bluuebunny/crossref_metadata_2025_split huggingface dataset:
O027 Integrating digital behavioural therapy for insomnia into primary care: a feasibility mixed-methods study
Authors: Rahimi M , Gordon C , Cheung J , Menczel Schrire Z , Aji M , Salomon H , Doggett I , Glozier N , Wong K , Marshall N , Bartlett D , Grunstein R 
Published: December 2024

Abstract

Introduction
Digital cognitive behavioural therapy (dCBT) programs have been developed for insomnia to increase access to treatment. However, these digital programs are not widely used in primary care settings. This study evaluated whether a digital insomnia therapy (SleepFix mobile application) could be integrated into routine primary care for patients suffering from insomnia.

Method
A single-arm feasibility trial of SleepFix was conducted involving a digital behavioural therapy for insomnia patients. SleepFix delivered sleep restriction therapy over six weeks to improve sleep efficiency. Health care professionals (HCPs) including general practitioners, pharmacists, and nurses participated in prescribing SleepFix to appropriate insomnia patients (i.e. having at least one item from a 3-item DSM-5 checklist). The main outcome measured was the number of SleepFix downloads. Interviews explored the responses of HCPs and patients on using digital insomnia treatments.

Results
30 HCPs (21 GPs, 6 pharmacists and 3 nurses) and 105 patients participated in the study between November 2021 and March 2022. 14 HCPs prescribed the digital therapy at least once and 50 patients (47.6%) downloaded and used SleepFix. Post-study interviews found HCPs were willing to incorporate digital sleep programs into practice, and patients found SleepFix acceptable. Significant improvements in insomnia, mood, and sleep quality were seen after 6 weeks of using SleepFix.

Discussion
This trial demonstrated the successful integration of a digital insomnia therapy program into primary care, offering a potential model for prescribing digital sleep interventions.
O029 The Impact of Adherence to Specific Components of CBT for Insomnia on Treatment Outcomes
Authors: Drummond S , Bei B 
Published: December 2024

Abstract

Introduction
CBT-I requires significant behavioural change. A recent systematic review found there are surprisingly few associations between adherence to that behaviour change and outcomes. Prior studies examined adherence over the entire course of treatment, however, the role of adherence may change throughout therapy. We examined the effect of adherence to Sleep Restriction (SR) and Stimulus Control (SC) using the recently proposed two-stage Build-Maintain Model of CBT-I.

Methods
83 participants underwent 7 weeks of therapist-led CBT-I. 78 initiated SR (age: 48.0±14.3, 57.7%F). Treatment was divided into “Build” (initial phase of SR, building sleep debt) and “Maintain” (starting the first week sleep opportunity increased) stages of therapy. Analyses examined the impact of adherence to SR (deviation from bed/wake times, naps) and SC (wake time-in-bed during daytime, overnight, and after final awakening) and stage of treatment on diary-based sleep efficiency (SE) and Insomnia Severity Index (ISI).

Results
Adherence to morning SC predicted both greater SE (regardless of the stage) and lower ISI (specifically during Maintain stage). Fewer average minutes napping predicted lower ISI scores, regardless of stage.

Discussion
Adherence to morning SC (i.e., getting out of bed right away after final awakening) and adherence to the no-nap rule of SR were associated with better CBT-I treatment outcomes. Surprisingly, adherence to neither the prescribed bed time nor wake time in SR were associated with treatment outcomes. While adherence to some aspects of CBT-I appear related to outcomes, more work needs to be conducted to determine the measure(s) of adherence most predictive of treatment outcomes.
O032 Is a fear of death keeping you awake at night? Examining the relationship between death anxiety and insomnia
Authors: Menzies R , Brown J , Turner M , Cunnington D , Burge M , Dunican I , Meaklim H 
Published: December 2024

Abstract

Introduction
The fear of death (death anxiety) is a risk factor for psychopathology, including anxiety and depressive disorders. There is little research on the role of death anxiety in sleep disorders like insomnia. We examined the relationship between death anxiety and insomnia and investigated whether distressing dreams/nightmares play a mediating role in this relationship.

Methods
The study consisted of 515 adult participants (360 females; M age=44.15 years) who completed an online survey via REDCAP. The survey assessed insomnia symptoms (ISI), death anxiety (DABBS), and nightmare severity (DDNSI). Correlations and hierarchical regression analyses were conducted to explore the relationship between insomnia symptoms and death anxiety, with an additional mediation analysis (Hayes PROCESS macro) examining the role of nightmare severity.

