Dual autoencoders modeling of electronic health records for adverse drug event preventability prediction

Background Elderly patients are at increased risk for Adverse Drug Events (ADEs). Proactively screening elderly people visiting the emergency department for the possibility of their hospital admission being drug-related helps to improve patient care as well as prevent potential unnecessary medical costs. Existing routine ADE assessment heavily relies on a rule-based checking process. Recently, machine learning methods have been shown to be effective in automating the detection of ADEs, however, most approaches used only either structured data or free texts for their feature engineering. How to better exploit all available EHRs data for better predictive modeling remains an important question. On the other hand, automated reasoning for the preventability of ADEs is still a nascent line of research. Methods Clinical information of 714 elderly ED-visit patients with ADE preventability labels was provided as ground truth data by Jeroen Bosch Ziekenhuis hospital, the Netherlands. Methods were developed to address the challenges of applying feature engineering to heterogeneous EHRs data. A Dual Autoencoders (2AE) model was proposed to solve the problem of imbalance embedded in the existing training data. Results Experimental results showed that 2AE can capture the patterns of the minority class without incorporating an extra process for class balancing. 2AE yields adequate performance and outperforms other more mainstream approaches, resulting in an AUPRC score of 0.481. Conclusions We have demonstrated how machine learning can be employed to analyze both structured and unstructured data from electronic health records for the purpose of preventable ADE prediction. The developed algorithm 2AE can be used to effectively learn minority group phenotype from imbalanced data

Auchenorrhyncha and Psylloidea collected during the 25th Central European Auchenorrhyncha meeting, Arnhem, The Netherlands (Hemiptera: Auchenorrhyncha and Psylloidea)

Die 25. Mitteleuropäische Zikadentagung fand vom 14.-17. September 2018 in Arnheim in den Niederlanden statt. Da es die erste Tagung in den Niederlanden war, wurden Sammelexkursionen in fünf typische niederländische Landschaften unternommen. Drei der Exkursionsziele befanden sich in neu geschaffenen Schutzgebieten, die sich auf ehemals landwirtschaftlich genutzten Flächen befinden. Die beiden weiteren Exkursionsziele waren alte, geschützte Heideflächen. Insgesamt konnten 117 Zikadenarten und 6 Psylloidea-Arten nachgewiesen werden. Drei Arten waren neu für die Niederlande: Macrosteles spinosus (in dieser Publikation vorgestellt), Kybos abstrusus (monophag an Populus nigra) und Macrosteles sardus (an Epilobium hirsutum). Für einige seltene Arten konnten neue Fundpunkte ermittelt werden: Kelisia monoceros, Aphrophora major, Stroggylocephalus agrestis, Edwardsiana diversa, E. tersa, Fruticidia bisignata, Ophiola russeola und Psammotettix pallidinervis. Durch die drei Neufunde erhöht sich die Anzahl der bislang in den Niederlanden nachgewiesenen Zikadenarten auf 421. Diese Arbeit zeigt zudem, dass selbst in erst seit kurzem bestehenden Schutzgebieten seltene und interessante Arten nachgewiesen werden können. The 25th Central European Auchenorrhyncha meeting took place in Arnhem, The Netherlands on 14-17 September 2018. It was the first time the meeting was held in The Netherlands, and for this reason, excursions were undertaken to five typical Dutch landscapes. Three of the excursions involved newly created nature reserves, located on former agricultural land. The other two were old, protected heathlands. In total, 115 Auchenorrhyncha species, and 6 Psylloidea species were collected. Three species were new for the Netherlands: Macrosteles spinosus (presented in this paper), Kybos abstrusus (monophagous on Populus nigra) and Macrosteles sardus (Epilobium hirsutum). For a number of rare species new occurrences were reported: Kelisia monoceros, Aphrophora major, Stroggylocephalus agrestis, Edwardsiana diversa, E. tersa, Fruticidia bisignata, Ophiola russeola and Psammotettix pallidinervis. Our results show that also in young, newly created nature reserves interesting species can be found.&nbsp

Concomitant Intake of Coca-Cola to Manage the Drug-Drug Interaction Between Velpatasvir and Omeprazole Studied in Healthy Volunteers

Contains fulltext : 208787.pdf (publisher's version ) (Closed access)We aimed to evaluate the effect of the acid beverage Coca-Cola on the pharmacokinetics of velpatasvir (VEL) when given with omeprazole. This was an open-label, randomized, crossover trial in 11 healthy adults. A single dose of sofosbuvir/velpatasvir (SOF/VEL) 400/100 mg was administered alone (reference) or with omeprazole 40 mg once daily with water (intervention I); in the intervention II arm, omeprazole 40 mg was combined with 250 mL of Coca-Cola. Geometric mean ratios (GMRs) were calculated for VEL area under the concentration-time curve from zero to infinity (AUC0-inf ) and maximum plasma concentration (Cmax ). VEL exposure was reduced by 26.7% when SOF/VEL was coadministered with omeprazole vs. reference: GMRs (90% confidence interval (CI)) were 73.3% (55.6-96.8) and 69.1% (52.3-91.2) for AUC0-inf and Cmax , respectively. Intake of SOF/VEL with Coca-Cola compensated for the interaction with omeprazole and resulted in a higher VEL exposure. GMRs (90% CI) were 161.6% (122.4-213.3) for AUC0-inf and 143.9% (109.0-190.0) for Cmax . Therefore, Coca-Cola can be used to overcome the drug-drug interaction between VEL and omeprazole

