YEBEH-05478; No of Pages 5 Epilepsy & Behavior xxx (2017) xxx–xxx
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Differentiating PNES from epileptic seizures using conversational analysis Costanza Papagno a,b,⁎,1, Lorenzo Montali b,1, Katherine Turner c,1, Alessandra Frigerio b, Martina Sirtori b, Elena Zambrelli c, Valentina Chiesa c, Maria Paola Canevini c,d a
CIMeC and CeRiN, University of Trento, via Matteo Del Ben 5/b, 38068 Rovereto, Italy Department of Psychology, University of Milano-Bicocca, Edificio U6, Piazza dell'Ateneo Nuovo 1, 20126 Milano, Italy Epilepsy Center, San Paolo Hospital, via A. Di Rudinì 8, 20142 Milano, Italy d Department of Health Sciences, University of Milan, 20100 Milano, Italy b c
a r t i c l e
i n f o
Article history: Received 21 July 2017 Revised 23 August 2017 Accepted 24 August 2017 Available online xxxx Keywords: Conversation analysis Psychogenic nonepileptic seizure Video-EEG
a b s t r a c t We applied conversation analysis in an unselected continuous series of 70 patients to discriminate patients with psychogenic nonepileptic seizures (PNES) from patients with epilepsy. Two psychologists examined the patients' recorded reports. Patients were also submitted to an extensive neuropsychological battery in order to verify whether specific cognitive deficits or mental health problems are typical of patients with PNES and whether some cognitive deficits could prevent the correct diagnosis. The results showed a good percentage of correct diagnosis, with a sensitivity of 0.795 and a specificity of 0.83, while no difference in the cognitive profile was found between patients with PNES and patients with epilepsy. The results also suggest that psychologists can apply the conversation analysis as well as linguists, which is an important finding since psychologists are employed in specialized centers, while linguists in general are not part of the team. © 2017 Elsevier Inc. All rights reserved.
1. Introduction An epileptic seizure is defined as a “transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain” [1]. Psychogenic nonepileptic seizures (PNES) are defined as an episode characterized by sudden and temporary motor, sensory, autonomic, cognitive, or emotional symptoms, and signs mimicking epileptic seizures but not associated with epileptic cortical discharges (for a detailed review on this topic see [2]). Therefore, from a clinical point of view, the two disturbances share many similarities, preventing a reliable differential diagnosis. As a consequence, epilepsy tends to be overdiagnosed and, frequently, it takes several years to reach a correct diagnosis of PNES. At present, video-EEG (VEEG) is the gold standard technique used in order to differentiate the two conditions; however, it is available only in a limited number of specialized epilepsy centers and nevertheless, the two types of seizure can coexist, increasing the difficulty of making a correct diagnosis [3]. When seizures are recorded with VEEG, it is necessary to make sure that the recorded episodes were the same type of events experienced outside
⁎ Corresponding author at: CeRiN (Centro di Riabilitazione Neurocognitiva), Via Matteo del Ben 5/b, University of Trento, 38068 Rovereto, TN, Italy. E-mail addresses: [email protected], [email protected] (C. Papagno). 1 The first three authors equally contributed to the paper.
the VEEG Lab. In a recent study, Erba et al. [4] investigated whether and to what extent information contained in a video-recorded event in the absence of EEG allowed four experienced epileptologists to predict the diagnosis of PNES. In 7 out of 23 videos, all raters predicted the diagnosis correctly, while in 5 cases, all four failed. Moreover, home video recording is often not sufficiently informative. For all of these reasons, even if the diagnosis relies in many cases on the interpretation of the patient's history and witness accounts of events, PNES are hard to distinguish only on the basis of their symptoms. Patients' perception and subjective experience of PNES have been extensively investigated, mainly by means of self-report questionnaires focusing on the seizure disorder, or addressing the experience of individual seizures [5,6]. However, the relevance of subjective symptoms might not be revealed using self-report questionnaires. In this prospective, a multidisciplinary research group in Germany developed the so-called EpiLing project which aimed at assessing how patients describe their subjective seizure experiences, namely how they communicate it; indeed, it has been suggested that patients use a range of different communicative styles when describing their seizures, and these communication styles seem to concord with the medical diagnoses of epileptic or PNES. The descriptions were produced in an interactional setting, talks between doctors and patients, so that they can be considered as a method that patients use to share and make understandable to others their subjective accounts. With this method, qualitative aspects of the patients' description are given special value.
http://dx.doi.org/10.1016/j.yebeh.2017.08.034 1525-5050/© 2017 Elsevier Inc. All rights reserved.
