Overlap of cognitive concepts in chronic widespread pain: An exploratory study

<p>Abstract</p> <p>Background</p> <p>A wide variety of cognitive concepts have been shown to play an important role in chronic widespread pain (CWP). Although these concepts are generally considered to be distinct entities, some might in fact be highly overlapping. The objectives of this study were to (i) to establish inter-relationships between self-efficacy, cognitive coping styles, fear-avoidance cognitions and illness beliefs in patients with CWP and (ii) to explore the possibility of a reduction of these cognitions into a more limited number of domains.</p> <p>Methods</p> <p>Baseline measurement data of a prospective cohort study of 138 patients with CWP were used. Factor analysis was used to study the associations between 16 different cognitive concepts.</p> <p>Results</p> <p>Factor analysis resulted in three factors: 1) negative emotional cognitions, 2) active cognitive coping, and 3) control beliefs and expectations of chronicity.</p> <p>Conclusion</p> <p>Negative emotional cognitions, active cognitive coping, control beliefs and expectations of chronicity seem to constitute principal domains of cognitive processes in CWP. These findings contribute to the understanding of overlap and uniqueness of cognitive concepts in chronic widespread pain.</p

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

Antimicrobial knowledge and confidence amongst final year medical students in Australia

Introduction: Inappropriate use of antimicrobials is one of the major modifiable contributors to antimicrobial resistance. There is currently no validated survey tool available to assess knowledge and confidence of medical students in infectious diseases (ID) compared to other diseases states, and little is known about this topic. Materials and methods: A cross-sectional survey of final year medical students attending universities around Australia was conducted between August and September, 2015. A survey unique from other published studies was developed to survey satisfaction in education, confidence and knowledge in ID, and how this compared to these factors in cardiovascular diseases. Results: Reliability and validity was demonstrated in the survey tool used. Students were more likely to rate university education as sufficient for cardiovascular diseases (91.3%) compared to ID (72.5%), and were more confident in their knowledge of cardiovascular diseases compared to ID (74.38% vs. 53.76%). Students tended to answer more cardiovascular disease related clinical questions correctly (mean score 78%), compared to questions on antimicrobial use (mean score 45%). Conclusions: Poor knowledge and confidence amongst final year medical students in Australia were observed in ID. Antimicrobial stewardship agenda should include the provision of additional training in antimicrobial prescribing to the future medical workforce

Continence technologies whitepaper: Informing new engineering science research

Advances in healthcare technology for continence have historically been limited compared to other areas of medicine, reflecting the complexities of the condition and social stigma which act as a barrier to participation. This whitepaper has been developed to inspire and direct the engineering science community towards research opportunities that exist for continence technologies that address unmet needs in diagnosis, treatment and long-term management. Our aim is to pinpoint key challenges and highlight related research opportunities for novel technological advances. To do so, we draw on experience and expertise from academics, clinicians, patients and patient groups linked to continence healthcare. This is presented in four areas of consideration: the clinical pathway, patient perspective, research challenges and effective innovation. In each we introduce seminal research, background information and demonstrative case-studies, before discussing their relevance to engineering science researchers who are interested in approaching this overlooked but vital area of healthcare