Gitsels, Lisanne (2017) Cardiovascular disease and its impact on longevity and longevity improvement. Doctoral thesis, University of East Anglia.
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Abstract
An increased risk or a history of cardiovascular disease (CVD) is associated with worse
survival prospects. Clinical guidelines recommend several treatments for primary
and secondary prevention. These guidelines are mainly based on clinical trials and
hospital data. Data from routine clinical practice could provide insights in longevity
and longevity improvement in the general population as opposed to selected patients.
The primary objectives of this research were to investigate how a history of CVD
affects longevity in residents of the United Kingdom at retirement age, and to investigate
which treatments improve longevity.
Medical records from 1987 to 2011 from general practices contributing to The
Health Improvement Network (THIN) database were used to develop two specific
survival models: to estimate the hazards of all-cause mortality associated with a history
of acute myocardial infarction (AMI) and related treatments, and to estimate
the hazard of all-cause mortality associated with statins prescribed as primary prevention
of CVD. The models were multilevel Cox's proportional hazards regressions
that included comorbidities, treatments, lifestyle choices, and socio-demographic factors.
The models were specified for ages 60, 65, 70, and 75. More accurate estimates
of longevity at these key ages could inform future medical management by clinicians
and financial planning for retirement by individuals, actuaries, and the government.
This research found that survival prospects after AMI were reduced by less than
previous studies have reported. Furthermore, currently recommended treatments for
CVD were associated with mixed survival prospects, in which coronary revascularisation
and prescription of beta blockers and statins were associated with improved
prospects and prescription of ACE inhibitors and aspirin were associated with worsened
prospects.
Item Type: | Thesis (Doctoral) |
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Faculty \ School: | Faculty of Science > School of Computing Sciences |
Depositing User: | Jackie Webb |
Date Deposited: | 28 Jun 2017 13:18 |
Last Modified: | 28 Jun 2017 13:20 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/63945 |
DOI: |
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