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Qualitative methods allow patients to communicate their feelings and thoughts in more fine-grained and richer detail compared with quantitative self-report methods. They enable patients to clarify what is important to them rather than forcing them to reply by endorsing predefined categorical responses that may oversimplify the idiosyncrasies of the condition. The analysis identified two distinct communicative styles, as reported above, which are characterized by some systematic patterns in the method that patients use to describe their seizures and showed some relevant differences between the description of patients with epilepsy and of patients with PNES. This approach has been successfully applied in two different languages, German [7] and English [8], and in a limited sample of Italian patients, both adults [9] and pediatric and adolescent patients [10]. In fact, with the so-called conversational analysis (CA), the proportion of correctly identified PNES and ES has been found to be around 90% to 100%. However, with few exceptions, the sample size of these studies is limited, namely 10 patients in Cornaggia et al. [9], and 11 in Schwabe et al. [11]. The features characterizing the two different styles were operationalized in a diagnostic scoring aid (DSA) to convert the qualitative assessments into a numeric score. In a further study on 20 patients, two linguists blinded to all medical information were able to correctly classify 85% of patients [8], using DSA. With the DSA, diagnoses were predicted with a sensitivity of 85.7% (71.4%) and a specificity of 84.6% (92.3%). A similar percentage was found also with adolescent and pediatric patients [10]. In an attempt to investigate whether people with PNES have a specific mental profile, it has been reported that patients with PNES frequently have a mental health problem (see [2,12] for review), sometimes (but not always) a higher IQ than patients with epilepsy [3], but also the opposite pattern (a lower IQ in PNES) has been found [13]; in any case, it is not clear how cognitive deficits could affect the correct diagnosis. Therefore, the aim of this study was twofold: first, we applied CA in an unselected continuous large series of patients to discriminate patients with PNES from patients with epilepsy, and, second, we verified whether specific cognitive deficits or mental health problems could have prevented the correct diagnosis. 2. Material and methods
not show any concomitant ictal activity, or postictal slowing; and (3) no evidence of any alternative paroxistic disease (e.g., movement disorders, syncope). Independently from the diagnosis performed by means of VEEG, each subject underwent an audio-recorded interview conducted by a trained psychologist. Subsequently, two external psychologists evaluated the recordings using CA, ignoring the clinical and VEEG diagnoses, to which, therefore, they were blind (see Section 2.3). More specifically, the two external psychologists transcribed all the audio-recorded interviews and then analyzed the transcriptions. In the transcriptions, they reported the content of the conversations and not the many details of the speech that are typically noted in the formal CA. However, when they had any doubt mainly concerning pauses, uncertainties, etc., they listened to the audio again. The protocol was carried out in accordance with the ethical standards of the Declaration of Helsinki and The Ethics Committee of San Paolo Hospital reviewed and approved the study protocol. 2.2. Neuropsychological assessment All patients were submitted to an extensive neuropsychological battery, including memory (digit span forward and backward, Corsi span, Short Story, and Rey figure delayed recall), executive functions (TMT, Attentional Matrices), and language (Boston Naming test, phonemic and semantic fluency, and Token Test) tasks, abstract reasoning (Raven Colored Progressive Matrices), as well as two tasks assessing cognitive decline, the Milan Overall Dementia Assessment (MODA) and the Mini Mental State Examination (MMSE). In addition, the WAIS-R and the Beck Depression scale were performed. 2.3. Clinical interview According to Reuber et al. [8] and the German EpiLing project [7], the interviewer asked five questions: – – – – –
What was your expectation when you came here? What do you remember about your first seizure? What do you remember about your last seizure? What do you remember about your worst seizure? What do you like doing in your spare time?
2.1. Participants The study was performed at the University of Milan, Epilepsy Center, San Paolo Hospital and at the University of Milano-Bicocca, Psychology Department, where the recorded conversations were analyzed. All patients had given their written informed consent before answering the interviews. Between July 2015 and July 2016, 70 inpatients admitted to the Epilepsy Center, St. Paolo Hospital were consecutively enrolled in the study according to the following criteria: age 16–80 years, education level equal to or higher than primary school, and normal intelligence (IQ ≥ 85) according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition classification (DSM-5). We excluded subjects with progressive neurological pathologies. The diagnosis of epilepsy was based on the International League Against Epilepsy (ILAE) classification. Seizure types were classified according to clinical semiology provided by a witness' description or when possible, by VEEG recording of the episode. Refractory epilepsy was defined as uncontrolled seizures after at least two first-line anticonvulsant medication trials. Patients were considered seizure-free if they were without clinical seizures for at least 1 year, using the last clinical visit documenting seizure status as the end point of follow-up. The diagnosis of PNES was made on the basis of the consensus of at least two epilepsy specialists based on the clinical history and VEEG monitoring. The following criteria were used to diagnose PNES: (1) at least one single typical clinical event captured on VEEG; (2) EEG did
The first open question (“Which are your expectations regarding this consultation?”) allows the patients to set the agenda of the conversation and to freely articulate their point of view on their illness experience. The second question was difficult for those patients who had their first seizure many years before. All participants easily understood and replied to the other two main questions. Following the guidelines, the interviewer also asked some probing questions (e.g., “Can you please articulate more on this topic?”) to obtain more specific and in-depth information by the patients. 2.4. Data analysis Data are presented as means and standard deviations (SDs). Statistical analyses were performed using SPSS version 22 (Statistical Package for the Social Sciences). Significance was set at a p value of 0.05. Categorical or ordinal variables were compared using the Mann– Whitney U test where appropriate; continuous variables were compared using Student's t-test after applying Levene's test for equality of variance. If the variance was unequal, nonparametric tests were performed. Simultaneous logistic regression models were used to evaluate the ability of independent variables to predict outcomes. We did not perform a group size calculation; the group sizes in this study were based on the recruitment capacity of our center, and the modest size of the groups could have increased the risk of false negative findings.
