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BACKGROUND: Patients with young onset Alzheimer's disease (YOAD) face long diagnostic delays. Prescription medication use may provide insights into early signs and symptoms, which may help facilitate timely diagnosis. METHODS: In a register-based nested case-control study, we examined medication use for everyone diagnosed with YOAD in a Danish memory clinic during 2016-2020 compared to cognitively healthy controls. Prescription medication use were grouped into 13 overall categories (alimentary tract and metabolism, blood and blood forming organs, cardiovascular system, dermatologicals, genitourinary system and sex hormones, systemic hormonal preparations, antiinfectives for systemic use, antineoplastic and immunomodulating agents, musculo-skeletal system, nervous system, antiparasitic products, respiratory system, and sensory organs). Further stratifications were done for predetermined subcategories with a use-prevalence of at least 5% in the study population. Conditional logistic regression produced odds ratios, which given the use of incidence-density matching is interpretable as incidence rate ratios (IRRs). The association between prescription medication use and subsequent YOAD diagnosis was examined in the entire 10-year study period and in three time-intervals. RESULTS: The study included 1745 YOAD cases and 5235 controls. In the main analysis, several overall categories showed significant associations with YOAD in one or more time-intervals, namely blood and blood forming organs and nervous system. Prescription medication use in the nervous system category was increased for YOAD cases compared to controls already 10->5 years prior to diagnosis (IRR 1.17, 95% CI 1.05-1.31), increasing to 1.57 (95% CI 1.39-1.78) in the year preceding diagnosis. This was largely driven by antidepressant and antipsychotic use, and especially prominent for first-time users. CONCLUSIONS: In this study, medication use in several categories was associated with YOAD. Onset of treatment-requiring psychiatric symptoms such as depression or psychosis in mid-life may serve as potential early indicators of YOAD.

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This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven approaches that address limitations and risks associated with traditional methods. Developing the hypotension prediction index and introducing CircEWSTM and CircEWS-lite TM showcase AI's effectiveness in predicting and managing circulatory failure. The crucial aspects include the balance between AI and healthcare professionals, ethical considerations, and the need for regulatory frameworks. The use of AI in haemodynamic monitoring will keep growing with ongoing research, better technology, and teamwork. As we navigate these advancements, it is crucial to balance AI's power and healthcare professionals' essential role. Clinicians must continue to use their clinical acumen to ensure that patient outliers or system problems do not compromise the treatment of the condition and patient safety.

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BACKGROUND: Severe Mental Disorders (SMDs) cause mental health worldwide challenges because of several relapses and extensive recovery periods of hospitalization, which put a lot of economic and social burden on families and governments. Therefore, interventions are necessary to decrease the relapse of these disorders. AIM: This study was conducted to investigate the effect of Information Technology Assisted Relapse Prevention Program (ITAREP) on relapse among people who live with SMDs. METHOD: This study was a randomized clinical trial with intervention and control groups. ITAREP is a remote intervention based on monitoring the Early Warning Signs (EWS) to decrease the number of potential relapses. Using convenience sampling, people with SMDs admitted to Sina Juneqan Psychiatric Hospital and their caregivers were recruited in this study and randomly allocated to the control and intervention groups. Two checklists of the EWS for the patient and the patient's caregiver were used for monitoring the relapse signs. Data were collected at baseline and 90 days after discharge and were analyzed using t-test and Chi-square statistical tests and linear regression in SPSS software. RESULTS: Fifty-two patients who lived with SMDs participated in this study (26 in the intervention group and 26 in the control group). The two groups were homogeneous regarding age, gender, type of mental disorder, and duration of the disorder. Forty-two males and ten females participated in this research. Most of the participants were diagnosed with schizophrenia. The results showed that the number of relapses in the intervention group was significantly lower than in the control group in the post-test. CONCLUSION: Social workers, as the case managers and a member of the interdisciplinary psychiatric team, can actively perform follow-up measures after discharge using ITAREP, and it can be expected that these interventions will reduce the number of relapses among patients who live with SMDs.

