Development of 24-hour rhythms in cortisol secretion across infancy: a systematic review and meta-analysis of individual participant data.

BACKGROUND: In adults, cortisol levels show a pronounced 24-hour rhythm with a peak in the early morning. It is unknown at what age this early-morning peak in cortisol emerges during infancy, hampering the establishment of optimal dosing regimens for hydrocortisone replacement therapy in infants with an inborn form of adrenal insufficiency. Therefore, we aimed to characterize daily variation in salivary cortisol concentration across the first year of life. METHODS: We conducted a systematic review followed by an individual participant data meta-analysis of studies reporting on spontaneous (i.e., not stress induced) salivary cortisol concentrations in healthy infants aged 0-1 year. A one-stage approach using linear mixed-effects modelling was used to determine the interaction between age and time of day on cortisol concentrations. FINDINGS: Through the systematic review, 54 eligible publications were identified, reporting on 29,177 cortisol observations. Individual participant data were obtained from 15 study cohorts, combining 17,079 cortisol measurements from 1,904 infants. The morning/evening cortisol ratio increased significantly from 1.7 (95% CI: 1.3-2.1) at birth to 3.7 (95% CI: 3.0-4.5) at 6-9 months (p < 0.0001). Cosinor analysis using all available data revealed the gradual emergence of a 24-hour rhythm during infancy. INTERPRETATION: The early-morning peak in cortisol secretion gradually emerges from birth onwards to form a stable morning/evening ratio from age 6-9 months. This might have implications for hydrocortisone replacement therapy in infants with an inborn form of adrenal insufficiency.

Implementation barriers and facilitators of remote monitoring, remote consultation and digital care platforms through the eyes of healthcare professionals: a review of reviews.

OBJECTIVES: Digital transformation in healthcare is a necessity considering the steady increase in healthcare costs, the growing ageing population and rising number of people living with chronic diseases. The implementation of digital health technologies in patient care is a potential solution to these issues, however, some challenges remain. In order to navigate such complexities, the perceptions of healthcare professionals (HCPs) must be considered. The objective of this umbrella review is to identify key barriers and facilitators involved in digital health technology implementation, from the perspective of HCPs. DESIGN: Systematic umbrella review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. DATA SOURCES: Embase.com, PubMed and Web of Science Core Collection were searched for existing reviews dated up to 17 June 2022. Search terms included digital health technology, combined with terms related to implementation, and variations in terms encompassing HCP, such as physician, doctor and the medical discipline. ELIGIBILITY CRITERIA: Quantitative and qualitative reviews evaluating digital technologies that included patient interaction were considered eligible. Three reviewers independently synthesised and assessed eligible reviews and conducted a critical appraisal. DATA EXTRACTION AND SYNTHESIS: Regarding the data collection, two reviewers independently synthesised and interpreted data on barriers and facilitators. RESULTS: Thirty-three reviews met the inclusion criteria. Barriers and facilitators were categorised into four levels: (1) the organisation, (2) the HCP, (3) the patient and (4) technical aspects. The main barriers and facilitators identified were (lack of) training (n=22/33), (un)familiarity with technology (n=17/33), (loss of) communication (n=13/33) and security and confidentiality issues (n=17/33). Barriers of key importance included increased workload (n=16/33), the technology undermining aspects of professional identity (n=11/33), HCP uncertainty about patients' aptitude with the technology (n=9/33), and technical issues (n=12/33). CONCLUSIONS: The implementation strategy should address the key barriers highlighted by HCPs, for instance, by providing adequate training to familiarise HCPs with the technology, adapting the technology to the patient preferences and addressing technical issues. Barriers on both HCP and patient levels can be overcome by investigating the needs of the end-users. As we shift from traditional face-to-face care models towards new modes of care delivery, further research is needed to better understand the role of digital technology in the HCP-patient relationship.

Mobile Phone Applications Voice Tools and Voice Pitch Analyzer Validated With LingWAVES to Measure Voice Frequency.

OBJECTIVES: Voice frequency can be measured to assess the voice change in transgender men and women during treatment. There are many applications that can analyze voice frequency. This validation study aimed to compare the ability to measure voice frequency of the mobile phone applications "Voice Tools" and "Voice Pitch Analyzer" with the registration program LingWAVES as the gold standard. STUDY DESIGN: Prospective validation study. METHODS: A total of 45 participants of whom 20 transgender individuals were included. They were asked to read "The North Wind and the Sun" twice. The first measurement compared voice frequency measured by Voice Tools with LingWAVES while the second measurement compared Voice Pitch Analyzer with LingWAVES. The two applications that were being compared simultaneously measured the voice frequency. Pearson's regression correlations were performed to test for correlation between the mobile phone applications and LingWAVES. RESULTS: Significant correlations were demonstrated between the measurements of Voice Tools and LingWAVES (P < 0.001) and between Voice Pitch Analyzer and LingWAVES (P < 0.001). Voice Tools overestimated voice frequency with a median deviation of 2Hz (range -4 to 20). The overestimation was more pronounced in the high ranges. Voice Pitch Analyzer showed underestimation of voice frequency in high ranges. Median deviation was -2Hz (range -16 to 14). CONCLUSIONS: This validation study shows that voice frequency can be reliably measured with the mobile phone applications "Voice Tools" and "Voice Pitch Analyzer". Combined with the ease of use, these applications can be used to measure voice frequency in clinical practice and for research purposes.