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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2.4.1. Analysis with the differential diagnosis scoring table The analysis of the transcribed interviews was conducted with the Differential Diagnosis Scoring Table, a DSA developed by Reuber et al. [8]. The authors identified 17 specific features that differently characterize the seizure descriptions provided by patients suffering from epileptic seizures and by patients suffering from psychogenic seizures. In the DSA, features are organized into three main areas: interactional features, indicating whether information is spontaneously provided by the patient or is requested by the interviewer; topical features, which mainly assess the level of detail in the patient's descriptions; and linguistic features, which assess the formulation efforts of the patient and her/his metaphoric conceptualization of the seizures. Each feature corresponds to one item in the DSA, and the analysts have to rate each item on a 3-point scale (1/0/− 1), so that the maximum DSA score is 17 and the minimum score is − 17. Positive scores correspond to a stereotypical epileptic seizure description; negative score to a stereotypical nonepileptic seizure description. The two raters who analyzed the Italian data presented in this paper had no preliminary epileptological experience and did not receive any prior medical information about the patients, similar to the study by Reuber et al. [8]. Different from the previous studies, the two raters were not linguists; they had a psychological background and a specific competence in the qualitative analysis of textual data. Before starting the analysis, the two raters participated to some training sessions on the use of the DSA. To this end, they read and discussed the three studies mentioned above, and they collaborated on the translation of the DSA into Italian. Secondly, they received the instruction to assign the score to each item based on the whole interview and not of one extract. Finally, they independently coded three casually chosen interviews, and after that, they discussed about their scores to reach a consensus about how to interpret the data. 3. Results Seventy patients (46 females [65.7%]; mean age: 46.0 years [SD: 16.87 years]) took part in the study. Nine patients were excluded for the following reasons: three showed borderline intellectual functioning (BIF), two patients were not Italian native speakers (1 Hispanic and 1 Arabic), while four patients suffered from severe or acute Axis I disorders. The final group included 49 patients with epilepsy (mean age: 47.63 years; SD: 17.46; range 17–80 years) and 12 patients with PNES (mean age: 42.42 years; SD: 17.26; range 16–65 years). The ratio of epilepsy (80.32%) and PNES (19.68%) is typical of patients admitted to the Epilepsy Center of that Hospital in Milan and is approximately the ratio reported for specialized centers [14,15]. In the epilepsy group (n = 49), 11 patients (22%) presented a psychiatric diagnosis (Axis I, Axis II, or Axis I + Axis II). On the other hand, nine (75%) patients with PNES had a psychiatric disorder (p b 0.05). We also observed a higher prevalence of women compared with men in PNES cases (p b 0.05). Seizure frequency was significantly higher in subjects with PNES compared with those with epilepsy (p b 0.05). The psychiatric diagnosis was made by means of a psychiatric interview, according to the DSM IV-TR. The two groups did not differ in the neuropsychological profile. The demographic and clinical characteristics of the two groups are set out in Table 1. 3.1. Analysis with DSA Both psychologists correctly identified 49 (80.3%) cases out of 61 using DSA; in one case, there was no agreement. Diagnostic scoring aid demonstrated a sensitivity of 0.795 and a specificity of 0.83. In Table 2, the individual data of patients for whom an incorrect diagnosis was done are summarized. Among the 12 subjects (6 [50.0%] males; 6 [50.0%] females; mean age 44.0 years, range 16–74 years)
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Table 1 Demographic and clinical data of the two groups of patients.
Gender Male/Female (%) Age, years (SD) Education, years (SD) Duration, years (SD) Type of epilepsies Focal epilepsy Idiopathic generalized epilepsy Frequency per month AEDs Monotherapy (%) Polytherapy (%) No therapy (%) Raven Colored Progressive Matrices Verbal fluency Semantic fluency Attentional Matrices Digit span forward Digit span backward Corsi span Short Story Rey–Osterrieth complex figure
Group with epilepsy n = 49
Group with PNES n = 12
18/31 (36.73/63.27) 47.63 (17.46) 11.78 (3.48) 26.72 (18.10)
2/10 (16.67/83.33) 42.42 (17.26) 11.83 (3.46) 23.0 (21.15)
Significance
Ns Ns Ns
29 (59.18) 20 (40.82) 3.85 (8.85) 100% 26 (53.1) 23 (46.9)
0.032 Ns
28.67 (5.11)
15.2 (13.97) 83.3% 3(25) 7 (58.3) 2 (16.7) 28.0 (5.02)
27.68 (8.72) 35.95 (9.5) 51.41 (6.69) 4.86 (1.25) 3.5 (0.7) 4.57 (1.25) 10.69 (5.16) 15.66 (8.34)
27.89 (9.03) 34.33 (8.63) 48.0 (9.26) 5.89 (1.53) 3.5 (2.12) 4.13 (0.64) 10.29 (3.86) 12.81 (10.36)
Ns Ns Ns Ns Ns Ns Ns Ns
Ns
who were misdiagnosed, 10 had epilepsy (83.3%), whereas 2 (16.7%) suffered PNES. In the misdiagnosed population with epilepsy, two patients suffered a psychiatric comorbidity, as did both patients with PNES. Five misdiagnosed patients affected by epilepsy had been seizure-free since some years (see Table 3 for global data), while none of the group with PNES had been seizure-free.