Pharmacokinetic similarity demonstrated after crushing of the elbasvir/grazoprevir fixed-dose combination tablet for HCV infection

Contains fulltext : 225279.pdf (Publisher’s version ) (Open Access)BACKGROUND: Finding a suitable treatment for HCV patients with swallowing disorders is still a major challenge. In practice, direct-acting antivirals are crushed without knowledge of adequate absorption. Crushing can alter drug exposure, possibly leading to treatment failure, development of resistance or toxicity. Currently, there is no information about crushing of the fixed-dose combination tablet of elbasvir/grazoprevir; therefore, crushing of this tablet is not recommended. OBJECTIVES: To investigate the influence of crushing on the pharmacokinetics of the elbasvir/grazoprevir fixed-dose combination tablet. METHODS: We conducted an open-label, two-period, randomized, cross-over, Phase I, single-dose trial in 11 healthy adult volunteers. Subjects randomly received whole-tablet elbasvir/grazoprevir or crushed and suspended elbasvir/grazoprevir in a fasted state. Pharmacokinetic similarity criteria (90% CIs lie within 70%-143% acceptance range) were used for AUC0-∞ and AUC0-72. RESULTS: Mean plasma concentration-time curves of elbasvir and grazoprevir showed similar pharmacokinetic profiles. The primary pharmacokinetic parameters AUC0-∞ and AUC0-72 of elbasvir and grazoprevir after intake of a crushed tablet were on average 12%-16% higher compared with the whole tablet, but 90% CIs were all within the predefined boundaries of pharmacokinetic similarity. Crushing leads to a higher Cmax of grazoprevir (42%); no significant difference was found between treatments with regard to the Cmax of elbasvir. No serious adverse events were reported during the trial. CONCLUSIONS: Pharmacokinetic similarity could be demonstrated for a crushed and suspended tablet compared with a whole tablet, without impacting drug safety or efficacy. Crushed and suspended administration of elbasvir/grazoprevir can be used in patients with swallowing disorders

Dual autoencoders modeling of electronic health records for adverse drug event preventability prediction

Background Elderly patients are at increased risk for Adverse Drug Events (ADEs). Proactively screening elderly people visiting the emergency department for the possibility of their hospital admission being drug-related helps to improve patient care as well as prevent potential unnecessary medical costs. Existing routine ADE assessment heavily relies on a rule-based checking process. Recently, machine learning methods have been shown to be effective in automating the detection of ADEs, however, most approaches used only either structured data or free texts for their feature engineering. How to better exploit all available EHRs data for better predictive modeling remains an important question. On the other hand, automated reasoning for the preventability of ADEs is still a nascent line of research. Methods Clinical information of 714 elderly ED-visit patients with ADE preventability labels was provided as ground truth data by Jeroen Bosch Ziekenhuis hospital, the Netherlands. Methods were developed to address the challenges of applying feature engineering to heterogeneous EHRs data. A Dual Autoencoders (2AE) model was proposed to solve the problem of imbalance embedded in the existing training data. Results Experimental results showed that 2AE can capture the patterns of the minority class without incorporating an extra process for class balancing. 2AE yields adequate performance and outperforms other more mainstream approaches, resulting in an AUPRC score of 0.481. Conclusions We have demonstrated how machine learning can be employed to analyze both structured and unstructured data from electronic health records for the purpose of preventable ADE prediction. The developed algorithm 2AE can be used to effectively learn minority group phenotype from imbalanced data

Crushed application of sofosbuvir and velpatasvir in a patient with swallowing disorder

Contains fulltext : 220631.pdf (Publisher’s version ) (Closed access

Review article: direct-acting antivirals for the treatment of HCV during pregnancy and lactation - implications for maternal dosing, foetal exposure, and safety for mother and child

BACKGROUND: With the global efforts to eradicate hepatitis C virus (HCV), treatment during pregnancy is becoming a priority for research as this, and maternal cure should reduce vertical transmission. However, as information on the efficacy and safety of direct-acting antivirals (DAAs) in pregnancy is generally lacking, treatment of HCV infection during pregnancy is not currently recommended. AIM: To provide an overview of current knowledge regarding maternal exposure, placental handling and safety of DAAs during pregnancy and lactation METHODS: A literature search was performed focusing on the effect of pregnancy on maternal exposure to DAAs, the placental handling of DAAs, the safety of DAAs for mother and child during pregnancy and the safety of DAAs during lactation. RESULTS: Exposure to all DAAs studied is likely to be altered during pregnancy, mostly related to pregnancy-induced effects on drug absorption and metabolism. Although animal studies show that most DAAs are reported to cross the placenta and transfer into breast milk, most DAA combinations show a favourable safety profile. Because of the rapid viral decline after treatment initiation, and to avoid the critical period of organogenesis, treatment may be started at the end of the second trimester or early third trimester. CONCLUSIONS: Treatment of HCV infection during pregnancy is realistic, as DAAs are highly effective and treatment duration is relatively short. There is an urgent need to study DAAs during pregnancy and lactation to contribute to the goal of HCV elimination