Machine learning as a diagnostic decision aid for patients with transient loss of consciousness.

BACKGROUND: Transient loss of consciousness (TLOC) is a common reason for presentation to primary/emergency care; over 90% are because of epilepsy, syncope, or psychogenic non-epileptic seizures (PNES). Misdiagnoses are common, and there are currently no validated decision rules to aid diagnosis and management. We seek to explore the utility of machine-learning techniques to develop a short diagnostic instrument by extracting features with optimal discriminatory values from responses to detailed questionnaires about TLOC manifestations and comorbidities (86 questions to patients, 31 to TLOC witnesses). METHODS: Multi-center retrospective self- and witness-report questionnaire study in secondary care settings. Feature selection was performed by an iterative algorithm based on random forest analysis. Data were randomly divided in a 2:1 ratio into training and validation sets (163:86 for all data; 208:92 for analysis excluding witness reports). RESULTS: Three hundred patients with proven diagnoses (100 each: epilepsy, syncope and PNES) were recruited from epilepsy and syncope services. Two hundred forty-nine completed patient and witness questionnaires: 86 epilepsy (64 female), 84 PNES (61 female), and 79 syncope (59 female). Responses to 36 questions optimally predicted diagnoses. A classifier trained on these features classified 74/86 (86.0% [95% confidence interval 76.9%-92.6%]) of patients correctly in validation (100 [86.7%-100%] syncope, 85.7 [67.3%-96.0%] epilepsy, 75.0 [56.6%-88.5%] PNES). Excluding witness reports, 34 features provided optimal prediction (classifier accuracy of 72/92 [78.3 (68.4%-86.2%)] in validation, 83.8 [68.0%-93.8%] syncope, 81.5 [61.9%-93.7%] epilepsy, 67.9 [47.7%-84.1%] PNES). CONCLUSIONS: A tool based on patient symptoms/comorbidities and witness reports separates well between syncope and other common causes of TLOC. It can help to differentiate epilepsy and PNES. Validated decision rules may improve diagnostic processes and reduce misdiagnosis rates. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for patients with TLOC, patient and witness questionnaires discriminate between syncope, epilepsy and PNES.

Value of witness observations in the differential diagnosis of transient loss of consciousness.

OBJECTIVE: This retrospective study explores to what extent additional information from event witnesses provided using the novel 31-item Paroxysmal Event Observer (PEO) Questionnaire improves the differentiation among epilepsy, syncope, and psychogenic nonepileptic seizures (PNES) achievable with information provided by patients alone. METHODS: Patients with transient loss of consciousness caused by proven epilepsy (n = 86), syncope (n = 79), or PNES (n = 84) attending specialist neurology/syncope services in the United Kingdom and event observers provided Paroxysmal Event Profile (PEP), PEO, and personal information (PI) (e.g., sex, age, medical history) data. PEO data were subjected to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). PEO, PEP, and PI data were used separately and in combination to differentiate diagnoses by pairwise and multinomial logistic regressions. Predicted diagnoses were compared with gold standard medical diagnoses. RESULTS: EFA/CFA identified a 4-factor structure of the PEO based on 26/31 questionnaire items with loadings ≥0.4. Observer-reported factors alone differentiated better between syncope and epilepsy than patient-reported factors (accuracy: 96% vs 85%, p = 0.0004). Observer-reported data improved accuracy over differentiation based on patient-reported data alone from 90% to 100% between syncope and epilepsy (p = 0.005), 76% to 83% between epilepsy and PNES (p = 0.006), and 93% to 95% between syncope and PNES (p = 0.098). CONCLUSIONS: Information from observers can make an important contribution to the differentiation of epilepsy from syncope or PNES but adds less to that of syncope from PNES.

Value of patient-reported symptoms in the diagnosis of transient loss of consciousness.

OBJECTIVE: Epileptic seizures, syncope, and psychogenic nonepileptic seizures (PNES) account for over 90% of presentations with transient loss of consciousness (TLOC). The patient's history is crucial for the diagnosis, but the diagnostic value of individual semiologic features is limited. This study explores the diagnostic potential of a comprehensive questionnaire focusing on TLOC-associated symptoms. METHODS: A total of 386 patients with proven epilepsy, 308 patients with proven PNES, and 371 patients with proven syncope were approached by post to recruit 100 patients in each diagnostic group. Symptoms were self-reported on an 86-item questionnaire (the Paroxysmal Event Profile [PEP]) using a 5-point Likert scale (always to never). Data were subjected to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). Factors were used to differentiate between diagnoses by pairwise and multinomial regression. RESULTS: Patients with PNES reported more and more frequent TLOC-associated symptoms than those with epilepsy or syncope (p < 0.001). EFA/CFA identified a 5-factor structure based on 74/86 questionnaire items with loadings ≥0.4. Pairwise logistic regression analysis correctly classified 91% of patients with epilepsy vs those with syncope, 94% of those with PNES vs those with syncope, and 77% of those with epilepsy vs those with PNES. Multinomial logistic regression analysis yielded a similar pattern. CONCLUSIONS: Clusters of self-reported TLOC symptoms can be used to direct patients to appropriate investigation and treatment pathways for syncope on the one hand and seizures on the other, although additional information is required for a reliable distinction, especially between epilepsy and PNES.

Psychogenic nonepileptic seizure manifestations reported by patients and witnesses.

