Tool Texturing for Deep Drawing Applications

The application of surface texturing on sheet metal is a widely used approach to improve lubrication and control friction in deep drawing applications. However, it has been shown that current texturing processes are not robust to produce uniform textures on the sheet due to rapid and severe wear on texture-rolls. Furthermore, in multi-stage forming processes, deterioration of the sheet texture even at the first stage of forming makes texturing of the sheet metal surface ineffective. Tool surface texturing is a new method to control friction and tool wear in metal forming industry. In the current study, a multi-scale friction model is adopted to investigate the effect of tool texturing on the evolution of friction during sheet metal forming operations. The multi-scale friction model accounts for surface topography changes due to deformation of asperities and ploughing of tool asperities on the sheet metal surface, mixed lubrication regime and furthermore the tool micro-texture effects on lubricant distribution at tool-sheet metal interface. The model is validated with respect to strip-draw experiments using different tool textures. The model is later applied to the simulation of a U-bend forming process. The results show that using textured tools, it is possible to reduce friction and punch force in sheet metal forming processes. The model can be used to tailor and optimize textures on stamping tools for complex parts

The construction of confidence intervals for frequency analysis using resampling techniques

International audienceResampling techniques such as the Bootstrap and the Jack-knife are generic methods for the estimation of uncertainties in statistics. When applied in frequency analysis, resampling techniques can provide estimates of the uncertainties in both distribution parameters and quantile estimates in circumstances in which confidence limits cannot be obtained theoretically. Test experiments using two different parameter estimation methods on two types of distributions with different initial sample sizes and numbers of resamples has confirmed the utility of such methods. However, care is necessary in evaluating the skewness of the resampled quantiles, especially with small initial sample sizes. Keywords: Bootstrap, Jack-knife, frequency analysis, maximum likelihood method, maximum product of spacings metho

Development and validation of PRE-DELIRIC (PREdiction of DELIRium in ICu patients) delirium prediction model for intensive care patients: observational multicentre study

Objectives To develop and validate a delirium prediction model for adult intensive care patients and determine its additional value compared with prediction by caregivers

Adherence to Tuberculosis Therapy among Patients Receiving Home-Based Directly Observed Treatment: Evidence from the United Republic of Tanzania.

\ud \ud Non-adherence to tuberculosis (TB) treatment is the leading contributor to the selection of drug-resistant strains of Mycobacterium tuberculosis and subsequent treatment failure. Tanzania introduced a TB Patient Centred Treatment (PCT) approach which gives new TB patients the choice between home-based treatment supervised by a treatment supporter of their own choice, and health facility-based treatment observed by a medical professional. The aim of this study was to assess the extent and determinants of adherence to anti-TB therapy in patients opting for home-based treatment under the novel PCT approach. In this cross-sectional study, the primary outcome was the percentage of patients adherent to TB therapy as detected by the presence of isoniazid in urine (IsoScreen assay). The primary analysis followed a non-inferiority approach in which adherence could not be lower than 75%. Logistic regression was used to examine the influence of potentially predictive factors. A total of 651 new TB patients were included. Of these, 645 (99.1%) provided urine for testing and 617 patients (95.7%; 90%CI 94.3-96.9) showed a positive result. This result was statistically non-inferior to the postulated adherence level of 75% (p<0.001). Adherence to TB therapy under home-based Directly Observed Treatment can be ensured in programmatic settings. A reliable supply of medication and the careful selection of treatment supporters, who preferably live very close to the patient, are crucial success factors. Finally, we recommend a cohort study to assess the rate of adherence throughout the full course of TB treatment

Multinational development and validation of an early prediction model for delirium in ICU patients

Rationale Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention. Purpose To develop and validate a model based on data available at ICU admission to predict delirium development during a patient’s complete ICU stay and to determine the predictive value of this model in relation to the time of delirium development. Methods Prospective cohort study in 13 ICUs from seven countries. Multiple logistic regression analysis was used to develop the early prediction (E-PRE-DELIRIC) model on data of the first two-thirds and validated on data of the last one-third of the patients from every participating ICU. Results In total, 2914 patients were included. Delirium incidence was 23.6 %. The E-PRE-DELIRIC model consists of nine predictors assessed at ICU admission: age, history of cognitive impairment, history of alcohol abuse, blood urea nitrogen, admission category, urgent admission, mean arterial blood pressure, use of corticosteroids, and respiratory failure. The area under the receiver operating characteristic curve (AUROC) was 0.76 [95 % confidence interval (CI) 0.73–0.77] in the development dataset and 0.75 (95 % CI 0.71–0.79) in the validation dataset. The model was well calibrated. AUROC increased from 0.70 (95 % CI 0.67–0.74), for delirium that developed 6 days. Conclusion Patients’ delirium risk for the complete ICU length of stay can be predicted at admission using the E-PRE-DELIRIC model, allowing early preventive interventions aimed to reduce incidence and severity of ICU delirium

Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study

Purpose Recalibration and determining discriminative power, internationally, of the existing delirium prediction model (PRE-DELIRIC) for intensive care patients. Methods A prospective multicenter cohort study was performed in eight intensive care units (ICUs) in six countries. The ten predictors (age, APACHE-II, urgent and admission category, infection, coma, sedation, morphine use, urea level, metabolic acidosis) were collected within 24 h after ICU admission. The confusion assessment method for the intensive care unit (CAM-ICU) was used to identify ICU delirium. CAM-ICU screening compliance and inter-rater reliability measurements were used to secure the quality of the data. Results A total of 2,852 adult ICU patients were screened of which 1,824 (64 %) were eligible for the study. Main reasons for exclusion were length of stay <1 day (19.1 %) and sustained coma (4.1 %). CAM-ICU compliance was mean (SD) 82 ± 16 % and inter-rater reliability 0.87 ± 0.17. The median delirium incidence was 22.5 % (IQR 12.8–36.6 %). Although the incidence of all ten predictors differed significantly between centers, the area under the receiver operating characteristic (AUROC) curve of the eight participating centers remained good: 0.77 (95 % CI 0.74–0.79). The linear predictor and intercept of the prediction rule were adjusted and resulted in improved re-calibration of the PRE-DELIRIC model. Conclusions In this multinational study, we recalibrated the PRE-DELIRIC model. Despite differences in the incidence of predictors between the centers in the different countries, the performance of the PRE-DELIRIC-model remained good. Following validation of the PRE-DELIRIC model, it may facilitate implementation of strategies to prevent delirium and aid improvements in delirium management of ICU patients

Cost-effectiveness of twice-weekly versus once-weekly sessions of cognitive-behavioural therapy and interpersonal psychotherapy for depression at 12 months after start of treatment : randomised controlled trial

BACKGROUND: Cost-effective treatments are needed to reduce the burden of depression. One way to improve the cost-effectiveness of psychotherapy might be to increase session frequency, but keep the total number of sessions constant. AIM: To evaluate the cost-effectiveness of twice-weekly compared with once-weekly psychotherapy sessions after 12 months, from a societal perspective. METHOD: An economic evaluation was conducted alongside a randomised controlled trial comparing twice-weekly versus once-weekly sessions of psychotherapy (cognitive-behavioural therapy or interpersonal psychotherapy) for depression. Missing data were handled by multiple imputation. Statistical uncertainty was estimated with bootstrapping and presented with cost-effectiveness acceptability curves. RESULTS: Differences between the two groups in depressive symptoms, physical and social functioning, and quality-adjusted life-years (QALY) at 12-month follow-up were small and not statistically significant. Total societal costs in the twice-weekly session group were higher, albeit not statistically significantly so, than in the once-weekly session group (mean difference €2065, 95% CI -686 to 5146). The probability that twice-weekly sessions are cost-effective compared with once-weekly sessions was 0.40 at a ceiling ratio of €1000 per point improvement in Beck Depression Inventory-II score, 0.32 at a ceiling ratio of €50 000 per QALY gained, 0.23 at a ceiling ratio of €1000 per point improvement in physical functioning score and 0.62 at a ceiling ratio of €1000 per point improvement in social functioning score. CONCLUSIONS: Based on the current results, twice-weekly sessions of psychotherapy for depression are not cost-effective over the long term compared with once-weekly sessions

Fasting before living-kidney donation:effect on donor well-being and postoperative recovery: study protocol of a multicenter randomized controlled trial

BACKGROUND: One of the main effectors on the quality of life of living-kidney donors is postoperative fatigue. Caloric restriction (CR) and short-term fasting (STF) are associated with improved fitness and increased resistance to acute stress. CR/STF increases the expression of cytoprotective genes, increases immunomodulation via increased anti-inflammatory cytokine production, and decreases the expression of pro-inflammatory markers. As such, nutritional preconditioning by CR or STF represents a non-invasive and cost-effective method that could mitigate the effects of acute surgery-induced stress and postoperative fatigue. To investigate whether preoperative STF contributes to a reduction in fatigue after living-kidney donation, a randomized clinical trial is indicated. METHODS: We aim to determine whether 2.5 days of fasting reduces postoperative fatigue score in subjects undergoing living-kidney donation. In this randomized study, the intervention group will follow a preoperative fasting regime for 2.5 days with a low-dose laxative, while the control group will receive standard care. The main study endpoint is postoperative fatigue, 4 weeks after living-kidney donation. Secondary endpoints include the effect of preoperative fasting on postoperative hospital admission time, the feasibility of STF, and the postoperative recovery of donor and recipient kidney function. This study will provide us with knowledge of the feasibility of STF and confirm its effect on postoperative recovery. DISCUSSION: Our study will provide clinically relevant information on the merits of caloric restriction for living-kidney donors and recipients. We expect to reduce the postoperative fatigue in living-kidney donors and improve the postoperative recovery of living-kidney recipients. It will provide evidence on the clinical merits and potential caveats of preoperative dietary interventions. TRIAL REGISTRATION: Netherlands Trial Register NL9262. EudraCT 2020-005445-16. MEC Erasmus MC MEC-2020-0778. CCMO NL74623.078.21 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05950-x