4. Discussion In our study, we investigated in a large sample of patients whether the DSA developed by Reuber et al. [8] might be a reliable tool to differentiate epilepsy and PNES. We also tried to assess whether there are selective cognitive or psychiatric features that are associated with PNES; finally, we verified whether there are specific reasons that prevent a correct diagnosis through DSA. First of all, our results are in line with previous studies, since the percentage of correctly diagnosed patients was similar to those obtained in previous studies (see for example, [8]); however, in our study, this information was obtained with a larger sample of patients. Considering the diagnostic interview, we suggest that some questions need to be revised. Indeed, a typical reply to the first one, concerning expectations, was “Why should I have expectations on this consultation? I attended so many consultations!” The second question about the patient's first seizure was also considered as quite awkward, since seizures had started several years before. A typical reaction was “How can I remember what happened so many years ago?” Therefore, answers to the first question were not informative, while the second question gave rise to false interpretations, since the descriptions were sometimes very poor, due to the fact that many years have passed since onset. The second result was a negative one, since we found no differences in the cognitive profile of patients with PNES as compared with those with epileptic seizures. This negative result suggests that the interactional and linguistic differences between the two patient groups cannot be explained by differences in cognitive performance. Reuber [16] reports that in many studies, patients with PNES tend to perform below
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Table 2 Misdiagnosed patients' individual demographic and clinical data. Patient
Gender
Age
Education
Diagnosis
Duration (years)
Frequency
Seizure-free
Seizure type
AEDs
Comorbidity
NPS deficit
1
Female
40
16
TLE left
26
Yearly
No
Focal complex
LEV, PRM
No
2
Male
42
13
35
Stop seizures (2000)
Yes
Focal
CBZ
Blind, OSAS
3
Male
43
13
Focal symptomatic epilepsy Focal cryptogenic epilepsy
Frontal impairments /
33
Monthly
No
Focal
CBZ, VPA
GAD
4
Male
54
13
2
Stop seizures (2013)
Yes
Focal complex
LTG
/
5
Female
28
13
12
Stop seizures (2011)
Yes
Absences
LEV
/
No deficit
6
Female
48
16
Focal symptomatic epilepsy Generalized idiopathic epilepsy PNES
Short term verbal and visual–spatial memory /
8
Weekly
/
“Focal simple”
CBZ, LEV
AD
7 8
Female Female
16 35
10 17
6 17
Weekly Monthly
/ No
“Focal simple” Absences
TPM CBZ
Anxiety disorder /
9
Male
28
16
1
Only 2 seizures
Yes
Anxiety disorder
No deficit
Male
55
13
45
Stop seizures (2010)
Yes
Complex partial seizures Focal
LTG
10
LEV, LTG
Aphasia
/
11
Female
66
8
PNES Generalized idiopathic epilepsy Focal cryptogenic epilepsy Focal symptomatic epilepsy Generalized idiopathic epilepsy
Visual–spatial long term memory No deficit No deficit
47
Yearly
No
LEV
/
12
Male
74
13
Focal symptomatic epilepsy
9
Yearly
No
Generalized tonic–clonic seizures Focal simple
CBZ
OSAS
Short term visual–spatial memory /
NPS: neuropsychological; LEV: levetiracetam; PRM: primidone, CBZ: carbamazepine; VPA: valproic acid; LTG: lamotrigine; TPM: topiramate; OSAS: obstructive sleep apnea syndrome; GAD: generalized anxiety disorder; AD: adjustment disorder.
expectation in neuropsychological tests. In their own study, 60.6% of all patients with PNES performed at least 1.5 SD below norm populations in at least one domain of testing [17]. Functions tested were verbal and visual memory, alertness, motor skills, abstraction, and verbal fluency, as well as IQ. However, many studies comparing performance in patients with PNES and patients with epilepsy found no differences between the two groups (see for example [18]). In addition, it depends on the type of epilepsy we are dealing with. For example, when a group of women with PNES was compared with a group with temporal lobe epilepsy matched for age and education, the group with PNES performed significantly worse in working memory and attention tasks, while they outperformed the group with epilepsy in verbal and visual long-term memory [19]. What seems to differentiate the two groups is the maximal effort that they put forth during neuropsychological testing, and it has been suggested that the cognitive impairment reported by the group with PNES could be a function of motivational factors [20]. Another possibility is a qualitative difference in the type of errors produced by patients with PNES [21], since a difference has been found in word recognition with patients with PNES producing few false-positive errors, which resulted in failure to endorse a significant
Table 3 Clinical features of patients incorrectly classified divided by diagnosis. Misdiagnosis
n = 12 Group with epilepsy n = 10 Group with PNES n = 2
Gender Male/female (%) Age, years (SD) Education, years (SD) Duration, years (SD) Frequency per month (SD) Seizure-free (%) AEDs Monotherapy (%) Polytherapy (%) No therapy (%) Comorbidity (%)
6/4 (60.0/40.0) 46.5 (15.4) 13.6 (2.67) 18.36 (6.43) 7.91 (12.91) 5 (50) 100% 6 (60) 4 (40)
0/2 (0/100) 31.5 (23.3) 13.0 (4.24) 7.0 (2.82) 16.5 (16.26) 0 100% 1 (50) 1 (50)
2 (20)
2 (100)
number of items on the recognition test. We did not include a word recognition task in our battery, and, as far as other tests were considered, there were no remarkable qualitative differences in the type of error. Similarly, there were no specific mental features we could suggest that can produce a wrong diagnosis. However, among the misdiagnosed patients, five had seizures since 25–47 years; consequently, their answers were very limited; one patient suffered nonfluent aphasia, so that also in his case, responses were poor due to the production deficit. There is, however, an aspect that differentiates the two groups, namely the presence of psychiatric comorbidity that was significantly more frequent in the group with PNES, in line with a recent review [22]. Finally, we can highlight that patients with PNES were never seizure-free, while this was the case for some of the patients with epilepsy. A conclusion that can be certainly drawn from our study is that DSA is not effective if seizures started long before this technique is applied to reach a diagnosis. A relevant result