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Obesity increases the risk of morbidity and mortality. A major driver has been the increased availability of ultra-processed food (UPF), now the main UK dietary energy source. The UK Eatwell Guide (EWG) provides public guidance for a healthy balanced diet but offers no UPF guidance. Whether a healthy diet can largely consist of UPFs is unclear. No study has assessed whether the health impact of adhering to dietary guidelines depends on food processing. Furthermore, our study will assess the impact of a 6-month behavioural support programme aimed at reducing UPF intake in people with overweight/obesity and high UPF intakes.
UPDATE is a 2x2 cross-over randomised controlled trial with a 6-month behavioural intervention. Fifty-five adults aged ≥18, with overweight/obesity (≥25 to 2), and ≥50% of habitual energy intake from UPFs will receive an 8-week UPF diet and an 8-week minimally processed food (MPF) diet delivered to their home, both following EWG recommendations, in a random order, with a 4-week washout period. All food/drink will be provided. Participants will then receive 6 months of behavioural support to reduce UPF intake. The primary outcome is the difference in weight change between UPF and MPF diets from baseline to week 8. Secondary outcomes include changes in diet, waist circumference, body composition, heart rate, blood pressure, cardiometabolic risk factors, appetite regulation, sleep quality, physical activity levels, physical function/strength, well-being and aspects of behaviour change/eating behaviour at 8 weeks between UPF/MPF diets, and at 6-month follow-up. Quantitative assessment of changes in brain MRI functional resting-state connectivity between UPF/MPF diets, and qualitative analysis of the behavioural intervention for feasibility and acceptability will be undertaken.
Sheffield Research Ethics Committee approved the trial (22/YH/0281). Peer-reviewed journals, conferences, PhD thesis and lay media will report results.
To develop and internally validate risk prediction models for subsequent clinical deterioration, unplanned ICU admission and death among ward patients following medical emergency team (MET) review.
A retrospective cohort study of 1500 patients who remained on a general ward following MET review at an Australian quaternary hospital.
Logistic regression was used to model (1) subsequent MET review within 48 h, (2) unplanned ICU admission within 48 h and (3) hospital mortality. Models included demographic, clinical and illness severity variables. Model performance was evaluated using discrimination and calibration with optimism-corrected bootstrapped estimates. Findings are reported using the TRIPOD guideline for multivariable prediction models for prognosis or diagnosis. There was no patient or public involvement in the development and conduct of this study.
Within 48 h of index MET review, 8.3% (n = 125) of patients had a subsequent MET review, 7.2% (n = 108) had an unplanned ICU admission and in-hospital mortality was 16% (n = 240). From clinically preselected predictors, models retained age, sex, comorbidity, resuscitation limitation, acuity-dependency profile, MET activation triggers and whether the patient was within 24 h of hospital admission, ICU discharge or surgery. Models for subsequent MET review, unplanned ICU admission, and death had adequate accuracy in development and bootstrapped validation samples.
Patients requiring MET review demonstrate complex clinical characteristics and the majority remain on the ward after review for deterioration. A risk score could be used to identify patients at risk of poor outcomes after MET review and support general ward clinical decision-making.
Our risk calculator estimates risk for patient outcomes following MET review using clinical data available at the bedside. Future validation and implementation could support evidence-informed team communication and patient placement decisions.
Hospital-acquired pressure injuries (HAPIs) pose significant challenges in healthcare and cause increased patient suffering, longer hospital stays, and higher healthcare costs. Paediatric patients face unique risks, but evidence remains scarce. This study aimed to identify and describe HAPI admission incidence and severity predictors in a large Australian children's hospital.
This retrospective cohort study investigated all paediatric patients between January 2020 and December 2021 using a census approach. Demographic and clinical data including HAPI-related data were accessed from the incident monitoring and hospital administration databases. The incidence rate (per 1000 patient admissions) was calculated based on all admissions. Predictors of HAPI severity were identified using multivariable multinomial logistic regression. The study adhered to the STROBE guidelines for retrospective cohort studies.
The HAPI incidence rate was 6.96 per 1000 patient admissions. Of the age groups, neonates had the highest HAPI incidence (15.5 per 1000 admissions). Critically ill children had the highest rate for admission location (12.8 per 1000 patient admissions). Most reported cases were stage I (64.2%). Age was associated with injury severity, with older paediatric patients more likely to develop higher-stage HAPIs. Additionally, Aboriginal and/or Torres Strait Islander patients had a higher HAPI severity risk.
HAPI injuries in paediatric patients are unacceptably high. Prevention should be prioritized, and the quality of care improved in Australia and beyond. Further research is needed to develop targeted prevention strategies for these vulnerable populations.
This research emphasizes the need for standardized reporting, culturally sensitive care and tailored prevention strategies.
The research has the potential to influence healthcare policies and practices, ultimately enhancing the quality of patient care.
STROBE guidelines.
There was no patient or public contribution to the conduct of this study.