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INTRODUCTION: Early symptoms in young onset Alzheimer's disease (YOAD) may be misinterpreted, causing delayed diagnosis. This population-based study aimed to map morbidity prior to YOAD diagnosis. METHODS: In a register-based incidence density matched nested case-control study, we examined hospital-diagnosed morbidity for people diagnosed with YOAD in Danish memory clinics during 2016-2020 compared to controls in a 10-year period. Conditional logistic regression produced incidence rate ratios (IRRs). RESULTS: The study included 1745 cases and 5235 controls. YOAD patients had a higher morbidity burden in the year immediately before dementia diagnosis, for certain disorders up to 10 years before. This was especially evident for psychiatric morbidity with the highest increased IRRs throughout the entire period and IRR 1.43 (95% confidence interval 1.14-1.79) in the 5-10-years before dementia diagnosis. DISCUSSION: YOAD patients display a different pattern of morbidity up to 10 years prior to diagnosis. Awareness of specific alterations in morbidity may improve efforts toward a timely diagnosis. HIGHLIGHTS: Retrospective, nested case-control study of young onset Alzheimer's disease (YOAD). YOAD cases had a higher morbidity burden than controls. YOAD cases had a higher psychiatric morbidity burden up to 10 years before diagnosis. Altered morbidity patterns could serve as an early warning sign of YOAD.

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BACKGROUND AND OBJECTIVES: Much of the burden of depressive illness is due to relapses that occur after treatment into remission. Prediction of an individual's imminent depressive relapse could lead to just-in-time interventions to prevent relapse, reducing depression's substantial burden of disability, costs, and suicide risk. Increasingly strong relationships in the form of autocorrelations between depressive symptoms, a signal of a phenomenon described as critical slowing down (CSD), have been proposed as a means of predicting relapse. METHODS: In the current study, four participants in remission from depression, one of whom relapsed, responded to daily smartphone surveys with depression symptoms. We used p-technique factor analysis to identify depression factors from over 100 survey responses. We then tested for the presence of CSD using time-varying vector autoregression and detrended fluctuation analysis. RESULTS: We found evidence that CSD provided an early warning sign for depression in the participant who relapsed, but we also detected false positive indications of CSD in participants who did not relapse. Results from time-varying vector autoregression and detrended fluctuation analysis were not in agreement. LIMITATIONS: Limitations include use of secondary data and a small number of participants with daily responding to a subset of depression symptoms. CONCLUSIONS: CSD provides a compelling framework for predicting depressive relapse and future research should focus on improving detection of early warning signs reliably. Improving early detection methods for depression is clinically significant, as it would allow for the development of just-in-time interventions.

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OBJECTIVE: Our aim was to identify changes in healthcare utilization prior to a young-onset Alzheimer's disease diagnosis. METHODS: In a retrospective incidence density matched nested case-control study using national health registers, we examined healthcare utilization for those diagnosed with young-onset Alzheimer's disease in Danish memory clinics during 2016-2018 compared with age- and sex-matched controls. Negative binomial regression analysis produced contact rate ratios. RESULTS: The study included 1082 young-onset Alzheimer's disease patients and 3246 controls. In the year preceding diagnosis, we found increased contact rate ratios for all types of contacts except physiotherapy. Contact rate ratios for contacts with a general practitioner were significantly increased also > 1-5 and > 5-10 years before diagnosis. The highest contact rate ratios were for psychiatric emergency contacts (8.69, 95% CI 4.29-17.62) ≤ 1 year before diagnosis. INTERPRETATION: Results demonstrate that young-onset Alzheimer's disease patients have increased healthcare utilization from 5 to 10 years prior to diagnosis. Awareness of specific alterations in health-seeking behaviour may help healthcare professionals provide timely diagnoses.

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Living systems are hierarchical control systems that display a small world network structure. In such structures, many smaller clusters are nested within fewer larger ones, producing a fractal-like structure with a 'power-law' cluster size distribution (a mereology). Just like their structure, the dynamics of living systems shows fractal-like qualities: the timeseries of inner message passing and overt behavior contain high frequencies or 'states' (treble) that are nested within lower frequencies or 'traits' (bass), producing a power-law frequency spectrum that is known as a 'state-trait continuum' in the behavioral sciences. Here, we argue that the power-law dynamics of living systems results from their power-law network structure: organisms 'vertically encode' the deep spatiotemporal structure of their (anticipated) environments, to the effect that many small clusters near the base of the hierarchy produce high frequency signal changes and fewer larger clusters at its top produce ultra-low frequencies. Such ultra-low frequencies exert a tonic regulatory pressure that produces morphological as well as behavioral traits (i.e., body plans and personalities). Nested-modular structure causes higher frequencies to be embedded within lower frequencies, producing a power-law state-trait continuum. At the heart of such dynamics lies the need for efficient energy dissipation through networks of coupled oscillators, which also governs the dynamics of non-living systems (e.q., earthquakes, stock market fluctuations). Since hierarchical structure produces hierarchical dynamics, the development and collapse of hierarchical structure (e.g., during maturation and disease) should leave specific traces in system dynamics (shifts in lower frequencies, i.e. morphological and behavioral traits) that may serve as early warning signs to system failure. The applications of this idea range from (bio)physics and phylogenesis to ontogenesis and clinical medicine.

