Statistical Validation of An Automated Method for Calculating Time Domain Heart Rate Variability on The QT Dataset.

Heart rate variability measures calculated from electrocardiography recordings reflect social competence. Clinical assessments of social skills have found that reduced heart rate variability is related to differences in the development of social skills in children and increase the risk of mental disorders. Limited by widespread manual signal processing and R-peak detection in current clinical assessments, most literature reports only short-term baseline studies, with fewer studies reporting social interaction settings with prolonged recording. There is an urgent need for an automated physiological signal processing toolbox to detect R-peaks and perform heart rate variability measurements in social settings. This paper proposes a modified automated Neurokit2 toolbox with signal processing procedures similar to the MindWare software that requires manual inspection of R-peak locations. We calculate time domain heart rate variability metrics from the publicly available QT database by PhysioNet collected at resting states and under stress tests, mimicking social interaction stress scenarios. Statistical analysis conveys that heart rate variability metrics calculation applying both signal processing approaches using the Neurokit2 toolbox are statistically equivalent in comparison to the hand-labelled R-peaks from the QT database (n= 10 in the normal sinus rhythm group, and n= 6 in the ST Change group). Such validation results are crucial for the adoption of automated toolboxes for heart rate variability measures in social interaction assessments, where more movement and mood changes of participants are expected.Clinical Relevance- This contributes to the body of evidence of the reliability of the Neurokit2 toolbox for automatic cleaning of prolonged cardiac electrophysiological signals and calculation of heart rate variability in time-domain characterization in social interaction stress assessment.

Burden of paediatric hospitalisations to the health care system, child and family: a systematic review of Australian studies (1990-2022).

Background: Paediatric hospitalisations represent a significant cost to the health system and cause significant burden to children and their families. Understanding trends in hospitalisation costs can assist with health planning and support strategies across stakeholders. The objective of this systematic review is to examine the trends in costs and burden of paediatric hospitalisations in Australia to help inform policy and promote the well-being of children and their families. Methods: Electronic data sources (Embase, Medline, Web of Science, PSYCH-Info, CINAHL and Scopus) were searched from 1990 until December 2022. Any quantitative or qualitative studies conducted in Australian tertiary hospitals were included in the review. Eligible studies were those that included paediatric (<18 years) hospitalisations and reported on economic and/or non-economic costs for the child, family unit and/or health system. Study quality and risk of bias for each study were assessed with the Joanna Briggs Critical Appraisal Tools. We present a summary of the findings of the hospitalisation burden across major diagnostic admission categories and for the child and family unit. The systematic review was registered with Prospero (ID: CRD42021276202). Findings: The review summarises a total of 88 studies published between 1990 and December 2022. Overall, the studies identified that paediatric hospitalisations incur significant financial costs, which have not shown significant reductions over time. In-patient direct hospital costs varied depending on the type of treatment and diagnostic condition. The costs per-case were found to range from just below AUD$2000 to AUD$20,000 or more. The financial burden on the family unit included loss of productivity, transport and travel costs. Some studies reported estimates of these costs upward of AUD$500 per day. Studies evaluating 'hospital in the home' options identified significant benefits in reducing hospitalisations and costs without compromising care. Interpretation: Increasing focus on alternative models of care may help alleviate the significant costs associated with paediatric hospitalisation. Funding: This research was supported by Hospitals United for Sick Kids (formerly Curing Homesickness).