The relevance of Short-Term Variation (STV) value measured within 1 hour before delivery in predicting adverse neonatal outcome

Objectives: Computer CTG analysis (cCTG) included short-term variation (STV) is one of the methods of monitoring fetal condition during delivery. The aim of our study was to define appropriability of STV measured within 1 hour before delivery in prediction of neonatal outcomes. Material and methods: The retrospective study included 1014 pregnant women, who gave birth in the Department of Obstetrics and Perinatology. Participants were divided into two groups: group 1 — term pregnancies (37–41 weeks) and group 2 — preterm pregnancies (lower than 37 weeks). In each of them, two subgroups have been separated: control (STV ≥ 3 ms) and study group (STV < 3 ms). Results: In both groups 1 and 2, there were no statistically significant differences related to Apgar scores in 1st, 3rd and 5th minute between group with STV < 3 ms and group with STV > 3 ms Moreover, for 37–41 weeks the sensitivity, specificity, positive predictive value and negative predictive value were: 22.7%, 83.9%, 3.3% and 97.8% and for lower than 37: 45.7%, 65.4%, 47.1%, 64.2% in 1th minute after delivery. In group 1 the area under curve (AUC) measurements were 0.45 (95% CI: 0.32–0.58) for 1st minute and 0.55 (95% CI: 0.35–0.74) for 5th minute and in group 2: 0.58 (95% CI: 0.45–0.71) for 1th minute and 0.57 (95% CI: 0.42–0.72) for 5th minute.   Conclusions: High specificity and negative predictive value of STV indicates a good Apgar score of newborns in term pregnancies. Analysis of STV in preterm pregnancy is not clear. Fetal well-being in preterm pregnancy should include STV and other non-invasive and invasive tools

Consumer perception and behaviour related to low-alcohol wine: do people overcompensate?

Objective: Compared with standard wines, low-alcohol wines may have several social and health benefits. Innovative production processes have led to high-quality light wines. It is, however, unclear how consumers perceive and consume these alcohol-reduced wines. The current study aimed to investigate how people evaluate low-alcohol wine (Sauvignon Blanc) and if the reduction in alcohol and the information that a wine is low in alcohol influences consumption. Design: Randomised controlled trial (RCT). Setting: Participants were invited to a wine tasting and randomised into one of the three conditions: they either tasted a 'new white wine' (12 center dot 5 % alcohol content), a 'new low-alcohol white wine' (8 center dot 0 % alcohol content) or they tasted the low-alcohol wine but were not aware that the wine was reduced in alcohol (low-alcohol, blinded). Participants: Ninety participants (42 % male, mean age = 41 (sd14) years). Results: Mean comparisons showed similar ratings for the low-alcohol conditions and the standard alcohol condition (mean > 5 center dot 6/7). The mean consumed amount across all conditions did not differ (162 (sd71) ml, (F-2,F-86= 0 center dot 43,P> 0 center dot 05)), hence people who tasted the low-alcohol wine consumed approximately 30 % less alcohol. However, participants were willing to pay more for the normal wine compared with the low-alcohol wine, (F-2,F-87= 3 center dot 14,P< 0 center dot 05). Conclusions: Participants did not alter their drinking behaviour in response to the reduced alcohol content, and the low-alcohol wine was perceived positively. There might be an emerging market potential for wine of reduced alcohol content, but consumers may not be willing to pay the same price as for the standard wine

Integrating smartphone technology, social support and the outdoor physical environment to improve fitness among adults at risk of, or diagnosed with, Type 2 Diabetes: Findings from the 'eCoFit' randomized controlled trial