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Background Prodromal symptoms are warning signs of an impending acute myocardial infarction (AMI). However, they are often overlooked by both patients and primary clinicians, and little is known about them. Therefore, this study aims to assess the frequency and types of prodromal symptoms in patients with AMI. Methodology This descriptive cross-sectional study was conducted at a tertiary care cardiac center. Consecutive patients diagnosed with AMI within the last week were evaluated for prodromal symptoms. The prodromal symptoms included chest pain, chest heaviness, chest burning, palpitations, fatigue, sleep disturbance, shortness of breath (SOB), dizziness, anxiety, sudden heat or cold, back pain, and vomiting. Results In a sample of 242 patients, 79.6% were males, with a mean age of 54.7 ± 12.2 years, and 179 (74%) were diagnosed with ST-segment elevation myocardial infarction (STEMI). Among the participants, 142 (58.7%) showed no prodromal symptoms. Among those with prodromal symptoms, chest pain was the predominantly reported prodromal symptom with a frequency of 68%, followed by chest heaviness at 44%, palpitations at 42%, shortness of breath at 34%, and chest burning at 27%. Unusual fatigue in 23% and sleep disturbance in 22% of the patients were also reported. Conclusion The findings from this study revealed that prodromal symptoms were present in a significant proportion of acute myocardial infarction (MI) cases, with more than four in 10 patients reporting these early warning signs. The most commonly observed prodromal symptoms were chest pain, chest heaviness, palpitations, shortness of breath, and chest burning. The timely identification of these symptoms can help prevent infarction, thereby reducing the burden of heart failure and other related mortalities.

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BACKGROUND: Self-management of early warning signs of relapse is critical when it comes to having an impact on the relapse rate and developing methods to successfully handle and manage those signs of relapse. OBJECTIVE: The purpose of this study was to test the validity and reliability of the adapted management of early warning signs of relapse questionnaire. METHODS: Consisted of two main steps: first, adapting and validating, which involved a literature review, a panel of experts, the calculation of the CVI, the Kaiser-Meyer-Olkin (KMO) test, Bartlett's test of sphericity, and exploratory factor analysis (EFA); and secondly, reliability analysis, using the test-retest method, to assess the questionnaire's internal consistency (Cronbach's alpha) and reproducibility (intraclass correlation coefficient-ICC). RESULTS: The results showed that the questionnaire adapted was valid and reliable and can represent each item of the questionnaire for assessing the self-management of early warning signs of relapse. CONCLUSION: This proves that all 20 items used to assess it are appropriate for assessing the effectiveness of the patients' and their primary caregivers' abilities to self-manage early warning signs of relapse.

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Background Early identification of warning symptoms among out-of-hospital cardiac arrest (OHCA) patients remains challenging. Thus, we examined the registered prodromal symptoms of patients who called medical helpline services within 30-days before OHCA. Methods Patients unwitnessed by emergency medical services (EMS) aged ≥18 years during their OHCA were identified from the Danish Cardiac Arrest Registry (2014-2018) and linked to phone records from the 24-h emergency helpline (1-1-2) and out-of-hours medical helpline (1813-Medical Helpline) in Copenhagen before the arrest. The registered symptoms were categorized into chest pain; breathing problems; central nervous system (CNS)-related/unconsciousness; abdominal/back/urinary; psychiatric/addiction; infection/fever; trauma/exposure; and unspecified (diverse from the beforementioned categories). Analyses were divided by the time-period of calls (0-7 days/8-30 days preceding OHCA) and call type (1-1-2/1813-Medical Helpline). Results Of all OHCA patients, 18% (974/5442) called helpline services (males 56%, median age 76 years[Q1-Q3:65-84]). Among these, 816 had 1145 calls with registered symptoms. The most common symptom categories (except for unspecified, 33%) were breathing problems (17%), trauma/exposure (17%), CNS/unconsciousness (15%), abdominal/back/urinary (12%), and chest pain (9%). Most patients (61%) called 1813-Medical Helpline, especially for abdominal/back/urinary (17%). Patients calling 1-1-2 had breathing problems (24%) and CNS/unconsciousness (23%). Nearly half of the patients called within 7 days before their OHCA, and CNS/unconsciousness (19%) was the most registered. The unspecified category remained the most common during both time periods (32%;33%) and call type (24%;39%). Conclusions Among patients who called medical helplines services up to 30-days before their OHCA, besides symptoms being highly varied (unspecified (33%)), breathing problems (17%) were the most registered symptom-specific category.

