preprints of 3. IFAC Symp. on Identification and System Parameters Estimation, Paper TM-2, 1973, Hague. 2 Peterka

disturbance. Here the reliance has been placed on its most plausible feature, namely its independence of input. This yields a set of assumptions in excess of the minimal requirement and an endeavor has been made to exploit this excess to reduce the sum of squares of estimation errors. developed operational matrix, the expansion coefficients of the shifted Legendre series which represents the approximate responses of transfer functions are computed by the recursive formula. The significance of the present research is that the present method is simple, straightforward and the computational results are accurate as well as the final time of the system can be adjustable without any restriction. Based on the model reduction technique, the design of a feedback control system to satisfy the prescribed specifications is studied by the proposed new algebraic method. Satisfactory examples are given to illustrate the method. References Properties of Shifted Legendre Functions The shifted Legendre function, P" (t) is related to the wellknown Legendre function P" ( T) by transforming the independent variable as T = 2(t/ Tj) -1. One of the properties of shifted Legendre polynomial functions is, 2(2« +1) Thus, the integration of P"(t) with respect to t can be ob- Introduction Model reduction has been receiving great attention in the field of process analysis and synthesis with the last twenty years. The purpose of model reduction is to provide a lower order model which is computationally simpler than the original higher order system. In this paper, an effective method of shifted Legendre functions is employed to approach the problems of model reduction. The operational matrix for the integration of the shifted Legendre polynomial vectors whose elements are shifted Legendre function are first developed. Using th

Protocol for secondary data analysis of 4 UK cohorts examining youth adversity and mental health in the context of intersectionality.

BACKGROUND: Youth adversity (e.g., abuse and bullying victimisation) is robust risk factor for later mental health problems (e.g., depression and anxiety). Research shows the prevalence of youth adversity and rates of mental health problems vary by individual characteristics, identity or social groups (e.g., gender and ethnicity). However, little is known about whether the impact of youth adversity on mental health problems differ across the intersections of these characteristics (e.g., white females). This paper reports on a component of the ATTUNE research programme (work package 2) which aims to investigate the impact and mechanisms of youth adversity on depressive and anxiety symptoms in young people by intersectionality profiles. METHODS: The data are from 4 UK adolescent cohorts: HeadStart Cornwall, Oxwell, REACH, and DASH. These cohorts were assembled for adolescents living in distinct geographical locations representing coastal, suburban and urban places in the UK. Youth adversity was assessed using a series of self-report questionnaires and official records. Validated self-report instruments measured depressive and anxiety symptoms. A range of different variables were classified as possible social and cognitive mechanisms. RESULTS AND ANALYSIS: Structural equation modelling (e.g., multiple group models, latent growth models) and multilevel modelling will be used, with adaptation of methods to suit the specific available data, in accord with statistical and epidemiological conventions. DISCUSSION: The results from this research programme will broaden our understanding of the association between youth adversity and mental health, including new information about intersectionality and related mechanisms in young people in the UK. The findings will inform future research, clinical guidance, and policy to protect and promote the mental health of those most vulnerable to the negative consequences of youth adversity

Inflammation and epithelial repair predict mortality, hospital readmission, and growth recovery in complicated severe acute malnutrition.

Severe acute malnutrition (SAM) is the most high-risk form of undernutrition, particularly when children require hospitalization for complications. Complicated SAM is a multisystem disease with high inpatient and postdischarge mortality, especially in children with comorbidities such as HIV; however, the underlying pathogenesis of complicated SAM is poorly understood. Targeted multiplex biomarker analysis in children hospitalized with SAM (n = 264) was conducted on plasma samples, and inflammatory markers were assessed on stool samples taken at recruitment, discharge, and 12 to 24 and 48 weeks after discharge from three hospitals in Zimbabwe and Zambia. Compared with adequately nourished controls (n = 173), we found that at baseline, complicated SAM was characterized by systemic, endothelial, and intestinal inflammation, which was exacerbated by HIV infection. This persisted over 48 weeks despite nutritional recovery and was associated with children's outcomes. Baseline plasma concentrations of vascular endothelial growth factor, glucagon-like peptide-2, and intestinal fatty acid-binding protein were independently associated with lower mortality or hospital readmission over the following 48 weeks. Following principal components analysis of baseline biomarkers, higher scores of a component representing growth factors was associated with greater weight-for-height z score recovery and lower mortality or hospital readmission over the 48 weeks. Conversely, components representing higher gut and systemic inflammation were associated with higher mortality or hospital readmission. These findings highlight the interplay between inflammation, which damages tissues, and growth factors, which mediate endothelial and epithelial regeneration, and support further studies investigating interventions to reduce inflammation and promote epithelial repair as an approach to reducing mortality and improving nutritional recovery

