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Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis
Thesis (PhD)--Stellenbosch University, 2025.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : Stellenbosch University
2025
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| _version_ | 1867613858705702912 |
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| access_status_str | Open Access |
| author | Vilyte, Gabriele Beata |
| author2 | Pretorius, Chrisma |
| author_browse | Pretorius, Chrisma Vilyte, Gabriele Beata |
| author_facet | Pretorius, Chrisma Vilyte, Gabriele Beata |
| author_sort | Vilyte, Gabriele Beata |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (PhD)--Stellenbosch University, 2025. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/134413 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:42:49.487Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/134413 Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis Vilyte, Gabriele Beata Pretorius, Chrisma Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Psychology. Thesis (PhD)--Stellenbosch University, 2025. Vilyte, G. B. 2025. Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis. Unpublished doctoral thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/47ec08e6-35b7-462d-a629-c89e00d81867 A major challenge in functional seizure (FS) diagnosis is accurately distinguishing them from epileptic seizures (ES). Video-electroencephalography (video-EEG), the gold standard for diagnosing FS, is largely inaccessible in many low- and middle-income countries (LMICs), including South Africa. As a result, many patients with FS may be misdiagnosed with epilepsy and inappropriately treated with antiseizure medications (ASMs). This not only imposes financial strain on both individuals and the public health system but also increases health risks and complications while delaying access to appropriate care. Despite this, very little is known about the FS population in South Africa, and no comprehensive efforts have been made to develop affordable, efficient, and easy-to-administer clinical decision support tools for FS in this context. The aim of this thesis was twofold: first, to develop a comprehensive clinical profile of patients with FS in South Africa; and second, to investigate whether patient-reported information can be used to create a contextually-sensitive clinical decision support tool. I employ a retrospective patient chart review to describe the psychosocial, medication-use, comorbidity, and semiological profiles of patients with FS from both public and private healthcare settings in Cape Town, South Africa. I then use the collected information to develop and cross-validate a clinical decision tool for the public healthcare setting. To describe this patient population I use descriptive and inferential statistics, and to develop the clinical decision tool I employ machine-learning techniques and predictive modelling. The first part of this thesis presents a comprehensive analysis of the clinical profiles of 389 patients with FS, including 321 from a private hospital and 68 from a public hospital. While some aspects of clinical history and presentation differed between these two cohorts, I found that FS in South Africa, across these different socioeconomic groups, aligned closely with patterns observed in international literature. This highlights that FS is, by and large, a stable and consistent disorder globally. In the second part of this thesis, I employ the least absolute shrinkage and selection operator (Lasso), a machine learning technique that performs both variable selection and regularisation in regression models, to harness the comprehensive set of 185 FS clinical predictors collected from 67 FS and 168 ES patients at the public hospital. Using the selected predictors I develop a clinical decision tool for FS in the public health setting achieving an overall classification accuracy of 86%, sensitivity of 85% (95% CI 74.3-92.6), specificity of 87% (95% CI 80.8-91.6), a positive predictive value of 72% (95% CI 60.9-81.7) and a negative predictive value of 94% (95% CI 88.5-96.9) at the selected cut-off score. The tool shows promise as a supportive aid for clinicians in the tertiary public health setting, offering a potential way to streamline the diagnostic process for FS. Overall, this project presents an in-depth study of the clinical characteristics of patients with FS in South Africa and offers a first step towards developing a practical, accessible tool to aid patient management in the tertiary public healthcare setting. Together, these contributions represent an important step toward improving our understanding of FS in South Africa and supporting clinicians in addressing the challenge of FS misdiagnosis. Doctoral 2025-11-20T07:52:55Z 2025-11-20T07:52:55Z 2025-03 Thesis https://scholar.sun.ac.za/handle/10019.1/134413 en Stellenbosch University 301 pages application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Vilyte, Gabriele Beata Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis |
| title | Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis |
| title_full | Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis |
| title_fullStr | Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis |
| title_full_unstemmed | Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis |
| title_short | Psychogenic Non-epileptic Seizure (PNES) Patient Profiles in Two Western Cape Epilepsy Monitoring Units and Their Utility in PNES Diagnosis |
| title_sort | psychogenic non epileptic seizure pnes patient profiles in two western cape epilepsy monitoring units and their utility in pnes diagnosis |
| url | https://scholar.sun.ac.za/handle/10019.1/134413 |
| work_keys_str_mv | AT vilytegabrielebeata psychogenicnonepilepticseizurepnespatientprofilesintwowesterncapeepilepsymonitoringunitsandtheirutilityinpnesdiagnosis |