Daily Progression Research Articles

The patient-reported outcomes for the new brand-generic teriflunomide in relapsing-remitting multiple sclerosis

BackgroundPatient-reported outcomes (PROs) provide valuable insights into the impact of disease-modifying therapies (DMTs) on patients' daily lives and disease progression. This study evaluates treatment satisfaction and tolerability among patients using a brand-generic Teriflunomide (Tebazio®, 14 mg tablet) manufactured by Zistdaru Danesh Biopharmaceuticals. Materials and MethodsA Phase IV observational study was conducted on patients with Relapsing-Remitting Multiple Sclerosis (RRMS) who were either initiated on or switched to Teriflunomide 14 mg. The primary focus was on the medication's safety. Patient satisfaction was measured using the Treatment Satisfaction Questionnaire for Medication [Version 1.4] (TSQM-14). Additionally, medication adherence and discontinuation rates were monitored. ResultsOf the 235 RRMS patients enrolled, participated in this study, all received the Teriflunomide treatment orally on a daily basis. Over the 18-month follow-up period, 25.96 % of patients discontinued the treatment. Discontinuation was mainly due to adverse events (11 %), lack of patient willingness to continue (12.7 %), and disease progression (4.2 %). The most commonly reported adverse events included dermatologic disorders, elevated liver enzymes, and gastrointestinal issues. TSQM-14 scores demonstrated significant improvements over the 18-month period. A high medication adherence rate of 98.1 % was also recorded. ConclusionPatients reported notable satisfaction with Teriflunomide, as reflected in their TSQM scores, which suggests a likelihood of improved patient adherence. The 14 mg brand-generic Teriflunomide was well-accepted by Iranian RRMS patients, with no significant concerns arising during the study. These findings also highlight the significance of patient-reported outcomes in DMTs, with potential benefits for adherence and clinical practice.

The dynamics of L2 teacher boredom and their link to creativity: A ban or boon for boredom

AbstractResearch has revealed a prevalence of boredom among L2 teachers, despite efforts to mitigate this negative emotion. The interplay between teacher boredom and creativity, especially their concurrent development, has not been extensively studied longitudinally. Utilizing control‐value theory as its foundation, this study investigates the daily progression of boredom and creativity among L2 teachers, their mutual development, and how control‐value beliefs influence these dynamics. A 5‐day experience sampling method study involving 98 L2 teachers generated 423 observations. Dynamic structural equation modeling (DSEM) was employed at the individual (Level 1) and group (Level 2) levels. DSEM results revealed varied relationships between boredom and creativity changes over a week, influenced by teachers’ control and value beliefs. In innovators, with high perceived control and intrinsic value beliefs and moderate to high extrinsic value beliefs, previous experiences of boredom might positively influence the teacher's creativity the next day. This creativity might, in turn, decrease the teacher's boredom. This suggests a potential positive relationship between boredom and creativity in innovative language teachers. In adaptors, with moderate perceived control and intrinsic value beliefs and medium to low extrinsic value beliefs, previous experiences of boredom did not necessarily influence the teacher's creativity the next day. However, teacher creativity might still decrease teacher boredom. For traditionalists, with medium perceived control and intrinsic value beliefs and moderate to high extrinsic value beliefs, previous experiences of boredom might have decreased the teacher's creativity the next day, while teacher creativity might have decreased the teacher's boredom the same day. Finally, in dissatisfied teachers with low perceived control, intrinsic value, and extrinsic value beliefs, previous experiences of boredom might have decreased the teacher's creativity the next day, while teacher creativity might not necessarily predict the teacher's boredom. Results suggest a reciprocal relationship between boredom and creativity in adaptable and traditionalist teachers. Additionally, Level 2 analysis identified correlations between random effect parameters across four clusters.

The Canadian Fire Spread Dataset

Satellite data are effective for mapping wildfires, particularly in remote locations where monitoring is rare. Geolocated fire detections can be used for enhanced fire management and fire modelling through daily fire progression mapping. Here we present the Canadian Fire Spread Dataset (CFSDS), encompassing interpolated progressions for fires >1,000 ha in Canada from 2002–2021, representing the day-of-burning and 50 environmental covariates for every pixel. Day-of-burning was calculated by ordinary kriging of active fire detections from the Moderate Resolution Imaging Spectroradiometer and the Visible Infrared Imaging Radiometer Suite, enabling a substantial improvement in coverage and resolution over existing datasets. Day of burning at each pixel was used to identify environmental conditions of burning such as daily weather, derived weather metrics, topography, and forest fuels characteristics. This dataset can be used in a broad range of research and management applications, such as retrospective analysis of fire spread, as a benchmark dataset for validating statistical or machine-learning models, and for forecasting the effects of climate change on fire activity.