Results
Death anxiety was positively correlated with insomnia (r=.27; p&lt;.001). In the hierarchical regression analysis, death anxiety remained a significant predictor of insomnia, even after controlling for general anxiety (p=.037). Notably, nightmare severity mediated the relationship between death anxiety and insomnia, with higher levels of death anxiety associated with more severe nightmares and, subsequently, more severe insomnia symptoms (all p’s&lt;.001). As the direct effect of death anxiety on insomnia remained significant (p&lt;.001) in the mediation model, our results suggest that nightmares are a partial mediator of the relationship.

Discussion
Death anxiety is associated with insomnia symptoms, with nightmares partially mediating the relationship. Fears of death may, therefore, play a greater role in insomnia symptomatology than previously thought. Targeting death anxiety in insomnia treatment may be an important avenue for future research.
O034 Development and Evaluation of Two Non-Invasive Approaches for Estimating Breath-by-Breath Ventilatory Drive in Obstructive Sleep Apnea Patients
Authors: Zhang J , Mann D , Leppänen T , Sands S , Terrill P 
Published: December 2024

Abstract

Introduction
Estimation of breath-by-breath ventilatory drive is an important step in quantifying key obstructive sleep apnea (OSA) endotypes. However, the gold-standard for measuring ventilatory drive requires invasive instrumentation. Here, we extend two published methods for estimating breath-by-breath ventilatory drive non-invasively from polysomnography.

Methods
We retrospectively analysed sleep studies of 33 OSA patients (apnea-hypopnea index&gt;5) who underwent a clinical in-lab polysomnography with the addition of intraoesophageal diaphragmatic electromyography (Edi). The ventilatory drive was estimated on a breath-by-breath basis using two independent methods: (a) a flow-shape-based machine learning approach (Flow-Drive method), Mann et al 2019 ERJ; and (b) a chemoreflex model-based approach (Loop-gain method), Terrill et al 2014 ERJ. The Spearman’s rank correlation (ρ) between the two estimated breath-by-breath ventilatory drive signals and Edi (gold-standard) was calculated: (i) for 7-min overlapping windows throughout the night for each individual; and (ii) an overnight ensemble average of obstructive respiratory events at onset and termination periods (three breaths before and after event onset and termination respectively).

Results
The Spearman’s ρ in the 7-minute window was similar between the Flow-Drive and Loop-gain methods, and Edi [0.40(0.10)vs.0.27(0.13), mean(SD)]. Flow-Drive and Loop-gain methods both showed similar Spearman’s ρ with Edi at event onset [0.69(0.34)vs.0.69(0.25) respectively]. At event termination, the Loop-gain method [0.85(0.13)] was more strongly correlated with Edi than the Flow-Drive method [0.78(0.30)].

Conclusions
These promising results set a foundation for integrating the advantages of a machine learning approach and a physiological model-based approach in a unified method to improve the non-invasive estimation of breath-by-breath ventilatory drive.
O035 Refining the desaturation area-based parameters by investigating different baseline methods
Authors: de Chazal P , He S , Cistulli P 
Published: December 2024

Abstract

Introduction
Repetitive hypoxia serves as the principal mechanistic bridge between Obstructive Sleep Apnoea and cardiovascular disease (CVD). Desaturation area-based parameters, like Hypoxic Burden (HB) and the Respiratory Event Desaturation Transient Area (REDTA), are promising metrics for predicting CVD mortality. These metrics are not without limitations. HB calculation is complex and noise sensitive, while REDTA may be overly simplistic. We investigated six area-based methods, each with a different choice of sampling window and baseline.

Methods
The oximetry signals from the Sleep Heart Health Study (SHHS) with CVD mortality outcomes and covariate information was used. The HB method was implemented and denoted as ARE. It uses a record-specific sampling window and event-specific baseline. We extended the experiment to include two additional baseline methods: a record-specific baseline (ARR) and a fixed baseline (ARF). Similarly, REDTA which uses a fixed sampling window and baseline (AFF), was extended to an event-specific baseline (AFE) and a record-specific baseline (AFR). Six desaturation area-based methods were performed in this study. The performance of each parameter in predicting CVD mortality was assessed using an adjusted Cox proportional hazard ratio(HR) analysis.

