3,446 research outputs found

    Multimodal interventions to enhance adherence to secondary preventive medication after stroke: a systematic review and meta-analyses

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    Summary: Introduction: Nonadherence to secondary preventative medications after stroke is common and is associated with poor outcomes. Numerous strategies exist to promote adherence. We performed a systematic review and meta-analysis to describe the efficacy of strategies to improve adherence to stroke secondary prevention. Methods: We created a sensitive search strategy and searched multiple electronic databases (MEDLINE, EMBASE, CINAHL, PsycINFO, CENTRAL, and Web of Knowledge) for studies of interventions that aimed to enhance adherence to secondary preventative medication after stroke. We assessed quality of included studies using the Cochrane tool for assessing risk of bias. We performed narrative review and performed meta-analysis where data allowed. Results: From 12,237 titles, we included seventeen studies in our review. Eleven studies were considered to have high risk of bias, 3 with unclear risk, and 3 of low risk. Meta-analysis of available data suggested that these interventions improved adherence to individual medication classes (blood pressure-lowering drugs – OR, 2.21; 95% CI (1.63, 2.98), [P < 0.001], lipid-lowering drugs – OR, 2.11; 95% CI (1.00, 4.46), [P = 0.049], and antithrombotic drugs – OR, 2.32; 95% CI (1.18, 4.56, [P = 0.014]) but did not improve adherence to an overall secondary preventative medication regimen (OR, 1.96; 95% CI (0.50, 7.67), [P = 0.332]). Conclusion: Interventions can lead to improvement in adherence to secondary preventative medication after stroke. However, existing data is limited as several interventions, duration of follow-up, and various definitions were used. These findings need to be interpreted with caution

    Procedural Risk in Congenital Cardiac Catheterization (PREDIC3T)

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    Background Advancements in the field, including novel procedures and multiple interventions, require an updated approach to accurately assess patient risk. This study aims to modernize patient hemodynamic and procedural risk classification through the creation of risk assessment tools to be used in congenital cardiac catheterization. Methods and Results Data were collected for all cases performed at sites participating in the C3PO (Congenital Cardiac Catheterization Project on Outcomes) multicenter registry. Between January 2014 and December 2017, 23 119 cases were recorded in 13 participating institutions, of which 88% of patients were \u3c18 years of age and 25% \u3c1 year of age; a high-severity adverse event occurred in 1193 (5.2%). Case types were defined by procedure(s) performed and grouped on the basis of association with the outcome, high-severity adverse event. Thirty-four unique case types were determined and stratified into 6 risk categories. Six hemodynamic indicator variables were empirically assessed, and a novel hemodynamic vulnerability score was determined by the frequency of high-severity adverse events. In a multivariable model, case-type risk category (odds ratios for category: 0=0.46, 1=1.00, 2=1.40, 3=2.68, 4=3.64, and 5=5.25; al

    Who benefits from a prostate rectal spacer? Secondary analysis of a phase III trial

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    PURPOSE: Previously a phase III trial of a hydrogel rectal spacer during prostate radiation therapy found decreased toxicity and a clinically significant improvement in bowel quality of life (QOL) at 3 years by the Expanded Prostate Cancer Index. We performed a secondary analysis to identify men less likely to benefit. METHODS AND MATERIALS: Clinical and dosimetric data for the 222 patients enrolled on the SpaceOAR phase III trial were analyzed. The volume of rectum treated to 70 Gy (V70) and the quantitative analysis of normal tissue effects in the clinic (QUANTEC) rectal dose goals were used as surrogates for clinical benefit and plan quality. Mean bowel QOL was assessed at 15 and 36 months posttreatment and the likelihood of 1Ă— (5 points) or 2Ă— (10 points) minimally important difference changes were assessed. RESULTS: Rectal V70 was correlated with physician scored toxicity (P = .033) and was used as a surrogate for plan quality. There was no correlation between prostate volume and rectal V70 (r = 0.077). Rectal V70 pre- and post-hydrogel was 13% and 3% for the smallest prostates (\u3c40 mL) and 12% and 2% for the largest (\u3e80 mL). The relative reduction in rectal V70 of 78% did not vary by prespacer V70, but the absolute reduction was greater for a higher V70. All spacer plans met the 5 QUANTEC rectal dose constraints, although 92% of control plans met all constraints. At 3 years, those not meeting all QUANTEC goals had a 15.0-point (standard deviation 15.1) decline, control patients meeting QUANTEC goals had a 4.0-point (9.5) decline, and spacer had \u3e0.5 (7.6; P \u3c .01). Previous surgery was not correlated with QOL (P = .8). Across prognostic groups, including age, body mass index, previous surgery, target volume, or quality of radiation plans, there was no statistically significant heterogeneity in the relative benefit of spacer in decreasing the risk of 1Ă— or 2Ă— the minimally important difference declines. CONCLUSIONS: There was little heterogeneity in the likelihood of spacer reducing the risk of declines in bowel QOL across clinical and dosimetric variables. Even for the \u3e95% of plans meeting QUANTEC rectal criteria, hydrogel spacer provided potentially meaningful benefits

