Can flash glucose monitoring improve glucose management for Aboriginal and Torres Strait Islander peoples with type 2 diabetes? A protocol for a randomised controlled trial

Background: Aboriginal and Torres Strait Islander peoples are disproportionately impacted by type 2 diabetes. Continuous glucose monitoring (CGM) technology (such as Abbott Freestyle Libre 2, previously referred to as Flash Glucose Monitoring) offers real-time glucose monitoring that is convenient and easy to use compared to self-monitoring of blood glucose (SMBG). However, this technology’s use is neither widespread nor subsidised for Aboriginal and Torres Strait Islander peoples with type 2 diabetes. Building on existing collaborations with a national network of Aboriginal and Torres Strait Islander communities, this randomised controlled trial aims to assess the effect of CGM compared to SMBG on (i) haemoglobin A1c (HbA1c), (ii) achieving blood glucose targets, (iii) reducing hypoglycaemic episodes and (iv) cost-effective healthcare in an Aboriginal and Torres Strait Islander people health setting. Methods: This is a non-masked, parallel-group, two-arm, individually randomised, controlled trial (ACTRN12621000753853). Aboriginal and Torres Strait Islander adults with type 2 diabetes on injectable therapy and HbA1c ≥ 7.5% (n = 350) will be randomised (1:1) to CGM or SMBG for 6 months. The primary outcome is change in HbA1c level from baseline to 6 months. Secondary outcomes include (i) CGM-derived metrics, (ii) frequency of hypoglycaemic episodes, (iii) health-related quality of life and (iv) incremental cost per quality-adjusted life year gained associated with the CGM compared to SMBG. Clinical trial sites include Aboriginal Community Controlled Organisations, Aboriginal Medical Services, primary care centres and tertiary hospitals across urban, rural, regional and remote Australia. Discussion: The trial will assess the effect of CGM compared to SMBG on HbA1c for Aboriginal and Torres Strait Islander people with type 2 diabetes in Australia. This trial could have long-term benefits in improving diabetes management and providing evidence for funding of CGM in this population. Trial registration: Australian and New Zealand Clinical Trials Registry ACTRN12621000753853. Registered on 15th June 2021

A cognitive framework for object recognition with application to autonomous vehicles

Autonomous vehicles or self-driving cars are capable of sensing the surrounding environment so they can navigate roads without human input. Decisions are constantly made on sensing, mapping and driving policy using machine learning techniques. Deep Learning – massive neural networks that utilize the power of parallel processing – has become a popular choice for addressing the complexities of real time decision making. This method of machine learning has been shown to outperform alternative solutions in multiple domains, and has an architecture that can be adapted to new problems with relative ease. To harness the power of Deep Learning, it is necessary to have large amounts of training data that are representative of all possible situations the system will face. To successfully implement situational awareness in driverless vehicles, it is not possible to exhaust all possible training examples. An alternative method is to apply cognitive approaches to perception, for situations the autonomous vehicles will face. Cognitive approaches to perception work by mimicking the process of human intelligence – thereby permitting a machine to react to situations it has not previously experienced. This paper proposes a novel cognitive approach for object recognition. The proposed cognitive object recognition algorithm, referred to as Recognition by Components, is inspired by the psychological studies pertaining to early childhood development. The algorithm works by breaking down images into a series of primitive forms such as square, triangle, circle or rectangle and memory based aggregation to identify objects. Experimental results suggest that Recognition by Component algorithm performs significantly better than algorithms that require large amounts of training data

The impact of the nursing hours per patient day (NHPPD) staffing method on patient outcomes: A retrospective analysis of patient and staffing data

In March 2002 the Australian Industrial Relations Commission ordered the introduction of a new staffing method – nursing hours per patient day (NHPPD) – for implementation in Western Australia public hospitals. This method used a ‘‘bottom up’’ approach to classify each hospital ward into one of seven categories using characteristics such as patient complexity, intervention levels, the presence of high dependency beds, the emergency/elective patient mix and patient turnover. Once classified, NHPPD were allocated for each ward. The objective of this study was to determine the impact of implementing the NHPPD staffing method on 14 nursing-sensitive outcomes: central nervous system complications, wound infections, pulmonary failure, urinary tract infection, pressure ulcer, pneumonia, deep vein thrombosis, ulcer/gastritis/upper gastrointestinal bleed, sepsis, physiologic/metabolic derangement, shock/cardiac arrest, mortality, failure to rescue and length of stay. The research design was an interrupted time series using retrospective analysis of patient and staffing administrative data from three adult tertiary hospitals in metropolitan Perth over a 4-year period. All patient records (N = 236,454) and nurse staffing records (N = 150,925) from NHPPD wards were included. The study found significant decreases in the rates of nine nursing-sensitive outcomes when examining hospital-level data following implementation of NHPPD; mortality, central nervous system complications, pressure ulcers, deep vein thrombosis, sepsis, ulcer/gastritis/upper gastrointestinal bleed shock/cardiac arrest, pneumonia and average length of stay. At the ward level, significant decreases in the rates of five nursingsensitive outcomes; mortality, shock/cardiac arrest, ulcer/gastritis/upper gastrointestinal bleed, length of stay and urinary tract infections occurred. Conclusions: The findings provide evidence to support the continuation of the NHPPD staffing method. They also add to evidence about the importance of nurse staffing to patient safety; evidence that must influence policy.This study is one of the first to empirically review a specific nurse staffing method, based on an individual assessment of each ward to determine staffing requirements, rather than a ‘‘one-size-fits-all’’ approach

Post-occlusive reactive hyperaemia of skin microvasculature and foot complications in type 2 diabetes