Results
ARR and AFR outperformed other methods The HRs were ARR:1.79 (95% CI: 1.00-3.19, p&lt;0.05), and AFR:1.64 (95% CI: 1.16-2.32, p&lt;0.01).

Discussion
Computational complexity was also considered. AFR was easier to calculate than ARR as it used a fixed sampling window. We believe AFR provides a step towards a novel parameter with easy calculation providing early risk stratification in cardiovascular patients.
O039 Agreement between MotionWatch8 and Polysomnography sleep outcomes in Menopausal Women
Authors: Li X , Chow C , Halaki M 
Published: December 2024

Abstract

Introduction
Polysomnography (PSG) is the gold standard for sleep measurement but is costly and can disrupt sleep. Actigraphy offers a non-invasive alternative for longer-term monitoring. This study aims to validate the MotionWatch8 device against PSG for sleep outcomes among menopausal women.

Methods
Sixteen healthy women aged 45-65 years with menopausal symptoms underwent four in-lab overnight PSG studies while wearing the MotionWatch8. Sleep parameters including time in bed (TIB), total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO) were measured. Agreements between MotionWatch8 and PSG was assessed using Bland-Altman plots.

Results
MotionWatch8 tended to overestimate: TIB by 1.2 minutes with limits of agreement (LOA): 6.7 to 9.2 minutes; SE by 3.5%, LOA: -11.7% and 18.7%, and significant proportional error especially for nights with SE&lt;92%; and TST by 18.6 minutes, LOA: -56.8 to 94.0 minutes. MotionWatch8 underestimated: SOL by 11.2 minutes, LOA: -53.6 to 31.3 minutes, and a significant proportional error especially for a longer sleep latency (SOL&gt;20minutes); and WASO by 7.4 minutes, LOA: 40.5 to 25.7 minutes.

Discussion
The results indicate that the MotionWatch8 provides acceptable agreement and LOA with PSG for TIB, TST and WASO; and for SOL and SE for people without significant sleep problem. The device is not recommended to be used for people with longer sleep latency and poorer sleep efficiency. While the MotionWatch is a feasible tool for large-scale sleep studies in menopausal women, it should be used with caution for these specific situations.
O041 Prevalence, patterns and clinical associations of sleep disordered breathing in children with neuromuscular disorders
Authors: Withers A , Lam J , Pettigrew G , Downs J , Spano J , Deegan S , Filmer K , Gauld L , Milla C , Buu M , Wilson A 
Published: December 2024

Abstract

Objectives
to determine prevalence, patterns and clinical associations of sleep disordered breathing in a cohort of children with neuromuscular disorders.

Methods
children from three sites had a laboratory polysomnogram and clinical data collection. Sleep disordered breathing (SDB) was defined as the presence of obstructive sleep apnoea (OSA), hypoventilation and/or central sleep apnoea (CSA).

Results
64 children aged 6.0-16.7 years (median 11.5) were included, 72% were male and diagnoses were Duchenne Muscular Dystrophy (DMD) (40%), spinal muscular atrophy (SMA) (28%), congenital muscular dystrophy (CMD) (13%) and congenital myopathy (CM) (19%). Scoliosis was present in 50%, 51% could ambulate and median BMI z-score was -0.23. Of the 13 (20%) who used non-invasive ventilation (NIV), 6 (46%) had SMA and 10 (77%) used NIV during the entire polysomnogram. Sleep disordered breathing was present in 48%, OSA in 31%, CSA in 14%, hypoventilation in 16% and mixed SDB in 23%. SDB was present in 50% of children with DMD, SMA and CM, most often OSA in DMD (70%) and SMA (78%). Hypoventilation was most common in children with CM (83%) and CMD (100%). SDB and OSA were associated with older age and OSA with inability to ambulate (OR 4.45). Hypoventilation was significantly more common in CM, CMD and those with lower BMI z-scores.

Conclusions
The prevalence of SDB was high and likely under-estimated due to use of NIV, particularly in those with SMA. The findings reflect the heterogeneity of the cohort and suggest individual risk factors for each type of SDB.
O043 Performance of a machine-learning based automated oximetry algorithm for detection of sleep apnoea in children
Authors: Kevat A , Hartnett C , Suresh S , Terrill P , Iyer K 
Published: December 2024

Abstract

Background
In-laboratory polysomnography (PSG) remains the gold-standard method for the detection of significant paediatric sleep-disordered breathing, although it is resource-intensive. We therefore trained, using data from 2380 diagnostic PSGs, a support vector regression (SVR) algorithm to predict apnoea hypopnea index (AHI) using oximetry data alone, for potential use as a pre-PSG screening/triage tool. This study aimed to test the algorithm’s performance in detecting potentially significant sleep apnoea, defined as AHI ≥5.

