1,745 research outputs found
Patient-reported outcomes in patients with vitreous floaters:A systematic literature review
Seeking treatment for bothersome vitreous floaters is patient driven. To measure the impact of floaters and treatment on an individual's quality of life, patient-reported outcome measurements (PROMs) are essential. We review all studies using a PROM for patients with floaters. We evaluated content coverage against quality-of-life domains previously identified in other ophthalmic disorders, and against a qualitative study investigating quality-of-life issues in patients with floaters. We assessed measurement properties of PROMs using an extensive range of psychometric quality criteria. We identified 59 studies using 28 different PROMs. Many PROMs were not specifically developed for patients with floaters. Floater-specific PROMs were mostly based on content validation from an ophthalmologist or researcher perspective; two included a patient perspective. Using the outcomes of the qualitative study, we found that the floater-specific PROMs were narrow in their content coverage, with most items relating to visual symptoms and activity limitations. Testing the psychometric quality of PROMs was rare, and when employed mostly limited to responsiveness and known group validity. The remarkable high number of floater-specific PROMs reveals a need for such measurements in ophthalmology. Unfortunately, reporting on psychometric quality is limited, and content development is most often done without patient involvement.</p
Climate and surface mass balance of coastal West Antarctica resolved by regional climate modelling
West Antarctic climate and surface mass balance (SMB) records are sparse. To fill this gap, regional atmospheric climate modelling is useful, providing that such models are employed at sufficiently high horizontal resolution and coupled with a snow model. Here we present the results of a high-resolution (5.5 km) regional atmospheric climate model (RACMO2) simulation of coastal West Antarctica for the period 1979–2015. We evaluate the results with available in situ weather observations, remote-sensing estimates of surface melt, and SMB estimates derived from radar and firn cores. Moreover, results are compared with those from a lower-resolution version, to assess the added value of the resolution. The high-resolution model resolves small-scale climate variability invoked by topography, such as the relatively warm conditions over ice-shelf grounding zones, and local wind speed accelerations. Surface melt and SMB are well reproduced by RACMO2. This dataset will prove useful for picking ice core locations, converting elevation changes to mass changes, for driving ocean, ice-sheet and coupled models, and for attributing changes in the West Antarctic Ice Sheet and shelves to changes in atmospheric forcing
Gamma-glutamyltransferase is a strong predictor of secondary sclerosing cholangitis after lung transplantation for COVID-19 ARDS
Background: Lung transplantation (LTx) can be considered for selected patients suffering from COVID-19 acute respiratory distress syndrome (ARDS). Secondary sclerosing cholangitis in critically ill (SSC-CIP) patients has been described as a late complication in COVID-19 ARDS survivors, however, rates of SSC-CIP after LTx and factors predicting this detrimental sequela are unknown. Methods: This retrospective analysis included all LTx performed for post-COVID ARDS at 8 European LTx centers between May 2020 and January 2022. Clinical risk factors for SSC-CIP were analyzed over time. Prediction of SSC-CIP was assessed by ROC-analysis. Results: A total of 40 patients were included in the analysis. Fifteen patients (37.5%) developed SSC-CIP. GGT at the time of listing was significantly higher in patients who developed SSC-CIP (median 661 (IQR 324-871) vs 186 (109-346); p = 0.001). Moreover, higher peak values for GGT (585 vs 128.4; p < 0.001) and ALP (325 vs 160.2; p = 0.015) were found in the ‘SSC’ group during the waiting period. Both, GGT at the time of listing and peak GGT during the waiting time, could predict SSC-CIP with an AUC of 0.797 (95% CI: 0.647-0.947) and 0.851 (95% CI: 0.707-0.995). Survival of ‘SSC’ patients was severely impaired compared to ‘no SSC’ patients (1-year: 46.7% vs 90.2%, log-rank p = 0.004). Conclusions: SSC-CIP is a severe late complication after LTx for COVID-19 ARDS leading to significant morbidity and mortality. GGT appears to be a sensitive parameter able to predict SSC-CIP even at the time of listing
Reports of Perceived Adverse Events of Stimulant Medication on Cognition, Motivation, and Mood:Qualitative Investigation and the Generation of Items for the Medication and Cognition Rating Scale
Items were identified that capture potential/perceived cognitive, motivational, and mood-related adverse events of MPH. The items generated will allow us to further develop and psychometrically examine their prevalence, and the extent to which they are associated with medication adherence, treatment outcome, impairment, and other reported adverse events (e.g., loss of appetite/cardiovascular effects)
The Impact of Methylphenidate on Pubertal Maturation and Bone Age in ADHD Children and Adolescents:Results from the ADHD Drugs Use Chronic Effects (ADDUCE) Project
Objective: The short-term safety of methylphenidate (MPH) has been widely demonstrated; however the long-term safety is less clear. The aim of this study was to investigate the safety of MPH in relation to pubertal maturation and to explore the monitoring of bone age.Method: Participants from ADDUCE, a two-year observational longitudinal study with three parallel cohorts (MPH group, no-MPH group, and a non-ADHD control group), were compared with respect to Tanner staging. An Italian subsample of medicated-ADHD was further assessed by the monitoring of bone age.Results: The medicated and unmedicated ADHD groups did not differ in Tanner stages indicating no higher risk of sexual maturational delay in the MPH-treated patients. The medicated subsample monitored for bone age showed a slight acceleration of the bone maturation after 24 months, however their predicted adult height remained stable.Conclusion: Our results do not suggest safety concerns on long-term treatment with MPH in relation to pubertal maturation and growth.</p