of our study is that we demonstrated that psychologists with an adequate training in textual analysis can apply this methodology with similar results than linguists; this may be a facilitation for the dissemination of DSA as a diagnostic tool since psychologists work in many hospital teams, while the presence of a linguist is relatively unlikely. Accordingly, it has been recently demonstrated that a brief conversation analytic teaching intervention can enable neurologists to identify linguistic and interactional features that help in differentiating epilepsy and PNES while taking patients' history in routine seizure clinic consultations [23]. Following the intervention, doctors were significantly more likely to use nondirective approach to soliciting patient accounts [24]. Indeed, a comparison of video recordings of 38 routine consultations before and 20 consultations after the intervention showed that the doctors' approach changed and the patient responses better revealed diagnostically relevant features [25]. Patients were given more time to describe their seizures, but, apparently, the overall appointment length did not increase significantly. In any case, it is necessary to transcribe conversations from videos (or audios, as in our sample) and analyze these transcriptions; these
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Differentiating PNES from epileptic seizures using conversational analysis Costanza Papagno a,b,⁎,1, Lorenzo Montali b,1, Katherine Turner c,1, Alessandra Frigerio b, Martina Sirtori b, Elena Zambrelli c, Valentina Chiesa c, Maria Paola Canevini c,d a
CIMeC and CeRiN, University of Trento, via Matteo Del Ben 5/b, 38068 Rovereto, Italy Department of Psychology, University of Milano-Bicocca, Edificio U6, Piazza dell'Ateneo Nuovo 1, 20126 Milano, Italy Epilepsy Center, San Paolo Hospital, via A. Di Rudinì 8, 20142 Milano, Italy d Department of Health Sciences, University of Milan, 20100 Milano, Italy b c
a r t i c l e
i n f o
Article history: Received 21 July 2017 Revised 23 August 2017 Accepted 24 August 2017 Available online xxxx Keywords: Conversation analysis Psychogenic nonepileptic seizure Video-EEG
a b s t r a c t We applied conversation analysis in an unselected continuous series of 70 patients to discriminate patients with psychogenic nonepileptic seizures (PNES) from patients with epilepsy. Two psychologists examined the patients' recorded reports. Patients were also submitted to an extensive neuropsychological battery in order to verify whether specific cognitive deficits or mental health problems are typical of patients with PNES and whether some cognitive deficits could prevent the correct diagnosis. The results showed a good percentage of correct diagnosis, with a sensitivity of 0.795 and a specificity of 0.83, while no difference in the cognitive profile was found between patients with PNES and patients with epilepsy. The results also suggest that psychologists can apply the conversation analysis as well as linguists, which is an important finding since psychologists are employed in specialized centers, while linguists in general are not part of the team. © 2017 Elsevier Inc. All rights reserved.
1. Introduction An epileptic seizure is defined as a “transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain” [1]. Psychogenic nonepileptic seizures (PNES) are defined as an episode characterized by sudden and temporary motor, sensory, autonomic, cognitive, or emotional symptoms, and signs mimicking epileptic seizures but not associated with epileptic cortical discharges (for a detailed review on this topic see [2]). Therefore, from a clinical point of view, the two disturbances share many similarities, preventing a reliable differential diagnosis. As a consequence, epilepsy tends to be overdiagnosed and, frequently, it takes several years to reach a correct diagnosis of PNES. At present, video-EEG (VEEG) is the gold standard technique used in order to differentiate the two conditions; however, it is available only in a limited number of specialized epilepsy centers and nevertheless, the two types of seizure can coexist, increasing the difficulty of making a correct diagnosis [3]. When seizures are recorded with VEEG, it is necessary to make sure that the recorded episodes were the same type of events experienced outside
⁎ Corresponding author at: CeRiN (Centro di Riabilitazione Neurocognitiva), Via Matteo del Ben 5/b, University of Trento, 38068 Rovereto, TN, Italy. E-mail addresses: [email protected], [email protected] (C. Papagno). 1 The first three authors equally contributed to the paper.
the VEEG Lab. In a recent study, Erba et al. [4] investigated whether and to what extent information contained in a video-recorded event in the absence of EEG allowed four experienced epileptologists to predict the diagnosis of PNES. In 7 out of 23 videos, all raters predicted the diagnosis correctly, while in 5 cases, all four failed. Moreover, home video recording is often not sufficiently informative. For all of these reasons, even if the diagnosis relies in many cases on the interpretation of the patient's history and witness accounts of events, PNES are hard to distinguish only on the basis of their symptoms. Patients' perception and subjective experience of PNES have been extensively investigated, mainly by means of self-report questionnaires focusing on the seizure disorder, or addressing the experience of individual seizures [5,6]. However, the relevance of subjective symptoms might not be revealed using self-report questionnaires. In this prospective, a multidisciplinary research group in Germany developed the so-called EpiLing project which aimed at assessing how patients describe their subjective seizure experiences, namely how they communicate it; indeed, it has been suggested that patients use a range of different communicative styles when describing their seizures, and these communication styles seem to concord with the medical diagnoses of epileptic or PNES. The descriptions were produced in an interactional setting, talks between doctors and patients, so that they can be considered as a method that patients use to share and make understandable to others their subjective accounts. With this method, qualitative aspects of the patients' description are given special value.
http://dx.doi.org/10.1016/j.yebeh.2017.08.034 1525-5050/© 2017 Elsevier Inc. All rights reserved.
