Dynamic modeling of Haidinger's brush phenomenon and analysis of the cornea effect based on the model

Starting from the dynamic feature of the vision process and taking into account the time constants of the polarization-dependent process of cones, this study proposed a physical model that can mathematically describe the transient nature of Haidinger's brushes (HB). A saturated exponential growth function was proposed to describe the dynamic process, and the corresponding formulas were derived and discussed. The sensitivities of both static and rotating HB were considered in the model, and the visibility of HB was also investigated. Additionally, the impact of the cornea on the visions of HB was examined by using this model. Analytical results reveal that there exist two types of patterns in the rotating HB phenomenon. The visual perception of the rotating HB is related to the magnitude and interaction of these two patterns, as well as the corneal phase shift. The rotation orientation reversal at large corneal phase shifts observed by some researchers can also be explained by the model. The results are consistent with experimental observations and might help with the clinical diagnosis of macula disorders and corneal abnormalities.

Transition of adolescents with severe asthma from pediatric to adult care in Spain: the STAR consensus

OBJECTIVE

To assess the consensus level among a multidisciplinary expert panel on the transition of adolescents with severe asthma from pediatric to adult care.

METHODS

A 61-item survey was developed based on guidelines for other chronic pathologies, covering transition planning, preparation, effective transfer, and follow-up. A two-round Delphi process assessed the consensus level among 98 experts (49 pediatricians, 24 allergists and 25 pulmonologists). Consensus was established with ≥70% agreement.

RESULTS

Forty-two items (70%) reached consensus. No age range to initiate the transition was agreed upon by the panelists. The main goal to achieve during the transition identified by the experts is that adolescents gain autonomy to manage their severe asthma and prescribed treatments. The panelists agreed on the importance of developing an individualized plan, promoting patient's autonomy, and identifying home environment factors. They agreed that the adult healthcare team should have expertise in severe asthma, biologics and management of adolescent patients. Pediatric and adult healthcare teams should share clinical information, agree on the criteria to maintain the biological therapy, and have an on-site joint visit with the patient before the effective transfer. Adult healthcare professionals should closely follow the patient after the effective transfer to ensure correct inhaler technique, treatment adherence and attendance to healthcare appointments.

CONCLUSION

This consensus document provides the first roadmap for Spanish pediatric and adult teams to ensure that key aspects of the transition process in severe asthma are covered. The implementation of these recommendations will improve the quality of care offered to the patient.

Patients' Experiences in Transitioning to Secondary Progressive Multiple Sclerosis: Qualitative Interviews

Introduction

Critical gaps exist in the understanding of the continuum of multiple sclerosis (MS) progression, particularly with regard to the patient experience prior to and during the transition from relapsing–remitting MS (RRMS) to secondary-progressive MS (SPMS) stages. To date, there are no clear diagnostic criteria in the determination of the clinical transition. We report here the use of patient experience data to support the development of a qualitative conceptual model of MS that describes the patient journey of transition from active-relapsing disease to progressive MS.

Methods

The study used a single-encounter, multicenter, qualitative observational study design that included a targeted literature review and individual, in-depth interviews with adult patients with a clinically confirmed diagnosis of SPMS and their adult care partners. Descriptions of symptoms and impacts of RRMS and SPMS were extracted from the literature review and used to support development of the interview guide and conceptual model.

Results

Participants described a slow progression in terms of change in symptoms over time, including both the development of new symptoms and the worsening of existing symptoms.

Conclusions

The conceptual model of the transitionary period from RRMS to SPMS expands the current understanding of the progression of MS from the patient and care partner perspectives.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-021-00265-0.

Modeling and analyzing hospital to home transition processes of frail older adults using the functional resonance analysis method (FRAM)

The main purpose of this study was to model and analyze hospital to home transition processes of frail older adults in order to identify the challenges within this process. A multi-phase, multi-sited and mixed methods design was utilized, in which, Phase 1 included collecting semi-structured interviews and focus group data, and Phase 2 consisted of six patient/caregiver dyad prospective case studies. This study was conducted in three hospitals in three cities in a single province in Canada. The Functional Resonance Analysis Method (FRAM) was employed to model daily operations of the transition process. The perspectives of both healthcare providers and patients/caregivers were used to build the FRAM model. The transition model was then tested using a customized version of the FRAM. The six patient/caregiver cases were used in the process of testing the FRAM model. The results of building the FRAM model showed that five categories of functions contributed to the transition model, including admission, assessment, synthesis, decision-making, and readmission. The outcomes of using the customized version of the FRAM revealed challenges affecting the transition process including waitlists for geriatric units, team-based care, lack of a discharge planner, financial concerns, and follow-up plans. The findings of this study could assist managers and other decision makers to improve the transition processes of frail older adults by addressing these challenges. The FRAM method employed in this study can be applied widely to identify work practices that are more or less successful, so that procedures and practices can be adapted to nudge healthcare processes towards paths that will yield better outcomes.

Noisy network attractor models for transitions between EEG microstates

The brain is intrinsically organized into large-scale networks that constantly re-organize on multiple timescales, even when the brain is at rest. The timing of these dynamics is crucial for sensation, perception, cognition, and ultimately consciousness, but the underlying dynamics governing the constant reorganization and switching between networks are not yet well understood. Electroencephalogram (EEG) microstates are brief periods of stable scalp topography that have been identified as the electrophysiological correlate of functional magnetic resonance imaging defined resting-state networks. Spatiotemporal microstate sequences maintain high temporal resolution and have been shown to be scale-free with long-range temporal correlations. Previous attempts to model EEG microstate sequences have failed to capture this crucial property and so cannot fully capture the dynamics; this paper answers the call for more sophisticated modeling approaches. We present a dynamical model that exhibits a noisy network attractor between nodes that represent the microstates. Using an excitable network between four nodes, we can reproduce the transition probabilities between microstates but not the heavy tailed residence time distributions. We present two extensions to this model: first, an additional hidden node at each state; second, an additional layer that controls the switching frequency in the original network. Introducing either extension to the network gives the flexibility to capture these heavy tails. We compare the model generated sequences to microstate sequences from EEG data collected from healthy subjects at rest. For the first extension, we show that the hidden nodes 'trap' the trajectories allowing the control of residence times at each node. For the second extension, we show that two nodes in the controlling layer are sufficient to model the long residence times. Finally, we show that in addition to capturing the residence time distributions and transition probabilities of the sequences, these two models capture additional properties of the sequences including having interspersed long and short residence times and long range temporal correlations in line with the data as measured by the Hurst exponent.