Spiveymccleary7115
Altered resting-state functional connectivity in the default mode network (DMN) is characteristic of both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Standard analytical pipelines for resting-state functional connectivity focus on linear correlations in activation time courses between neural networks or regions of interest. These features may be insensitive to temporally lagged or nonlinear relationships.
In a twin cohort study comprising 292 children, including 52 with a diagnosis of ASD and 70 with a diagnosis of ADHD, we applied nonlinear analytical methods to characterize periodic dynamics in the DMN. Using recurrence quantification analysis and related methods, we measured the prevalence, duration, and complexity of periodic processes within and between DMN regions of interest. We constructed generalized estimating equations to compare these features between neurotypical children and children with ASD and/or ADHD while controlling for familial relationships, anbe a useful methodology for future neuroimaging studies.
The discovery of coding variants in genes that confer risk of intellectual disability (ID) is an important step toward understanding the pathophysiology of this common developmental disability.
Homozygosity mapping, whole-exome sequencing, and cosegregation analyses were used to identify gene variants responsible for syndromic ID with autistic features in two independent consanguineous families from the Arabian Peninsula. For invivo functional studies of the implicated gene's function in cognition, Drosophila melanogaster and mice with targeted interference of the orthologous gene were used. Behavioral, electrophysiological, and structural magnetic resonance imaging analyses were conducted for phenotypic testing.
Homozygous premature termination codons in PDZD8, encoding an endoplasmic reticulum-anchored lipid transfer protein, showed cosegregation with syndromic ID in both families. Drosophila melanogaster with knockdown of the PDZD8 ortholog exhibited impaired long-term courtship-based memory. selleck Mice ho with accruing evidence that synaptic defects are a common denominator of ID and other neurodevelopmental conditions.The IMPROVE study describes a large perioperative quality improvement project with reporting of both compliance with improvement activities and patient outcomes. It highlights the importance of such projects, as well as the challenges in implementing change and proving benefit. Challenges identified include the importance of effective training in practice change, selection of trial design and relevant quality measures, and how the context of quality improvement initiatives may influence outcomes. Quality improvement programmes of this nature, despite the difficulties with implementation and trial design, remain a high priority because of their positive influence on improving clinical practice.
This study aimed to examine the extent and quality of evidence from economic evaluations (EEs) of genetic-guided pharmacotherapy (PGx) for atrial fibrillation (AF) and to identify variables influential in changing base-case conclusions.
From systematic searches, we included EEs of existing PGx testing to guide pharmacotherapy for AF, without restrictions on population characteristics or language. Articles excluded were genetic tests used to guide device-based therapy or focused on animals.
We found 18 EEs (46 comparisons), all model-based cost-utility analysis with or without cost-effectiveness analysis mostly from health system's perspectives, of PGx testing to determine coumadin/direct-acting anticoagulant (DOAC) dosing (14 of 18), to stratify patients into coumadin/DOACs (3 of 18), or to increase patients' adherence to coumadin (1 of 18) versus non-PGx. Most PGx to determine coumadin dosing found PGx more costly and more effective than standard or clinical coumadin dosing (19 of 24 comparisons) but le approaches used to account for the effect of PGx testing to inform data collection and study design.
Several studies have shown that patients with heart disease value hypothetical health states differently from the general population. We aimed to investigate the health preferences of patients with heart disease and develop a value set for the 5-level EQ-5D (EQ-5D-5L) based on these patient preferences.
Patients with confirmed heart disease were recruited from 2 hospitals in Singapore. A total of 86 EQ-5D-5L health states (10 per patient) were valued using a composite time trade-off method according to the international valuation protocol for EQ-5D-5L; 20-parameter linear models and 8-parameter cross-attribute level effects models with and without an N45 term (indicating whether any health state dimension at level 4 or 5 existed) were estimated. Each model included patient-specific random intercepts. Model performance was evaluated for out-of-sample and in-sample predictive accuracy in terms of root mean square error. The discriminative ability of the utility values was assessed using heart disease-related functional classes.
A total of 576 patients were included in the analysis. The preferred model, with the lowest out-of-sample root mean square error, was a 20-parameter linear model including N45. Predicted utility values ranged from-0.727 for the worst state to 1 for full health; the value for the second-best state was 0.981. Utility values demonstrated good discriminative ability in differentiating among patients of varied functional classes.
An EQ-5D-5L value set representing the preferences of patients with heart disease was developed. The value set could be used for patient-centric economic evaluation and health-related quality of life assessment for patients with heart disease.
An EQ-5D-5L value set representing the preferences of patients with heart disease was developed. The value set could be used for patient-centric economic evaluation and health-related quality of life assessment for patients with heart disease.