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Qualitative methods allow patients to communicate their feelings and thoughts in more fine-grained and richer detail compared with quantitative self-report methods. They enable patients to clarify what is important to them rather than forcing them to reply by endorsing predefined categorical responses that may oversimplify the idiosyncrasies of the condition. The analysis identified two distinct communicative styles, as reported above, which are characterized by some systematic patterns in the method that patients use to describe their seizures and showed some relevant differences between the description of patients with epilepsy and of patients with PNES. This approach has been successfully applied in two different languages, German [7] and English [8], and in a limited sample of Italian patients, both adults [9] and pediatric and adolescent patients [10]. In fact, with the so-called conversational analysis (CA), the proportion of correctly identified PNES and ES has been found to be around 90% to 100%. However, with few exceptions, the sample size of these studies is limited, namely 10 patients in Cornaggia et al. [9], and 11 in Schwabe et al. [11]. The features characterizing the two different styles were operationalized in a diagnostic scoring aid (DSA) to convert the qualitative assessments into a numeric score. In a further study on 20 patients, two linguists blinded to all medical information were able to correctly classify 85% of patients [8], using DSA. With the DSA, diagnoses were predicted with a sensitivity of 85.7% (71.4%) and a specificity of 84.6% (92.3%). A similar percentage was found also with adolescent and pediatric patients [10]. In an attempt to investigate whether people with PNES have a specific mental profile, it has been reported that patients with PNES frequently have a mental health problem (see [2,12] for review), sometimes (but not always) a higher IQ than patients with epilepsy [3], but also the opposite pattern (a lower IQ in PNES) has been found [13]; in any case, it is not clear how cognitive deficits could affect the correct diagnosis. Therefore, the aim of this study was twofold: first, we applied CA in an unselected continuous large series of patients to discriminate patients with PNES from patients with epilepsy, and, second, we verified whether specific cognitive deficits or mental health problems could have prevented the correct diagnosis. 2. Material and methods
not show any concomitant ictal activity, or postictal slowing; and (3) no evidence of any alternative paroxistic disease (e.g., movement disorders, syncope). Independently from the diagnosis performed by means of VEEG, each subject underwent an audio-recorded interview conducted by a trained psychologist. Subsequently, two external psychologists evaluated the recordings using CA, ignoring the clinical and VEEG diagnoses, to which, therefore, they were blind (see Section 2.3). More specifically, the two external psychologists transcribed all the audio-recorded interviews and then analyzed the transcriptions. In the transcriptions, they reported the content of the conversations and not the many details of the speech that are typically noted in the formal CA. However, when they had any doubt mainly concerning pauses, uncertainties, etc., they listened to the audio again. The protocol was carried out in accordance with the ethical standards of the Declaration of Helsinki and The Ethics Committee of San Paolo Hospital reviewed and approved the study protocol. 2.2. Neuropsychological assessment All patients were submitted to an extensive neuropsychological battery, including memory (digit span forward and backward, Corsi span, Short Story, and Rey figure delayed recall), executive functions (TMT, Attentional Matrices), and language (Boston Naming test, phonemic and semantic fluency, and Token Test) tasks, abstract reasoning (Raven Colored Progressive Matrices), as well as two tasks assessing cognitive decline, the Milan Overall Dementia Assessment (MODA) and the Mini Mental State Examination (MMSE). In addition, the WAIS-R and the Beck Depression scale were performed. 2.3. Clinical interview According to Reuber et al. [8] and the German EpiLing project [7], the interviewer asked five questions: – – – – –
What was your expectation when you came here? What do you remember about your first seizure? What do you remember about your last seizure? What do you remember about your worst seizure? What do you like doing in your spare time?
2.1. Participants The study was performed at the University of Milan, Epilepsy Center, San Paolo Hospital and at the University of Milano-Bicocca, Psychology Department, where the recorded conversations were analyzed. All patients had given their written informed consent before answering the interviews. Between July 2015 and July 2016, 70 inpatients admitted to the Epilepsy Center, St. Paolo Hospital were consecutively enrolled in the study according to the following criteria: age 16–80 years, education level equal to or higher than primary school, and normal intelligence (IQ ≥ 85) according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition classification (DSM-5). We excluded subjects with progressive neurological pathologies. The diagnosis of epilepsy was based on the International League Against Epilepsy (ILAE) classification. Seizure types were classified according to clinical semiology provided by a witness' description or when possible, by VEEG recording of the episode. Refractory epilepsy was defined as uncontrolled seizures after at least two first-line anticonvulsant medication trials. Patients were considered seizure-free if they were without clinical seizures for at least 1 year, using the last clinical visit documenting seizure status as the end point of follow-up. The diagnosis of PNES was made on the basis of the consensus of at least two epilepsy specialists based on the clinical history and VEEG monitoring. The following criteria were used to diagnose PNES: (1) at least one single typical clinical event captured on VEEG; (2) EEG did
The first open question (“Which are your expectations regarding this consultation?”) allows the patients to set the agenda of the conversation and to freely articulate their point of view on their illness experience. The second question was difficult for those patients who had their first seizure many years before. All participants easily understood and replied to the other two main questions. Following the guidelines, the interviewer also asked some probing questions (e.g., “Can you please articulate more on this topic?”) to obtain more specific and in-depth information by the patients. 2.4. Data analysis Data are presented as means and standard deviations (SDs). Statistical analyses were performed using SPSS version 22 (Statistical Package for the Social Sciences). Significance was set at a p value of 0.05. Categorical or ordinal variables were compared using the Mann– Whitney U test where appropriate; continuous variables were compared using Student's t-test after applying Levene's test for equality of variance. If the variance was unequal, nonparametric tests were performed. Simultaneous logistic regression models were used to evaluate the ability of independent variables to predict outcomes. We did not perform a group size calculation; the group sizes in this study were based on the recruitment capacity of our center, and the modest size of the groups could have increased the risk of false negative findings.