PURPOSE: Psychogenic nonepileptic seizures (PNES) continue to represent a serious diagnostic challenge for neurologists. Video-electroencephalography (EEG) studies have provided detailed knowledge of the spectrum of visible PNES manifestations. However, little is known about how patients or seizure witnesses experience PNES, although many diagnoses in seizure clinics are made on the basis of self-reported information rather than video-EEG observations. This study describes the range of PNES manifestations as they are reported by patients or seizure witnesses. METHODS: Three hundred eight candidates for this study were consecutively diagnosed with PNES on the basis of video-EEG recordings of habitual seizures involving impairment of consciousness without epileptic ictal EEG activity at the Royal Hallamshire Hospital in Sheffield and the National Hospital for Neurology in London, United Kingdom. One hundred patients responded to a postal questionnaire and participated in this study. Eighty-four of the questionnaires completed by patients were accompanied by questionnaires completed by seizure witness. The patient questionnaire contained 12 demographic and clinical questions and the 86-item Paroxysmal Event Profile (PEP), asking patients to rate statements about their attacks on a five-point Likert scale ("always,""frequently,""sometimes,""rarely,""never"). The Paroxysmal Event Observer (PEO) questionnaire uses 34-items with the same Likert scale. The PEP questionnaire includes inquiries about symptoms of panic or dissociation as well as symptoms previously found to distinguish between generalized tonic-clonic seizures and syncope or thought to differentiate between epilepsy and PNES. KEY FINDINGS: The item-by-item analysis revealed the inter- and intraindividual variability of PNES experiences. The majority of patients with PNES reported some phenomena, which have traditionally been attributed to epilepsy (such as seizures from sleep, experiencing a rising sensation in their body, postictal myalgia). Although most PNES were experienced as striking without warning and reported to cause loss or impairment of consciousness, most patients also reported seizure warnings in at least some of the seizures. Despite the clinical heterogeneity apparent from these findings, a correlation matrix showed that symptoms were not randomly distributed. Significant correlations were seen between duration of seizures and seizures from reported sleep (r = -0.28, p = 0.006), seizure-related motor activity and seizures from reported sleep (p = -0.48, p < 0.001), flashbacks and anxiety (p = 0.44, p < 0.001) or dissociation (p = 0.66, p < 0.001), and anxiety and dissociation (r = 0.53, p < 0.001). The comparison of similarly worded items on the PEP and PEO questionnaires showed that witnesses were more often aware of seizure triggers and a relationship between PNES and emotional stress than were patients (p = 0.001/p < 0.001). SIGNIFICANCE: These findings based on the self-report of patients with well-characterized PNES and witnesses of their seizures demonstrate why it can be difficult to distinguish descriptions of PNES from those of epilepsy on the basis of factual items. The differences between patient and witness reports suggest that clinicians have to take note of the source of information they use in their diagnostic considerations. The intra- and interindividual variability of reported PNES manifestations demonstrates the clinical heterogeneity of PNES disorders. The positive correlation of symptoms of dissociation and anxiety in these patients may reflect psychopathologic differences between subgroups of PNES patients.

Common genetic variation and susceptibility to partial epilepsies: a genome-wide association study.

Partial epilepsies have a substantial heritability. However, the actual genetic causes are largely unknown. In contrast to many other common diseases for which genetic association-studies have successfully revealed common variants associated with disease risk, the role of common variation in partial epilepsies has not yet been explored in a well-powered study. We undertook a genome-wide association-study to identify common variants which influence risk for epilepsy shared amongst partial epilepsy syndromes, in 3445 patients and 6935 controls of European ancestry. We did not identify any genome-wide significant association. A few single nucleotide polymorphisms may warrant further investigation. We exclude common genetic variants with effect sizes above a modest 1.3 odds ratio for a single variant as contributors to genetic susceptibility shared across the partial epilepsies. We show that, at best, common genetic variation can only have a modest role in predisposition to the partial epilepsies when considered across syndromes in Europeans. The genetic architecture of the partial epilepsies is likely to be very complex, reflecting genotypic and phenotypic heterogeneity. Larger meta-analyses are required to identify variants of smaller effect sizes (odds ratio<1.3) or syndrome-specific variants. Further, our results suggest research efforts should also be directed towards identifying the multiple rare variants likely to account for at least part of the heritability of the partial epilepsies. Data emerging from genome-wide association-studies will be valuable during the next serious challenge of interpreting all the genetic variation emerging from whole-genome sequencing studies.

Are current recommendations to diagnose orthostatic hypotension in Parkinson's disease satisfactory?

We interviewed 50 Parkinson's disease (PD) patients using a questionnaire to verify the reliability of orthostatic symptoms in warning the presence of orthostatic hypotension (OH). OH is defined as 20 mm Hg systolic or 10 mm Hg diastolic BP fall within 3 min of tilting or standing but if this fall occurs after 3 min we called it 'late OH' (L-OH). We compared if OH in Parkinson's disease (PD) was more frequent after head-up tilt or on standing and if the period of postural challenge matters in detecting OH. Twenty-one (42%) patients had OH that occurred twice more often after tilting (n = 20) than on standing (n = 10). OH occurred within 3 min of tilting in 9 patients (18%) and appeared beyond the currently recommended 3 min in 11 patients (55%) (L-OH). Ten of the 20 patients developing OH on tilting were symptomatic. The 10 patients who had OH on standing were asymptomatic. Reporting of symptoms was independent of age or severity of BP fall. Most (90%) patients reporting orthostatic symptoms on standing had OH on tilting for 3 min. Orthostatic symptoms in PD have a high specificity but low sensitivity in predicting OH. In Parkinson's disease OH occurs often after tilting than on standing and is delayed (after 3 min). As OH in PD is often asymptomatic and delayed it could contribute to falls and increase morbidity. We suggest routine evaluation of OH in PD by tilting them longer than the recommended 3 minutes to detect delayed OH.