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Identifying early warning signs of sudden population changes and mechanisms leading to regime shifts are highly desirable in population biology. In this paper, a two-trophic ecosystem comprising of two species of predators, competing for their common prey, with explicit interference competition is considered. With proper rescaling, the model is portrayed as a singularly perturbed system with fast prey dynamics and slow dynamics of the predators. In a parameter regime near singular Hopf bifurcation, chaotic mixed-mode oscillations (MMOs), featuring concatenation of small and large amplitude oscillations are observed as long-lasting transients before the system approaches its asymptotic state. To analyze the dynamical cause that initiates a large amplitude oscillation in an MMO orbit, the model is reduced to a suitable normal form near the singular-Hopf point. The normal form possesses a separatrix surface that separates two different types of oscillations. A large amplitude oscillation is initiated if a trajectory moves from the "inner" to the "outer side" of this surface. A set of conditions on the normal form variables are obtained to determine whether a trajectory would exhibit another cycle of MMO dynamics before experiencing a regime shift (i.e. approaching its asymptotic state). These conditions serve as early warning signs for a sudden population shift as well as detect the onset of a regime shift in this ecological model.

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INTRODUCTION: Cardiac arrest patients presenting with back pain are at risk of not receiving the appropriate help when calling emergency medical services. In telephone consultations regarding patients with back pain preceding an out-of-hospital cardiac arrest, we investigated how communication between caller and call-taker influenced the call-taker's interpretation of back pain descriptions and decision-making about choice of response. METHOD: The study was conducted using 20 recorded phone calls from 17 patients who contacted the Copenhagen Emergency Medical Services (Denmark) reporting back pain up to 24 hours before an out-of-hospital cardiac arrest. Qualitative content analysis was applied. RESULTS: Two main categories emerged: (1) reasons, including subcategories: reported conditions, descriptions of conditions, patient's interpretation of condition and patient's own remedial actions; and (2) considerations, including subcategories: assessment of the severity, call-taker's interpretation of the condition, arguments for chosen response and conditions not facilitating further communication by the call-taker. CONCLUSION: In telephone consultations regarding patients with back pain preceding an out-of-hospital cardiac arrest the communication was influenced by the communicative preconditions of the call-taker. Communication in consultations where ambulances were not dispatched was characterized by complex descriptions of symptoms not easily fitting into the health system's interpretations of conditions warranting an urgent response.