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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2.4.1. Analysis with the differential diagnosis scoring table The analysis of the transcribed interviews was conducted with the Differential Diagnosis Scoring Table, a DSA developed by Reuber et al. [8]. The authors identified 17 specific features that differently characterize the seizure descriptions provided by patients suffering from epileptic seizures and by patients suffering from psychogenic seizures. In the DSA, features are organized into three main areas: interactional features, indicating whether information is spontaneously provided by the patient or is requested by the interviewer; topical features, which mainly assess the level of detail in the patient's descriptions; and linguistic features, which assess the formulation efforts of the patient and her/his metaphoric conceptualization of the seizures. Each feature corresponds to one item in the DSA, and the analysts have to rate each item on a 3-point scale (1/0/− 1), so that the maximum DSA score is 17 and the minimum score is − 17. Positive scores correspond to a stereotypical epileptic seizure description; negative score to a stereotypical nonepileptic seizure description. The two raters who analyzed the Italian data presented in this paper had no preliminary epileptological experience and did not receive any prior medical information about the patients, similar to the study by Reuber et al. [8]. Different from the previous studies, the two raters were not linguists; they had a psychological background and a specific competence in the qualitative analysis of textual data. Before starting the analysis, the two raters participated to some training sessions on the use of the DSA. To this end, they read and discussed the three studies mentioned above, and they collaborated on the translation of the DSA into Italian. Secondly, they received the instruction to assign the score to each item based on the whole interview and not of one extract. Finally, they independently coded three casually chosen interviews, and after that, they discussed about their scores to reach a consensus about how to interpret the data. 3. Results Seventy patients (46 females [65.7%]; mean age: 46.0 years [SD: 16.87 years]) took part in the study. Nine patients were excluded for the following reasons: three showed borderline intellectual functioning (BIF), two patients were not Italian native speakers (1 Hispanic and 1 Arabic), while four patients suffered from severe or acute Axis I disorders. The final group included 49 patients with epilepsy (mean age: 47.63 years; SD: 17.46; range 17–80 years) and 12 patients with PNES (mean age: 42.42 years; SD: 17.26; range 16–65 years). The ratio of epilepsy (80.32%) and PNES (19.68%) is typical of patients admitted to the Epilepsy Center of that Hospital in Milan and is approximately the ratio reported for specialized centers [14,15]. In the epilepsy group (n = 49), 11 patients (22%) presented a psychiatric diagnosis (Axis I, Axis II, or Axis I + Axis II). On the other hand, nine (75%) patients with PNES had a psychiatric disorder (p b 0.05). We also observed a higher prevalence of women compared with men in PNES cases (p b 0.05). Seizure frequency was significantly higher in subjects with PNES compared with those with epilepsy (p b 0.05). The psychiatric diagnosis was made by means of a psychiatric interview, according to the DSM IV-TR. The two groups did not differ in the neuropsychological profile. The demographic and clinical characteristics of the two groups are set out in Table 1. 3.1. Analysis with DSA Both psychologists correctly identified 49 (80.3%) cases out of 61 using DSA; in one case, there was no agreement. Diagnostic scoring aid demonstrated a sensitivity of 0.795 and a specificity of 0.83. In Table 2, the individual data of patients for whom an incorrect diagnosis was done are summarized. Among the 12 subjects (6 [50.0%] males; 6 [50.0%] females; mean age 44.0 years, range 16–74 years)
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Table 1 Demographic and clinical data of the two groups of patients.
Gender Male/Female (%) Age, years (SD) Education, years (SD) Duration, years (SD) Type of epilepsies Focal epilepsy Idiopathic generalized epilepsy Frequency per month AEDs Monotherapy (%) Polytherapy (%) No therapy (%) Raven Colored Progressive Matrices Verbal fluency Semantic fluency Attentional Matrices Digit span forward Digit span backward Corsi span Short Story Rey–Osterrieth complex figure
Group with epilepsy n = 49
Group with PNES n = 12
18/31 (36.73/63.27) 47.63 (17.46) 11.78 (3.48) 26.72 (18.10)
2/10 (16.67/83.33) 42.42 (17.26) 11.83 (3.46) 23.0 (21.15)
Significance
Ns Ns Ns
29 (59.18) 20 (40.82) 3.85 (8.85) 100% 26 (53.1) 23 (46.9)
0.032 Ns
28.67 (5.11)
15.2 (13.97) 83.3% 3(25) 7 (58.3) 2 (16.7) 28.0 (5.02)
27.68 (8.72) 35.95 (9.5) 51.41 (6.69) 4.86 (1.25) 3.5 (0.7) 4.57 (1.25) 10.69 (5.16) 15.66 (8.34)
27.89 (9.03) 34.33 (8.63) 48.0 (9.26) 5.89 (1.53) 3.5 (2.12) 4.13 (0.64) 10.29 (3.86) 12.81 (10.36)
Ns Ns Ns Ns Ns Ns Ns Ns
Ns
who were misdiagnosed, 10 had epilepsy (83.3%), whereas 2 (16.7%) suffered PNES. In the misdiagnosed population with epilepsy, two patients suffered a psychiatric comorbidity, as did both patients with PNES. Five misdiagnosed patients affected by epilepsy had been seizure-free since some years (see Table 3 for global data), while none of the group with PNES had been seizure-free.