A tailored psychological intervention for anxiety and depression management in people with chronic obstructive pulmonary disease: TANDEM RCT and process evaluation

Background: People with chronic obstructive pulmonary disease have high levels of anxiety and depression, which is associated with increased morbidity and poor uptake of effective treatments, such as pulmonary rehabilitation. Cognitive-behavioural therapy improves mental health of people with long-term conditions and could potentially increase uptake of pulmonary rehabilitation, enabling synergies that could enhance the mental health of people with chronic obstructive pulmonary disease. Aim: Our aim was to develop and evaluate the clinical effectiveness and cost effectiveness of a tailored cognitive-behavioural approach intervention, which links into, and optimises the benefits of, routine pulmonary rehabilitation. Design: We carried out a pragmatic multicentre randomised controlled trial using a 1.25 : 1 ratio (intervention : control) with a parallel process evaluation, including assessment of fidelity. Setting: Twelve NHS trusts and five Clinical Commissioning Groups in England were recruited into the study. The intervention was delivered in participant\u27s own home or at a local NHS facility, and by telephone. Participants: Between July 2017 and March 2020 we recruited adults with moderate/very severe chronic obstructive pulmonary disease and mild/moderate anxiety and/or depression, meeting eligibility criteria for assessment for pulmonary rehabilitation. Carers of participants were invited to participate. Intervention: The cognitive-behavioural approach intervention (i.e. six to eight 40- to 60-minute sessions plus telephone support throughout pulmonary rehabilitation) was delivered by 31 trained respiratory healthcare professionals to participants prior to commencing pulmonary rehabilitation. Usual care included routine pulmonary rehabilitation referral. Main outcome measures: Co-primary outcomes were Hospital Anxiety and Depression Scale - anxiety and Hospital Anxiety and Depression Scale - depression at 6 months post randomisation. Secondary outcomes at 6 and 12 months included health-related quality of life, smoking status, uptake of pulmonary rehabilitation and healthcare use. Results: We analysed results from 423 randomised participants (intervention, n = 242; control, n = 181). Forty-three carers participated. Follow-up at 6 and 12 months was 93% and 82%, respectively. Despite good fidelity for intervention delivery, mean between-group differences in Hospital Anxiety and Depression Scale at 6 months ruled out clinically important effects (Hospital Anxiety and Depression Scale - anxiety mean difference -0.60, 95% confidence interval -1.40 to 0.21; Hospital Anxiety and Depression Scale - depression mean difference -0.66, 95% confidence interval -1.39 to 0.07), with similar results at 12 months. There were no between-group differences in any of the secondary outcomes. Sensitivity analyses did not alter these conclusions. More adverse events were reported for intervention participants than for control participants, but none related to the trial. The intervention did not generate quality-of-life improvements to justify the additional cost (adjusted mean difference \ua3770.24, 95% confidence interval -\ua327.91 to \ua31568.39) to the NHS. The intervention was well received and many participants described positive affects on their quality of life. Facilitators highlighted the complexity of participants\u27 lives and considered the intervention to be of potential valuable; however, the intervention would be difficult to integrate within routine clinical services. Our well-powered trial delivered a theoretically designed intervention with good fidelity. The respiratory-experienced facilitators were trained to deliver a low-intensity cognitive-behavioural approach intervention, but high-intensity cognitive-behavioural therapy might have been more effective. Our broad inclusion criteria specified objectively assessed anxiety and/or depression, but participants were likely to favour talking therapies. Randomisation was concealed and blinding of outcome assessment was breached in only 15 participants. Conclusions: The tailored cognitive-behavioural approach intervention delivered with fidelity by trained respiratory healthcare professionals to people with chronic obstructive pulmonary disease was neither clinically effective nor cost-effective. Alternative approaches that are integrated with routine long-term condition care are needed to address the unmet, complex clinical and psychosocial needs of this group of patients. Trial registration: This trial is registered as ISRCTN59537391. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 13/146/02) and is published in full in Health Technology Assessment; Vol. 28, No. 1. See the NIHR Funding and Awards website for further award information.People with long-standing lung problems, such as chronic obstructive pulmonary disease, often also have anxiety and depression, which further reduces their quality of life. Two existing treatments could help. Pulmonary rehabilitation (a programme of exercise and education) improves both the physical and mental health of people with chronic obstructive pulmonary disease. Cognitive–behavioural therapy (a talking therapy) may reduce anxiety and depression. The TANDEM [Tailored intervention for Anxiety and Depression Management in chronic obstructive pulmonary disease (COPD)] intervention linked these two treatments by providing talking therapy based on cognitive–behavioural therapy during the waiting time following referral for pulmonary rehabilitation. The TANDEM treatment was delivered by respiratory healthcare professionals (e.g. nurses or physiotherapists) trained to deliver the talking therapy in six to eight weekly sessions. The sessions were conducted in the participant’s home (or another convenient location), with brief telephone support during the pulmonary rehabilitation. Of 423 participants recruited to the study, 242 participants received TANDEM talking therapy and 181 participants received usual care (including a referral to pulmonary rehabilitation). We measured mental health, quality of life, social life, attendance at pulmonary rehabilitation and healthcare use in both groups at 6 and 12 months. Forty-three carers joined the study and we assessed their mental well-being. We interviewed patients, carers and health professionals to find out their views and experience of the TANDEM treatment. We also examined whether or not the TANDEM treatment was good value for money. The TANDEM treatment did not improve the mental or the physical health of people with chronic obstructive pulmonary disease. In addition, the TANDEM treatment cost the NHS an extra \ua3770 per patient, which was not good value for money. The TANDEM treatment was well received, and many participants told us how it had helped them. Heath-care professionals noted how participants did not just have chronic obstructive pulmonary disease, but were coping with many physical, mental and social problems. The TANDEM intervention was not effective and, therefore, other strategies will be needed to help people with chronic obstructive pulmonary disease and mental health problems live with their condition

