dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2013) ; 6) the Information System for the Development of Research in Primary Care (SIDIAP), Catalonia, Spain  (García-Gil et al. , 2011) ; 7) the Clinical Practice Research Datalink (CPRD), United Kingdom (Williams et al. , 2012; , Herrett et al. , 2015); and 8) the 'Echantillon Généraliste de Bénéficiaires' (EGB), France  (Bezin et al. , 2017). The characteristics of the databases are described in Table  1  and in a previous publication  (Ibáñez et al. , 2019).
Analysis The analysis was performed using the first treatment episode, and stratified by database and individual DOAC at 12 months after the index date and by sex and age for the whole study period. Primary non-adherence was only performed in the SIDIAP and BIFAP databases on a sample where both prescriptions and dispensing could be linked for the individual patient. In BIFAP, since 2011 onwards and progressively implemented, currently only 14. 4% of all prescriptions could be linked to pharmacy dispensations while all prescriptions in SIDIAP could. These were the only participating databases with available information. -The persistence rate was estimated as the proportion of patients still on treatment at 3, 6, and 12 months (deceased patients were censored). The log-rank test was applied for analyzing differences in the time until discontinuation between the individual DOACs and specific subgroups of patients (chronic kidney disease [CDK] by diagnosis codes, see Supplementary Table  S2 ).
This information was available for all databases, except for the Bavarian Claims database. -The switching rate of all DOACs at 12 months was calculated as the number of patients switching treatment divided by the total number of patients included in the study population *100. The switching percentage by individual DOAC was calculated as patients switching treatment from the individual DOAC divided by the total number of patients treated with that individual DOAC *100. -The discontinuation rate was calculated as patients discontinuing treatment divided by patients initiating treatment *100 at 12 months and during the whole study period.
Persistence Rate The highest persistence rate for a DOAC at 12 months from treatment initiation was seen for apixaban in the CPRD database (81%) and the lowest rate was seen for dabigatran in the Mondriaan database (22%). Apixaban had the highest persistence at 12 months in all databases, except in the Mondriaan and AOK NORDWEST databases (range: 66% in the SIDIAP database to 81% in the CPRD database). Dabigatran showed the lowest persistence at 12 months in all databases except in the AOK NORDWEST database (range: 22% in the Mondriaan database to 70% in the CPRD database). The crude differences in persistence between each individual DOAC were statistically significant (log-rank test p values <0. 05) in all databases (Table  2 ; Figure  1 ). The results regarding persistence by the presence of CKD at baseline by an individual DOAC showed that patients with CKD had a lower persistence to DOACs than those without CKD (Figure  2 ).
Switching Rate The cumulative switching percentage at 12 months for all DOAC users ranged from 2. 4% in the Mondriaan database to 13. 1% in the EGB database. This percentage for the individual DOACs ranged from 1. 4% for rivaroxaban in the Mondriaan database to 20% for dabigatran in the EGB database (Table  3 ). Dabigatran had the highest switching rate at 12 months in all databases. No differences in the switcher rates in the overall period were observed among the different age groups, either for all DOACs or by individual DOACs (Supplementary Table  S5 ).
Discontinuation Rate Cumulative discontinuation rates of DOACs at 12 months ranged from 16% in the CPRD database to 63. 9% in the Bavarian CD database. The cumulative discontinuation percentage at 12 months ranged from 12. 3% for apixaban in the CPRD database to 69. 5% for apixaban in the Bavarian CD database (Table  3 ). Dabigatran had the highest percentage of discontinuers at 12 months in all databases (from 23. 2% in the CPRD database to 64. 6% in the Mondriaan database), except in the Bavarian CD and AOK NORDWEST databases, where apixaban and rivaroxaban had the highest proportion of discontinuers (69. 5 and 40. 2%, respectively) (Table  3 ). No differences were observed among the different age groups regarding discontinuation rates during the whole study period, either overall or by individual type of DOAC.