The risk and prevalence of Type 2 Diabetes (T2D) has dramatically increased over the past decade. The aim of this study was to develop, implement and evaluate a physical activity intervention to improve aerobic and muscular fitness among adults at risk of, or diagnosed with T2D. A 20-week, assessor blinded, parallel-group randomized controlled trial (RCT) was conducted at the University of Newcastle (June-December 2015). Adults were randomized to the intervention (n=42) or wait-list control group (n=42). The theory-based intervention included: Phase 1 (weeks 1-10) integrated group sessions (outdoor physical activity and cognitive mentoring), and the 'eCoFit' smartphone application (app). Phase 2 (weeks 11-20) only included the 'eCoFit' app. Participants were assessed at baseline, 10 weeks and 20 weeks. Linear mixed models (intention-to-treat) were used to determine group-by-time interactions at 10 weeks (primary time-point) and 20 weeks for the primary outcomes. Several secondary outcomes were also assessed. After 10 weeks, significant group-by-time effects were observed for aerobic fitness (4.5 mL/kg/min; 95% CI [1.3, 7.7], d=0.68) and muscular fitness (lower body) (3.4 reps, 95% CI [2.7, 4.2], d=1.45). Intervention effects for secondary outcomes included significant increased physical activity (1330 steps/week), improved upper body muscular fitness (5 reps; arm-curl test), improved functionality (-1.8 s; timed-up and go test) reduced waist circumference (2.8 cm) and systolic blood pressure (-10.4 mm Hg). After 20 weeks, significant effects were observed for lower body muscular fitness and health outcomes. 'eCoFit' is an innovative lifestyle intervention which integrates smartphone technology, social support, and the outdoor environment to improve aerobic and muscular fitness

Rationale and study protocol for the 'eCoFit' randomized controlled trial: Integrating smartphone technology, social support and the outdoor physical environment to improve health-related fitness among adults at risk of, or diagnosed with, Type 2 Diabetes

Introduction: The prevalence and risk of Type 2 Diabetes (T2D) has dramatically increased over the past decade. Physical activity (PA) has significant benefits for the treatment and prevention of T2D. The aim of this study is to develop, implement and evaluate a community-based PA intervention to improve aerobic and muscular fitness among adults at risk of, or diagnosed with T2D. Research design and methods: The eCoFit pilot intervention will be evaluated using a randomized controlled trial (RCT) design. The 20-week (Phases 1 and 2) multi-component intervention was guided by Social Cognitive Theory, Health Action Process Approach Model, and Cognitive Behavior Therapy strategies. Phase 1 (Weeks 1-10) includes: i) 5 group face-to-face sessions consisting of outdoor training and cognitive mentoring; and ii) the use of the eCoFit smartphone application with a description of where and how to use the outdoor environment to be more physically active. Phase 2 (Weeks 11-20) includes the use of the eCoFit smartphone application only. Assessments are to be conducted at baseline, 10-weeks (primary end-point) and 20-weeks (secondary end-point) post-baseline. Primary outcomes are cardio-respiratory fitness and muscular fitness (lower body). Secondary outcomes include physical, behavioral, mental health and quality of life, and social-cognitive outcomes. Discussion: eCoFit is an innovative, multi-component intervention, which integrates smartphone technology, social support and the outdoor physical environment to promote aerobic and resistance training PA among adults at risk of, or diagnosed with T2D. The findings will be used to guide future interventions and to develop and implement effective community-based prevention programs