Aims Diabetes-related microvascular disease has been implicated in the development of foot ulceration and amputation. Assessment of microvascular function may be effective in identifying those at risk of diabetic foot complications. We investigated the relationship between active or previous foot complication and post-occlusive reactive hyperaemia (PORH) measured by laser-Doppler fluxmetry (LDF) in people with type 2 diabetes. Methods PORH measures were obtained from the hallux apex in 105 people with type 2 diabetes. Associations were investigated between active or previous foot complication and PORH measures: time to peak (TtPeak) and peak as a percentage of baseline (P%BL). Multinomial logistic regression was used to determine the association of PORH with the likelihood of active foot ulcer or previous foot complication. Results For each second increase in TtPeak, the likelihood of a participant having a history of foot complication is increased by 2% (OR = 1.019, p = 0.01). This association was not reflected in people with an active foot ulcer (OR = 1.003, p = 0.832). P%BL was not found to be significantly different between those with a current or previous foot complication and those without (p = 0.404). Conclusions This investigation in a cohort with type 2 diabetes has demonstrated that longer TtPeak is associated with history of diabetic foot complications

[In Press] The effect of high-intensity interval training versus moderate-intensity continuous training on liver fat : a systematic review and meta-analysis

Aim: This systematic review aimed to determine the effect of aerobic exercise interventions, including high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT), on liver fat in adults. A secondary aim was to investigate the interaction between total weekly exercise volume and exercise-related energy expenditure and change in liver fat. Methods: Relevant databases were searched to December 2020 for randomised trials, comparing HIIT to control, MICT to control, or HIIT to MICT. Studies were excluded if they did not implement ≥2 weeks intervention or assess liver fat using magnetic resonance-based techniques. Weighted mean differences and 95% confidence intervals (CI) were calculated. Regression analyses were undertaken to determine the interaction between weekly exercise volume in minutes and kcal with change in liver fat %. Results: The search returned 28,262 studies of which 19 were included involving 745 participants. Both HIIT and MICT elicited moderate reductions in liver fat % when compared to control (HIIT:-2.85%, 95%CI:-4.86 to -0.84, p=0.005, I2=0%, n=114, low certainty evidence; MICT:-3.14%, 95%CI:-4.45 to -1.82, p<0.001, I2=5.2%, n=533, moderate certainty evidence). There was no difference between HIIT or MICT (-0.34%, 95%CI:-2.20 to 1.52, p=0.721, I2=0%, n=177, moderate certainty evidence). Neither total exercise volume in minutes (β=0.0002, SE=0.0017, Z=0.13, p=0.89) nor exercise-related energy expenditure in kcal (β=0.0001, SE=0.0002, Z=-0.63, p=0.52) were related to changes in liver fat %. Conclusion: HIIT elicits comparable improvements in liver fat to MICT despite often requiring less energy and time commitment. Further studies should be undertaken to assess the relative importance of aerobic exercise prescription variables, such as intensity, on liver fat

Feasibility and acceptability of the use of flash glucose monitoring encountered by Indigenous Australians with type 2 diabetes mellitus: initial experiences from a pilot study

Abstract Background Type 2 diabetes mellitus (T2DM) is highly prevalent within the Indigenous Australian community. Novel glucose monitoring technology offers an accurate approach to glycaemic management, providing real-time information on glucose levels and trends. The acceptability and feasibilility of this technology in Indigenous Australians with T2DM has not been investigated. Objective This feasibility phenomenological study aims to understand the experiences of Indigenous Australians with T2DM using flash glucose monitoring (FGM). Methods Indigenous Australians with T2DM receiving injectable therapy (n = 8) who used FGM (Abbott Freestyle Libre) for 6-months, as part of a clinical trial, participated in semi-structured interviews. Thematic analysis of the interviews was performed using NVivo12 Plus qualitative data analysis software (QSR International). Results Six major themes emerged: 1) FGM was highly acceptable to the individual; 2) FGM’s convenience was its biggest benefit; 3) data from FGM was a tool to modify lifestyle choices; 4) FGM needed to be complemented with health professional support; 5) FGM can be a tool to engage communities in diabetes management; and 6) cost of the device is a barrier to future use. Conclusions Indigenous Australians with T2DM had positive experiences with FGM. This study highlights future steps to ensure likelihood of FGM is acceptable and effective within the wider Indigenous Australian community

Data schemas for multiple hazards, exposure and vulnerability

Purpose – Using risk-related data often require a significant amount of upfront work to collect, extract and transform data. In addition, the lack of a consistent data structure hinders the development of tools that can be used with more than one set of data. The purpose of this paper is to report on an effort to solve these problems through the development of extensible, internally consistent schemas for risk-related data. Design/methodology/approach – The consortia coordinated their efforts so the hazard, exposure and vulnerability schemas are compatible. Hazard data can be provided as either event footprints or stochastic catalogs. Exposure classes include buildings, infrastructure, agriculture, livestock, forestry and socio-economic data. The vulnerability component includes fragility and vulnerability functions and indicators for physical and social vulnerability. The schemas also provide the ability to define uncertainties and allow the scoring of vulnerability data for relevance and quality. Findings – As a proof of concept, the schemas were populated with data for Tanzania and with exposure data for several other countries. Research limitations/implications – The data schema and data exploration tool are open source and, if widely accepted, could become widely used by practitioners. Practical implications – A single set of hazard, exposure and vulnerability schemas will not fit all purposes. Tools will be needed to transform the data into other formats. Originality/value – This paper describes extensible, internally consistent, multi-hazard, exposure and vulnerability schemas that can be used to store disaster risk-related data and a data exploration tool that promotes data discovery and use