Sensitivity Analysis The analysis performed in users that received DOACs indicated for treating NVAF and had no other DOAC registered indications did not differ from the main analysis for switchers and discontinuers (Supplementary Table  S6 ). The analysis where a 60-days gap was applied to construct treatment episodes resulted in a decrease of discontinuation percentage for all patients compared to the main analysis, regardless of the type of DOAC used. The overall rates of DOAC discontinuers at 12 months decreased, ranging from 10. 2% in the CPRD database to 37. 0% in the Mondriaan database (for detailed information on the sensitivity analysis see Supplementary Tables S6-S8 of the Supplementary Material).
DISCUSSION This study provides an overview of DOAC adherence in eight different databases from six European countries. To the best of our knowledge, this is the first study displaying information on primary non-adherence and persistence to DOAC treatment in several European countries at a national or regional level using a common protocol approach. Primary non-adherence of all DOACs was 11. 1% in the BIFAP database and 14. 0% in the SIDIAP database. Apixaban is the DOAC with the highest persistence rate and lowest discontinuation rate at 12 months in all databases except in the German AOK and Dutch Mondriaan databases. Dabigatran had the highest proportion of discontinuers and switchers at 12 months in most databases.
Primary Non-Adherence Our results on primary non-adherence of all DOACs comparing two Spanish databases covering different populations are quite similar to those described in a study performed in the Valencia region of Spain, with primary non-adherence seen in 11% of all patients that received a prescription for a DOAC in the BIFAP database and 14% in the SIDIAP database  (Rodriguez-Bernal et al. , 2018). However, differences were found among individual DOACs between both databases. Apixaban had the lowest percentage of primary non-adherence (9%) in the BIFAP database while it showed the highest percentage (18%) in the SIDIAP database. The study from Valencia showed high differences between individual DOACs (from 5% for apixaban to 16% for rivaroxaban)  (Rodriguez-Bernal et al. , 2018). The progressive and lowest implementation, from 2011 in BIFAP, of the possibility to identify the dispensation linked to the prescription could explain the differences between BIFAP and SIDIAP.
Switching Rates In other published studies, the switching percentage was higher for dabigatran (17. 0-24. 7%) compared to rivaroxaban (14. 3-17. 6%) (Hellfritzsch et al. , 2017; Maura et al. , 2017) , which is consistent with our results. Moreover, the special precaution or contraindication of use of DOACs in patients with different levels of renal impairment could also help explain either the switch in some cases or the discontinuation in others. In addition, the ARISTOTLE trial publication showed that apixaban had less risk of bleeding than warfarin which could have favored the higher switching to apixaban  (Granger et al. , 2011). The switching percentages at 12 months for each one of the DOACs in the EGB, DNR, and CPRD databases in our study are slightly different (ranged from 2. 6 to 20%) than those observed in other studies performed in France, Denmark, and the United Kingdom  (Durham et al.
, 2017; Hellfritzsch et al. , 2017; Maura et al. , 2017)  (ranged from 24. 7 to 7%). In the French study, the switchers were defined as patients who had at least one reimbursement for VKA or for a DOAC that was different from the one initially received. This definition was different from our study  (Maura et al. , 2017). In the Danish study, using the Danish National Prescription Registry  (Hellfritzsch et al. , 2017) , the different exclusion criteria (excluding those patients with a history of valvular atrial fibrillation) in our study may explain the difference. In the published study using the CPRD database the inclusion criteria were different as they included new oral anticoagulants and DOAC users  (Durham et al. , 2017). In these three studies, as well as in ours, dabigatran was the DOAC with the highest percentage of switchers, maybe because it was poorly tolerated in some patients  (Connolly et al.
, 2009). An observational retrospective Dutch study using pharmacy dispensing data from the Foundation of Pharmaceutical Statistics (SFK) showed that 31% of incident DOAC users with atrial fibrillation (valvular atrial fibrillation included) switched to another anticoagulant at 12 months, with the majority switching to a VKA (67%), while 34% had discontinued at 12 months  (Zielinski et al. , 2019). In our study, the Mondriaan database showed a lower switching percentage and had the lowest switching percentages compared to the other databases. Perhaps the exclusion of the valvular atrial fibrillation, the lowest population coverage and the inclusion of specialist dispensing in the SFK may explain these differences  (Smeets et al. , 2018).