4. Discussion In our study, we investigated in a large sample of patients whether the DSA developed by Reuber et al. [8] might be a reliable tool to differentiate epilepsy and PNES. We also tried to assess whether there are selective cognitive or psychiatric features that are associated with PNES; finally, we verified whether there are specific reasons that prevent a correct diagnosis through DSA. First of all, our results are in line with previous studies, since the percentage of correctly diagnosed patients was similar to those obtained in previous studies (see for example, [8]); however, in our study, this information was obtained with a larger sample of patients. Considering the diagnostic interview, we suggest that some questions need to be revised. Indeed, a typical reply to the first one, concerning expectations, was “Why should I have expectations on this consultation? I attended so many consultations!” The second question about the patient's first seizure was also considered as quite awkward, since seizures had started several years before. A typical reaction was “How can I remember what happened so many years ago?” Therefore, answers to the first question were not informative, while the second question gave rise to false interpretations, since the descriptions were sometimes very poor, due to the fact that many years have passed since onset. The second result was a negative one, since we found no differences in the cognitive profile of patients with PNES as compared with those with epileptic seizures. This negative result suggests that the interactional and linguistic differences between the two patient groups cannot be explained by differences in cognitive performance. Reuber [16] reports that in many studies, patients with PNES tend to perform below
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Table 2 Misdiagnosed patients' individual demographic and clinical data. Patient
Gender
Age
Education
Diagnosis
Duration (years)
Frequency
Seizure-free
Seizure type
AEDs
Comorbidity
NPS deficit
1
Female
40
16
TLE left
26
Yearly
No
Focal complex
LEV, PRM
No
2
Male
42
13
35
Stop seizures (2000)
Yes
Focal
CBZ
Blind, OSAS
3
Male
43
13
Focal symptomatic epilepsy Focal cryptogenic epilepsy
Frontal impairments /
33
Monthly
No
Focal
CBZ, VPA
GAD
4
Male
54
13
2
Stop seizures (2013)
Yes
Focal complex
LTG
/
5
Female
28
13
12
Stop seizures (2011)
Yes
Absences
LEV
/
No deficit
6
Female
48
16
Focal symptomatic epilepsy Generalized idiopathic epilepsy PNES
Short term verbal and visual–spatial memory /
8
Weekly
/
“Focal simple”
CBZ, LEV
AD
7 8
Female Female
16 35
10 17
6 17
Weekly Monthly
/ No
“Focal simple” Absences
TPM CBZ
Anxiety disorder /
9
Male
28
16
1
Only 2 seizures
Yes
Anxiety disorder
No deficit
Male
55
13
45
Stop seizures (2010)
Yes
Complex partial seizures Focal
LTG
10
LEV, LTG
Aphasia
/
11
Female
66
8
PNES Generalized idiopathic epilepsy Focal cryptogenic epilepsy Focal symptomatic epilepsy Generalized idiopathic epilepsy
Visual–spatial long term memory No deficit No deficit
47
Yearly
No
LEV
/
12
Male
74
13
Focal symptomatic epilepsy
9
Yearly
No
Generalized tonic–clonic seizures Focal simple
CBZ
OSAS
Short term visual–spatial memory /
NPS: neuropsychological; LEV: levetiracetam; PRM: primidone, CBZ: carbamazepine; VPA: valproic acid; LTG: lamotrigine; TPM: topiramate; OSAS: obstructive sleep apnea syndrome; GAD: generalized anxiety disorder; AD: adjustment disorder.
expectation in neuropsychological tests. In their own study, 60.6% of all patients with PNES performed at least 1.5 SD below norm populations in at least one domain of testing [17]. Functions tested were verbal and visual memory, alertness, motor skills, abstraction, and verbal fluency, as well as IQ. However, many studies comparing performance in patients with PNES and patients with epilepsy found no differences between the two groups (see for example [18]). In addition, it depends on the type of epilepsy we are dealing with. For example, when a group of women with PNES was compared with a group with temporal lobe epilepsy matched for age and education, the group with PNES performed significantly worse in working memory and attention tasks, while they outperformed the group with epilepsy in verbal and visual long-term memory [19]. What seems to differentiate the two groups is the maximal effort that they put forth during neuropsychological testing, and it has been suggested that the cognitive impairment reported by the group with PNES could be a function of motivational factors [20]. Another possibility is a qualitative difference in the type of errors produced by patients with PNES [21], since a difference has been found in word recognition with patients with PNES producing few false-positive errors, which resulted in failure to endorse a significant
Table 3 Clinical features of patients incorrectly classified divided by diagnosis. Misdiagnosis
n = 12 Group with epilepsy n = 10 Group with PNES n = 2
Gender Male/female (%) Age, years (SD) Education, years (SD) Duration, years (SD) Frequency per month (SD) Seizure-free (%) AEDs Monotherapy (%) Polytherapy (%) No therapy (%) Comorbidity (%)
6/4 (60.0/40.0) 46.5 (15.4) 13.6 (2.67) 18.36 (6.43) 7.91 (12.91) 5 (50) 100% 6 (60) 4 (40)
0/2 (0/100) 31.5 (23.3) 13.0 (4.24) 7.0 (2.82) 16.5 (16.26) 0 100% 1 (50) 1 (50)
2 (20)
2 (100)
number of items on the recognition test. We did not include a word recognition task in our battery, and, as far as other tests were considered, there were no remarkable qualitative differences in the type of error. Similarly, there were no specific mental features we could suggest that can produce a wrong diagnosis. However, among the misdiagnosed patients, five had seizures since 25–47 years; consequently, their answers were very limited; one patient suffered nonfluent aphasia, so that also in his case, responses were poor due to the production deficit. There is, however, an aspect that differentiates the two groups, namely the presence of psychiatric comorbidity that was significantly more frequent in the group with PNES, in line with a recent review [22]. Finally, we can highlight that patients with PNES were never seizure-free, while this was the case for some of the patients with epilepsy. A conclusion that can be certainly drawn from our study is that DSA is not effective if seizures started long before this technique is applied to reach a diagnosis. A relevant result of our study is that we demonstrated that psychologists with an adequate training in textual analysis can apply this methodology with similar results than linguists; this may be a facilitation for the dissemination of DSA as a diagnostic tool since psychologists work in many hospital teams, while the presence of a linguist is relatively unlikely. Accordingly, it has been recently demonstrated that a brief conversation analytic teaching intervention can enable neurologists to identify linguistic and interactional features that help in differentiating epilepsy and PNES while taking patients' history in routine seizure clinic consultations [23]. Following the intervention, doctors were significantly more likely to use nondirective approach to soliciting patient accounts [24]. Indeed, a comparison of video recordings of 38 routine consultations before and 20 consultations after the intervention showed that the doctors' approach changed and the patient responses better revealed diagnostically relevant features [25]. Patients were given more time to describe their seizures, but, apparently, the overall appointment length did not increase significantly. In any case, it is necessary to transcribe conversations from videos (or audios, as in our sample) and analyze these transcriptions; these
Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
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Please cite this article as: Papagno C, et al, Differentiating PNES from epileptic seizures using conversational analysis, Epilepsy Behav (2017), http://dx.doi.org/10.1016/j.yebeh.2017.08.034