Biogeographic patterns of daily wildfire spread and extremes across North America

IntroductionClimate change is predicted to increase the frequency of extreme single-day fire spread events, with major ecological and social implications. In contrast with well-documented spatio-temporal patterns of wildfire ignitions and perimeters, daily progression remains poorly understood across continental spatial scales, particularly for extreme single-day events (“blow ups”). Here, we characterize daily wildfire spread across North America, including occurrence of extreme single-day events, duration and seasonality of fire and extremes, and ecoregional climatic niches of fire in terms of Actual Evapotranspiration (AET) and Climatic Water Deficit (CWD) annual climate normals.MethodsRemotely sensed daily progression of 9,636 wildfires ≥400 ha was used to characterize ecoregional patterns of fire growth, extreme single-day events, duration, and seasonality. To explore occurrence, extent, and impacts of single-day extremes among ecoregions, we considered complementary ecoregional and continental extreme thresholds (Ecoregional or Continental Mean Daily Area Burned + 2SD). Ecoregional spread rates were regressed against AET and CWD to explore climatic influence on spread.ResultsWe found three-fold differences in mean Daily Area Burned among 10 North American ecoregions, ranging from 260 ha day−1 in the Marine West Coast Forests to 751 ha day−1 in Mediterranean California. Ecoregional extreme thresholds ranged from 3,829 ha day−1 to 16,626 ha day−1, relative to a continental threshold of 7,173 ha day−1. The ~3% of events classified as extreme cumulatively account for 16–55% of total area burned among ecoregions. We observed four-fold differences in mean fire duration, ranging from 2.7 days in the Great Plains to 10.5 days in Northwestern Forested Mountains. Regions with shorter fire durations also had greater daily area burned, suggesting a paradigm of fast-growing short-duration fires in some regions and slow-growing long-duration fires elsewhere. CWD had a weak positive relationship with spread rate and extreme thresholds, and there was no pattern for AET.DiscussionRegions with shorter fire durations had greater daily area burned, suggesting a paradigm of fast-growing short-duration fires in some regions and slow-growing long-duration fires elsewhere. Although climatic conditions can set the stage for ignition and influence vegetation and fuels, finer-scale mechanisms likely drive variation in daily spread. Daily fire progression offers valuable insights into the regional and seasonal distributions of extreme single-day spread events, and how these events shape net fire effects.

Current Situation of Breast Cancer in Pakistan and the Dire Need of Early Diagnosis

Globocan statistics underscore Pakistan’s noticeable position in terms of the breast cancer burden, highlighting a concerning and escalating trajectory in its daily progression. Breast cancer stands as the most predominant and fatal malignancy in Pakistan, reporting 25,928 cases in the year 2020, accounting for 14% of all cancer diagnosis. The country is reported to have the maximum incidence and mortality rates in Asia, a dire result of the lack of national cancer registry. Late diagnosis, often determined by sociocultural factors, considerably contributes to the high mortality rate. Several risk factors, such as reproductive factors, age, dietary habits, further complicate the situation. Moreover, economic obstacles deter many from receiving the required treatment. The current review features the dire need for inclusive policies and improved affordability to battle breast cancer’s escalating influence in Pakistan.

All-hazards dataset mined from the US National Incident Management System 1999–2020

This paper describes a dataset mined from the public archive (1999–2020) of the US National Incident Management System Incident Status Summary (ICS-209) forms (a total of 187,160 reports for 35,170 incidents, including 34,478 wildland fires). This system captures detailed daily/regular information on incident development and response, including social and economic impacts. Most (98.4%) reports are wildland fire-related, with other incident types including hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use for research due to multiple record formats, inconsistent data entry, and no clean pathway from individual reports to high-level incident analysis. Here, we describe the open-source, reproducible methods used to produce a science-grade version of the data, including formal connections made to other published wildland fire data products. Among other applications, this integrated and spatially augmented dataset enables exploration of the daily progression of the most costly, damaging, and deadly environmental-hazard events in recent US history.