5% of dabigatran users to 11. 4% of apixaban users in the Danish study. Both studies included patients with atrial fibrillation without excluding those with diagnoses of cardiac valvular disease, and both included naive patients and patients switching from VKA. However, the German study may reflect a selected population of moderate-high risk patients, which may explain the observed differences. In the Danish study, the allowed gap for discontinuation was 60 days, which is similar to the one used in our sensitivity analysis. As expected, the results of our sensitivity analysis for the Danish database decreased the percentage of discontinuers and were more similar to those of the referenced studies. The different proportion of patients with previous use of VKA included in the German and Danish studies  (Beyer-Westendorf et al.
, 2015; Hellfritzsch et al. , 2017)  and the differences in the inclusion criteria might explain some of the divergences. In addition in the Bavarian databases due to the quarterly definition, an interruption of one quarter could not necessarily mean a termination of the therapy in all cases (e. g. , two prescriptions were prescribed in one quarter and then a quarter was skipped). Bleeding complications and the changes in underlying disease severity (e. g. , restoration of sinus rhythm) have been found to be the main reason for DOAC discontinuation  (Beyer-Westendorf et al. , 2015; Hellfritzsch et al. , 2017). Unfortunately, these data are not available in our study, but the high proportion of discontinuers warns us that we must be aware of these cases in clinical practice. The different approval dates for each DOAC (dabigatran was the first DOAC to be approved and apixaban is the more recent) could play a role in interpreting these results since older drugs might have a higher probability of being either switched or discontinued to new ones  (Ibáñez et al.
Strengths and Limitations The main strength is the use of eight databases that provided a large amount of real-world adherence data about patients receiving new DOAC prescriptions in six European countries. Common protocol and data specifications were used by all participants, with consistent inclusion and exclusion criteria for users, operational case definitions, and common analytical procedures in order to minimize methodological discrepancies as much as possible and facilitate comparison of results across data sources. In addition, results were blinded and shared with the whole consortium only after each center had completed their analysis, avoiding some information bias and promoting independent results. Moreover, the results of the sensitivity analysis excluding the users with other indications than NVAF were not different from the main analysis for switchers and discontinuers.
This suggests that the analysis with the whole included population is representative of DOAC use for NVAF. Primary non-adherence has been shown to predict health outcomes  (Jackevicius et al. , 2017; Rodriguez-Bernal et al. , 2018). Therefore it is important to have information about primary non-adherence. Our results could be useful as an approximation of the percentage of non-dispensed prescriptions when databases have only dispensing data  (Rodriguez-Bernal et al. , 2018). Unfortunately, in the present study, this information was only available for two databases (BIFAP and SIDIAP). In terms of limitations, we should first mention that validation of adherence to the first prescription, discontinuation, or switching through confirmation by physicians, patients, or clinical history notes was not performed.
In addition, inherent differences in the coding systems used in the databases may also have created differences in capturing the diagnosis of NVAF although efforts have been made to unify the different code systems. Despite the fact that codes had not been validated in this study, outcome validation has been performed in other studies showing high validity  (Ibáñez et al. , 2019). Information on the indication associated with the prescription might be incomplete since definite linkage between compound and indication is lacking in most of the databases  (Ibáñez et al. , 2019). Differences in the database characteristics such as population and drug coverage (DNR is the only national database), prescription or dispensing databases, and reimbursement conditions over time could partly explain the observed differences among databases  (Ibáñez et al.
, 2019). Additionally, each country has different health policies, national prescribing guidelines, and prescription patterns, which, among other intrinsic characteristics of the populations and their lifestyle, may contribute to the variability of results among the databases  (Komen et al. , 2017; Vlahović-Palcevski et al. , 2016). Our results suggest that adherence multifaceted interventions such as counseling or daily treatment support are needed and should be systematically encouraged at the DOAC initiation and repeatedly throughout the course of therapy  (Vrijens B, 2016) , although evidence of the interventions effects are inconsistent from study to study, and only a minority of controlled studies show an improvement on both adherence and clinical outcomes. Adherence is acknowledged as a complex behavior.