Methods
We extracted oximetry data (oxygen saturation and heart rate, down-sampled to 1Hz) from 300 PSGs performed in 2018 in a single Australian paediatric centre. De-identified demographic and clinical information was extracted from medical records. Oximetry data was then evaluated by the SVR algorithm, which utilised 19 heart rate and oxygen saturation-derived features to predict AHI. The SVR-predicted AHI was compared to gold-standard AHI determined by original PSG, with AHIs undergoing binary classification into AHI &lt;5 or ≥5.

Results
Of 297 patients (median age 7.4 years), 26% had a significant neuromuscular, neurologic or genetic disorder diagnosed, 15% had undergone previous adenoidectomy+/-tonsillectomy and 14% were obese. On PSG 102 (34%) had AHI ≥5. Sensitivity and specificity of the SVR algorithm for detecting this was 0.75 and 0.76 respectively; positive predictive value was 0.62 and negative predictive value was 0.85.

Conclusion
This demonstration of a machine learning algorithm classifying oximetry traces from a real-world cohort of a diverse group of children undergoing evaluation for possible sleep apnoea demonstrates the automated tool may be useful in helping with PSG waitlist prioritisation.
O048 Ultrasound evaluation of the pterygomandibular raphe in Obstructive Sleep Apnoea
Authors: Necati E , Jugé L , Bilston L , Brown E 
Published: December 2024

Abstract

Introduction
The pterygomandibular raphe (PMR) is an aponeurotic junction in the lateral upper airway soft tissue that may be an anatomical marker to predict mandibular advancement splint (MAS) treatment success (Brown et al. 2021). We evaluated the feasibility of a novel ultrasound (US) protocol to assess these lateral soft tissues, particularly PMR.

Methods
31 participants (n=19(61.3%) female) with and without obstructive sleep apnoea (OSA) underwent lateral upper airway ultrasound. Inclusion criteria were age 18-75 years and previous polysomnogram. Eight participants also underwent MRI. The anatomical landmarks of PMR were measured.

Results
Participants were middle aged (56.5±15.9 years), overweight or obese (BMI 29.4±6.4 kg/m2) and had moderate OSA (mean AHI 24.4±21.7 events/hour). PMR was detected in all subjects. Submandibular gland depth (4.8±1.2 mm), US-PMR depth (18.1±3.0 mm) and US-PMR width (2.4±0.4 mm) were measured (n=31), and tonsil depth was recorded (n=24, 19.5±3.8 mm). US-PMR width measurements of OSA (n=24, 2.5±0.3 mm) and non-OSA (n=7, 2.5±0.6 mm) subjects were not different (p&gt;0.05). MRI-PMR width values were similar (OSA 3.1±0.9 vs. non-OSA 2.5±1.5 mm, p&gt;0.05). The width of MRI-PMR (2.7±1.2 mm) compared to and US-PMR (2.8±0.5 mm) was not significantly different (p&gt;0.05).

Discussion
This research highlights the potential of US as a useful tool to study lateral upper airway tissues, particularly the PMR. We plan to correlate these findings in a larger number of participants who have undergone both MRI and US to demonstrate the sensitivity, specificity and clinical utility of US.
O053 Relationship between cardiovascular risk and pulse wave amplitude characteristics in a sleep clinic cohort
Authors: Stewart G , Tong B , Flood J , Cistulli P 
Published: December 2024

Abstract

Introduction
Novel pulse oximetry-derived measures of autonomic vasoreactivity have recently been developed as a biomarker of cardiovascular outcomes in patients with obstructive sleep apnoea (OSA). It is currently unclear if these measures relate to general cardiovascular risk in an unselected population undergoing polysomnography.

Methods
This study examined pulse wave amplitude characteristics (from photoplethysmography) in 547 individuals who underwent a diagnostic in-laboratory polysomnogram and had sufficient clinical data to calculate a modified Framingham cardiovascular risk score. Individuals were categorised as either having an established cardiovascular disease (CVDest, n=47) or a calculated Framingham 10-year CVD risk score that was low (CVDlow-risk, n=177) or intermediate-to-high (CVDelevated-risk, n=323). Standard polysomnography variables and the pulse-wave amplitude drops index (defined by the number of drops in pulse wave amplitude of &gt;30% per hour of sleep, PWADIn) were derived and compared between the 3 groups.

