Cohort of haemodialysis patients with COVID-19 in an Irish nephrology centre

Aims COVID-19 has a mortality of 29-41% in haemodialysis (HD) patients, compared to 2% in the general population. In our HD centre, the largest nationally, we report a higher mortality rate of 50%, and aimed to determine underlying factors driving this.  Methods In this retrospective observational study, we collected demographic and clinical data on our HD patients infected with COVID-19.  Results 20/296 HD patients were infected with sudden acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 10 of whom died. These cases represent 20/87 (23%) of COVID-19 positive HD patients nationally and 37% of deaths (10/27). Non-survivors were more likely to present with upper respiratory tract symptoms. Underlying frailty was associated with increased mortality (RR=2, CI 0.57,7.03).  Discussion  Dialysis patients remain susceptible to fatal COVID-19 illness, so efforts need to be made to reduce its spread, including isolation measures, and separate COVID-19 teams </p

Interindividual and intraindividual variability in adolescent sleep patterns across an entire school term: A pilot study

Objectives: This study aimed to investigate sleep patterns in adolescent males over a 12-week period (a 10-week school term and pre and post term holidays). Design: Intensive longitudinal design, with sleep data collected daily via actigraphy for 81 consecutive days. Setting: Five Secondary Schools in Adelaide, South Australia. Participants: Convenience sample of 47 adolescent males aged 14 to 17 years. Measurements: Daily sleep duration, bedtimes, rise times, and sleep efficiency were collected via actigraphy with all (except sleep efficiency) also measured by sleep diary. Mood was measured weekly with Depression Anxiety Stress Scale-21 (DASS-21) and weekly wellbeing with the Satisfaction with Life Scale (SWLS). Age, body mass index, self-reported mood, life satisfaction, and chronotype preference assessed at baseline (pre-term holiday week) were included as covariates. Results: Dynamic Structural Equation Modeling indicated significant but small fixed-effect and random-effect auto-regressions for all sleep variables. Collectively, these findings demonstrate day-to-day fluctuations in sleep patterns, the magnitude of which varied between individuals. Age, morningness, and mood predicted some of the temporal dynamics in sleep over time but other factors (BMI, life satisfaction) were not associated with sleep dynamics. Conclusions: Using intensive longitudinal data, this study demonstrated inter-individual and intra-individual variation in sleep patterns over 81 consecutive days. These findings provide important and novel insights into the nature of adolescent sleep and require further examination in future studies

Sleep genotypes in Indigenous children and relationship with academic performance

: Individual differences in paediatric sleep duration and sleep phase preferences have been clearly identified and could be described as different ‘phenotypes’ of sleepers. Understanding these differences impacts treatment planning. There is a paucity of empirical evidence regarding sleep genotypes in Australian children and even less in Australian Indigenous children. This is important given the health education and equity gap between indigenous and non-indigenous children

Sleep schedules and school performance in indigenous Australian children

Background: Sleep duration and sleep schedule variability have been related to negative health and wellbeing outcomes in children, but little is known about Australian Indigenous children. Methods: Data for children aged 7-9 years came from the Australian Longitudinal Study of Indigenous Children and the National Assessment Program–Literacy and Numeracy (NAPLAN). Latent class analysis determined sleep classes taking into account sleep duration, bedtimes, waketimes, and variability in bedtimes from weekdays to weekends. Regression models tested whether the sleep classes were cross-sectionally associated with grade 3 NAPLAN scores. Latent change score modeling then examined whether the sleep classes predicted changes in NAPLAN performance from grades 3 to 5. Results: Five sleep schedule classes were identified: normative sleep, early risers, long sleep, variable sleep, and short sleep. Overall, long sleepers performed best, with those with reduced sleep (short sleepers and early risers) performing the worse on grammar, numeracy, and writing performance. Latent change score results also showed that long sleepers performed best in spelling and writing and short sleepers and typical sleepers performed the worst over time. Conclusions: In this sample of Australian Indigenous children, short sleep was associated with poorer school performance compared with long sleep, with this performance worsening over time for some performance indicators. Other sleep schedules (eg, early wake times and variable sleep) also had some relationships with school performance. As sleep scheduling is modifiable, this offers opportunity for improvement in sleep and thus performance outcomes for these and potentially all children

Sleep schedules and school performance in Indigenous Australian children

Background: Sleep duration and sleep schedule variability have been related to negative health and well-being outcomes in children, but little is known about Australian Indigenous children. Methods: Data for children aged 7-9 years came from the Australian Longitudinal Study of Indigenous Children and the National Assessment Program–Literacy and Numeracy (NAPLAN). Latent class analysis determined sleep classes taking into account sleep duration, bedtimes, waketimes, and variability in bedtimes from weekdays to weekends. Regression models tested whether the sleep classes were cross-sectionally associated with grade 3 NAPLAN scores. Latent change score modeling then examined whether the sleep classes predicted changes in NAPLAN performance from grades 3 to 5. Results: Five sleep schedule classes were identified: normative sleep, early risers, long sleep, variable sleep, and short sleep. Overall, long sleepers performed best, with those with reduced sleep (short sleepers and early risers) performing the worse on grammar, numeracy, and writing performance. Latent change score results also showed that long sleepers performed best in spelling and writing and short sleepers and typical sleepers performed the worst over time. Conclusions: In this sample of Australian Indigenous children, short sleep was associated with poorer school performance compared with long sleep, with this performance worsening over time for some performance indicators. Other sleep schedules (eg, early wake times and variable sleep) also had some relationships with school performance. As sleep scheduling is modifiable, this offers opportunity for improvement in sleep and thus performance outcomes for these and potentially all children. © 2018 National Sleep Foundation