Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

Hospital utilization rates following antipsychotic dose reductions: implications for tardive dyskinesia

Abstract Background Data are limited on the benefits and risks of dose reduction in managing side effects associated with antipsychotic treatment. As an example, antipsychotic dose reduction has been recommended in the management of tardive dyskinesia (TD), yet the benefits of lowering doses are not well studied. However, stable maintenance treatment is essential to prevent deterioration and relapse in schizophrenia. Methods A retrospective cohort study was conducted to analyze the healthcare burden of antipsychotic dose reduction in patients with schizophrenia. Medical claims from six US states spanning a six-year period were analyzed for ≥10% or ≥ 30% antipsychotic dose reductions compared with those from patients receiving a stable dose. Outcomes measured were inpatient admissions and emergency room (ER) visits for schizophrenia, all psychiatric disorders, and all causes, and TD claims. Results A total of 19,556 patients were identified with ≥10% dose reduction and 15,239 patients with ≥30% dose reduction. Following a ≥ 10% dose reduction, the risk of an all-cause inpatient admission increased (hazard ratio [HR] 1.17; 95% confidence interval [CI] 1.11, 1.23; P < 0.001), and the risk of an all-cause ER visit increased (HR 1.09; 95% CI 1.05, 1.14; P < 0.001) compared with controls. Patients with a ≥ 10% dose reduction had an increased risk of admission or ER visit for schizophrenia (HR 1.27; 95% CI 1.19, 1.36; P < 0.001) and for all psychiatric disorders (HR 1.16; 95% CI 1.10, 1.23; P < 0.001) compared with controls. A dose reduction of ≥30% also led to an increased risk of admission for all causes (HR 1.23; 95% CI 1.17, 1.31; P < 0.001), and for admission or ER visit for schizophrenia (HR 1.31; 95% CI 1.21, 1.41; P < 0.001) or for all psychiatric disorders (HR 1.21; 95% CI 1.14, 1.29; P < 0.001) compared with controls. Dose reductions had no significant effect on claims for TD. Conclusion Patients with antipsychotic dose reductions showed significant increases in both all-cause and mental health–related hospitalizations, suggesting that antipsychotic dose reductions may lead to increased overall healthcare burden in some schizophrenia patients. This highlights the need for alternative strategies for the management of side effects, including TD, in schizophrenia patients that allow for maintaining effective antipsychotic treatment

Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading

Abstract Background Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and transformed into a common format and standard terminologies, and optimally linked to other data sources. The expertise and scalable solutions needed to transform data to conform to network requirements are beyond the scope of many health care organizations and there is a need for practical tools that lower the barriers of data contribution to clinical research networks. Methods We designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code, while retaining manual aspects of the process that requires knowledge of complex coding syntax. This approach provides the flexibility required for the ETL of heterogeneous data, variations in semantic expertise, and transparency of transformation logic that are essential to implement ETL conventions across clinical research sharing networks. Processing workflows are directed by the ETL specifications guideline, developed by ETL designers with extensive knowledge of the structure and semantics of health data (i.e., “health data domain experts”) and target common data model. Results D-ETL was implemented to perform ETL operations that load data from various sources with different database schema structures into the Observational Medical Outcome Partnership (OMOP) common data model. The results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets. Conclusions D-ETL supports a flexible and transparent process to transform and load health data into a target data model. This approach offers a solution that lowers technical barriers that prevent data partners from participating in research data networks, and therefore, promotes the advancement of comparative effectiveness research using secondary electronic health data

Additional file 1: of Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading

Description of the custom D-ETL rules. (DOCX 13 kb

Supplementary Table 1: Aromatic L-amino acid decarboxylase deficiency: a systematic review

   Supplemental Table 1: Natural history database reference list</p

2018 National Beef Flavor Audit: Consumer and Descriptive Sensory Attributes

Beef flavor has been identified as a driver of consumer acceptability; however, little is known about variability of flavor in major United States retail beef cuts. Four beef cuts (chuck roast; top sirloin steaks; top loin steaks; and 80/20 ground beef) were obtained from retail stores (n=30 per cut per city) in Miami, Los Angeles, Portland, New York, and Denver during a 2-mo period in 2018. Production systems or package claims were documented. An expert trained flavor and texture descriptive attribute sensory panel evaluated beef flavors, aromas, and textures (n=10 cuts per city or 50 cuts evaluated). Consumer sensory panels in Fort Collins, CO (n=10 per cut/city), and Lubbock, TX (n=10 per cut/city), evaluated beef for overall liking, overall flavor, beef flavor, grilled flavor, juiciness, and texture liking. Ground beef patties (GB) were more intense (P&lt;0.0001) in brown, fat-like, green hay-like, and sour milk/sour dairy flavor aromatics and salty and sweet basic taste than steak or roast cuts. Additionally, GB had the lowest levels (P&lt;0.0001) of bloody/serumy, metallic, and liver-like flavor aromatics. Chuck roasts had the lowest levels of (P&lt;0.0001) beef flavor identity, brown, and roasted flavor aromatics and salt and umami basic tastes. Top sirloin steaks were lowest (P&lt;0.0001) in fat-like flavor aromatics and most intense (P&lt;0.0001) in burnt, cardboardy, bitter, and sour attributes. Top sirloin steaks and chuck roasts were more intense in metallic and liver-like (P&lt;0.0001) flavor aromatics. Consumers rated chuck roasts lowest for overall, overall flavor, grilled flavor, and juiciness liking (P&lt;0.04). GB and top loin steaks had the highest consumer texture liking (P&lt;0.0002). Beef descriptive flavor and texture attributes were related to consumer liking, and negative flavor aromatic attributes were identified. Variation in beef flavor attributes were reported in retail beef cuts and ground beef that impact consumer liking

Summary of TRACK-FA study procedures according to participant age.

The testing schedule varies according to age. All participants will also undergo a speech assessment, whilst all FRDA participants will undergo additional clinical testing.</p

The brain regions, modalities, and outcome measures for the TRACK-FA MRI protocol.

The brain regions, modalities, and outcome measures for the TRACK-FA MRI protocol.</p