Daniel Pape
email: danielpape@ua.pt

Luis M T Jesus

Pascal Perrier
email: pascal.perrier@gipsa-lab.grenoble-inp.fr

Constructing physically realistic VCV stimuli for the perception of stop voicing in European Portuguese

Keywords: biomechanical modelling, perceptual cues, cue weighting, European Portuguese, voicing perception

In this book chapter we present the generation of physically realistic stimuli with a biomechanical speech production model, with the aim to produce perceptually appropriate VCV sets for the European Portuguese (EP) voicing distinction. The duration measures necessary for the biomechanical model were extracted from an extensive EP speech production database, recorded for this aim. The same database was used to generate realistic voicing extinction contours for the perceptual continuum. To assess the realistic accuracy of the biomechanically generated stimuli, we compared the biomechanical stimuli set to linear interpolation between articulatory targets, traditionally used for speech synthesis.

Introduction

The work outlined in this book chapter consists of perceptual stimuli modelling as part of a research project on the importance of voicing maintenance in both speech production and perception in European Portuguese (EP) compared to other languages. For velar stop perception, we used and compared extracted voicing patterns and durational values from real speech productions (see [START_REF] Pape | Devoicing of phonologically voiced obstruents: Is European Portuguese different from other Romance languages?[END_REF]) in a matched cross-linguistic speech perception study, with the aim to examine the actual use and interaction (cue weighting) of the perceptual cues vowel duration, consonant duration and voicing maintenance. The speech material generated for the perceptual experiments consisted of biomechanically modelled stimuli acoustically synthesized with a three mass vocal fold model. The biomechanical modelling has the main advantage that all obtained tongue movements, trajectories and phoneme targets are comparable to natural speech, but with the additional possibility to manipulate all important temporal and glottal source parameters while maintaining articulatory realism. In sum, the use of biomechanical modelling is the best compromise to guarantee highly realistic perceptual stimuli, and to independently control parameters such as duration, transition and targets.

Perceptual Cues for Stop Voicing

For speech production, phonological voicing distinction is defined as the presence or absence of vocal fold vibrations during consonant production [START_REF] Jakobson | Preliminaries to Speech Analysis[END_REF]. For speech perception, a stop voicing distinction is mainly based on Voice Onset Time (VOT) [START_REF] Lisker | Cross-language study of voicing in initial stops[END_REF][START_REF] Lisker | Some effects of context on voice onset time in English stops[END_REF]. Cross-linguistic differences in voicing perception are captured by changes in the VOT boundaries, i.e., by the location of the identification boundaries between voicing categories on a VOT continuum [START_REF] Hoonhorst | French native speakers in the making: From language-general to language-specific voicing boundaries[END_REF]). In languages with three voicing categories (voiced, voiceless and voiceless aspirated) the mean VOT boundaries are located around ±30ms. Twocategory languages differ in the nature of their voicing categories. In languages with a voiceless aspirated contrast the boundary is at +30ms [START_REF] Lisker | The voicing dimension: Some experiments in comparative phonetics[END_REF], whereas for languages with voiced/voiceless contrast without aspiration the boundary is 0ms (for Spanish [START_REF] Williams | The voicing contrast in Spanish[END_REF]for French: Serniclaes 1987). Infants below six months of age raised in an English environment are sensitive to both VOT boundaries (±30ms, 0ms), although only the positive VOT boundary is phonological in English [START_REF] Aslin | Discrimination of voice onset time by human infants: New findings and implications for the effect of early experience[END_REF] or the 0ms VOT in the other language (French: [START_REF] Hoonhorst | French native speakers in the making: From language-general to language-specific voicing boundaries[END_REF]Spanish: Lasky et al. 1975).

VOT is one of the most dominant cues for characterising stops in a number of languages, but a number of additional perceptual cues are found to influence the perception of voicing: consonant and adjacent vowel duration [START_REF] Luce | Contextual effects on vowel duration, closure duration, and the consonant vowel ratio in speech production[END_REF][START_REF] Jessen | Phonetics and phonology of tense and lax obstruents in German[END_REF][START_REF] Cuartero | Voicing Assimilation in Catalan and English[END_REF][START_REF] Viana | Etude de deux aspects de consonantisme du portugais: fricatisation et devoisement[END_REF], and loudness [START_REF] Repp | Relative Amplitude of Aspiration Noise as a Voicing Cue for Syllable-Initial Stop Consonants[END_REF], among others. These other cues distinguish voicing, in combination with VOT but also without VOT, i.e., when VOT is ambiguous or missing. Further, the literature shows (Morrison 2005;[START_REF] Escudero | Native, non-native and L2 perceptual cue weighting for Dutch vowels: The case of Dutch, German, and Spanish listeners[END_REF]) that human perception does not rely only on a single perceptual cue, but rather on a combination of different cues to guarantee a stable and robust perceptual outcome. Taking into account the variety of perceptual cues for stop voicing, the question arises how different languages weight the available cue to achieve robust perception. However, few studies [START_REF] Francis | Effects of training on attention to acoustic cues[END_REF] attempted to study the simultaneous variation and cue weighting for stop voicing distinction, and (to our knowledge) no studies examined this cue weighting framework for stop voicing in a cross-linguistic context. The last point is of utmost importance when one takes into account speech production differences, for example, in voicing maintenance between different languages (see, e.g., Solé 2011 for Spanish vs. English, and Pape et al. (submitted) for EP vs. German and Italian). Given these cross-linguistic differences, the question arises whether these are also reflected in the perception, and if so, how these differences influence the cue weighting of the available cues.

Modelling Physically Realistic Perceptual Stimuli

One important point to take into account when designing a valid multidimensional cue weighting experiment are the transitions between the phoneme targets: For example, velar stops show a strong articulatory forward loop (see, e.g., [START_REF] Mooshammer | On loops[END_REF], additionally the shape of the loops differs for voiceless and voiced consonantal targets [START_REF] Brunner | Supralaryngeal control in Korean velar stops[END_REF]. Assuming that these loops could play a perceptual role, in the design of multidimensional perceptual stimuli one preferably aims for the most realistic synthesis model, with the aim to not disregard possible important influences on the perceptual system. However, it is not well understood how the temporal changes of articulatory pattern and thus the resulting articulatory trajectories are processed by the perceptual system. Thus, the particular model that is used to define and build a multidimensional stimuli space for perceptual experiments should be able to generate realistic articulatory movements, while simultaneously allowing for independent parametrical control of perceptual parameters, such as closure duration, vowel duration and transition duration. That is, in order to generate adequate perceptual stimuli for a cross-linguistic study on voicing distinction it is important to take into account the time-varying articulatory changes while producing a realistic phoneme chain with adequately realistic transitions. The most realistic perceptual stimuli would consist of naturally recorded speech, but for this condition one cannot control for the presence or lack of possible perceptual cues, therefore introducing an unwanted perceptual bias into the experiment.

There is no shortage of different models for articulatory motivated synthesis [START_REF] Maeda | Compensatory articulation during speech: Evidence from the analysis and synthesis of vocal-tract shapes using an articulatory model[END_REF][START_REF] Teixeira | Simulation of human speech production applied to the study and synthesis of European Portuguese[END_REF][START_REF] Birkholz | Articulatory synthesis and perception of plosive-vowel syllables with virtual consonant targets[END_REF]. However, very few of these models can claim to respect adequate articulatory movements. As soon as articulatory realistic transitions between the targets are required, only biomechanical models are currently capable of producing the required physically realistic articulatory trajectories. Thus, the use of a biomechanical modelling is the best compromise to guarantee highly realistic perceptual stimuli and independently control the varying parameters. Taking all these considerations into account, we used the advanced 2D tongue model described in [START_REF] Perrier | Influences of tongue biomechanics on speech movements during the production of velar stop consonants: A modeling study[END_REF] for the generation of suitable stimuli.