The Impact of Methylphenidate on Pubertal Maturation and Bone Age in ADHD Children and Adolescents:Results from the ADHD Drugs Use Chronic Effects (ADDUCE) Project
Objective: The short-term safety of methylphenidate (MPH) has been widely demonstrated; however the long-term safety is less clear. The aim of this study was to investigate the safety of MPH in relation to pubertal maturation and to explore the monitoring of bone age.Method: Participants from ADDUCE, a two-year observational longitudinal study with three parallel cohorts (MPH group, no-MPH group, and a non-ADHD control group), were compared with respect to Tanner staging. An Italian subsample of medicated-ADHD was further assessed by the monitoring of bone age.Results: The medicated and unmedicated ADHD groups did not differ in Tanner stages indicating no higher risk of sexual maturational delay in the MPH-treated patients. The medicated subsample monitored for bone age showed a slight acceleration of the bone maturation after 24 months, however their predicted adult height remained stable.Conclusion: Our results do not suggest safety concerns on long-term treatment with MPH in relation to pubertal maturation and growth.</p
Eliciting taxpayer preferences increases tax compliance
Two experiments show that eliciting taxpayer preferences on government spending—providing taxpayer agency--increases tax compliance. We first create an income and taxation environment in a laboratory setting to test for compliance with a lab tax. Allowing a treatment group to express nonbinding preferences over tax spending priorities, leads to a 16% increase in tax compliance. A followup online study tests this treatment with a simulation of paying US federal taxes. Allowing taxpayers to signal their preferences on the distribution of government spending, results in a 15% reduction in the stated take-up rate of a questionable tax loophole. Providing taxpayer agency recouples tax payments with the public services obtained in return, reduces general anti-tax sentiment, and holds satisfaction with tax payment stable despite increased compliance with tax dues. With tax noncompliance costing the US government $385billion annually, providing taxpayer agency could have meaningful economic impact. At the same time, giving taxpayers a voice may act as a two-way "nudge," transforming tax payment from a passive experience to a channel of communication between taxpayers and government
Dark sectors 2016 Workshop: community report
This report, based on the Dark Sectors workshop at SLAC in April 2016,
summarizes the scientific importance of searches for dark sector dark matter
and forces at masses beneath the weak-scale, the status of this broad
international field, the important milestones motivating future exploration,
and promising experimental opportunities to reach these milestones over the
next 5-10 years
Optic Nerve Head Quantification in Idiopathic Intracranial Hypertension by Spectral Domain OCT
Objective: To evaluate 3D spectral domain optical coherence tomography (SDOCT) volume scans as a tool for quantification of optic nerve head (ONH) volume as a potential marker for treatment effectiveness and disease progression in idiopathic intracranial hypertension (IIH). Design and Patients: Cross-sectional pilot trial comparing 19 IIH patients and controls matched for gender, age and body mass index. Each participant underwent SDOCT. A custom segmentation algorithm was developed to quantify ONH volume (ONHV) and height (ONHH) in 3D volume scans. Results:Whereas peripapillary retinal nerve fiber layer thickness did not show differences between controls and IIH patients, the newly developed 3D parameters ONHV and ONHH were able to discriminate between controls, treated and untreated patients. Both ONHV and ONHH measures were related to levels of intracranial pressure (ICP). Conclusion: Our findings suggest 3D ONH measures as assessed by SDOCT as potential diagnostic and progression markers in IIH and other disorders with increased ICP. SDOCT may promise a fast and easy diagnostic alternative to repeated lumba
Non-Negative Matrix Factorization for Learning Alignment-Specific Models of Protein Evolution
Models of protein evolution currently come in two flavors: generalist and specialist. Generalist models (e.g. PAM, JTT, WAG) adopt a one-size-fits-all approach, where a single model is estimated from a number of different protein alignments. Specialist models (e.g. mtREV, rtREV, HIVbetween) can be estimated when a large quantity of data are available for a single organism or gene, and are intended for use on that organism or gene only. Unsurprisingly, specialist models outperform generalist models, but in most instances there simply are not enough data available to estimate them. We propose a method for estimating alignment-specific models of protein evolution in which the complexity of the model is adapted to suit the richness of the data. Our method uses non-negative matrix factorization (NNMF) to learn a set of basis matrices from a general dataset containing a large number of alignments of different proteins, thus capturing the dimensions of important variation. It then learns a set of weights that are specific to the organism or gene of interest and for which only a smaller dataset is available. Thus the alignment-specific model is obtained as a weighted sum of the basis matrices. Having been constrained to vary along only as many dimensions as the data justify, the model has far fewer parameters than would be required to estimate a specialist model. We show that our NNMF procedure produces models that outperform existing methods on all but one of 50 test alignments. The basis matrices we obtain confirm the expectation that amino acid properties tend to be conserved, and allow us to quantify, on specific alignments, how the strength of conservation varies across different properties. We also apply our new models to phylogeny inference and show that the resulting phylogenies are different from, and have improved likelihood over, those inferred under standard models
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