Wearable computing devices allow collection of densely sampled real-time information on movement enabling researchers and medical experts to obtain objective and non-obtrusive records of actual activity of a subject in the real world over many days. Our interest here is motivated by the use of activity data for evaluating and monitoring the circadian rhythmicity of subjects for research in chronobiology and chronotherapeutic healthcare. In order to translate the information from such high-volume data arising we propose the use of a Markov modelling approach which (i) naturally captures the notable square wave form observed in activity data along with heterogeneous ultradian variances over the circadian cycle of human activity, (ii) thresholds activity into different states in a probabilistic way while respecting time dependence and (iii) gives rise to circadian rhythm parameter estimates, based on probabilities of transitions between rest and activity, that are interpretable and of interest to circadian research.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Experimental and epidemiologic studies have shown that circadian clocks disruption can play an important role in the development of cancer and metabolic diseases. The cellular clocks outside the brain are effectively coordinated by the body temperature rhythm. We hypothesized that concurrent measurements of body temperature and rest-activity rhythms would assess circadian clocks coordination in individual patients, thus enabling the integration of biological rhythms into precision medicine. Objective: The study aimed at the real-time demonstration of large inter-subject differences in the circadian clocks of people during their daily routine, using a mobile e-Health platform. Such critical step further aimed at the integration of circadian rhythm disorders diagnosis and treatments into precision e-medicine. Methods: Non-invasive real-time measurements of rest-activity and chest temperature rhythms were recorded during the subject’s daily life, using a dedicated new mobile e-health platform (PiCADo). It involved a chest sensor that jointly measured accelerations, 3D-orientation and skin surface temperature every 1-5 min, and relayed them out to a mobile gateway via Bluetooth-Low-Energy. The gateway tele-transmitted all stored data to a server via GPRS every 24 h. The technical capabilities of PiCADo were validated in 55 healthy subjects and 12 cancer patients, whose rhythms were e-monitored during their daily routine for 3-30 days. Spectral analyses enabled to compute rhythm parameters values, with their 90% confidence limits, and their dynamics in each subject. Results: All the individuals displayed a dominant circadian rhythm in activity with maxima occurring from 12:09 to 20:25. This was not the case for the dominant temperature period, which clustered around 24 h for 51 subjects (76.1%), and around 12 h for 13 others (19.4%). Statistically significant sex- and age- related differences in circadian coordination were identified in the non-cancerous subjects, based upon the range of variations in temperature rhythm amplitudes, maxima (acrophases), and phase relations with rest-activity. The circadian acrophase of chest temperature was located at night for the majority of people, but it occurred at daytime for 26% of the non-cancerous people and 33.3% of the cancer patients, hence supporting important inter-subject differences in circadian coordination. Sex, age and cancer significantly impacted on circadian coordination. Conclusions: Complementing rest-activity with chest temperature circadian e-monitoring revealed striking inter-subject differences regarding human circadian clocks coordination and timing during daily routine. To further delineate the clinical importance of such finding, the PiCADo platform is currently applied for both the assessment of health effects resulting from atypical work schedules, and the identification of the key determinants of circadian disruption in cancer patients.

The dichotomy index (I < O), a quantitative estimate of the circadian regulation of daytime activity and sleep, predicted overall cancer survival and emergency hospitalization, supporting its integration in a mHealth platform. Modifiable causes of I < O deterioration below 97.5%—(I < O)_low—were sought in 25 gastrointestinal cancer patients and 33 age- and sex-stratified controls. Rest-activity and temperature were tele-monitored with a wireless chest sensor, while daily activities, meals, and sleep were self-reported for one week. Salivary cortisol rhythm and dim light melatonin onset (DLMO) were determined. Circadian parameters were estimated using Hidden Markov modelling, and spectral analysis. Actionable predictors of (I < O)_low were identified through correlation and regression analyses. Median compliance with protocol exceeded 95%. Circadian disruption—(I < O)_low—was identified in 13 (52%) patients and four (12%) controls (p = 0.002). Cancer patients with (I < O)_low had lower median activity counts, worse fragmented sleep, and an abnormal or no circadian temperature rhythm compared to patients with I < O exceeding 97.5%—(I < O)_high—(p < 0.012). Six (I < O)_low patients had newly-diagnosed sleep conditions. Altered circadian coordination of rest-activity and chest surface temperature, physical inactivity, and irregular sleep were identified as modifiable determinants of (I < O)_low. Circadian rhythm and sleep tele-monitoring results support the design of specific interventions to improve outcomes within a patient-centered systems approach to health care.