According to the biomechanical model described in [START_REF] Payan | Synthesis of V-V Sequences with a 2D biomechanical tongue model controlled by the Equilibrium Point Hypothesis[END_REF] and the improved version in [START_REF] Perrier | Influences of tongue biomechanics on speech movements during the production of velar stop consonants: A modeling study[END_REF], the tongue trajectories are obtained by activating (and thus deforming) different tongue muscles (Posterior and Anterior Genioglossus, Hyoglossus, Styloglossus, Verticalis, and Inferior longitudinalis) in a 2D Finite Element biomechanical model of the vocal tract, controlled on a target-totarget basis. The necessary vocal tract contours were extracted from X-ray data. The target for each phoneme is specified as a set of motor commands for each muscle. The movements between targets are achieved by a constant time shift of the motor commands between successive target values (as described in Perrier et al. 1996), resulting in time-varying vocal tract shapes (i.e., one complete 2D vocal tract shape each sampling period). Following, each of the obtained mid-sagittal vocal tract shapes is then converted to a time-dependent area function [START_REF] Perrier | Vocal tract area function estimation from midsagittal dimensions with CT scans and a vocal tract cast: Modeling the transition with two sets of coefficients[END_REF]. Then, the area functions were acoustically synthesized with a reflection-type line analog of the vocal tract [START_REF] Story | Acoustic impedance of an artificially lengthened and constricted vocal tract[END_REF]. Vocal folds oscillations are generated and controlled with a numerical implementation of the three mass model designed by [START_REF] Story | Voice simulation with a body-cover model of the vocal folds[END_REF] based on lumped-elements [START_REF] Titze | Rules for controlling low-dimensional vocal fold models with muscle activation[END_REF].

The biomechanical model was chosen because it has been shown to accurately account for articulatory trajectory shaping [START_REF] Perrier | Influences of tongue biomechanics on speech movements during the production of velar stop consonants: A modeling study[END_REF]) and velocity profiles [START_REF] Payan | Synthesis of V-V Sequences with a 2D biomechanical tongue model controlled by the Equilibrium Point Hypothesis[END_REF] in the mid-sagittal plane, all possibly important for consonant perception [START_REF] Sussman | Linear correlates in the speech signal: The orderly output constraint[END_REF][START_REF] Perrier | Speed-curvature relations in speech production challenge the 1/3 power jaw[END_REF]. Further, the model respects the relations between curvature and speed, which is found to be important in the correct perception of movements in general [START_REF] Viviani | Biological movements look uniform: evidence of motor-perceptual interactions[END_REF], and also for articulatory movements and thus speech [START_REF] Perrier | Speed-curvature relations in speech production challenge the 1/3 power jaw[END_REF]. As can be seen in figure 3 for the movement of the different tongue nodes, the biomechanical model accurately accounts for the articulatory forward loops observed in natural velar stop productions. These articulatory loops -and thus the naturalness of the model -mark an important difference between simple kinematic modelling (i.e., interpolating between consecutive articulatory target positions) and realistic biomechanical models. As described, the obtained accuracy of the transitions in the biomechanical model is important for our aims of the perceptual experiments, requiring that the resulting stimuli being as realistic as possible, but with the simultaneous independent control of all important parameters.

For the generation of the tongue contours, the biomechanical model needs the phoneme sequence identity (e.g., /aka/), the holding phase of each phone (e.g., 100ms) and the transition time from one phone to the other. Since all values for the biomechanical model are defined at the muscle command level that means that, e.g., the required holding phase does not correspond to the acoustic duration of a phone, but rather to a combination of transition and holding time (see section 2.1).

Method

Parameterisation of the Biomechanical Tongue Model

The biomechanical model, as described in [START_REF] Perrier | Influences of tongue biomechanics on speech movements during the production of velar stop consonants: A modeling study[END_REF], can be controlled with two different approaches as the input to the generation of the tongue contours: Inverse Synthesis; directly by entering the corresponding lambda commands for the different muscles 1 . For the EP stimuli generation we used the Inverse Synthesis approach. This Inverse Synthesis is implemented as follows: (1) Convex target regions have been defined in the (F1,F2,F3) acoustic space to specify the spectral characteristics of the elementary sounds of EP ; (2) relations between motor commands and formant values have been learned in the form of a radial basis functions model based on a large number of simulations with the biomechanical model; (3) for a given sequence of phonemes, the Inverse Synthesis Model finds the sequence of motor commands that minimizes the global change in motor commands while making sure that the successive target regions are reached at with the right timing. For more details about the procedure see [START_REF] Perrier | Modeling the production of VCV sequences via the inversion of a biomechanical model of the tongue[END_REF]. It is optimised by the inclusion of real speech formant and position data and their variance, thus Inverse Synthesis guarantees correct articulatory targets, which were extracted from cross-linguistic EMMA data. The biomechanical model's Inverse Synthesis approach accepts the input of phoneme 1 To obtain input of raw muscle data, the model accepts the input of alpha values for each target and muscle. These values contribute to specify muscle activation together with feedback information about current muscle length and length change rate. Muscle tissues stiffness is increased as a function of muscle activation. The more force is applied, the stiffer the muscle fiber remains. This possibility can be used to generate preferred articulatory targets and trajectories not already predefined, i.e., to force model to generate non-existing or impossible articulatory targets.

identity, phoneme duration and transition duration to generate from this information the resulting appropriate motor commands and corresponding muscle forces.

Figure 1 shows a block diagram illustrating the process of controlling the biomechanical model with the EP values extracted from the EP speech production database described in section 2.2. For our perceptual experiments in EP, the VCV stimuli were generated by the biomechanical model by defining the following parameters as the input:

identity of the context vowels adjacent to the velar stop (e.g., /aka/ or /iki/); vowel duration of the preceding and following vowel (from 70ms to 130ms); stop closure duration (from 50ms to 150ms); voicing maintenance during closure (from fully voiced to fully devoiced). We modelled the first three factors based on the durational values for EP as described in section 3.1. For this reason, we chose the vertices and step sizes of the parameters in accordance with the durational values shown in figure 2. Table 1 shows all parameters and the corresponding values used as orthogonal factors for the perceptual experiments. While the parameters vowel duration and consonant duration are controlled during the synthesis of the biomechanical tongue contours (by selecting appropriate t_hold and t_transition values for consonants and vowels), the parameter consonant voicing (or voicing maintenance) is generated during the following acoustic synthesis of the stimuli with the [START_REF] Story | Acoustic impedance of an artificially lengthened and constricted vocal tract[END_REF] model (see section 3.3).

In sum, for each vowel-stop-vowel item 15 fully factorized stimuli are generated (3 vowel_durations paired with 5 consonant_durations), which then are acoustically synthesized with 7 different consonant_voicing curves. The phoneme-to-phoneme transition time is set to a standard value of 60ms obtained from the EP database.

EP Real Speech Corpus

To obtain the holding and transition phase as the input into the biomechanical model it was necessary to measure durational values in the acoustic space from real EP speech data. For this aim, we computed durational measures from an extensive speech production database (see [START_REF] Pape | Devoicing of phonologically voiced obstruents: Is European Portuguese different from other Romance languages?[END_REF] generated for this purpose. The database was recorded for 4 EP speakers, consisting of /CV 1 CV 2 / items in the frame sentence Diga CVCV outra vez, with all EP stops and fricatives /p b t d k ɡ f v s z ʃ ʒ/ with the (identical) preceding and following (V 1 ,V 2 ) four vowel contexts /i e o a/. Thus, the consonants can be compared in initial (CV 1 CV 2 ) and medial (CV 1 CV 2 ) position. Each item was randomly repeated 9 times. Vowels and consonant boundaries are defined on base of the onset and offset of stable formant structure. We concentrate here on velar stops, the consonant modelled later in different contexts.