To rank the US payers' preferences for attributes of real-world evidence (RWE) studies in the context of chronic disease and to quantify trade-offs among them.
We conducted a discrete choice experiment in which 180 employees from payer organizations were tasked to choose between 2 RWE studies assuming they were assessing evidence to inform formulary decisions for chronic disease treatment. Each RWE study was characterized by 7 attributes with 3 levels each very informative, moderately informative, and not measured. We used a D-optimal main-effects design. Survey data were fitted to a conditional logit model to obtain a relative measure of the ranking of importance for each attribute.
Clinical outcomes were the most preferred attribute. It was 4.68 times as important as productivity outcomes-the least preferred attribute. It was followed by health-related quality of life (2.78), methodologic rigor (2.09), resource utilization (1.71), and external validity (1.56).
This study provides a quantification ofesign.
The UK Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS-OM) developed using 30-year (1977-2007) data from the UKPDS is widely used for health outcomes' projections and economic evaluations of therapies for patients with type 2 diabetes (T2D). Nevertheless, its reliability for contemporary UK T2D populations is unclear. We assessed the performance of version 2 of the model (UKPDS-OM2) using data from A Study of Cardiovascular Events in Diabetes (ASCEND), which followed participants with diabetes in the UK between 2005 and2017.
The UKPDS-OM2 was used to predict the occurrence of myocardial infarction (MI), other ischemic heart disease, stroke, cardiovascular (CV) death, and other death among the 14 569 participants with T2D in ASCEND, all without previous CV disease at study entry. Calibration (comparison of predicted and observed year-on-year cumulative incidence over 10 years) and discrimination (c-statistics) of the model were assessed for each endpoint. The percentage error in event rates at year 7 (mean duration of follow up) was used to quantify model bias.
The UKPDS-OM2 substantially overpredicted MI, stroke, CV death, and other death over the 10-year follow-up period (by 149%, 42%, 269%, and 52%, respectively, at year 7). Discrimination of the model for MI and other ischemic heart disease (c-statistics 0.58 and 0.60, respectively) was poorer than that for other outcomes (c-statistics ranging from 0.66 to 0.72).
The UKPDS-OM2 substantially overpredicted risks of key CV outcomes and death in people with T2D in ASCEND. Appropriate adjustments or a new model may be required for assessments of long-term effects of treatments in contemporary T2D cohorts.
The UKPDS-OM2 substantially overpredicted risks of key CV outcomes and death in people with T2D in ASCEND. Appropriate adjustments or a new model may be required for assessments of long-term effects of treatments in contemporary T2D cohorts.
Most spending for prescription drugs is on branded drugs that do not have direct generic equivalents but many of these drugs do have therapeutic alternatives within class. We estimate the potential savings from providing patients a financial incentive to switch from a higher cost drug to a lower cost, therapeutic alternative drug.
We used individual state-transition microsimulations to model medication use and spending with and without financial incentives over a 12-month time horizon with a healthcare sector perspective. Costs and utilization inputs were from individuals on branded insulins or multiple sclerosis drugs enrolled in a regional mixed-model health maintenance organization. Base-case model used a one-time financial incentive of $83 and $250 offered to patients on higher cost insulin and multiple sclerosis treatments, respectively, to switch to lower cost drugs within class.
Savings per individual offered an incentive in the insulin and multiple sclerosis classes were, respectively, $84 (95% CI $46-$122) and $2,127 (95% CI $267-$3,987). Varying the incentive size and switch probability resulted in maximum savings of $712 at elasticity of 0.2 and incentive size $250 for the insulin drug class. For the multiple sclerosis drug class, maximum savings of $5945 was at elasticity of 0.2 and incentive size of $1000. Short time horizon makes our savings estimates conservative.
If programs such as financial incentives could encourage even a small proportion of patients to switch among drugs within therapeutic class, then substantial savings could be generated.
If programs such as financial incentives could encourage even a small proportion of patients to switch among drugs within therapeutic class, then substantial savings could be generated.
To the best of our knowledge, no published clinical guidelines have ever undergone an economic evaluation to determine whether their implementation represented an efficient allocation of resources. Here, we perform an economic evaluation of national clinical guidelines designed to reduce unnecessary blood transfusions before, during, and after surgery published in 2012 by Australia's sole public blood provider, the National Blood Authority (NBA).
We performed a cost analysis from the government perspective, comparing the NBA's cost of implementing their perioperative patient blood management guidelines with the estimated resource savings in the years after publication. The impact on blood products, patient outcomes, and medication use were estimated for cardiac surgeries only using a large national registry. We adopted conservative counterfactual positions over a base-case 3-year time horizon with outcomes predicted from an interrupted time-series model controlling for differences in patient characteristics and hospitals.