Plotting Persuasive Progress in Biblical Hebrew Language Learning

Bible Online Learner (https://bibleol.3bmoodle.dk/) claims to deliver a text that can persuade a language learner to practice best online. This corpus-driven learning technology was created as the engine and dashboard to drive learners through four crucial steps in a persuasive technology and design for language learning. The first step is to reduce challenges of learning through instant feedback on practice and to reward the learner with ongoing assessment of progress. The second step is to design for effective and efficient learning by forcing students to follow a specific path through tasks under surveillance of performance. This case is made for learning to read the Hebrew Bible through course material delivered at the My Biblical Hebrew Moodle website (https://mbh.3bmoodle.dk/). The third step is to enhance learning through adaptive tailoring to the need of learners who monitor their own practice. We discuss rich empirical evidence on daily online progression that documents self-directed learning. We have not yet reached the fourth and final step in a persuasive online language learning system, but we believe that it should include social experience from intensive courses, peer-based collaborative learning and enrichment by exposure to a use of modern Hebrew in Israel.

International Swimming League: Do Successive Events Lead to Improve Swimming Performance?

To quantify the impact of successive competitions on swimming performance in world-class swimmers. An entire data set of all events swum during a new competition named the International Swimming League was collected. A Bayesian linear mixed model has been proposed to evaluate whether a progression could be observed during the International Swimming League's successive competitions and to quantify this effect according to event, age, and gender. An overall progression of 0.0005 (0.0001 to 0.0010)m/s/d was observed. The daily mean progression (ie,faster performance) was twice as high for men as for women (0.0008 [0.00 to 0.0014] vs 0.0003 [-0.0003 to 0.0009]m·s-1). A tendency toward higher progression for middle distances (200 and 400m) and for swimmers of a higher caliber (above 850 FINA [Fédération Internationale de Natation] points) was also observed. Swimmers between 23 and 26years of age seemed to improve their swimming speed more in comparison with the other swimmers. This new league format, which involves several competitions in a row, seems to allow for an enhancement in swimming performance. Coaches and their support staff can now adapt their periodization plan in order to promote competition participation.

A PRELIMINARY EVALUATION ON BIVARIATE ALLOMETRY IN ACTIVE-FEEDING Chrysomya megacephala (FABRICIUS, 1794) (DIPTERA: CALLIPHORIDAE) LARVAE

The potential use of larval cephalopharyngeal skeleton as an alternative growth indicator in forensic entomology practice was assessed based on its developmental pattern, growth performance and allometric relationship with larval body. Chrysomya megacephala (Fabricius, 1794), was used as an experimental species and larval development were studied at ambient temperatures and relative humidity. Larval body size was measured from furthest part of the head to the last abdominal segment. Cephalopharyngeal skeleton was extracted from the body and measured from the tip of dorsal bridge to the left face of dorsal cornu. Daily progression of larval body length and cephalopharyngeal skeleton length showed the latter significantly had slower growth rates. The allometry of larval body and cephalopharyngeal skeleton showed they were correlated only because both variables increased across the three larval instars, which suggesting a spurious correlation. Separate bivariate correlations between the two variables showed only the first instar larvae had a significant (p<0.01) but weak correlation, r=0.33. However, removing the effect of larval instars still produced statistically significant correlation (p<0.001) albeit with moderate strength, r=0.57. From this study, there was not enough evidence to support cephalopharyngeal skeleton as an equal or a better alternative to larval body as growth indicator.

Modeling of Flowering Time in Vigna radiata with Approximate Bayesian Computation

Flowering time is an important target for breeders in developing new varieties adapted to changing conditions. A new approach is proposed that uses Approximate Bayesian Computation with Differential Evolution to construct a pool of models for flowering time. The functions for daily progression of the plant from planting to flowering are obtained in analytic form and depend on daily values of climatic factors and genetic information. The resulting pool of models demonstrated high accuracy on the dataset. Day length, solar radiation and temperature had a large impact on the model accuracy, while the impact of precipitation was comparatively small and the impact of maximal temperature has the maximal variation. The model pool was used to investigate the behavior of accessions from the dataset in case of temperature increase by 0.05–6.00°. The time to flowering changed differently for different accessions. The Pearson correlation coefficient between the SNP value and the change in time to flowering revealed weak but significant association of SNP7 with behavior of the accessions in warming climate conditions. The same SNP was found to have a considerable influence on model prediction with a permutation test. Our approach can help breeding programs harness genotypic and phenotypic diversity to more effectively produce varieties with a desired flowering time.