Results

Durational Measures from the EP Real Speech Corpus

Figure 2 shows the durational measures for the preceding vowel and velar stop in medial position. As can be seen, the consonant duration is higher for voiceless stops. Further, the vowel preceding the consonant is nearly twice as long for the voiced stop when compared to its voiceless counterpart. Thus, our EP data show clear differences for both preceding vowel and consonant duration between voiceless and voiced velar stops. The consonant durations are in line with EP durations found by Veloso (1995a[START_REF] Veloso | Aspectos da percepção das "ocusivas fricatizadas" do português. Contributo para a compreensão do processamento de contrastes alofónicos[END_REF][START_REF] Delgado Martins | Vogais e consoantes do Português: estatística de ocorrência, duração e intensidade[END_REF]. With respect to the expected intrinsic vowel duration differences (with low vowels being longer than high vowels [START_REF] Lehiste | Suprasegmentals[END_REF])) our database confirms this tendency for the preceding vowel duration.

We computed an ANOVA with the duration measures as dependent variable and the consonant identity /k ɡ/ as factor. For both the initial and the medial consonant position, the consonant duration was highly significantly (initial: p < 0.001; medial: p < 0.001). Further, the preceding vowel duration was highly significant for the medial consonant position (p < 0.001) but not for the initial position (p = 0.54). The duration of the following vowel was not significant for the medial position (p = 0.35). For initial position, nothing can be concluded about the following vowel duration, since the following vowel for the initial position is the preceding vowel for the medial position, so it is not clear which of the consonants influences the durational cues. The voiced and voiceless character of each item is defined by its phonological status.

Tongue Contour Trajectories for the EP Stimuli

For the biomechanical EP VCV stimulus (velar consonant, 100ms vowel duration, 125ms consonant duration), figure 3 shows the trajectories of selected tongue nodes for the production of /aka eke iki oko/ stimuli. All four plots clearly confirm that the biomechanical model correctly reproduces the forward articulatory loop that can be observed for natural velar stop production [START_REF] Mooshammer | On loops[END_REF].

We compared our modelled biomechanical stimuli with target-to-target synthesis approaches. These approaches are the standard in articulatory synthesis. Examples can be found in the [START_REF] Maeda | Compensatory articulation during speech: Evidence from the analysis and synthesis of vocal-tract shapes using an articulatory model[END_REF] approach, the 3D articulatory synthesizer [START_REF] Birkholz | Articulatory synthesis and perception of plosive-vowel syllables with virtual consonant targets[END_REF], the SpeechTrainer [START_REF] Kröger | Ein visuelles Modell der Artikulation[END_REF] and SAPWindows [START_REF] Teixeira | Simulation of human speech production applied to the study and synthesis of European Portuguese[END_REF]. For all these synthesis approaches, a number of articulatory targets are defined, and trajectories are achieved by a linear interpolation between targets. Figure 4 shows the illustration of the difference between several points on the tongue contour in the biomechanical model (in black) and targets for a target-to-target synthesis approach (dots in light colour). As can be seen in the right panel, the definition of one articulatory consonant target (here the highest point of the tongue contour) would results in very different articulatory tongue trajectories when comparing the biomechanical model (solid lines) and target-to-target approaches (dashed lines). It has to be noted that the differences between biomechanical and other synthesis approaches are less notorious when two consonantal targets are considered (e.g., the beginning and end of velar contact), however this approach is rarely used (Pape et al. 2011). Thus, the target-to-target approaches traditionally used for articulatory synthesis suffer from unrealistic modelling of the articulatory trajectories between targets, and are therefore unable to successfully model the articulatory loops seen in real speech articulatory data. Only the biomechanical model is able to reproduce these loops, as shown for all vowels and tongue nodes in the trajectories in figure 4.

Consonant Voicing Contours

To obtain the shapes of the velar stop consonant voicing curves we computed the mean curve over all repetitions and vowel contexts for each speaker of the EP database. Figure 5 shows the mean voicing probability estimate (9 repetitions, four vowels) computed for 10 consecutive equidistant landmarks throughout normalised consonant duration (see [START_REF] Pape | Devoicing of phonologically voiced obstruents: Is European Portuguese different from other Romance languages?[END_REF]. As can be seen, none of the voiced velar stops shows a linear decrease in voicing probability. Instead, the voicing decreases slower at the onset/offset of the curves, but faster during the mid. Due to this non-linear behaviour throughout the consonant closure, we chose to model our EP biomechanical stimuli by applying more realistic non-linear amplitude damping throughout the consonant closure. This was achieved by multiplying a weight to the consonant closure of the acoustically synthesized stimulus (i.e., the acoustic synthesis of the biomechanical tongue contours). In acoustic terms, this stimulus would correspond to the acoustic prototype of the /VɡV/ biomechanical synthesis without amplitude damping due to the closure of the vocal tract and glottal damping (Pape et al. 2011). The obtained amplitude damping for the generation of the different consonant voicing contours was generated by applying a weighting function to the amplitude of the /VɡV/ biomechanical stimulus. The shape of the weighting function was set as a cosine function ranging from 0 to π/2. The length of the cosine decrease was set to one quarter of the complete consonant duration. It was held identical for all consonant_voicing curves (steps given in table 1). The percentages of the consonant_voicing steps from table 1 define the landmarks where the cosine weighting reaches zero (π/2). Further, to avoid possible audible distortions due to jumps from full devoicing (zero) to full voicing amplitude we modelled the last 10ms of the consonant closure by weighting the fully voiced consonant with a sine function ranging from 0 to π/2. Figure 6 shows the modelled normalised six different weighting curves of the consonant_voicing steps (125ms stop duration, f s =48kHz). The procedure is illustrated for the 50% consonant_voicing curve (step5): At the consonant onset, no damping is applied to the acoustic synthesis output. Ranging from the first quarter until the consonant duration midpoint the amplitude is damped with a cosine weighting. The fully devoiced status is maintained until 10ms prior to consonant offset, where the 10ms sine-shaped increase to the consonant offset begins.

The fully devoiced condition (step1), was modelled by a 5ms cosine decrease at consonant onset and identical 10ms sine rise at consonant offset. The right panels in figure 6 show oscillograms of the acoustic synthesis for four different consonant_voicing steps with the overlaid weighting function envelopes.

Conclusions

For a perceptual experiment examining European Portuguese (EP) stop voicing we modelled physically realistic stimuli by means of a biomechanical model. The input to the biomechanical model, i.e., phoneme identities, phoneme durations, transitions between phonemes and voicing extinction curves, were generated from an extensive EP real speech corpus. The resulting EP biomechanical tongue contours comply with articulatory and aerodynamic laws, e.g., articulatory loops observed for velar stops. The models (voicing curves) for the generation of different devoicing conditions were based on the voicing curves in the EP database. The extraction of the EP velar stops devoicing slopes showed a nonlinear behaviour in real speech.

Fig. 1 .

 1 Fig. 1. Block diagram illustrating the process of integrating the EP production data into the biomechanical model.

Table 1 .

 1 Factors and step size for the generation of the perceptual stimuli. The steps are determined in accordance with the durational values given in section 3

Fig. 2 .

 2 Fig. 2. Boxplots of the preceding vowel duration (left panel) and velar stop duration (right panel) for medial position (all values in milliseconds), with the neighbouring vowel context on the x-axis. The voiced stop is shown in darker shading, the voiceless stop in lighter shading.The voiced and voiceless character of each item is defined by its phonological status.

Fig. 3 .

 3 Fig. 3. Trajectories of selected tongue nodes for /VkV/ stimuli for the vowel contexts /a e i o/. The lines in light colour show the vowel and velar stop target positions.

Fig. 4 .

 4 Fig. 4. The left panel shows four tongue surface trajectories for the /aka/ stimulus generated with the biomechanical model (in black). The dots in light colour exemplify the articulatory targets for a target-based synthesis. The right panel shows the differences in one tongue node trajectory between the biomechanical model (solid lines) and a given linear target-to-target trajectory (dashed lines, articulatory target at the highest point of the tongue contour).

Fig. 5 .

 5 Fig. 5. Mean voicing probability curves (over all vowel contexts and repetitions) for the EP velar stops during the normalised stop closure. Each panel corresponds to one EP speaker of the database, each line represents the mean of 36 items (9 repetitions x 4 vowel contexts).

