national incidence of such lower limb congenital malformations is reported as 1.7 per 10,000 births 1.

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.

Good nutrition for good surgery: clinical and quality of life outcomes

Undernutrition is common in patients admitted for surgery and is often unrecognised, untreated and worsens in hospital. The complex synergistic relationship between nutritional status and the physiological responses to surgery puts patients at high nutritional risk. There are clear prospective associations between inadequate nutritional status and the risk of poorer outcomes for surgical patients, including infection, complications and length of stay. However, practically and ethically evidence that nutritional interventions can significantly reduce these poor outcomes is difficult to obtain. Nevertheless health professionals have a duty of care to ensure our patients are properly fed, by whatever means, to meet their physiological requirements.

Is it necessary to re-fuse a non-union of a hallux metatarsophalangeal joint arthrodesis?

BACKGROUND: The standard treatment for a non-union of the hallux metatarsophalangeal joint fusion has been to revise the fusion. Revision fusion is technically more demanding, often involving bone grafting, more substantial fixation and prolonged period of immobilization postoperatively. We present data to suggest that removal of hardware and debridement alone is an alternative treatment option. ---------- MATERIALS AND METHODS: A case note review identified patients with a symptomatic non-union after hallux metatarsophalangeal joint (MTPJ) fusion. It is our practice to offer these patients revision fusion or removal of hardware and debridement. For the seven patients that chose hardware removal and were left with a pseudarthrosis, a matched control group was selected from patients who had had successful fusions. Three outcome scores were used. Hallux valgus and dorsiflexion angles were recorded.---------- RESULTS: One hundred thirty-nine hallux MTPJ arthrodeses were carried out. Fourteen non-unions were identified. The rate of non-union in males and following previous hallux MTPJ surgery was 19% and 24%, respectively. In females undergoing a primary MTPJ fusion, the rate was 2.4%. Twelve non-union patients were reviewed at 27 months (mean). Eleven patients had elected to undergo removal of hardware and debridement. Four patients with pseudarthrosis were unhappy with the results and proceeded to either revision fusion or MTPJ replacement. Seven non-union patients, who had removal of hardware alone, had outcome scores marginally worse compared to those with successful fusions.---------- CONCLUSION: Removal of hardware alone is a reasonable option to offer as a relatively minor procedure following a failed arthrodesis of the first MTPJ. This must be accepted on the proviso that in this study four out of 11 (36%) patients proceeded to a revision first MTPJ fusion or first MTPJ replacement. We also found that the rate of non-union in primary first MTPJ fusion was significantly higher in males and those patients who had undergone previous surgery.

Repair and regeneration of osteochondral defects in the articular joints

People suffering from pain due to osteoarthritic or rheumatoidal changes in the joints are still waiting for a better treatment. Although some studies have achieved success in repairing small cartilage defects, there is no widely accepted method for complete repair of osteochondral defects. Also joint replacements have not yet succeeded in replacing of natural cartilage without complications. Therefore, there is room for a new medical approach, which outperforms currently used methods. The aim of this study is to show potential of using a tissue engineering approach for regeneration of osteochondral defects. The critical review of currently used methods for treatment of osteochondral defects is also provided. In this study, two kinds of hybrid scaffolds developed in Hutmacher's group have been analysed. The first biphasic scaffold consists of fibrin and PCL. The fibrin serves as a cartilage phase while the porous PCL scaffold acts as the subchondral phase. The second system comprises of PCL and PCL-TCP. The scaffolds were fabricated via fused deposition modeling which is a rapid prototyping system. Bone marrow-derived mesenchymal cells were isolated from New Zealand White rabbits, cultured in vitro and seeded into the scaffolds. Bone regenerations of the subchondral phases were quantified via micro CT analysis and the results demonstrated the potential of the porous PCL and PCL-TCP scaffolds in promoting bone healing. Fibrin was found to be lacking in this aspect as it degrades rapidly. On the other hand, the porous PCL scaffold degrades slowly hence it provides an effective mechanical support. This study shows that in the field of cartilage repair or replacement, tissue engineering may have big impact in the future. In vivo bone and cartilage engineering via combining a novel composite, biphasic scaffold technology with a MSC has been shown a high potential in the knee defect regeneration in the animal models. However, the clinical application of tissue engineering requires the future research work due to several problems, such as scaffold design, cellular delivery and implantation strategies.