Simulation Model for Time to Flowering with Climatic and Genetic Inputs for Wild Chickpea

Accurate prediction of flowering time helps breeders to develop new varieties that can achieve maximal efficiency in a changing climate. A methodology was developed for the construction of a simulation model for flowering time in which a function for daily progression of the plant from one to the next phenological phase is obtained in analytic form by stochastic minimization. The resulting model demonstrated high accuracy on the recently assembled data set of wild chickpeas. The inclusion of genotype-by-climatic factors interactions accounted to 77% of accuracy in terms of root mean square error. It was found that the impact of minimal temperature is positively correlated with the longitude at primary collection sites, while the impact of day length is negatively correlated. It was interpreted as adaptation of accessions from highlands to lower temperatures and those from lower elevation river valleys to shorter days. We used bootstrap resampling to construct an ensemble of models, taking into account the influence of genotype-by-climatic factors interactions and applied it to forecast the time to flowering for the years 2021–2099, using generated daily weather in Turkey, and for different climate change scenarios. Although there are common trends in the forecasts, some genotypes and SNP groups have distinct trajectories.

Extreme Temperature Events Can Mitigate COVID-19 Morbidity in Warm Arid Environments: A Conclusion from Late Spring 2020 Heatwave in Egypt

The COVID-19 pandemic disease affects us all and get the world into an enormous crisis. Temperature is an important factor in infectivity reduction of viral disease. The current study screens the probable association between the extreme temperature events and COVID-19 outbreak. The most recent heatwave that hit Egypt in May 2020 selected as a case study. We studied the daily progression and current situation of COVID-19 morbidity in Egypt. The concurrent heatwave was identified and synoptically explained in deep. Considering the incubation-induced lag time between heatwave intensities and COVID-19 confirmed cases, visual interpretation of line graphs discovered an interesting identical

Wizards, Masks, and Metagnosis: Is the Pandemic Truly Changing Us?

Wizards, Masks, and Metagnosis: Is the Pandemic Truly Changing Us? Danielle Spencer (bio) How has the pandemic changed us, and what tools might we use to understand these changes? The mask is a useful figure in following these shifts. In March of 2020 when the first U.S. COVID-19 wave hit New York City, where I live, the streets were silent save the sound of ambulance sirens. Initially, wearing masks was verboten for non-clinicians. Then it became a voluntary act for the civic-minded, and then a mandate. In the present limbo of August 2021, as I write this piece, depending upon the context a mask can signal any number of things, from health status to political stance, to the daily progression of the Delta variant, to the intersection of global, federal, state, and local guidance and regulations—all in constant flux. And while living outside of societal norms has often been symbolized by masking (western gunslingers, superhero vigilantes, bank robbers), such a stance is now more likely struck by refusing to mask in the face of policy. How might the mask represent the changes wrought by the pandemic, and the possibilities it offers for further transformation? Alongside the figure of the mask, these changes can also be understood as an experience of metagnosis, a term I coined to describe the experience of learning something new about oneself when the “something” has always been there. It can occur with a medical diagnosis of a long-standing condition either when a condition remained undetected, or because of shifting diagnostic boundaries. Suddenly finding oneself in a different category often prompts abrupt reevaluation of terms like normal, impaired, or disabled. For example, when I learned of my lifelong undetected visual field “defect,” none of the labels such as defect or impairment seemed to fit, as it was my normal; yet at the same time, it was unquestionably real. Or when adults receive diagnoses [End Page 198] of ADHD or autism spectrum disorders—both of which have had considerable diagnostic expansion—they may feel an attenuation of life-long guilt and shame while simultaneously questioning the neurotypical bias of such pathological designations. Because these experiences often provoke a change in knowledge, “metagnosis” literally means changed-knowledge. In Metagnosis: Revela-tory Narratives of Health and Identity I examine this phenomenon as a fulcrum which generatively illuminates and destabilizes the balance between our bodies, lived experience, the material world, and the social constructions we deploy.1 Beyond individual diagnoses, it can illuminate experiences such as genetic revelations of biological parentage and geographic origin as well as broader realizations, such as societal reckoning with the longstanding disease of systemic racism. When it comes to the mask and its variable meanings for non-clinicians during the pandemic—it, too, can be understood as metagnosis, as it reveals ideologies, vulnerabilities, and attitudes which may not have been visible but were likely there all along. What is the significance of the mask for clinicians? What metagnostic moments might it reveal? Beyond their functional purpose, masks often symbolize professional identity. The physician memoir genre, for example, exhibits a persistent pattern of masking/unmasking, hiding and revealing. This theme is made explicit in titles such as Behind the Mask, Life Behind the Mask, Man Behind the Mask, View from Behind the Mask, Voice from Behind the Mask.2 Most of these “Behind the Mask” memoirs are by surgeons (who do wear masks while performing surgery) and all on this list are by men. Here the mask represents the barrier between physician and patient which these accounts tantalizingly promise to pull aside, showing the wizard behind the curtain. As surgeon Paul Ruggieri describes in his 2012 Confessions of a Surgeon: The Good, the Bad, and the Complicated . . . Life Behind the O.R. Doors: “I wrote this book to take you right up to the operating room table and give you an up-close view of what I see as a surgeon. I want you to meet the person behind the surgical mask.”3 Physician memoirs display this masking/unmasking trope in their cover imagery as well—explicitly, with a masked physician’s face, or suggestively, by only showing part of the...