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Mid-life psychosocial work environment as a predictor of work exit by age 50.

OBJECTIVES: To examine whether psychosocial work characteristics at age 45 years predict exit from the labour market by the age of 50 years in data from the 1958 British Birth Cohort. METHODS: Psychosocial work characteristics (decision latitude, job demands, job strain and work social support at 45 years and job insecurity at 42 years) measured by questionnaire were linked to employment outcomes (unemployment, retirement, permanent sickness, homemaking) at 50 years in 6510 male and female participants. RESULTS: Low decision latitude (RR = 2.01, 95%CI 1.06,3.79), low work social support (RR = 1.96, 95%CI 1.12,3.44), and high job insecurity (RR = 2.27, 95%CI 1.41, 3.67) predicted unemployment at 50, adjusting for sex, housing tenure, socioeconomic status, marital status, and education. High demands were associated with lower risk of unemployment (RR = 0.50, 95%CI 0.29,0.88) but higher risk of permanent sickness (RR = 2.14, 95%CI 1.09,4.21). CONCLUSIONS: Keeping people in the workforce beyond 50 years may contribute to both personal and national prosperity. Employers may wish to improve working conditions for older workers, in particular, increase control over work, increase support and reduce demands to retain older employees in the workforce

External validation of prognostic models predicting pre-eclampsia : individual participant data meta-analysis

Abstract Background Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model’s calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. Trial registration PROSPERO ID: CRD42015029349