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BACKGROUND: Bipolar disorder is a severe mental illness characterized by recurrent episodes of depressed, elevated, and mixed mood states. The addition of psychotherapy to pharmacological management can decrease symptoms, lower relapse rates, and improve quality of life; however, access to psychotherapy is limited. Mental health technologies such as smartphone apps are being studied as a means to increase access to and enhance the effectiveness of adjunctive psychotherapies for bipolar disorder. Individuals with bipolar disorder find this intervention format acceptable, but our understanding of how people utilize and integrate these tools into their behavior change and maintenance processes remains limited. OBJECTIVE: The objective of this study was to explore how individuals with bipolar disorder perceive and utilize a smartphone intervention for health behavior change and maintenance. METHODS: Individuals with bipolar disorder were recruited via flyers placed at university-affiliated and private outpatient mental health practices to participate in a pilot study of LiveWell, a smartphone-based self-management intervention. At the end of the study, all participants completed in-depth qualitative exit interviews. The behavior change framework developed to organize the intervention design was used to deductively code behavioral targets and determinants involved in target engagement. Inductive coding was used to identify themes not captured by this framework. RESULTS: In terms of behavioral targets, participants emphasized the importance of managing mood episode-related signs and symptoms. They also discussed the importance of maintaining regular routines, sleep duration, and medication adherence. Participants emphasized that receiving support from a coach as well as seeking and receiving assistance from family, friends, and providers were important for managing behavioral targets and staying well. In terms of determinants, participants stressed the important role of monitoring for their behavior change and maintenance efforts. Monitoring facilitated self-awareness and reflection, which was considered valuable for staying well. Some participants also felt that the intervention facilitated learning information necessary for managing bipolar disorder but others felt that the information provided was too basic. CONCLUSIONS: In addition to addressing acceptability, satisfaction, and engagement, a person-based design of mental health technologies can be used to understand how people experience the impact of these technologies on their behavior change and maintenance efforts. This understanding may then be used to guide ongoing intervention development. The participants' perceptions aligned with the intervention's primary behavioral targets and use of a monitoring tool as a core intervention feature. Participant feedback further indicates that developing additional content and tools to address building and engaging social support may be an important avenue for improving LiveWell. A comprehensive behavior change framework to understand participant perceptions of their behavior change and maintenance efforts may help facilitate ongoing intervention development.

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BACKGROUND: Bipolar disorder is a serious mental illness that results in significant morbidity and mortality. Pharmacotherapy is the primary treatment for bipolar disorder; however, adjunctive psychotherapy can help individuals use self-management strategies to improve outcomes. Yet access to this therapy is limited. Smartphones and other technologies have the potential to increase access to therapeutic strategies that enhance self-management while simultaneously providing real-time user feedback and provider alerts to augment care. OBJECTIVE: This paper describes the user-centered development of LiveWell, a smartphone-based self-management intervention for bipolar disorder, to contribute to and support the ongoing improvement and dissemination of technology-based mental health interventions. METHODS: Individuals with bipolar disorder first participated in a field trial of a simple smartphone app for self-monitoring of behavioral targets. To develop a complete technology-based intervention for bipolar disorder, this field trial was followed by design sessions, usability testing, and a pilot study of a smartphone-based self-management intervention for bipolar disorder. Throughout all phases of development, intervention revisions were made based on user feedback. RESULTS: The core of the LiveWell intervention consists of a daily self-monitoring tool, the Daily Check-in. This self-monitoring tool underwent multiple revisions during the user-centered development process. Daily Check-in mood and thought rating scales were collapsed into a single wellness rating scale to accommodate user development of personalized scale anchors. These anchors are meant to assist users in identifying early warning signs and symptoms of impending episodes to take action based on personalized plans. When users identified personal anchors for the wellness scale, the anchors most commonly reflected behavioral signs and symptoms (40%), followed by cognitive (25%), mood (15%), physical (10%), and motivational (7%) signs and symptoms. Changes to the Daily Check-in were also made to help users distinguish between getting adequate sleep and keeping a regular routine. At the end of the pilot study, users reported that the Daily Check-in made them more aware of early warning signs and symptoms and how much they were sleeping. Users also reported that they liked personalizing their anchors and plans and felt this process was useful. Users experienced some difficulties with developing, tracking, and achieving target goals. Users also did not consistently follow up with app recommendations to contact providers when Daily Check-in data suggested they needed additional assistance. As a result, the human support roles for the technology were expanded beyond app use support to include support for self-management and clinical care communication. The development of these human support roles was aided by feedback on the technology's usability from the users and the coaches who provided the human support. CONCLUSIONS: User input guided the development of intervention content, technology, and coaching support for LiveWell. Users valued the provision of monitoring tools and the ability to personalize plans for staying well, supporting the role of monitoring and personalization as important features of digital mental health technologies. Users also valued human support of the technology in the form of a coach, and user difficulties with aspects of self-management and care-provider communication led to an expansion of the coach's support roles. Obtaining feedback from both users and coaches played an important role in the development of both the LiveWell technology and human support. Attention to all stakeholders involved in the use of mental health technologies is essential for optimizing intervention development.