Early-warning signals for disease activity in patients diagnosed with multiple sclerosis based on keystroke dynamics.

Within data gathered through passive monitoring of patients with Multiple Sclerosis (MS), there is a clear necessity for improved methodological approaches to match the emergence of continuous, objective, measuring technologies. As most gold standards measure infrequently and require clinician presence, fluctuations in the daily progression are not accounted for. Due to the underlying conditions of homogeneity and stationarity (the main tenets of ergodicity) not being met for the majority of the statistical methods employed in the clinical setting, alternative approaches should be investigated. A solution is to use a non-linear time series analysis approach. Here, Early-Warning Signals (EWS) in the form of critical fluctuations in Keystroke Dynamics (KD), collected using participant's smartphones, are investigated as indicators for a clinical change in three groups. These are patients with MS and changes in Magnetic Resonance Imaging (MRI), patients with MS but without changes in MRI, and healthy controls (HCs). Here, we report examples of EWS and changes in KD coinciding with clinically relevant changes in outcome measures in both patients with and without differences in the amount of MRI enhancing lesions. We also report no clinically relevant changes in EWS in the HC population. This study is a first promising step toward using EWS to identify periods of instability as measured by a continuous objective measure as a proxy for outcome measures in the field of MS.

S2678 Successful Immunosuppression Titration in Patient With Refractory Autoimmune Hepatitis and Severe COVID-19 Infection

INTRODUCTION: The clinical course and natural history of COVID-19 infection in patients with chronic liver disease on immunosuppressive therapy has not been well characterized. Below we describe a case of COVID-19 occurring in a man with severe autoimmune hepatitis (AIH), successfully treated with modification of his immunosuppression regimen and trial of remdesivir. CASE DESCRIPTION/METHODS: 37-year-old AA male with severe AIH, refractory to corticosteroids (CS) plus azathioprine and CS plus mycophenolate mofetil (MMF). Approximately 1 year ago he achieved a biochemical remission after treatment with high-dose intravenous CS and rituximab, followed by maintenance therapy with tacrolimus (trough levels 3-8), prednisone (10-40 mg daily) and MMF (3000 mg daily). One week prior to presentation, MMF was held and a hydroxychloroquine trial was started after COVID-19 testing was positive. Despite a 1-week trial, respiratory status declined requiring admission for oxygen supplementation. Vitals demonstrated a fever to 103.0F, tachycardia, and hypoxia to 83%. CT chest with contrast was consistent with COVID-19 respiratory infection. Non-rebreather mask was required within 72 hours for worsening hypoxia. With increasing oxygen demands, a trial of immunosuppression titration was begun. Home dosing was adjusted: tacrolimus lowered from 3mg BID to 1mg daily, prednisone 10mg BID switched to methylprednisolone 20mg BID, and a 5-day remdesivir trial was started. Tacrolimus level remained subtherapeutic (< 3ng/mL). Liver chemistries stayed within normal ranges with these changes. Oxygen demands decreased while on methylprednisolone/remdesivir and less tacrolimus. As clinical status improved, the patient was discharged on prednisone 15mg BID and tacrolimus 1mg daily with close follow-up for further titration. DISCUSSION: Immunosuppressed AIH patients with severe respiratory infections demonstrate significantly increased mortality. Currently no clinical data exist on immunosuppression titration during active COVID-19 infection and thus only anecdotal evidence is available. Viral clearance requires intact T-cell function, which is disrupted by purine synthesis and calcineurin inhibitors like MMF and tacrolimus. Holding these agents should permit more T-cell activity and better immune response to COVID-19. Steroid have been theorized to possibly aid during higher cytokine activity as COVID-19 progresses, but evidence is minimal. Larger retrospective COVID-19 studies could add insight to immunosuppressed AIH patient outcomes.Figure 1.: CT Chest with contrast at presentation demonstrating bilateral ground glass opacities 1 week after diagnosis of COVID-19 infection.Table 1.: Daily progression of liver chemistries, inflammatory markers, and oxygen requirements throughout immunosuppression titration

