Models characterized by autoregressive structure and random coefficients are powerful tools for the analysis of high-frequency, high-dimensional and volatile time series. The available literature on such models is broad, but also sector-specific, overlapping, and confusing. Most models focus on one property of the data, while much can be gained by combining the strength of various models and their sources of heterogeneity. We present a structured overview of the literature on autoregressive models with random coefficients. We describe hierarchy and analogies among models, and for each we systematically list properties, estimation methods, tests, software packages and typical applications.

To extend and validate a previously suggested model of the influence of uninterrupted sleep bouts on sleep onset misperception in a large independent dataset. Polysomnograms and sleep diaries of 139 insomnia patients and 92 controls were included. We modelled subjective sleep onset as the start of the first uninterrupted sleep fragment longer than L_s minutes, were parameter L_s reflects the minimum length of a sleep fragment required to be perceived as sleep. We compared the so-defined sleep onset latency (SOL) for various values of L_s. Model parameters were compared between groups, and across insomnia subgroups with respect to sleep onset misperception, medication use, age and sex. Next, we extended the model to incorporate the length of wake fragments. Model performance was assessed by calculating Root Mean Square errors (RMSEs) of the difference between estimated and perceived SOL. Participants with insomnia needed a median of 34 minutes of undisturbed sleep to perceive sleep onset, while healthy controls needed 22 minutes (Mann Whitney U=4426, p<0.001). Similar statistically significant differences were found between sleep onset misperceivers and non-misperceivers (median 40 vs 20 minutes, Mann Whitney U=984.5, p<0.001). Model outcomes were similar across other subgroups. Extended models including wake bout lengths resulted in only marginal improvements of model outcome. Patients with insomnia, particularly sleep misperceivers, need larger continuous sleep bouts to perceive sleep onset. The modelling approach yields a parameter for which we coin the term Sleep Fragment Perception Index, providing a useful measure to further characterize sleep state misperception.

Purpose: Cardiorespiratory fitness (CRF) plays an essential role in health outcomes and quality of life. However, it is often not assessed nor estimated. Objective CRF assessment is costly, labour intensive and not widely available. Patient-reported outcome measures estimate CRF more cost-efficiently, but current questionnaires lack accuracy. The aim of this study is to develop a new self-reported questionnaire to estimate CRF. Materials and Methods: The FitMáx©-questionnaire, consisting of only three questions assessing walking, stair climbing, and cycling capacity, was compared with the commonly used Duke Activity Status Index (DASI) and Veterans Specific Activity Questionnaire (VSAQ). These questionnaires were compared to peak oxygen uptake (VO_2peak) as measured with cardiopulmonary exercise testing. This study included 759 cardiac, pulmonary and oncologic patients and healthy persons aged 18‒90. Results: FitMáx© strongly correlated (r = 0.94 (0.92‒0.95) SEE = 4.14 mL∙kg^{− 1}∙min^{− 1}) with measured VO_2peak. Bias between predicted and measured VO_2peak was − 0.24 (− 9.23‒8.75; 95% limits of agreement) mL·kg^{− 1}·min^{− 1}. The FitMáx© scored superiorly on correlation and SEE compared with the DASI and VSAQ, r = 0.75 (0.68‒0.80) SEE = 4.62 mL∙kg^{− 1}∙min^{− 1} and r = 0.87 (0.83‒0.90) SEE = 6.75 mL∙kg^{− 1}∙min^{− 1}, respectively. Conclusion: FitMáx© is a valid and accessible questionnaire to estimate CRF expressed as VO_2peak in clinical practice and shows substantial improvement compared to currently used questionnaires.

Progression of atrial fibrillation (AF) and outcomes of ablation therapy are strongly affected by modifiable risk factors. Although previous studies show beneficial effects of modifying single risk factors, there is lack of evidence from randomized controlled trials on the effects of integrated AF lifestyle programmes. The POP trial is designed to evaluate the clinical outcomes of a dedicated nurse-led AF lifestyle outpatient clinic in patients with symptomatic AF. This study is a prospective, 1:1 randomized, single centre, investigator-initiated clinical trial in 150 patients with paroxysmal or persistent AF referred for a first pulmonary vein isolation (PVI). Prior to the ablation, patients in the intervention group receive a personalized risk factor treatment programme in a specialized, protocolized, nurse-led outpatient clinic. Patient education and durable lifestyle management is promoted with an e-health platform. Patients in the control group receive standard care by cardiologists before ablation. The primary endpoint is the number of hospitalizations for re-ablation and cardioversion, with a follow-up of 12 months after ablation. Secondary endpoints include mortality, number of acute ischemic events, stroke or hospitalizations for heart failure, quality of life, number of ablations cancelled because of symptom reduction, and ablation success rate at 12 months. Determinants of patient and staff experience are explored and a cost-effectiveness analysis is included. The POP trial will help ascertain the efficacy and cost-effectiveness of an integrated technology-supported lifestyle therapy in patients with symptomatic AF. The trial is funded by the Netherlands Organisation for Health Research and Development [10070012010001]. Home sleep apnoea testing devices were provided by Itamar Medical, Ltd.ClinicalTrials.gov Identifier NCT05148338. Graphical abstract AF atrial fibrillation, OSA obstructive sleep apnoea, PFA pulsed field ablation, PVI pulmonary vein isolation.

Background: A flow limitation in the iliac arteries (FLIA) in endurance athletes is notoriously difficult to diagnose with the currently available diagnostic tools. At present, a commonly used diagnostic measure is a decrease in ankle brachial index with flex hips (ABI_Flexed) following a maximal effort exercise test. Near-infrared spectroscopy (NIRS) is a non-invasive technique that measures skeletal muscle oxygenation as reflected by the balance of O₂ delivery from microvascular blood flow and O₂ uptake by metabolic activity. Therefore, NIRS potentially serves as a novel technique for diagnosing FLIA. The purpose of this study is to compare the diagnostic accuracy of NIRS-derived absolute, amplitude, and kinetic variables in legs during and after a maximal exercise test with ABI_Flexed. Methods: ABI_Flexed and NIRS were studied in 33 healthy subjects and 201 patients with FLIA diagnosed with echo-Doppler. Results: After maximal exercise, NIRS kinetic variables, such as the half value time and mean response time, resulted in a range of 0.921 to 0.939 AUC for the diagnosis of FLIA when combined with ABI_Flexed. Conversely, ABI_Flexed measurements alone conferred significantly worse test characteristics (AUC 0.717, p < 0.001). Conclusions: NIRS may serve as a diagnostic adjunct in patients with possible FLIA.

The robustness of the t linear mixed model (tLMM) has been proved and exploited in many applications. Various publications emerged with the aim of proving superiority with respect to traditional linear mixed models, extending to more general settings and proposing more efficient estimation methods. However, little attention has been paid to the mathematical properties of the model itself and to the evaluation of the proposed estimation methods. In this paper we perform an in-depth analysis of the tLMM, evaluating a direct maximum likelihood estimation method via an intensive simulation study and investigating some identifiability properties. The theoretical findings are illustrated through an application to a dataset collected from a sleep trial.