Digital contact tracing technologies in epidemics: a rapid review

Why is this question important? The global COVID‐19 pandemic highlights the importance of accurate and timely contact tracing. Contact tracing tells people that they may have been near someone with ‐ or showing symptoms of ‐ an infectious disease, allowing them to self‐isolate and helping to stop the spread of infection. Traditionally, contact tracing begins with notification that someone has an infectious disease. They are asked to recall their contacts, going back two to three days before symptom onset. This is time‐consuming and may not always give a complete picture, so digital aids could help contact tracers. Digital contact tracing uses technology to track and trace contacts. Individuals download an app onto their smartphones and record location and symptom information, or their devices might use location‐finding technology, like Bluetooth or GPS (global positioning system). If the user is infected, the technology identifies close contacts and/or secondary infections (people to whom they passed the disease), and informs people whom they have been near. The technology identifies where the infection was passed on and its duration (the context). However, problems may occur where access to technology is limited, in low‐income settings or for elderly people, for example. Also, some people see it as an invasion of privacy and are suspicious of how their data will be used. We wanted to know whether digital contact tracing, compared to manual contact tracing, is effective in reducing the spread of infection, as measured by secondary infections, identifying close contacts, tracing a complete set of contacts, and identifying the context of infection. What did we do? We searched medical databases for studies that assessed digital contact tracing. We preferred studies set during infectious disease outbreaks, which assessed real people in real time, but we included studies in any setting and of any design. To answer our question quickly, we shortened some steps of the Cochrane review process, however, we are confident in our conclusions. What we found We found 12 relevant studies. Six assessed the effectiveness of digital contact tracing on specific groups (cohorts) of people: three during an outbreak (Ebola in Sierra Leone; tuberculosis in Botswana; and whooping cough (pertussis) in USA); and three replicated an outbreak in schools to assess systems for identifying close contacts of participants. The remaining six were modelling studies, which simulated digital contact tracing. Main results Digital contact tracing with self‐isolation probably reduces the number of secondary infections, but not as much as manual contact tracing with self‐isolation (2 modelling studies). Digital contact tracing found more close contacts in two outbreaks than manual (2 studies in USA and Sierra Leone). Devices in non‐outbreak settings can identify more close contacts than self‐reported diaries or surveys. An app may reduce the time to complete a set of close contacts (1 study). Digital systems were faster to use than paper systems for recording new contacts and monitoring known contacts, and possibly less prone to data loss. Problems with system access (2 studies) included patchy network coverage, lack of data, technical problems and higher staff training needs. Contact tracers' personal expenses increased (1 study) due to travel and recharging phone batteries. Devices all appeared to protect diagnosed users from contacts, snoopers and authorities but one app's users were members of public health agencies. Studies recorded stolen hardware (second‐hand mobile phones); reported that paper forms were "often lost", and that digital data were password protected (2 studies) and encrypted (1 study). We found no evidence on contextual information and acceptability. What this means It is unlikely that digital technologies would be the sole method of contact tracing during an outbreak; they would probably be used alongside manual methods. Unfortunately, the technology is largely unproven in real‐world outbreak settings and none of our included studies assessed digital plus manual contact tracing with digital contact tracing alone. Our included studies assessed different technologies and used different methods from each other, so we are uncertain about their evidence. Governments that implement digital contact tracing should ensure that at‐risk populations are not disadvantaged and take privacy concerns into account. This review is up to date to May 2020

Mixed messages: An audit of alignment between study intent and interpretations

The objective of this review is to assess the alignment between study intent and the interpretation of results

Exploring Support Provided by Community Managed Organisations to Address Health Risk Behaviours Associated with Chronic Disease among People with Mental Health Conditions: A Qualitative Study with Organisational Leaders

People living with mental health conditions experience a significantly reduced life expectancy compared to people without, largely linked to health risk behaviours and associated chronic disease. Community managed organisations (CMOs) represent an important setting in which to address health risk behaviours among people with mental health conditions. However, little is known about how these behaviours (smoking, poor nutrition, alcohol consumption, inadequate physical activity, poor sleep: SNAPS) are being addressed in this setting. One-on-one, semi-structured telephone interviews were conducted with a sample of 12 senior staff, representing 12 CMOs in New South Wales, Australia to: (1) explore types of support provided by CMOs to address the SNAPS behaviours of consumers living with a mental health condition; and (2) assess perceived organisational and staff level barriers and facilitators to providing such support. Transcribed interviews were analysed using inductive thematic analysis. This study found there was a range of supports offered by CMOs, and these differed by health risk behaviour. Findings suggest CMOs are well-placed to embed SNAPS supports as a part of their service provision; however, available funding, consistency of supports, workplace policies and culture, collaboration with other available supports, staff training and education, all impacted capacity