All-hazards dataset mined from the US National Incident Management System 1999\u20132014

This paper describes a new dataset mined from the public archive (1999–2014) of the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (a total of 124,411 reports for 25,083 incidents, including 24,608 wildfires). This system captures detailed information on incident management costs, personnel, hazard characteristics, values at risk, fatalities, and structural damage. Most (98.5%) of the reports are fire-related, followed in decreasing order by other, hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use due to multiple record formats, inconsistent free-form fields, and no bridge between individual reports and high-level incident analysis. Here, we describe this improved dataset and the open, reproducible methods used, including merging records across three versions of the system, cleaning and aligning with the current system, smoothing values across reports, and supporting incident-level analysis. This integrated record offers the opportunity to explore the daily progression of the most costly, damaging, and deadly events in the U.S., particularly for wildfires.

Satellite-Based Fire Progression Mapping: A Comprehensive Assessment for Large Fires in Northern California

Satellite-based active fire (AF) products provide opportunities for constructing continuous fire progression maps, a critical dataset needed for improved fire behavior modeling and fire management. This study aims to investigate the geospatial interpolation techniques in mapping the daily fire progression and assess the accuracy of the derived maps from multisensor AF products. We focused on 42 large wildfires greater than 5000 acres in Northern California from 2017 to 2018, where the USDA Forest Service National Infrared Operations (NIROPS) daily fire perimeters were available for the comparison. The standard AF products from the moderate resolution imaging spectroradiometer (MODIS), the visible infrared imaging radiometer suite (VIIRS), and the combined products were used as inputs. We found that the estimated fire progression areas generated by the natural neighbor method with the combined MODIS and VIIRS AF input layers performed the best, with R 2 of 0.7 ± 0.31 and RMSE of 1.25 ± 1.21 (103 acres) at a daily time scale; the accuracy was higher when assessed at a two-day rolling window, e.g., R 2 of 0.83 ± 0.20 and RMSE of 0.74 ± 0.94 (103 acres). A relatively higher spatial accuracy was found using the 375 m VIIRS AF product as inputs, with a kappa score of 0.55 and an overall accuracy score of 0.59, when interpolated with the natural neighbor method. Furthermore, the locational pixel-based comparison showed 61% matched to a single day and an additional 25% explained within ±1 day of the estimation, revealing greater confidence in fire progression estimation at a two-day moving time interval. This study demonstrated the efficacy and potential improvements of daily fire progression mapping at local and regional scales.

Perspectives on decision making amongst older people with end-stage renal disease and caregivers in Singapore: A qualitative study.

BackgroundEnd‐stage renal disease (ESRD) is increasing both globally and in Asia. Singapore has the fifth highest incidence of ESRD worldwide, a trend that is predicted to rise. Older patients with ESRD are faced with a choice of haemodialysis, peritoneal dialysis or conservative management, all of which have their risks and benefits.ObjectiveThis study seeks to explore perspectives on decision making amongst older (≥70) Singaporean ESRD patients and their caregivers to undergo (or not to undergo) dialysis.DesignQualitative study design using semi‐structured interviews.Setting and participantsTwenty‐three participants were recruited from the largest tertiary hospital in Singapore: seven peritoneal dialysis patients, five haemodialysis patients, four patients on conservative management and seven caregivers.ResultsWhile some patients believed that they had made an independent treatment decision, others reported feeling like they had no choice in the matter or that they were strongly persuaded by their doctors and/or family members to undergo dialysis. Patients reported decision‐making factors including loss of autonomy in daily life, financial burden (on themselves or on their families), caregiving burden, alternative medicine, symptoms and disease progression. Caregivers also reported concerns about financial and caregiving burden.Discussion and conclusionThis study has identified several factors that should be considered in the design and implementation of decision aids to help older ESRD patients in Singapore make informed treatment decisions, including patients' and caregivers' decision‐making factors as well as the relational dynamics between patients, caregivers and doctors.