Fig. 6 :

 6 Fig. 6:The left panel shows modelled devoicing curves (step1 to step6 in table 1) for a 120ms stop closure. The voicing extinction curve for step5 (full devoicing at consonant mid) is shown as a dashed line, the fully devoiced condition (step1) is shown as a dotted line. The four different voicing statuses throughout the consonant closure for step5 are given in light colour, with arrows corresponding to the duration. The right panel shows the oscillograms for four steps of the consonant voicing continuum: top and bottom panel show the vertices (fully voiced and fully devoiced); second and third panel show the partly voiced conditions (second panel step6 = 75% voiced; third panel step4 = 37.5%voiced).

Acknowledgements

This work was partially supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT), Portugal (grant SFRH/BPD/ 48002/2008).


MSc Kathrin Jobski

Sigrid Behr

MD, MSc Edeltraut Garbe
email: garbe@bips.uni-bremen.de

Drug Interactions with Phenprocoumon and the Risk of Serious Haemorrhage: A Nested Case-Control Study in a Large Population-based German Database

Keywords: drug interactions, oral anticoagulants, phenprocoumon, German Pharmacoepidemiological Research Database, nested case-control study

Drug interactions with phenprocoumon and the risk of serious haemorrhage: a nested case-control study in a large population-based German database

Introduction

Coumarin-type anticoagulants are widely used for the treatment and prevention of thromboembolic diseases. However, their use is complicated by a large inter-individual and intra-individual variability and a narrow therapeutic margin, which necessitates frequent monitoring of the anticoagulant effect and dosage adjustments. The most serious complication of treatment with vitamin K antagonists is an increased risk of bleeding. Major or lifethreatening haemorrhage during anticoagulant therapy with coumarins occurs at an estimated rate of 1.2-3.5 per 100 patient-years [START_REF] Gasse | Drug interactions and risk of acute bleeding leading to hospitalisation or death in patients with chronic atrial fibrillation treated with warfarin[END_REF][START_REF] Hollowell | The incidence of bleeding complications associated with warfarin treatment in general practice in the United Kingdom[END_REF][START_REF] Lindh | Incidence and predictors of severe bleeding during warfarin treatment[END_REF][START_REF] Palareti | Bleeding complications of oral anticoagulant treatment: an inception-cohort, prospective collaborative study (ISCOAT). Italian Study on Complications of Oral Anticoagulant Therapy[END_REF][START_REF] Van Der Meer | Bleeding complications in oral anticoagulant therapy. An analysis of risk factors[END_REF]. Several studies examining hospital admission because of adverse drug reactions found that coumarins were an important cause [START_REF] Budnitz | National surveillance of emergency department visits for outpatient adverse drug events[END_REF][START_REF] Pirmohamed | Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients[END_REF][START_REF] Van Der Hooft | Adverse drug reactionrelated hospitalisations: a nationwide study in The Netherlands[END_REF]. In Germany, oral anticoagulation with coumarins is usually conducted with phenprocoumon. 325.7 million defined daily doses (DDD) were prescribed in 2008, compared to 3.1 million DDDs of warfarin [START_REF] Hein | Antikoagulantien und Thrombozytenaggregationshemmer[END_REF]. Despite the similar chemical structure of the coumarins, there are substantial differences in their pharmacokinetic profile [START_REF] Ufer | Identification of cytochromes P450 2C9 and 3A4 as the major catalysts of phenprocoumon hydroxylation in vitro[END_REF]. Compared to warfarin and acenocoumarol, phenprocoumon metabolism is less dependent on the polymorphic CYP2C9 enzyme, while it may be more liable to CYP3A4-mediated drug interactions [START_REF] Ufer | Comparative pharmacokinetics of vitamin K antagonists: warfarin, phenprocoumon and acenocoumarol[END_REF][START_REF] Pharma | Marcumar Fachinformation www.fachinfo[END_REF][START_REF] Beinema | Pharmacogenetic differences between warfarin, acenocoumarol and phenprocoumon[END_REF]. About 40% of an oral dose of phenprocoumon is excreted unchanged, whereas warfarin and acenocoumarol are almost completely metabolized [START_REF] Beinema | Pharmacogenetic differences between warfarin, acenocoumarol and phenprocoumon[END_REF]. S-and R-acenocoumarol have very short half-lives of approximately 2 and 8 hours, followed by S-and R-warfarin with half-lives of approximately 32 and 43 hours. The half-life of racemic phenprocoumon ranges from 156 to 172 hours [START_REF] Ansell | Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition)[END_REF]. A main aspect of the safety of coumarins is their sensitivity to drug interactions [START_REF]ABDA -Bundesvereinigung Deutscher Apothekerverbände Accessed 5[END_REF][START_REF]Drugdex evaluations[END_REF][START_REF] Harder | Clinically important drug interactions with anticoagulants. An update[END_REF]. However, the large majority of studies investigating overanticoagulation or bleeding as a result of interactions with coumarins refer to warfarin [START_REF] Gasse | Drug interactions and risk of acute bleeding leading to hospitalisation or death in patients with chronic atrial fibrillation treated with warfarin[END_REF][START_REF] Delaney | Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding[END_REF][START_REF] Battistella | Risk of upper gastrointestinal hemorrhage in warfarin users treated with nonselective NSAIDs or COX-2 inhibitors[END_REF][START_REF] Glasheen | The risk of overanticoagulation with antibiotic use in outpatients on stable warfarin regimens[END_REF][START_REF] Zhang | Administrative claims analysis of the relationship between warfarin use and risk of hemorrhage including drug-drug and drug-disease interactions[END_REF] or the combined group of acenocoumarol and phenprocoumon [START_REF] Penning-Van Beest | Risk of major bleeding during concomitant use of antibiotic drugs and coumarin anticoagulants[END_REF][START_REF] Bf | Main comedications associated with major bleeding during anticoagulant therapy with coumarins[END_REF][START_REF] Visser | Overanticoagulation associated with combined use of antibacterial drugs and acenocoumarol or phenprocoumon anticoagulants[END_REF][START_REF] Visser | Overanticoagulation associated with combined use of antifungal agents and coumarin anticoagulants[END_REF]. Due to the described pharmacokinetic differences, results of these studies cannot automatically be extrapolated to potential drug interactions with phenprocoumon. We conducted a nested case-control study within a phenprocoumon user cohort to investigate which drug interactions result in an increased risk of major bleeding during anticoagulant therapy with phenprocoumon.

Methods

Data Source

Data were obtained from the German Pharmacoepidemiological Research Database (GePaRD). This database consists of claims data from four German statutory health insurances (SHI) and includes more than 14 million insurants covering all German regions. It provides demographic information as well as information on hospital admissions, outpatient physician visits, and outpatient prescriptions. Hospital data include the dates of admission and discharge with their corresponding diagnoses, and information on inhospital diagnoses and procedures. Claims on outpatient physician visits contain diagnoses, ambulatory diagnostic procedures and nondrug treatments. Since these claims are reimbursed on a quarterly basis, ambulatory diagnoses can only be allocated to a quarter of the year and not to an exact date. All diagnoses are coded according to the German modification of the International Classification of Diseases (ICD-10 GM). Prescription data contain the prescribed drugs, characterized by the central pharmaceutical number (PZN), the dates of prescription and dispensation, and information on the prescribing physician. They are available for all outpatient prescriptions which are reimbursed by the SHIs. Prescription data are linked to a pharmaceutical reference database which adds information on the Defined Daily Dose (DDD), the anatomical-therapeutic-chemical (ATC) code, strength, packaging size, generic and brand name. The study was based on data from 2004 -2006 which were available at the time of the analysis. In preliminary analyses regarding age and sex distribution, the number of hospital admissions and drug use, the database was found to be representative for Germany [START_REF] Pigeot | Establishment of a pharmacoepidemiological database in Germany: methodological potential, scientific value and practical limitations[END_REF][START_REF] Schink | Externe Validierung von Verschreibungsdaten nichtsteroidaler Antirheumatika anhand des Arzneiverordnungsreports 54[END_REF]. The observed stability of patients' memberships makes long term follow-up studies feasible [START_REF] Pigeot | Establishment of a pharmacoepidemiological database in Germany: methodological potential, scientific value and practical limitations[END_REF]. The GePaRD has been used successfully to study haemorrhagic complications of phenprocoumon treatment [START_REF] Behr | Risk of intracerebral hemorrhage associated with phenprocoumon exposure: a nested case-control study in a large population-based German database[END_REF]. In Germany, the utilization of health insurance data for scientific research is regulated by the Code of Social Law (SGB X). This study was conducted with permission from the Federal Ministry of Health. Since it was based on pseudonymous data, informed consent was not required by law.