Current methods of improving medication adherence for chronic health problems are mostly complex and not very effective, so that the full benefits of treatment cannot be realized  (Nieuwlaat et al. , 2014). There is a need for further research and education to improve future DOAC utilization. This is a cross-national comparison study using real-world longitudinal data collected in eight European electronic health care databases. There were differences in the adherence characteristics and individual DOACs. The variations among database results might be explained by their characteristics, differences in national guidelines prescription pattern diversity, and the demographic characteristics of the population included. However, the overall adherence findings throughout the databases point to a common direction with a consistent similar pattern.
ACKNOWLEDGMENTS The research leading to these results was conducted as part of the activities of the  PE-PV Consortium (Pharmacoepidemiology and Pharmacovigilance Consortium) , which is a public academic partnership coordinated by the  University of Utrecht. The project has received support from the  European Medicines Agency  under the Framework service contract (nr EMA /2015/ 27/PH ) with regard to the reopening of competition no. 3. K. Janhsen  ( Witten/Herdecke University, Alfred-Herrhausen-Straße 50, 58448 Witten, Germany  ( UW/GH) ) and  A. Heeke  ( AOK NORDWEST, Kopenhagener Straße 1, 44269 Dortmund, Germany ). R. Gerlach  and  M. Tauscher  ( National Association of Statutory Health Insurance Physicians of Bavaria, Elsenheimerstr. 39, MD-80687 Munich, Germany ). The authors from the BIFAP database would like to acknowledge the excellent collaboration of the primary care general practitioners and pediatricians, and also the support of the regional governments to the database.
DATA AVAILABILITY STATEMENT The data analyzed in this study was obtained from the following databases: Julius General Practitioner Network (JHN), Danish National Registries (DNR), AOK NORDWEST database, Bavarian Association of Statutory Health Insurance Physicians database, base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP), Information System for Development of Research in Primary Care (SIDIAP), Clinical Practice Research Datalink (CPRD), Echantillon Généraliste de Bénéficiaires (EGB). Information on whom to contact with requests to access these datasets should be directed to EUPEPV@uu. nl.
, 2016. c is registered but not available for research due to confidentiality reasons. d For dispensing: MM/YY. e Number of reimbursed packages. f Only in prescribing data. Frontiers in Pharmacology | www. frontiersin. org November 2021 | Volume 12 | Article 682890 a Representative of general population. b Prescribing databases: collected information on prescribed drugs by GP; Reimbursement databases: collected information on dispensed drugs funded by Health Care Services; g Available for 28% of included population.
Intracellular calcium imaging DRG neuronal cells grown on coverslips were loaded with 2 μM of Fura2-AM (Invitrogen, Eugene, OR, USA) in Tyrode's solution (Sigma-Aldrich, St-Louis, MO, USA) [in nM 12 NaHCO 3 , 6 D-glucose, and 10 HEPES] for 20 min at room temperature in the dark. Cells were then washed twice with 0. 1% bovine serum albumin (BSA, EM Science, Darmstadt, Germany) and incubated 20 min in Tyrode's solution to de-esterify the dye. Calcium responses were determined by measuring fluorescence intensity changes using an epifluorescence microscope equipped with Metafluor software (Olympus Canada, Markham, ON, Canada). Isolated Fura2-AM loaded cells were selected and real-time calcium responses were monitored by alternating the excitation wavelengths between 340 and 380 nm every second.
Sciatic nerve sections were washed twice and incubated in appropriate secondary fluorescent antibody, goat anti-rabbit IgG Alexa Fluor™-488, or goat anti-guinea-pig IgG Alexa Fluor™-488 (1: 500, Invitrogen Molecular Probe, Burlington, ON, Canada) for 1 h at room temperature. Tissue sections were mounted with Aqua-Poly/Mount (Polysciences Inc. , Warrington, USA). The specificity of each assay was determined by omitting the primary or secondary antibody. Using a Leica DM4000B epifluorescence microscope (Leica Microsystems, Toronto, Canada), images were acquired using the same acquisition parameters (gain and exposure time). Captured images were analyzed using MetaMorph Offline Software. For each animal, 10 randomly selected sections were used for CCL2 or substance P fluorescence quantification.