BACKGROUND: Circadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of core body temperature (CBT) maximum (acrophase) or minimum (bathyphase). METHODS: We aimed at circadian phase determination and readout during daily routines in volunteers stratified by sex and age. We measured (a) chronotype, (b) every minute (q1min) CBT using 2 electronic pills swallowed 24 hours apart, (c) DLMO through hourly salivary samples from 1800 hours to bedtime, and (d) q1min accelerations and surface temperature at anterior chest level for 7 days, using a teletransmitting sensor. Circadian phases were computed using cosinor and hidden Markov modeling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase. RESULTS: Among the 33 participants, individual circadian phases were spread over 5 hours, 10 minutes (DLMO); 7 hours (CBT bathyphase); and 9 hours, 10 minutes (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e., with an error less than 1 hour for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score with computed center-of-rest time and surface temperature bathyphase (adjusted R ² = 0.637). CONCLUSION: INTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalization following further validation. FUNDING: Medical Research Council, United Kingdom; AP-HP Foundation; and INSERM.

Long-term survival is an important metric for health care evaluation, especially in functionally single-ventricle (f-SV) congenital heart disease (CHD). This study's aim was to evaluate the relationship between center volume and long-term survival in f-SV CHD within the centralized health care service of England and Wales. This was a retrospective cohort study of children born with f-SV CHD between 2000 and 2018, using the national CHD procedure registry, with survival ascertained in 2020. Of 56,039 patients, 3293 (5.9%) had f-SV CHD. Median age at first intervention was 7 days (interquartile range [IQR], 4, 27), and median follow-up time was 7.6 years (IQR, 1.0, 13.3). The largest diagnostic subcategories were hypoplastic left heart syndrome, 1276 (38.8%); tricuspid atresia, 440 (13.4%); and double-inlet left ventricle, 322 (9.8%). The survival rate at 1 year and 5 years was 76.8% (95% confidence interval [CI], 75.3%-78.2%) and 72.1% (95% CI, 70.6%-73.7%), respectively. The unadjusted hazard ratio for each 5 additional patients with f-SV starting treatment per center per year was 1.04 (95% CI, 1.02-1.06), P < .001. However, after adjustment for significant risk factors (diagnostic subcategory; antenatal diagnosis; younger age, low weight, acquired comorbidity, increased severity of illness at first procedure), the hazard ratio for f-SV center volume was 1.01 (95% CI, 0.99-1.04) P = .28. There was strong evidence that patients with more complex f-SV (hypoplastic left heart syndrome, Norwood pathway) were treated at centers with greater f-SV case volume (P < .001). After adjustment for case mix, there was no evidence that f-SV center volume was linked to longer-term survival in the centralized health service provided by the 10 children's cardiac centers in England and Wales.

Background: There is strong interest in the evaluation of longer‐term outcome metrics for congenital heart diseases (CHDs); however, registries focus on postoperative metrics. Methods and Results: Informed by user online discussion forums and scoping of national data, we selected sentinel CHDs and long‐term outcome metrics suitable for routine monitoring. We then developed sentinel CHD phenotypes and algorithms for identifying treatment pathway procedures using clinical codes. Finally, we calculated the metrics within a retrospective national cohort analysis. The 9 selected sentinel CHDs had a higher‐than‐average prevalence, typically involved surgery in infancy, and were associated with an increased risk of late mortality. The selected metrics of survival and reinterventions at 1, 5, and 10 years were both important and feasible. The cohort included 29 319 (41.3% of all operated CHD births) English and Welsh children born with sentinel CHDs in 2000 to 2022. Example metrics at age 10 years included: survival—hypoplastic left heart syndrome: 57.6% (95% CI, 54.9%–60.4%), functionally univentricular heart: 86.7% (95% CI, 84.6%–88.9%), transposition of the great arteries: 93.1% (95% CI, 92.2%–93.9%), pulmonary atresia: 81.0% (95% CI, 79.1%–82.9%), atrioventricular septal defect: 88.5% (95% CI, 87.5%–89.5%), tetralogy of Fallot: 95.1% (95% CI, 94.4%–95.8%), aortic stenosis: 94.4% (95% CI, 93.3%–95.6%), coarctation: 96.7% (95% CI, 96.2%–97.3%), and ventricular septal defect: 96.9% 95% CI, (96.4%–97.3%); and (2) cumulative incidence of reintervention—hypoplastic left heart syndrome : 54.5% (95% CI, 51.5%–57.3%), functionally univentricular heart: 57.3% (95% CI, 53.9%–60.5%), transposition of the great arteries: 20.9% (95% CI, 19.5%–22.3%), pulmonary atresia: 66.8% (95% CI, 64.2%–69.1%), atrioventricular septal defect: 21.6% (20.3%–23.0%), tetralogy of Fallot: 26.6% (95% CI, 25.2%–28.0%), aortic stenosis: 31.2% (95% CI, 28.8%–33.6%), coarctation: 19.8% (95% CI, 18.6%–21.1%), and ventricular septal defect: 6.1% (95% CI, 5.5%–6.8%). Conclusions: It is feasible to report important long‐term outcomes of survival and reintervention for sentinel CHDs using routinely collected procedure records, adding value to national audit.