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Our aim was to study the clinical profile, immediate outcome and risk factors associated with poor outcome in critically ill children presenting with seizures requiring PICU admission. As seizures lasting 10 min or more can potentially cause brain damage, we included all children regardless of seizure duration. The records of 157 children aged 1 month to 16 years admitted in the PICU at a tertiary hospital in India with seizures as the presenting symptom during a three-year period were studied retrospectively. Median age of patients was 4 years. 34 (21%) had pre-existing epilepsy and 33 (21%) had previous developmental delay/neuro-deficit. Seizure duration was > 30 min in 75 (47.7%) and 56 (35.6%) required the use of more than 2 antiseizure drugs. 101 (64%) had acute symptomatic seizures, 28 (17%) remote symptomatic and 27 (17.1%) had unknown cause. New onset neurological deficit was seen in 18 (15.6%) and 14 (8.9%) died. Young age, high PEWS score at presentation, prolonged/recurrent seizures, CNS infection, need for multiple antiseizure drugs and ventilation/pressor use were risk factors for poor outcome. Neurological outcome and survival of children in our study were good. Further all-inclusive studies irrespective of seizure duration are needed to obtain a complete picture of critical children presenting with seizures.

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BACKGROUND AND AIM: The association of Hirschsprung's disease (HD) and anorectal malformation (ARM) is rare. The aim of this study is to highlight the frequency of this rare association and comorbidity that may be related to this association. PATIENTS AND METHODS: Eleven cases out of four hundred forty six cases (2.5%) with ARM found to have HD association presented to Assiut University Children Hospital. All cases were diagnosed by complete clinical, radiological assessment and histopathological examination before correction. The evaluating parameters for those patients were the early warning signs for diagnosis, any unnecessary procedures done and any associated morbidity related to misdiagnosis of this association. RESULTS: Age at presentation of these eleven cases ranged from 2 days to 10 years. The diagnosis started early during neonatal period only in four cases either by change of bowel caliber or nonfunctioning stoma. In the remaining seven cases the diagnosis was delayed because of unsuspected association. Fecal fistula after closure of stoma and wound dehiscence followed by incisional hernia is evident associated comorbidity. CONCLUSIONS: The incidence of HD in ARM population seems to be more common than its incidence in the general pediatric population. Caliber change of the bowel during the first operation or nonfunctioning stoma is early alarming sign for diagnoses of such association and should direct the attention for stomal biopsy.

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INTRODUCTION: Little attention has been paid to the contribution of individual residual symptom to predict relapse in patients with schizophrenia receiving oral or long-acting injectable (LAI) antipsychotics. METHOD: We used the data from the Preventing Relapse on Oral Antipsychotics Compared to Injectables - Evaluating Efficacy (PROACTIVE) study, in which 305 outpatients with schizophrenia were randomly allocated to either biweekly LAI-risperidone (LAI-R) or daily oral second-generation antipsychotics (SGA) and assessed for up to 30 months. Baseline individual symptoms that could predict subsequent relapse were identified, using a Cox proportional hazards model. Moreover, among those who relapsed during the study (n = 73), individual symptoms were compared between baseline and biweekly ratings 8 to 2 weeks before relapse, using the linear mixed model. RESULTS: A greater score in grandiosity at baseline was significantly associated with subsequent relapse (adjusted HR = 1.24, p = 0.006). When the two treatment groups were separately analyzed, more severe grandiosity (adjusted HR = 1.43, p = 0.003) and less severe hallucinatory behavior (adjusted HR = 0.70, p = 0.013) at baseline were significantly associated with relapse in the oral SGA group, but none was identified in the LAI-R group. Emotional withdrawal was significantly worse 8 and 2 weeks before relapse compared to the baseline (p = 0.032 and p = 0.043, respectively). DISCUSSION: More severe grandiosity and less hallucination may have led to more frequent relapses in patients with schizophrenia receiving oral antipsychotics, which was not a case in those receiving LAI-R. The exploratory analysis indicates an increase in emotional withdrawal before relapse may be a useful marker for earlier interventions to possibly avert relapse.