Statistical analysis One-way or two-way analysis of variance followed by Bonferroni post-test to account for appropriate comparisons were used to analyze behavioral measurement and CCL2 release. The percentage of inhibition of mRNA increase measured by qPCR was analyzed with a Wilcoxon signed-rank test since a Gaussian distribution could not be assumed by d'Agostino and Pearson omnibus normality test. Calcium mobilization induced by CCL2 in CFA animals compared to naïve rats was evaluated by oneway ANOVA followed by Bonferroni post-test. The inhibitory effect of INCB3344 on calcium mobilization was assessed by a Student's t test. Statistical analyzes were performed by GraphPad Prism 7. 0 (GraphPad software Inc, San Diego, CA, USA). A P value under 0. 05 was considered significant.
The cumulative nociceptive response, expressed as mean area under the curve (A. U. C. ), is measured during the inflammatory phase. Data correspond to mean ± SEM (n = 8). Asterisks denote statistical significance (* , # P < 0. 05; ANOVA followed by Bonferroni's multiple comparison test) the cellular response as more than 30% of fluorescence change from baseline, we did not observe [Ca 2+ ] i response to CCL2 in DRG neurons from naïve animals, as compared to CFA-treated rats (Fig. 5e ). We next assessed if the blocking of CCR2 by preincubating INCB3344 prior to CCL2 stimulation reduced the calcium mobilization. At day 3 post-CFA, only 4% of INCB3344-treated neuronal cells responded to CCL2 compared to 66% in absence of the antagonist (Fig. 5d, e ). Furthermore, inhibition of CCR2 on day 10 post-CFA was less effective in reducing the [Ca 2+ ] i level.
Acknowledgements MAD held scholarships from the  CIHR  and the  Canadian Arthritis Network. EM was supported by a research fellowship from the  Fonds de Recherche en Santé du Québec (FRQ-S). VBL received a  CIHR scholarship award. PS is recipient of the  Canada Research Chair in Neurophysiopharmacology of Chronic Pain, director of the Sherbrooke's Neuroscience Centre  and member of the  FRQS-funded Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CR-CHUS ).
A depth series of Raman spectra were acquired from 7e10 different areas of the same skin site for each volunteer. The Raman instrument was calibrated once at the beginning of each experiment day according to the manufacturer's instructions. Before each measurement at a different skin site, the calcium fluoride window was cleaned with a single-use alcohol tissue wipe. Spectral analysis was performed using the SkinTools software (RiverD International B. V. ). The acquired spectra were fitted with the primary spectra of 18 components of the SC. To this database, the spectrum of caffeine was added. Each spectral series resulted in a depth caffeine concentration profile (given in mmol caffeine per gram of keratin). Caffeine concentration profiles were averaged for each time point. Before averaging, outliers were removed, including unstable values, owing to subject movement or pushing down too hard on the instrument window.
For each subject, the average profiles at baseline were subtracted from those after the patch application. Then the baseline-corrected average concentration profile for the infants was compared with that for adults. All data points in the graphs are shown as mean AE one SEM. Statistical comparison of two distributions was performed after Anderson-Darling normality test and test of variance (F-test) to select the appropriate t-test. Statistical significance was accepted at the level of a ¼ 0. 05. All data processing was performed using MATLAB routines and Excel software. The caffeine concentration profiles in the SC were used to calculate the following parameters: (i) the caffeine concentration at the SC surface; (ii) the gradient of the profile in the first 15 mmofthe SC, which relates to the diffusion coefficient; and (iii) the area under the curve representing the total amount of caffeine that penetrated the SC.
ACKNOWLEDGMENTS An initial development of the infant skin model as an adaptation of the original adult structural model was done in collaboration with  Erika Tsingos and Niels Grabe of the Hamamatsu Tissue Imaging and Analysis Center  ( BIOQUANT, University of Heidelberg, Germany ) and  Steinbeis Center for Medical Systems Biology, Heidelberg, Germany. We would like to thank  Pierre-Francois Roux  and  Elise Boireau-Adamezyk  for their help in Raman data analysis.