Ozaltin, Burcu;
(2024)
Idiopathic Pulmonary Fibrosis:
Delineating the Impact of
Comorbidities and Therapeutics on
Prognosis Using Electronic Health Record Data.
Doctoral thesis (Ph.D), UCL (University College London).
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UCL_PhD_Thesis_27_08_2024_Burcu_Ozaltin.pdf - Accepted Version Access restricted to UCL open access staff until 1 March 2025. Download (5MB) |
Abstract
Fibrosing lung disease (FLD) is a group of chronic, progressive, fibrotic lung diseases of unknown aetiology associated with reduced survival, and its incidence is increasing every year. It is often misdiagnosed and treated inappropriately, resulting in poor outcomes. This study uses electronic health records (EHRs) from the Clinical Practice Research Datalink (CPRD) GOLD database, which contains information on diagnoses, prescriptions and patient characteristics, to investigate patients with FLD, with a particular focus on idiopathic pulmonary fibrosis (IPF), a family of lung diseases characterised by abnormal thickening and stiffening of lung tissue. Patients with IPF aged 40 years and older were included in the study and followed until censoring (i.e. transfer from their GP, diagnosis, death or end of the study period). Two different retrospective case-control studies were conducted to observe the impact of risk factors on IPF survival. The first was a study of comorbidity in patients before they were diagnosed with IPF. We wanted to determine whether patients with IPF should be considered to have a largely single-system disease or whether IPF, like COPD, should be considered a disease with multi-organ damage. The second study aimed to investigate whether drugs prescribed for other non-respiratory diseases, used in IPF patients may influence IPF survival and slow the rate of disease progression.
Type: | Thesis (Doctoral) |
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Qualification: | Ph.D |
Title: | Idiopathic Pulmonary Fibrosis: Delineating the Impact of Comorbidities and Therapeutics on Prognosis Using Electronic Health Record Data |
Language: | English |
Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10196301 |
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