Blunt chest trauma (BCT) is characterised by forceful and non-penetrative impact to the chest region. Increased access to the internet has led to online healthcare resources becoming used by the public to educate themselves about medical conditions. This study aimed to determine whether online resources for BCT are at an appropriate readability level and visual appearance for the public.
We undertook a (1) a narrative overview assessment of the website; (2) a visual assessment of the identified website material content using an adapted framework of predetermined key criteria based on the Centers for Medicare and Medicaid Services toolkit and (3) a readability assessment using five readability scores and the Flesch reading ease score using Readable software.
Using a range of key search terms, we searched Google, Bing and Yahoo websites on 9 October 2023 for online resources about BCT.
We identified and assessed 85 websites. The median visual assessment score for the identified websites was 22, with a range of –14 to 37. The median readability score generated was 9 (14–15 years), with a range of 4.9–15.8. There was a significant association between the visual assessment and readability scores with a tendency for websites with lower readability scores having higher scores for the visual assessment (Spearman’s r=–0.485; p
Although the readability levels and visual appearance were acceptable for the public for many websites, many of the resources had much higher readability scores than the recommended level (8–10) and visually were poor.
Better use of images would improve the appearance of websites further. Less medical terminology and shorter word and sentence length would also allow the public to comprehend the contained information more easily.
Millions of people survive injuries to the central or peripheral nervous system for which neurorehabilitation is required. In addition to the physical and cognitive impairments, many neurorehabilitation patients experience pain, often not widely recognised and inadequately treated. This is particularly true for multiple sclerosis (MS) patients, for whom pain is one of the most common symptoms. In clinical practice, pain assessment is usually conducted based on a subjective estimate. This approach can lead to inaccurate evaluations due to the influence of numerous factors, including emotional or cognitive aspects. To date, no objective and simple to use clinical methods allow objective quantification of pain and the diagnostic differentiation between the two main types of pain (nociceptive vs neuropathic). Wearable technologies and artificial intelligence (AI) have the potential to bridge this gap by continuously monitoring patients’ health parameters and extracting meaningful information from them. Therefore, we propose to develop a new automatic AI-powered tool to assess pain and its characteristics during neurorehabilitation treatments using physiological signals collected by wearable sensors.
We aim to recruit 15 participants suffering from MS undergoing physiotherapy treatment. During the study, participants will wear a wristband for three consecutive days and be monitored before and after their physiotherapy sessions. Measurement of traditionally used pain assessment questionnaires and scales (ie, painDETECT, Doleur Neuropathique 4 Questions, EuroQoL-5-dimension-3-level) and physiological signals (photoplethysmography, electrodermal activity, skin temperature, accelerometer data) will be collected. Relevant parameters from physiological signals will be identified, and AI algorithms will be used to develop automatic classification methods.
The study has been approved by the local Ethical Committee (285-2022-SPER-AUSLBO). Participants are required to provide written informed consent. The results will be disseminated through contributions to international conferences and scientific journals, and they will also be included in a doctoral dissertation.
Little research exists on how risk scores are used in counselling. We examined (a) how Breast Cancer Risk Assessment Tool (BCRAT) scores are presented during counselling; (b) how women react and (c) discuss them afterwards.
Consultations were video-recorded and participants were interviewed after the consultation as part of the NRG Oncology/National Surgical Adjuvant Breast and Bowel Project Decision-Making Project 1 (NSABP DMP-1).
Two NSABP DMP-1 breast cancer care centres in the USA: one large comprehensive cancer centre serving a high-risk population and an academic safety-net medical centre in an urban setting.
Thirty women evaluated for breast cancer risk and their counselling providers were included.
Participants who were identified as at increased risk of breast cancer were recruited to participate in qualitative study with a video-recorded consultation and subsequent semi-structured interview that included giving feedback and input after viewing their own consultation. Consultation videos were summarised jointly and inductively as a team.tThe interview material was searched deductively for text segments that contained the inductively derived themes related to risk assessment. Subgroup analysis according to demographic variables such as age and Gail score were conducted, investigating reactions to risk scores and contrasting and comparing them with the pertinent video analysis data. From this, four descriptive categories of reactions to risk scores emerged. The descriptive categories were clearly defined after 19 interviews; all 30 interviews fit principally into one of the four descriptive categories.
Risk scores were individualised and given meaning by providers through: (a) presenting thresholds, (b) making comparisons and (c) emphasising or minimising the calculated risk. The risk score information elicited little reaction from participants during consultations, though some added to, agreed with or qualified the provider’s information. During interviews, participants reacted to the numbers in four primary ways: (a) engaging easily with numbers; (b) expressing greater anxiety after discussing the risk score; (c) accepting the risk score and (d) not talking about the risk score.
Our study highlights the necessity that patients’ experiences must be understood and put into relation to risk assessment information to become a meaningful treatment decision-making tool, for instance by categorising patients’ information engagement into types.
FreshRSS 