    Composition profiles of InAs–GaAs quantum dots determined by medium-energy ion scattering

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    The composition profile along the [001] growth direction of low-growth-rate InAs–GaAs quantum dots (QDs) has been determined using medium-energy ion scattering (MEIS). A linear profile of In concentration from 100% In at the top of the QDs to 20% at their base provides the best fit to MEIS energy spectra

    Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

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    OBJECTIVE: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vital parameter analytics using affordable computer-aided diagnosis could not only reduce diagnosis costs but improve patient management and outcomes. METHODS: In this study, we developed machine learning models using selective key pathological categories to identify clinical test attributes that will aid in accurate early diagnosis of CKD. Such an approach will save time and costs for diagnostic screening. We have also evaluated the performance of several classifiers with k-fold cross-validation on optimized datasets derived using these selected clinical test attributes. RESULTS: Our results suggest that the optimized datasets with important attributes perform well in diagnosis of CKD using our proposed machine learning models. Furthermore, we evaluated clinical test attributes based on urine and blood tests along with clinical parameters that have low costs of acquisition. The predictive models with the optimized and pathologically categorized attributes set yielded high levels of CKD diagnosis accuracy with random forest (RF) classifier being the best performing. CONCLUSIONS: Our machine learning approach has yielded effective predictive analytics for CKD screening which can be developed as a resource to facilitate improved CKD screening for enhanced and timely treatment plans

    PEO-PPO-PEO surfactant exfoliated graphene cyclodextrin drug carriers for photoresponsive release

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    Liquid exfoliated graphene sheets were incorporated within α-cyclodextrin-triblock copolymer supramolecular hydrogels prepared with a range of polyethylene oxide and polypropylene oxide block sizes and ratios allowing control over the release properties. The strong photothermal activity of graphene was employed to externally activate drug release from within the gels using near-infrared (NIR) irradiation. These supramolecular hybrid hydrogels showed thermoreversible changes in viscosity, which is necessary for an injectable, multiple release point drug delivery depot. This hybrid graphene-surfactant-α-CD gel system with thermoreversible properties is demonstrated herein to be externally NIR activated to induce controllable drug release.S.M.N. acknowledge financial support under the ARC Future Fellowship scheme FT100100177

    Characterisation of retrotransposon insertion polymorphisms in whole genome sequencing data from individuals with amyotrophic lateral sclerosis

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    The genetics of an individual is a crucial factor in understanding the risk of developing the neurodegenerative disease amyotrophic lateral sclerosis (ALS). There is still a large proportion of the heritability of ALS, particularly in sporadic cases, to be understood. Among others, active transposable elements drive inter-individual variability, and in humans long interspersed element 1 (LINE1, L1), Alu and SINE-VNTR-Alu (SVA) retrotransposons are a source of polymorphic insertions in the population. We undertook a pilot study to characterise the landscape of non-reference retrotransposon insertion polymorphisms (non-ref RIPs) in 15 control and 15 ALS individuals’ whole genomes from Project MinE, an international project to identify potential genetic causes of ALS. The combination of two bioinformatics tools (mobile element locator tool (MELT) and TEBreak) identified on average 1250 Alu, 232 L1 and 77 SVA non-ref RIPs per genome across the 30 analysed. Further PCR validation of individual polymorphic retrotransposon insertions showed a similar level of accuracy for MELT and TEBreak. Our preliminary study did not identify a specific RIP or a significant difference in the total number of non-ref RIPs in ALS compared to control genomes. The use of multiple bioinformatic tools improved the accuracy of non-ref RIP detection and our study highlights the potential importance of studying these elements further in ALS
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