Study design

We conducted a case-control study nested in a cohort of phenprocoumon users who had to be continuously enrolled for at least 6 months prior to cohort entry. Cohort entry was defined as the first prescription of phenprocoumon (ATC-code B01AA04) between July 1, 2004 and November 30, 2006, after 6 months of continuous insurance. All patients were followed from their first phenprocoumon prescription in the study period until either discontinuation of phenprocoumon, hospitalisation for bleeding, death, or the end of the study period, whichever occurred first. The end of the study period in November 2006 was set to avoid incomplete hospital data spanning the turn of the year. As phenprocoumon dosages depend on several patient-specific factors and the database does not include information on the prescribed daily dose, we estimated the duration of each prescription by assuming that a patient's daily dose was one DDD (3mg phenprocoumon), allowing a grace period of 7 days between two phenprocoumon prescriptions. In case of no consecutive prescription of phenprocoumon within this time frame, we defined that treatment was discontinued. Patients were only followed during their first period of continuous phenprocoumon exposure. Due to large inter-and intra-individual differences in phenprocoumon dose requirements we performed two sensitivity analyses, assuming that the daily dose of phenprocoumon was 1.5mg phenprocoumon and 4.5mg phenprocoumon, respectively. Since the initiation phase is supposed to be associated with a higher risk of bleeding [START_REF] Gasse | Drug interactions and risk of acute bleeding leading to hospitalisation or death in patients with chronic atrial fibrillation treated with warfarin[END_REF][START_REF] Palareti | Bleeding with anticoagulation therapy -Who is at risk, and how best to identify such patients[END_REF], we distinguished between incident and prevalent use of phenprocoumon. Incident use was defined as use during the first 90 days following start of phenprocoumon treatment and no prescriptions of phenprocoumon in the 6 months preceding cohort entry. All other use was defined as prevalent use.

Definition of cases and controls

Cases were defined as phenprocoumon users hospitalised with a main discharge diagnosis of bleeding. Since the main discharge diagnosis in Germany according to the coding rules reflects the main reason for hospital admission, patients in whom bleeding developed in hospital are not included in this definition. Bleeding included gastrointestinal, cerebral, urogenital or intraocular haemorrhage, haemorrhage from respiratory passages and other bleeding conditions. The list of ICD-10-GM codes used to define these outcomes is available upon request. The hospital admission day was defined as the index day of the case.

From the cohort of continuous phenprocoumon users, we randomly selected ten controls for each case, matching for sex, patient age (birth year), and SHI, using incidence-density sampling. An index day was assigned to each control that resulted in the same time of followup as for the corresponding case. We excluded cohort members who were hospitalised at the index day of the case from the set of potential controls, since information on drug use in hospital is not available in the GePaRD. In accordance with epidemiological principles, before becoming a case, a case patient could serve as a control for a different case, and controls could be used more than once [START_REF] Rothman | Case-Control Studies[END_REF].

Exposure to drugs with potential clinically relevant interaction with phenprocoumon

Potentially interacting drugs were obtained from the Summary of Product Characteristics (SPC) and the "Rote Liste" (a national compendium with abridged information from the SPC), which are important sources of reference information concerning drug interactions for German physicians [START_REF] Pharma | Marcumar Fachinformation www.fachinfo[END_REF][START_REF] Bergk | Requirements for a successful implementation of drug interaction information systems in general practice: results of a questionnaire survey in Germany[END_REF][START_REF] Liste | Cumarin-(4-Hydroxy)-Derivate Rote Liste[END_REF] as well as from Drugdex [START_REF]Drugdex evaluations[END_REF]. Additionally we included important inhibitors of the CYP isozymes 2C9, 2C8 and 3A4 involved in phenprocoumon metabolism [START_REF] Flockhart | Drug Interactions: Cytochrome P450 Drug Interaction Table[END_REF]. Potentially interacting drugs are presented in Table 1. All oral formulations of these drugs were taken into account in our statistical analyses of potentially interacting drugs. We considered only current exposure of these drugs which was defined as a drug supply which overlapped with the index date or ended in the 7-day period before the index date. Categorisation of current exposure was based on the date of the prescription of a potentially interacting drug and its assumed duration. The duration was estimated by multiplying the number of tablets prescribed with their strength and dividing this by the DDD of the respective drug, assuming full compliance.

Assessment of potential confounders

Potential confounders were ascertained from ambulatory and hospital care in the six-month continuous enrolment period before cohort entry. We assessed the following conditions as potential confounders: arterial hypertension, heart failure, ischaemic heart disease, diabetes, chronic obstructive pulmonary disease, diverticular disease of the intestine, upper gastrointestinal (GI) diseases including ulcers and diseases of the oesophagus, all types of cancer, hepatic failure, renal failure, alcohol dependence, cerebral amyloid angiopathy / aneurysm, and a prior ambulatory or hospital diagnosis of bleeding. ICD 10-GM codes for potential confounders are available on request. Additionally, we included as potential confounders use of proton pump inhibitors or H2-receptor antagonists as surrogate information for GI problems as well as heparins at the index date or ending in the 7-day period before the index date.

Statistical Analyses

We calculated incidence rates of hospitalisation for bleeding stratified by sex for different age groups and in another analysis stratified by incident and prevalent phenprocoumon use. Odds ratios (ORs) of hospitalisation for bleeding associated with current use of each potentially interacting drug were calculated by conditional logistic regression analysis using the SAS procedure PHREG (SAS 8.2, SAS Institute Inc., Cary, NC). For each analysis, the reference category was the absence of current use of the respective potentially interacting drug at the index date. All regression models controlled for relevant confounders and interacting medications selected in a backward selection procedure. Covariates were removed from the model step by step in case the Wald test was not significant (p>0.05). A p-value lower or equal 0.05 in the two-tailed test was considered significant, and 95% confidence intervals (CIs) were calculated for all ORs.