Results
The PWADIn was significantly different between each of the CVD risk groups (CVDest: 37.8±19.1; CVDelevated-risk: 42.2±22.3; CVDlow-risk: 50.6±19.3, p&lt;0.01). Similar findings were observed for PWADIn during REM and non-REM sleep, and group differences in PWADIn remained significant (p&lt;0.01) after adjusting for apnoea-hypopnea index, age, sex, and body mass index.

Conclusions
These data indicate that pulse oximetry-derived measures of autonomic vasoreactivity may provide a marker of cardiovascular disease risk in a general sleep clinic population undergoing polysomnography. The mechanistic link between recurrent nocturnal pulse wave amplitude drops and cardiovascular disease risk requires further study.
O056 Workplace fatigue in the New Zealand healthcare workforce: A snapshot survey
Authors: O’Keeffe K , Frampton C 
Published: December 2024

Abstract

Introduction
A growing body of research has highlighted that workplace fatigue is associated with decreased patient safety, increased healthcare costs and adverse health and safety consequences for healthcare workers.

Methods
All workers in the New Zealand District Health Board (DHB) workforce were invited to complete an anonymous online questionnaire evaluating personal and work demographics, work patterns in the last week, sleep, life outside work, and two fatigue-related outcomes. Workers were categorised into nine groups: Senior Medical Officer/Senior Dental Officer, Resident Medical Officer (RMO), Nurse, Midwife, Allied and Scientific, Care and Support, Corporate, Administration and Clerical, and Other.

Results
Fatigue-related outcomes were commonly experienced by the DHB workforce. The highest proportion of workers reporting making a fatigue-related error in the last 6 months was observed among RMOs (82.5%), and the highest proportion of workers experiencing feeling sleepy at the wheel in the last 12 months was observed among midwives (70.5%). The odds of reporting a fatigue-related error were generally higher in workers who had a higher frequency of shift extensions and fewer days when they could take breaks within their shifts. The odds of reporting drowsy driving were generally increased in workers who were younger, had fewer days when they could take breaks within their shifts, got fewer hours of sleep, worked more night shifts and had regular additional work responsibilities outside the home.

Discussion
Given the high safety risk, it is recommended that future work focus on the development of a more comprehensive approach to managing fatigue among healthcare workers.
O059 Examining the efficacy of the “SleepSync” app in improving sleep and performance in healthcare shift workers
Authors: Varma P , Postnova S , Knock S , Howard M , Rajaratnam S , Sletten T 
Published: December 2024

Abstract

Introduction
Two-thirds of shift workers experience inadequate sleep. Disruption of sleep and circadian rhythms is linked to decrements in performance and negative consequences for overall health. This study examined the efficacy of SleepSync in improving sleep in and performance in shift working nurses. SleepSync is a personalised sleep-wake management app, codesigned with nurses that delivers circadian-based optimal times for sleep using biomathematical models of sleep-wake and alertness regulation (the Model of Arousal Dynamics). The app includes educational toolkits, recovery metrics and visualisations for health management and engagement.

Methods
In this open-label trial, 32 nurses (41.4±7.1y; 27f) used the SleepSync app for a six-week period, including two-weeks of baseline where the app provided no recommendations. Following baseline, participants received daily recommendations for their sleep, education regarding light exposure, caffeine consumption and alertness management. Measures reported here: Insomnia Severity Index (ISI), Sleep Hygiene Index (SHI), PROMIS-Sleep Related Impairment (PROMIS-SRI), 3-min Psychomotor Vigilance Task (PVT; completed at multiple shifts).

Results
Preliminary analyses revealed improvements in ISI (Pre App Use=16.4±5.3; Post App Use=10.2±4.0; p&lt;.001) and SHI (Pre App Use=27.6±8.3; Post App Use=20.5±5.1; p&lt;.001), but not PROMIS-SRI. Median Reaction Time recorded improvement following the intervention and after controlling for shift type, start/end of shift and age (t-value = 4.2; p&lt;.01). 75.0% reported the app satisfactory, 65.6% suggested they would recommend it to a friend.

Conclusion
The study provides initial evidence for efficacy of SleepSync app in improving sleep and performance in shift workers, with participant feedback being incorporated into further development and implementation of the app.