Digital contact tracing technologies in epidemics: a rapid review

Why is this question important? The global COVID‐19 pandemic highlights the importance of accurate and timely contact tracing. Contact tracing tells people that they may have been near someone with ‐ or showing symptoms of ‐ an infectious disease, allowing them to self‐isolate and helping to stop the spread of infection. Traditionally, contact tracing begins with notification that someone has an infectious disease. They are asked to recall their contacts, going back two to three days before symptom onset. This is time‐consuming and may not always give a complete picture, so digital aids could help contact tracers. Digital contact tracing uses technology to track and trace contacts. Individuals download an app onto their smartphones and record location and symptom information, or their devices might use location‐finding technology, like Bluetooth or GPS (global positioning system). If the user is infected, the technology identifies close contacts and/or secondary infections (people to whom they passed the disease), and informs people whom they have been near. The technology identifies where the infection was passed on and its duration (the context). However, problems may occur where access to technology is limited, in low‐income settings or for elderly people, for example. Also, some people see it as an invasion of privacy and are suspicious of how their data will be used. We wanted to know whether digital contact tracing, compared to manual contact tracing, is effective in reducing the spread of infection, as measured by secondary infections, identifying close contacts, tracing a complete set of contacts, and identifying the context of infection. What did we do? We searched medical databases for studies that assessed digital contact tracing. We preferred studies set during infectious disease outbreaks, which assessed real people in real time, but we included studies in any setting and of any design. To answer our question quickly, we shortened some steps of the Cochrane review process, however, we are confident in our conclusions. What we found We found 12 relevant studies. Six assessed the effectiveness of digital contact tracing on specific groups (cohorts) of people: three during an outbreak (Ebola in Sierra Leone; tuberculosis in Botswana; and whooping cough (pertussis) in USA); and three replicated an outbreak in schools to assess systems for identifying close contacts of participants. The remaining six were modelling studies, which simulated digital contact tracing. Main results Digital contact tracing with self‐isolation probably reduces the number of secondary infections, but not as much as manual contact tracing with self‐isolation (2 modelling studies). Digital contact tracing found more close contacts in two outbreaks than manual (2 studies in USA and Sierra Leone). Devices in non‐outbreak settings can identify more close contacts than self‐reported diaries or surveys. An app may reduce the time to complete a set of close contacts (1 study). Digital systems were faster to use than paper systems for recording new contacts and monitoring known contacts, and possibly less prone to data loss. Problems with system access (2 studies) included patchy network coverage, lack of data, technical problems and higher staff training needs. Contact tracers' personal expenses increased (1 study) due to travel and recharging phone batteries. Devices all appeared to protect diagnosed users from contacts, snoopers and authorities but one app's users were members of public health agencies. Studies recorded stolen hardware (second‐hand mobile phones); reported that paper forms were "often lost", and that digital data were password protected (2 studies) and encrypted (1 study). We found no evidence on contextual information and acceptability. What this means It is unlikely that digital technologies would be the sole method of contact tracing during an outbreak; they would probably be used alongside manual methods. Unfortunately, the technology is largely unproven in real‐world outbreak settings and none of our included studies assessed digital plus manual contact tracing with digital contact tracing alone. Our included studies assessed different technologies and used different methods from each other, so we are uncertain about their evidence. Governments that implement digital contact tracing should ensure that at‐risk populations are not disadvantaged and take privacy concerns into account. This review is up to date to May 2020

Incubation period of the SARS-CoV-2 virus: Systematic review and pooled analysis from point-source outbreaks

A systematic review will be undertaken to estimate the distribution of the incubation period of COVID-19

Surgical complications and behavioural health risks

This project will systematically assess and describe the evidence relating to the type and magnitude of effects that behavioural health risks have on outcomes relating to elective musculoskeletal surgical interventions