Results

During the study period 13,397,148 insurants met the criterion of being insured for at least six months. Among these we identified 246,220 patients who were treated with phenprocoumon. These patients were followed for a total of 91,520 patient-years resulting in a mean follow-up time of 136 days (standard deviation (STD): 102 days) per patient. The mean age at cohort entry was 67.6 years (STD: 12.5 years). Fifty-six percent of cohort members were male. Within this cohort, we identified 2,553 cases of first bleeding requiring hospitalisation resulting in an overall incidence rate of 2.79 (95% CI: 2.68-2.90) hospitalisations for bleeding per 100 patient-years. Gastrointestinal bleeding was the most frequent cause of hospitalisation for bleeding with 33.5%, followed by other bleedings including "haemorrhagic disorder due to circulating anticoagulants" (32.7%), cerebral bleeding (13.6%), and bleeding from the respiratory (8.8%) and genitourinary tract (8.2%). The incidence rate of hospitalisation for bleeding was higher with incident (3.66, 95% CI: 3.47-3.85 per 100 patient-years) than with prevalent phenprocoumon use (2.15, 95% CI: 2.02-2.28 per 100 patient-years). The incidence of hospitalisations for bleeding increased gradually with rising age from 1.24 (95% CI: 1.03-1.48) hospitalisations for bleeding per 100 patient-years in phenprocoumon-users younger than 50 years of age to 4.98 (95% CI: 4.60-5.39) hospitalisations for bleeding per 100 patientyears in those who were older than 80 years. Incidence rates of major haemorrhage under treatment with phenprocoumon stratified by age group and sex are shown in Figure 1. The case-control analysis was based on 2,553 cases and 25,348 matched controls. Less than ten matched controls were found for 36 cases which were either very old or very young. Table 2 shows the characteristics of cases and controls. We observed elevated risks for several comorbid conditions including alcohol dependence (adjusted OR: 2.38, 95% CI: 1.71-3.30), renal failure (adjusted OR: 1.67, 95% CI: 1.46-1.90), and a history of bleeding (adjusted OR: 2.29, 95% CI: 2.03-2.59). We also found increased adjusted odds ratios for the concomitant use of proton pump inhibitors (OR: 1.56, 95% CI: 1.40-1.74) used as a proxy measure for GI problems and for concomitant use of heparins (OR: 2.66, 95% CI: 2.33-3.03). Table 3 displays the risks of major bleeding for drugs which showed a significant interaction with phenprocoumon in the adjusted statistical analysis. Drugs from table 1 which did not show a significant interaction are not further shown here. Ibuprofen and diclofenac, the most frequently used NSAIDs in this study, were associated with similar risks with an OR of 1.63 (95% CI: 1.26-2.11) for ibuprofen and 1.60 (95% CI: 1.33-1.91) for diclofenac, respectively. For ketoprofen and naproxen which were used by only few patients, the ORs were substantially higher, however, with wide confidence intervals. The combined use of antibiotics and phenprocoumon increased the ORs of bleeding 2-to 10-fold compared to phenprocoumon use alone. High ORs were observed for several antibiotics, including quinolones such as ciprofloxacin (adjusted OR: 2.74, 95% CI: 1.80-4.18) or levofloxacin (adjusted OR: 4.40, 95% CI: 2.45-7.89). The concomitant use of phenprocoumon and clopidogrel resulted in an elevated OR of 1.83 (95% CI: 1.41-2.36). Table 4 displays odds ratios for drugs with a possible pharmacokinetic interaction with phenprocoumon through inhibition of CYP3A4. None of these drugs was associated with a significant risk. Prevalence of exposure at the index date was low for several of these drugs. Table 5 shows the results of the sensitivity analyses with the respective number of cases and controls assuming an average daily dose of 1.5 or 4.5 mg phenprocoumon. The increased risk estimates observed in the main analysis remained elevated in both sensitivity analyses.

