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Eur Respir Rev ; 31(166)2022 Dec 31.
Article in English | MEDLINE | ID: covidwho-2162291


BACKGROUND: The coronavirus disease 2019 pandemic has accelerated the adoption of virtual care strategies for the management of patients with obstructive sleep apnoea/hypopnoea syndrome (OSAHS). RESEARCH QUESTION: What is the effectiveness of virtual consultations compared to in-person consultations for the management of continuous positive airway pressure (CPAP) therapy in adult patients with OSAHS? METHODS: A systematic review and meta-analysis (PROSPERO; CRD42022297532) based on six electronic databases plus manually selected journals was conducted in January 2022. Two researchers independently selected, quality appraised and extracted data. The co-primary outcomes were patient-reported sleepiness, assessed by the Epworth Sleepiness Scale (ESS), and reported cost-effectiveness. RESULTS: 12 studies (n=1823 adults) were included in the review. Seven studies (n=1089) were included in the meta-analysis which showed no difference in the magnitude of improvement in patient-reported sleepiness scores between virtual and in-person consultations (mean difference -0.39, 95% CI -1.38-0.60; p=0.4), although ESS scores improved in both groups. Virtual care strategies modestly increased CPAP therapy adherence and were found to be less costly than in-person care strategies in the three Spanish trials that reported cost-effectiveness. CONCLUSION: The findings of this review suggest that virtual care delivered by telephone or video consultations is as effective as in-person consultations for improving subjective sleepiness in patients with OSAHS treated with CPAP. This clinical management strategy may also improve CPAP adherence without increasing the costs, supporting its potential as a follow-up management strategy, where patients prefer this approach.

COVID-19 , Sleep Apnea, Obstructive , Adult , Humans , Sleepiness , Sleep Apnea, Obstructive/diagnosis , Sleep Apnea, Obstructive/therapy , Continuous Positive Airway Pressure , Referral and Consultation
Front Neurosci ; 16: 726880, 2022.
Article in English | MEDLINE | ID: covidwho-1742234


Background: The capacity to diagnose obstructive sleep apnoea (OSA) must be expanded to meet an estimated disease burden of nearly one billion people worldwide. Validated alternatives to the gold standard polysomnography (PSG) will improve access to testing and treatment. This study aimed to evaluate the diagnosis of OSA, using measurements of mandibular movement (MM) combined with automated machine learning analysis, compared to in-home PSG. Methods: 40 suspected OSA patients underwent single overnight in-home sleep testing with PSG (Nox A1, ResMed, Australia) and simultaneous MM monitoring (Sunrise, Sunrise SA, Belgium). PSG recordings were manually analysed by two expert sleep centres (Grenoble and London); MM analysis was automated. The Obstructive Respiratory Disturbance Index calculated from the MM monitoring (MM-ORDI) was compared to the PSG (PSG-ORDI) using intraclass correlation coefficient and Bland-Altman analysis. Receiver operating characteristic curves (ROC) were constructed to optimise the diagnostic performance of the MM monitor at different PSG-ORDI thresholds (5, 15, and 30 events/hour). Results: 31 patients were included in the analysis (58% men; mean (SD) age: 48 (15) years; BMI: 30.4 (7.6) kg/m2). Good agreement was observed between MM-ORDI and PSG-ORDI (median bias 0.00; 95% CI -23.25 to + 9.73 events/hour). However, for 15 patients with no or mild OSA, MM monitoring overestimated disease severity (PSG-ORDI < 5: MM-ORDI mean overestimation + 5.58 (95% CI + 2.03 to + 7.46) events/hour; PSG-ORDI > 5-15: MM-ORDI overestimation + 3.70 (95% CI -0.53 to + 18.32) events/hour). In 16 patients with moderate-severe OSA (n = 9 with PSG-ORDI 15-30 events/h and n = 7 with a PSG-ORD > 30 events/h), there was an underestimation (PSG-ORDI > 15: MM-ORDI underestimation -8.70 (95% CI -28.46 to + 4.01) events/hour). ROC optimal cut-off values for PSG-ORDI thresholds of 5, 15, 30 events/hour were: 9.53, 12.65 and 24.81 events/hour, respectively. These cut-off values yielded a sensitivity of 88, 100 and 79%, and a specificity of 100, 75, 96%. The positive predictive values were: 100, 80, 95% and the negative predictive values 89, 100, 82%, respectively. Conclusion: The diagnosis of OSA, using MM with machine learning analysis, is comparable to manually scored in-home PSG. Therefore, this novel monitor could be a convenient diagnostic tool that can easily be used in the patients' own home. Clinical Trial Registration:, identifier NCT04262557.

BMC Med Educ ; 22(1): 1, 2022 Jan 03.
Article in English | MEDLINE | ID: covidwho-1603673


BACKGROUND: As a result of the COVID-19 pandemic Imperial College School of Medicine developed a structured volunteering programme involving 398 medical students, across eight teaching hospitals. This case study aims to explore the relationship between the processes, context, participant experiences and impacts of the programme so that lessons can be learned for future emergencies and service-learning programmes. METHODS: Using an illuminative approach to evaluation we invited all volunteers and supervisors to complete a mixed-methods survey. This explored differences in experience across demographics and contextual factors, correlations between aspects of induction, supervision and overall experience, and reviewed the impacts of the programme. Quantitative responses were statistically analysed and qualitative reflections were thematically coded to triangulate and explain quantitative findings. Follow up interviews were carried out to check back findings and co-create conclusions. RESULTS: We received responses from 61 students and 17 supervisors. Student participants described predominantly altruistic motivations and transformational changes to their professional identity driven by feeling included, having responsibility, and engaging in authentic workplace-based learning afforded by freedom from the assessed curriculum. They reported new perspectives on their future professional role within the multidisciplinary team and the value of workplace-based learning. They reported increases in wellbeing and self-esteem related to feeling included and valued, and positively contributing to service provision at a time of need. Significantly higher overall satisfaction was associated with a personalised induction, active supervision, earlier stage of training, and male gender. Gender-related differences were not explained through our data but have been reported elsewhere and warrant further study. The duration, intensity and type of role that volunteers performed was similar across demographics and did not appear to modulate their overall experience. CONCLUSIONS: Whilst acknowledging the uniqueness of emergency volunteering and the survey response rate of 15% of volunteers, we suggest the features of a successful service-learning programme include: a learner-centred induction, regular contact with engaged and appreciative supervisors, and roles where students feel valued. Programmes in similar settings may find that service learning is most impactful earlier in medical students' training and that students with altruistic motivations and meaningful work may flourish without formal outcomes and assessments.

COVID-19 , Education, Medical, Undergraduate , Students, Medical , Humans , Male , Pandemics , SARS-CoV-2 , Volunteers