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INTRODUCTION: The National Early Warning Score is used as standard clinical practice in the UK as a track and trigger system to monitor hospitalised patients. Currently, nurses are tasked to take routine vital signs measurements and manually record these on a clinical chart. Wearable devices could provide an easier, reliable, more convenient and cost-effective method of monitoring. Our aim is to evaluate the clinical validity of Polso (ChroniSense Medical, Yokneam Illit, Israel), a wrist-based device, to provide National Early Warning Scores. METHODS AND ANALYSIS: We will compare Polso National Early Warning Score measurements to the currently used manual measurements in a UK Teaching District General Hospital. Patients aged 18 years or above who require recordings of observations of vital signs at least every 6 hours will be enrolled after consenting. The sample size for the study was calculated to be 300 participants based on the assumption that the final dataset will include four pairs of measurements per-patient and per-vital sign, resulting in a total of 1200 pairs of data points per vital sign. The primary outcome is the agreement on the individual parameter scores and values of the National Early Warning Score: (1) respiratory rate, (2) oxygen saturation, (3) body temperature, (4) systolic blood pressure and (5) heart rate. Secondary outcomes are the agreement on the aggregate National Early Warning Score. The incidence of adverse events will be recorded. The measurements by the device will not be used for the clinical decision-making in this study. ETHICS AND DISSEMINATION: We obtained ethical approval, reference number 18/LO/0123 from London-Hampstead Research Ethics Committee, through the Integrated Research Application System, (reference number: 235 034. The study received no objection from the Medicine and Health Regulatory Authority, reference number: CI/20018/005 and has National Institute for Health Research portfolio adoption status CPMS number: 32 532. TRIAL REGISTRATION NUMBER: NCT03448861; Pre-results.

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Banded patterns consisting of alternating bare soil and dense vegetation have been observed in water-limited ecosystems across the globe, often appearing along gently sloped terrain with the stripes aligned transverse to the elevation gradient. In many cases, these vegetation bands are arced, with field observations suggesting a link between the orientation of arcing relative to the grade and the curvature of the underlying terrain. We modify the water transport in the Klausmeier model of water-biomass interactions, originally posed on a uniform hillslope, to qualitatively capture the influence of terrain curvature on the vegetation patterns. Numerical simulations of this modified model indicate that the vegetation bands arc convex-downslope when growing on top of a ridge, and convex-upslope when growing in a valley. This behaviour is consistent with observations from remote sensing data that we present here. Model simulations show further that whether bands grow on ridges, valleys or both depends on the precipitation level. A survey of three banded vegetation sites, each with a different aridity level, indicates qualitatively similar behaviour.

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BACKGROUND: The detection of early warning signs is essential in the long-term treatment of bipolar disorders. However, in bipolar patients' daily life and outpatient treatment the assessment of upcoming state changes faces several difficulties. In this trial, we examine the effectiveness of a smartphone based automated feedback about ambulatory assessed early warning signs in prolonging states of euthymia and therefore preventing hospitalization. This study aims to assess, whether patients experience longer episodes of euthymia, when their treating psychiatrists receive automated feedback about changes in communication and activity. With this additional information an intervention at an earlier stage in the development of mania or depression could be facilitated. We expect that the amount of time will be longer between affective episodes in the intervention group. METHODS/DESIGN: The current study is designed as a randomized, multi-center, observer-blind, active-control, parallel group trial within a nationwide research project on the topic of innovative methods for diagnostics, prevention and interventions of bipolar disorders. One hundred and twenty patients with bipolar disorder will be randomly assigned to (1) the experimental group with included automated feedback or (2) the control group without feedback. During the intervention phase, the psychopathologic state of all participants is assessed every four weeks over 18 months. Kaplan-Meier estimators will be used for estimating the survival functions, a Log-Rank test will be used to formally compare time to a new episode across treatment groups. An intention-to-treat analysis will include data from all randomized patients. DISCUSSION: This article describes the design of a clinical trial investigating the effectiveness of a smartphone-based feedback loop. This feedback loop is meant to elicit early interventions at the detection of warning signs for the prevention of affective episodes in bipolar patients. This approach will hopefully improve the chances of a timely intervention helping patients to keep a balanced mood for longer periods of time. In detail, if our hypothesis can be confirmed, clinical practice treating psychiatrists will be enabled to react quickly when changes are automatically detected. Therefore, outpatients would receive an even more individually tailored treatment concerning time and frequency of doctor's appointments. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02782910 : Title: "Smartphone-based Ambulatory Assessment of Early Warning Signs (BipoLife_A3)". Registered May 25 2016. Protocol Amendment Number: 03. Issue Date: 26 March 2018. Author(s): ES.

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