Discussion

Drug interactions with warfarin are generally considered hazardous. In a US Top Ten list of dangerous drug-drug interactions in long-term care, warfarin was involved in half of the drug combinations [START_REF]Top Ten Dangerous Drug Interactions in Long-Term Care AMDA Annual Meeting[END_REF]. Data on the relevance of drug interactions with phenprocoumon are sparse, since most epidemiological studies investigating the relevance of drug interactions have been conducted in warfarin-treated patients [START_REF] Gasse | Drug interactions and risk of acute bleeding leading to hospitalisation or death in patients with chronic atrial fibrillation treated with warfarin[END_REF][START_REF] Zhang | Administrative claims analysis of the relationship between warfarin use and risk of hemorrhage including drug-drug and drug-disease interactions[END_REF][START_REF] Schelleman | Warfarin with fluoroquinolones, sulfonamides, or azole antifungals: interactions and the risk of hospitalization for gastrointestinal bleeding[END_REF]. Studies of possible drug interactions with phenprocoumon have so far also included users of acenocoumarol and not differentiated between both drugs [START_REF] Penning-Van Beest | Risk of major bleeding during concomitant use of antibiotic drugs and coumarin anticoagulants[END_REF][START_REF] Bf | Main comedications associated with major bleeding during anticoagulant therapy with coumarins[END_REF][START_REF] Visser | Overanticoagulation associated with combined use of antibacterial drugs and acenocoumarol or phenprocoumon anticoagulants[END_REF][START_REF] Visser | Overanticoagulation associated with combined use of antifungal agents and coumarin anticoagulants[END_REF][START_REF] Penning-Van Beest | Drug interactions as a cause of overanticoagulation on phenprocoumon or acenocoumarol predominantly concern antibacterial drugs[END_REF]. To our knowledge, this large nested case-control study is the first to study the risk of drug interactions with phenprocoumon alone. Our study shows that several frequently prescribed drugs were associated with an increased risk of major bleeding when taken concomitantly with phenprocoumon. We observed significantly elevated risks for drugs with a possible pharmacodynamic interaction with coumarins such as non-steroidal anti-inflammatory drugs (NSAIDs), platelet inhibitors and antibiotics. A similar spectrum of interacting drug groups has been described in a Dutch cohort study. In this study, ninety-five percent of the coumarin use was conducted with acenocoumarol [START_REF] Bf | Main comedications associated with major bleeding during anticoagulant therapy with coumarins[END_REF]. A pharmacodynamic interaction between NSAIDs and other coumarins is well known and attributed to injury caused by NSAIDs to the GI mucosa. An increased risk of major haemorrhage was observed in several studies when NSAIDs were co-administered with warfarin [START_REF] Delaney | Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding[END_REF][START_REF] Battistella | Risk of upper gastrointestinal hemorrhage in warfarin users treated with nonselective NSAIDs or COX-2 inhibitors[END_REF][START_REF] Cheetham | Gastrointestinal safety of nonsteroidal antiinflammatory drugs and selective cyclooxygenase-2 inhibitors in patients on warfarin[END_REF] or phenprocoumon and acenocoumarol [START_REF] Bf | Main comedications associated with major bleeding during anticoagulant therapy with coumarins[END_REF][START_REF] Knijff-Dutmer | Concomitant coumarin-NSAID therapy and risk for bleeding[END_REF]. Our results concur with these findings, revealing similar risks for concomitant use of phenprocoumon with diclofenac and ibuprofen, the two NSAIDs mainly used in Germany. Our study demonstrated an elevated risk of major haemorrhage when clopidogrel was coadministered with phenprocoumon. Several studies reported similarly increased risks of haemorrhage when drugs that impair platelet function, such as acetylsalicylic acid or clopidogrel were given to patients treated with warfarin [START_REF] Delaney | Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding[END_REF][START_REF] Buresly | Bleeding complications associated with combinations of aspirin, thienopyridine derivatives, and warfarin in elderly patients following acute myocardial infarction[END_REF][START_REF] Johnson | Outcomes associated with combined antiplatelet and anticoagulant therapy[END_REF] or other coumarins [START_REF] Schalekamp | Effect of oral antiplatelet agents on major bleeding in users of coumarins[END_REF]. Two recently published Danish cohort studies comparing different antithrombotic regimens recommended that the combination of clopidogrel and a vitamin K antagonist or an antithrombotic triple therapy should be considered very carefully [START_REF] Hansen | Risk of bleeding with single, dual, or triple therapy with warfarin, aspirin, and clopidogrel in patients with atrial fibrillation[END_REF][START_REF] Sorensen | Risk of bleeding in patients with acute myocardial infarction treated with different combinations of aspirin, clopidogrel, and vitamin K antagonists in Denmark: a retrospective analysis of nationwide registry data[END_REF]. Co-administration of antibiotics from different groups increased the risk of bleeding in phenprocoumon-treated patients. Assumed pharmacodynamic interaction mechanisms are a reduction of the intestinal flora that produces vitamin K or a direct inhibition of vitamin Kdependent coagulation factors by antibiotic therapy [START_REF] Harder | Clinically important drug interactions with anticoagulants. An update[END_REF][START_REF] Penning-Van Beest | Risk of major bleeding during concomitant use of antibiotic drugs and coumarin anticoagulants[END_REF]. Additionally the underlying indication as well as illness-related factors are supposed to increase the anticoagulant effect [START_REF] Visser | Overanticoagulation associated with combined use of antibacterial drugs and acenocoumarol or phenprocoumon anticoagulants[END_REF][START_REF] Schelleman | Warfarin with fluoroquinolones, sulfonamides, or azole antifungals: interactions and the risk of hospitalization for gastrointestinal bleeding[END_REF][START_REF] Demirkan | Response to warfarin and other oral anticoagulants: effects of disease states[END_REF]. This is supported by a Dutch nested case-control which found fever and diarrhoea to be risk factors for overanticoagulation with coumarins [START_REF] Penning-Van Beest | Characteristics of anticoagulant therapy and comorbidity related to overanticoagulation[END_REF]. Beyond that, some antibiotic drugs may also inhibit the hepatic metabolism of coumarins. This applies for example to cotrimoxazole which is known to be a strong inhibitor of CYP2C9 [START_REF] Flockhart | Drug Interactions: Cytochrome P450 Drug Interaction Table[END_REF]. Our results are in line with several studies that reported an increased risk of bleeding when cotrimoxazole was administered concomitantly with a coumarin [START_REF] Penning-Van Beest | Risk of major bleeding during concomitant use of antibiotic drugs and coumarin anticoagulants[END_REF][START_REF] Bf | Main comedications associated with major bleeding during anticoagulant therapy with coumarins[END_REF][START_REF] Visser | Overanticoagulation associated with combined use of antibacterial drugs and acenocoumarol or phenprocoumon anticoagulants[END_REF][START_REF] Fischer | Hemorrhage during warfarin therapy associated with cotrimoxazole and other urinary tract anti-infective agents: a population-based study[END_REF]. The elevated risk of haemorrhage we observed when phenprocoumon-treated patients were prescribed quinolones is worth a comment. Their frequent concomitant use with phenprocoumon might be explained by the fact that none of these drugs is listed as potential interaction in the German SPC or "Rote Liste" of phenprocoumon products [START_REF] Pharma | Marcumar Fachinformation www.fachinfo[END_REF][START_REF] Liste | Cumarin-(4-Hydroxy)-Derivate Rote Liste[END_REF]. For warfarin, there have been discrepant findings regarding an interaction with quinolones [START_REF] Carroll | Interactions between warfarin and three commonly prescribed fluoroquinolones[END_REF]. Numerous case reports and case series [START_REF] Arnold | Moxifloxacin and warfarin: additional evidence for a clinically relevant interaction[END_REF][START_REF] Elbe | Moxifloxacin-warfarin interaction: a series of five case reports[END_REF][START_REF] Ellis | Ciprofloxacin-warfarin coagulopathy: a case series[END_REF][START_REF] O'connor | The interaction of moxifloxacin and warfarin in three elderly patients[END_REF][START_REF] Vadlamudi | Interaction between warfarin and levofloxacin: Case series[END_REF] as well as population-based studies [START_REF] Schelleman | Warfarin with fluoroquinolones, sulfonamides, or azole antifungals: interactions and the risk of hospitalization for gastrointestinal bleeding[END_REF][START_REF] Fischer | Hemorrhage during warfarin therapy associated with cotrimoxazole and other urinary tract anti-infective agents: a population-based study[END_REF] have indicated that quinolones may potentiate the anticoagulant effect of warfarin and increased the risk of bleeding. In contrast, a large Canadian nested case-control study conducted in a cohort of chronic warfarin users did not find an elevated risk of hospitalisation for haemorrhage within 14 days after initiation of levofloxacin [START_REF] Stroud | The safety of levofloxacin in elderly patients on warfarin[END_REF]. However, this study compared levofloxacin against use of cefuroxim and not against no use. In summary, the spectrum of interacting drugs observed in our study with phenprocoumon is comparable to that reported for the other coumarins. Since interaction of the coumarins with these drugs is mainly through a pharmacodynamic mechanism, this could have been anticipated. Some additional pharmacokinetic interactions of phenprocoumon with CYP3A4 inhibitors might have been expected, since phenprocoumon metabolism is more dependent on the CYP3A4 isozyme than the other coumarins [START_REF] Ufer | Comparative pharmacokinetics of vitamin K antagonists: warfarin, phenprocoumon and acenocoumarol[END_REF][START_REF] Pharma | Marcumar Fachinformation www.fachinfo[END_REF][START_REF] Beinema | Pharmacogenetic differences between warfarin, acenocoumarol and phenprocoumon[END_REF]. However, none of the investigated CYP3A4 inhibitors was associated with an increased risk of bleeding. In the case of azole antimycotics or protease inhibitors, the low exposure prevalence did not permit statistical analyses with sufficient statistical power. However, many phenprocoumon-treated patients received concomitant prescriptions of the CYP3A4 inhibitors verapamil or diltiazem, but our results did not indicate an elevated risk for these drugs either. In the last years, two new oral anticoagulants, dabigatran and rivaroxaban were launched to market, offering future alternatives to coumarins. Besides their practical advantages such as fixed doses and no need of coagulation monitoring, they are hoped to be less prone to drug interactions. While one would expect pharmacodynamic interactions with NSAIDs or platelet inhibitors also for these agents, they will probably be less affected by interaction with antibiotics, if this interaction is caused by antibiotic-induced alterations of the gut flora and diminished vitamin K production and if it is not result of the underlying disease for which antibiotics are administered. Regarding pharmacokinetic interactions, both drugs are substrates for P-glycoprotein, which is involved in the transport of many drugs. In case of rivaroxaban also caution is required when combined with strong CYP3A4 inhibitors [START_REF] Bayer | Xarelto 10mg Filmtabletten Fachinformation www.fachinfo[END_REF][START_REF]Pradaxa 110mg Hartkapseln Fachinformation www.fachinfo[END_REF][START_REF] Walenga | Drug and dietary interactions of the new and emerging oral anticoagulants[END_REF]. Our study confirmed several well known risk factors of major bleeding such as increasing age, a previous history of bleeding [START_REF] Mcmahan | Risk of major hemorrhage for outpatients treated with warfarin[END_REF][START_REF] Shireman | Development of a contemporary bleeding risk model for elderly warfarin recipients[END_REF], alcohol use [START_REF] Delaney | Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding[END_REF][START_REF] White | Major bleeding after hospitalization for deep-venous thrombosis[END_REF], or renal failure [START_REF] Delaney | Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding[END_REF][START_REF] Limdi | Kidney function influences warfarin responsiveness and hemorrhagic complications[END_REF]. The high odds ratios we found for the concomitant use of heparins and phenprocoumon might reflect the bridging period of overlapping use of both drugs until phenprocoumon reaches its therapeutic effect. This period has been reported to be associated with a high risk of haemorrhage [START_REF] Hallevi | Anticoagulation after cardioembolic stroke: to bridge or not to bridge?[END_REF][START_REF] Tompkins | Dual antiplatelet therapy and heparin "bridging" significantly increase the risk of bleeding complications after pacemaker or implantable cardioverter-defibrillator device implantation[END_REF]. We also observed a substantially higher risk of bleeding in the beginning of phenprocoumon treatment which concurs with findings from other studies [START_REF] Palareti | Bleeding complications of oral anticoagulant treatment: an inception-cohort, prospective collaborative study (ISCOAT). Italian Study on Complications of Oral Anticoagulant Therapy[END_REF]. Our study had several limitations. Although we included a large number of risk factors in our statistical analysis, we lacked information on several others such as the International Normalized Ratio (INR) [START_REF] Oake | Anticoagulation intensity and outcomes among patients prescribed oral anticoagulant therapy: a systematic review and metaanalysis[END_REF], diet [START_REF] Holbrook | Systematic overview of warfarin and its drug and food interactions[END_REF] or body mass index [START_REF] Delaney | Drug drug interactions between antithrombotic medications and the risk of gastrointestinal bleeding[END_REF][START_REF] Zu Schwabedissen | Obesity is associated with a slower response to initial phenprocoumon therapy whereas CYP2C9 genotypes are not[END_REF]. The association between INR and haemorrhage is not perfect, since the INR level may increase as a consequence of bleeding and therefore INR data are needed for the time period just preceding or at the time of bleeding which is often not available even in prospective studies [START_REF] Bell | The safety of levofloxacin in patients on warfarin -Reply[END_REF]. We also did not have information on drugs bought over the counter such as high dose acetylsalicylic acid. Since low dose acetylsalicylic acid is not always prescribed but sometimes bought over the counter in Germany, we might have underestimated concomitant use of this drug. The same applies for low dose ibuprofen and low dose diclofenac. The resulting misclassification of exposed patients as unexposed is supposed to be non-differential and thus will lead to an attenuation of the risks observed for ibuprofen and diclofenac, i.e. the observed increased risks for these drugs may actually be higher. We also did not have information on the duration of phenprocoumon use, but calculated the duration of use based on the Defined Daily Dose. We therefore cannot exclude some misclassification in phenprocoumon exposure due to the large inter-and intra-individual differences in phenprocoumon dose requirements [START_REF] Schneeweiss | A review of uses of health care utilization databases for epidemiologic research on therapeutics[END_REF]. Sensitivity analyses based on 1.5mg or 4.5mg phenprocoumon, respectively, for the calculation of duration, however, showed our main results to be robust. A main strength of our study is its large size which allows the investigation of rare, but clinically important events such as hospitalisation for bleeding as well as the investigation of less frequent exposures. Because our study was designed as a nested case-control study in a defined cohort providing both cases and controls, selection bias in the choice of controls is unlikely. All information was recorded prospectively so that recall bias can be ruled out. Our study was population-based and unlike randomized clinical trials reflects clinical practice. In conclusion, several frequently prescribed drugs were associated with an increased risk of major bleeding when taken concomitantly with phenprocoumon. Among these, coadministration of antibiotics may be particularly hazardous, since antibiotics are mainly used as short-time medications and are often prescribed by a specialist and not by the general practitioner who mostly monitors anticoagulation therapy. Our results concerning drug interactions between phenprocoumon and quinolones warrant further attention, since these are not labelled in Germany [START_REF] Pharma | Marcumar Fachinformation www.fachinfo[END_REF][START_REF] Liste | Cumarin-(4-Hydroxy)-Derivate Rote Liste[END_REF]. Overall, we found the spectrum of interacting drugs to be quite similar for phenprocoumon and the other coumarins, despite their different pharmacokinetic profiles. Significantly increased risks of major haemorrhage were mainly observed for drugs with known pharmacodynamic interaction with phenprocoumon and less for those with possible pharmacokinetic interaction. a Adjusted for all other covariates included in the table as well as for arterial hypertension, heart failure, diabetes, diverticular disease of the intestine, renal failure, alcohol dependence, a prior ambulatory or hospital diagnosis of bleeding (assessed in the 6 months before cohort entry), and a drug supply with proton pump inhibitors or heparins which overlapped with the index date or ended in the 7 day period before the index date b Drug supply which overlapped with the index date or ended in the 7 day period before the index date c i.e. artovastatin, pravastatin, simvastatin

