Audit of a clinical guideline for neonatal hypoglycaemia screening

NHRMC Early Career Fellowship #511481RMT was supported by NHRMC Grant #63300

Model Development for Fat Mass Assessment Using Near-Infrared Reflectance in South African Infants and Young Children Aged 3–24 Months

Undernutrition in infants and young children is a major problem leading to millions of deaths every year. The objective of this study was to provide a new model for body composition assessment using near-infrared reflectance (NIR) to help correctly identify low body fat in infants and young children. Eligibility included infants and young children from 3–24 months of age. Fat mass values were collected from dual-energy x-ray absorptiometry (DXA), deuterium dilution (DD) and skin fold thickness (SFT) measurements, which were then compared to NIR predicted values. Anthropometric measures were also obtained. We developed a model using NIR to predict fat mass and validated it against a multi compartment model. One hundred and sixty-four infants and young children were included. The evaluation of the NIR model against the multi compartment reference method achieved an r value of 0.885, 0.904, and 0.818 for age groups 3–24 months (all subjects), 0–6 months, and 7–24 months, respectively. Compared with conventional methods such as SFT, body mass index and anthropometry, performance was best with NIR. NIR offers an affordable and portable way to measure fat mass in South African infants for growth monitoring in low-middle income settings

Examining service utilisation and impact among consumers of a national mental health stepped care programme in Australia: a protocol using linked administrative data

Introduction Mental well-being is a global public health priority with increasing mental health conditions having substantial burden on individuals, health systems and society. ‘Stepped care’, where services are provided at an intensity to meet the changing needs of the consumer, is the chosen approach to mental health service delivery in primary healthcare in Australia for its efficiencies and patient outcomes; yet limited evidence exists on how the programme is being rolled out and its impact in practice. This protocol outlines a data linkage project to characterise and quantify healthcare service utilisation and impacts among a cohort of consumers of a national mental health stepped care programme in one region of Australia.Methods and analysis Data linkage will be used to establish a retrospective cohort of consumers of mental health stepped care services between 1 July 2020 and 31 December 2021 in one primary healthcare region in Australia (n=approx. 12 710). These data will be linked with records from other healthcare service data sets (eg, hospitalisations, emergency department presentations, community-based state government-delivered mental healthcare, hospital costs). Four areas for analysis will include: (1) characterising the nature of mental health stepped care service use; (2) describing the cohort’s sociodemographic and health characteristics; (3) quantifying broader service utilisation and associated economic costs; and (4) assessing the impact of mental health stepped care service utilisation on health and service outcomes.Ethics and dissemination Approval from the Darling Downs Health Human Research Ethics Committee (HREA/2020/QTDD/65518) has been granted. All data will be non-identifiable, and research findings will be disseminated through peer-reviewed journals, conference presentations and industry meetings

Hierarchische Modellsysteme zur Optimierung der Beatmungstherapie

With the greatest burden of infant undernutrition and morbidity in low and middle income countries (LMICs), there is a need for suitable approaches to monitor infants in a simple, low-cost and effective manner. Anthropometry continues to play a major role in characterising growth and nutritional status.We developed a range of models to aid in identifying neonates at risk of malnutrition. We first adopted a logistic regression approach to screen for a composite neonatal morbidity, low and high body fat (BF%) infants. We then developed linear regression models for the estimation of neonatal fat mass as an assessment of body composition and nutritional status.We fitted logistic regression models combining up to four anthropometric variables to predict composite morbidity and low and high BF% neonates. The greatest area under receiver-operator characteristic curves (AUC with 95% confidence intervals (CI)) for identifying composite morbidity was 0.740 (0.63, 0.85), resulting from the combination of birthweight, length, chest and mid-thigh circumferences. The AUCs (95% CI) for identifying low and high BF% were 0.827 (0.78, 0.88) and 0.834 (0.79, 0.88), respectively. For identifying composite morbidity, BF% as measured via air displacement plethysmography showed strong predictive ability (AUC 0.786 (0.70, 0.88)), while birthweight percentiles had a lower AUC (0.695 (0.57, 0.82)). Birthweight percentiles could also identify low and high BF% neonates with AUCs of 0.792 (0.74, 0.85) and 0.834 (0.79, 0.88). We applied a sex-specific approach to anthropometric estimation of neonatal fat mass, demonstrating the influence of the testing sample size on the final model performance.These models display potential for further development and evaluation in LMICs to detect infants in need of further nutritional management, especially where traditional methods of risk management such as birthweight for gestational age percentiles may be variable or non-existent, or unable to detect appropriately grown, low fat newborns

A Screening strategy for HIV-associated neurocognitive disorders that accurately identifies patients requiring neurological review

Background. Human immunodeficiency virus (HIV)–associated neurocognitive disorders (HAND) are not routinely assessed due to the lack of an adequate screening strategy. We aimed to develop a clinically relevant screening procedure for symptomatic HAND, validated against a gold standard neuropsychological (NP) test battery. Methods. Representative HIV-infected (HIV+) and demographically matched HIV-uninfected (HIV−) participants in an observational study completed a standard evaluation for mood, drug and/or alcohol use, and activities of daily living and a newly designed 20-minute computerized CogState battery that assessed 5 cognitive domains. A subset completed standard NP assessment for 8 cognitive domains. HAND definition on screening and gold standard NP was determined using demographically corrected z scores and the global deficit score (≥ 0.5), applying the Frascati criteria. Participants were blinded to screening results, and the NP examiner was blinded to screening and HIV status. Results. A total of 254 HIV+ participants were enrolled—mean age, 48.9 ± 10.2 years; median nadir CD4, 270 cells/mL; tertiary educated, 54%; and HIV− controls, 72. HIV+ HAND screening prevalence was 30.7% (HIV-associated dementia, 3.2%; mild neurocognitive disorder, 12.6%; and asymptomatic neurocognitive disorder, 15.0%; HIV− group: 13.9%; P = .004). Of the 75 participants who completed the NP battery, the HAND rate in the HIV+ group was 50.9% vs 43.4% by screening (P > .50). HAND screening vs gold standard NP sensitivity was 76% and specificity was 71%. Clinically relevant HIV-associated dementia and mild neurocognitive disorder sensitivity was 100% and specificity was 98% (positive predictive value 0.92). Conclusions. Symptomatic HAND warranting neurological review was accurately predicted using a CogState-based screening procedure.7 page(s