SUN-256 Pure water intake and chronic kidney disease progression to end-stage

An adequate hydration seems to have a beneficial effect on the prevention of Chronic Kidney Disease (CKD) in the general population. In individuals with CKD, the associations between daily water intake and disease progression are unclear. The objective of this study was to investigate the association between pure water intake and the risk for end-stage kidney disease (ESKD) - requiring renal replacement therapy - in patients with moderate or advanced CKD. This study is based on 3032 patients from the national Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) that includes 40 nephrology clinics in France. Usual pure water intake at baseline (over a week) was assessed from patient interview. Cox models were used to estimate adjusted hazard ratios (HRs) and their 95% confidence intervals (CI) of ESKD associated with water intake divided into 5 classes: <0.5, 0.5-1, 1-1.5, 1.5-2.0, ≥2.0 L/d. In a sub-group of patients with baseline 24h urine collection (N=1271), we assessed the impact of adjusting for osmole excretion on this association. Patients’ median (IQR) age was 69 (60-76) years and eGFR, 31.8 (23.1-41.2) ml/min per 1.73m²; 35% were women and 43% had diabetes. Median (IQR) pure water intake at baseline was 1.5 (1.0-2.0) L/day. There was no difference in water intake according to CKD stage (p=0.11). Percentages of patients according to the 5 water intake classes were 7, 29, 36, 18, and 11, respectively. An older age, female gender, lower BMI, lack of dietician visit, and cardiovascular history were associated with lower water intake whereas high educational level, and living in the South of the France were associated with higher water intake. Over a median follow-up of 3.0 years (IQR, 2.0-3.2), 480 patients progressed to ESKD. As compared to patients with medium water intake (1-1.5L/d), adjusted HRs[CI] for ESKD were 1.24[0.83-1.86], 1.20[0.95-1.52], 1.17[0.89-1.53] and 1.29[0.97-1.72] for water intakes of <0.5, 0.5-1, 1.5-2.0, and ≥ 2.0L/d, respectively. In the subgroup, adjusted HRs were somewhat stronger, 1.55[0.87-2.78]. 1.53[1.05-2.25], 1.36[0.88-2.08] and 2.45[1.56-3.85] for <0.5, 0.5-1, 1.5-2.0 and ≥ 2.0L/d, respectively, despite similar median water intake and ESKD rate than the overall population. Osmole excretion rate decreased with decreasing eGFR, but adjusting for this variable did not modify the association: 1.48[0.82-2.66], 1.51[1.03-2.21], 1.35[0.88-2.08], 2.44[1.56-3.84] for each water intake class compared to patients with medium water intake. This study did not show an association between baseline pure water intake and CKD progression to end-stage. Further analyses are needed taking longitudinal water intake into account.

Disruption of skin microbiota contributes to salamander disease.

Escalating occurrences of emerging infectious diseases underscore the importance of understanding microbiome-pathogen interactions. The amphibian cutaneous microbiome is widely studied for its potential to mitigate disease-mediated amphibian declines. Other microbial interactions in this system, however, have been largely neglected in the context of disease outbreaks. European fire salamanders have suffered dramatic population crashes as a result of the newly emerged Batrachochytrium salamandrivorans (Bsal). In this paper, we investigate microbial interactions on multiple fronts within this system. We show that wild, healthy fire salamanders maintain complex skin microbiotas containing Bsal-inhibitory members, but these community are present at a remarkably low abundance. Through experimentation, we show that increasing bacterial densities of Bsal-inhibiting bacteria via daily addition slowed disease progression in fire salamanders. Additionally, we find that experimental-Bsal infection elicited subtle changes in the skin microbiome, with selected opportunistic bacteria increasing in relative abundance resulting in septicemic events that coincide with extensive destruction of the epidermis. These results suggest that fire salamander skin, in natural settings, maintains bacterial communities at numbers too low to confer sufficient protection against Bsal, and, in fact, the native skin microbiota can constitute a source of opportunistic bacterial pathogens that contribute to pathogenesis. By shedding light on the complex interaction between the microbiome and a lethal pathogen, these data put the interplay between skin microbiomes and a wildlife disease into a new perspective.