Figure 1

 1 Figure 1Incidence rates of major haemorrhage under treatment with phenprocoumon by age group and sex

Table 2 Characteristics of cases and matched controls Cases N= 2,553 Controls N= 25,348

 2 Obtained from univariate conditional logistic regression model b Adjusted for all other covariates included in the tablec Birth year and sex are matching variables d Assessed in the 6 months before cohort entry e Drug supply which overlapped with the index date or ended in the 7 day period before the index date

	Crude	Adjusted	95%
	odds	odds	confidence
	ratio a	ratio b	interval b

a f Used as surrogate for upper GI problems

Table 3 Crude and adjusted odds ratios and 95% confidence intervals for major haemorrhage associated with current use of potentially interacting drugs Cases N= 2,553 Controls N= 25,348

 3

	Crude	Adjusted	95%
	odds	odds	confidence
	ratio a	ratio b	interval b

a Obtained from univariate conditional logistic regression model b Adjusted for all other covariates included in the table as well as for arterial hypertension, heart failure, diabetes, diverticular disease of the intestine, renal failure, alcohol dependence, a prior ambulatory or hospital diagnosis of bleeding (assessed in the 6 months before cohort entry), and a drug supply with proton pump inhibitors or heparins which overlapped with the index date or ended in the 7 day period before the index date c Drug supply which overlapped with the index date or ended in the 7 day period before the index date d i.e. artovastatin, pravastatin, simvastatin

Table 4 Odds ratios a and 95% confidence intervals for major haemorrhage associated with concomitant use of CYP3A4 inhibitors Cases N= 2,553 Controls N= 25,348

 4 Obtained from univariate conditional logistic regression model, since only significant drugs or covariates were included in the multivariate model building b Drug supply which overlapped with the index date or ended in the 7 day period before the index date c i.e. fluconazole, ketoconazole, itraconazole, voriconazole d i.e. indinavir, nelfinavir, ritonavir, saquinavir

	Odds ratio a	95% confidence
		interval a

a

Table 5 Adjusted odds ratios (OR) and 95% confidence intervals (CI) for major haemorrhage associated with concomitant use of potentially interacting drugs assuming different daily doses of phenprocoumon (PPC)

 5

		Sensitivity analysis 1	Main analysis	Sensitivity analysis 2
		(daily dose = 1.5mg PPC)	(daily dose = 3mg PPC)	(daily dose = 4.5mg PPC)
		Cases N = 6,107	Cases N = 2,553	Cases N = 1,669
		Controls N = 60,820	Controls N = 25,348	Controls N = 16,541
		OR (95% CI) a	OR (95% CI) a	OR (95% CI) a
	Concomitant use of … b
	Amoxicillin	1.74 (1.31-2.29)	1.56 (1.01-2.40)	1.89 (1.10-3.23)
	Amoxicillin + clavulanic acid	2.99 (1.69-5.31)	2.99 (1.39-6.42)	2.03 (0.87-4.74)
	Cephalosporins (other)	1.92 (1.35-2.74)	2.16 (1.28-3.63)	1.79 (0.93-3.44)
	Cotrimoxazole	3.58 (2.67-4.81)	3.57 (2.36-5.40)	4.00 (2.43-6.57)
	Ciprofloxacin	3.02 (2.28-4.00)	2.74 (1.80-4.18)	2.14 (1.27-3.60)
	Levofloxacin	2.94 (1.89-4.56)	4.40 (2.45-7.89)	5.51 (2.64-11.50)
	Moxifloxacin	2.64 (1.62-4.32)	3.51 (1.77-6.96)	2.69 (1.11-6.53)
	Ofloxacin	3.27 (1.76-6.10)	3.60 (1.30-10.00)	4.99 (1. 80-13.87)
	Metronidazole	5.95 (2.14-16.60)	9.49 (2.44-37.00)	5.32 (1.45-19.54)
	Diclofenac	1.80 (1.60-2.02)	1.60 (1.33-1.91)	1.81 (1.45-2.26)
	Ibuprofen	1.84 (1.57-2.16)	1.63 (1.26-2.11)	1.61 (1.18-2.20)
	Ketoprofen	3.99 (1.76-9.05)	8.06 (2.74-23.75)	4.20 (0.80-22.21)
	Naproxen	3.66 (1.68-7.99)	4.29 (1.03-17.95)	3.79 (0.75-19.29)
	Clopidogrel	1.78 (1.47-2.16)	1.83 (1.41-2.36)	1.92 (1.44-2.56)
	Statins (other) c	0.94 (0.88-1.00)	0.88 (0.79-0.98)	0.91 (0.80-1.03)

Acknowledgement:

The authors are grateful to all SHIs that provided data for this study. Three of these are the Allgemeine Ortskrankenkasse (AOK) Bremen/Bremerhaven, the Deutsche Angestellten-Krankenkasse (DAK), and the Handelskrankenkasse (HKK).

Conflict of interest

The authors declare that they have no conflict of interest.