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Gareth Ambler

Publications and source records attributed to Gareth Ambler.

4 recordsLinked to original sources
PubMed2003

Off-Pump Coronary Artery Bypass (OPCAB) surgery reduces risk-stratified morbidity and mortality: a United Kingdom Multi-Center Comparative Analysis of Early Clinical Outcome.

OBJECTIVE: Off-Pump Coronary Artery Bypass (OPCAB) surgery is gaining more popularity worldwide. The aim of this United Kingdom (UK) multi-center study was to assess the early clinical outcome of the OPCAB technique and perform a risk-stratified comparison with the conventional Coronary Artery Bypass Grafting (CABG) using the Cardio-Pulmonary Bypass (CPB) technique. METHODS: Data were collected on 5,163 CPB patients from the database of the National Heart and Lung institute, Imperial College, University of London, and on 2,223 OPCAB patients from eight UK cardiac surgical centers, which run established OPCAB surgery programs. All patients had undergone primary isolated CABG for multi-vessel disease through a midline sternotomy approach, between January 1997 and April 2001. Postoperative morbidity and mortality were compared between the CPB and OPCAB patients after adjusting for case-mix. The mortality of the OPCAB patients was also compared, using risk stratification, to the mortality figures reported by the Society of Cardiothoracic Surgeons of Great Britain and Ireland (SCTS) based on 28,018 patients in the national database who were operated on between January 1996 and December 1999. RESULTS: Morbidity and mortality were significantly lower in the OPCAB patients compared with the CPB patients and the UK national database of CABG patients, over the same period of time, after adjusting for case-mix. CONCLUSIONS: This study demonstrates that risk stratified morbidity and mortality are significantly lower in OPCAB patients than CPB patients and patients in the UK national database.

Adult↗
PubMed2003

Non-linear models for the relation between cardiovascular risk factors and intake of wine, beer and spirits.

It is generally accepted that moderate consumption of alcohol is associated with a reduced risk of coronary heart disease (CHD). It is not clear however whether this benefit is derived through the consumption of a specific beverage type, for example, wine. In this paper the associations between known CHD risk factors and different beverage types are investigated using a novel approach with non-linear modelling. Two types of model are proposed which are designed to detect differential effects of beverage type. These may be viewed as extensions of Box and Tidwell's power-linear model. The risk factors high density lipoprotein cholesterol, fibrinogen and systolic blood pressure are considered using data from a large longitudinal study of British civil servants (Whitehall II). The results for males suggest that gram for gram of alcohol, the effect of wine differs from that of beer and spirits, particularly for systolic blood pressure. In particular increasing wine consumption is associated with slightly more favourable levels of all three risk factors studied. For females there is evidence of a differential relationship only for systolic blood pressure. These findings are tentative but suggest that further research is required to clarify the similarities and differences between the results for males and females and to establish whether either of the models is the more appropriate. However, having clarified these issues, the apparent benefit of consuming wine instead of other alcoholic beverages may be relatively small.

Adult↗
PubMed2002

Simplifying a prognostic model: a simulation study based on clinical data.

Prognostic models are designed to predict a clinical outcome in individuals or groups of individuals with a particular disease or condition. To avoid bias many researchers advocate the use of full models developed by prespecifying predictors. Variable selection is not employed and the resulting models may be large and complicated. In practice more parsimonious models that retain most of the prognostic information may be preferred. We investigate the effect on various performance measures, including mean square error and prognostic classification, of three methods for estimating full models (including penalized estimation and Tibshirani's lasso) and consider two methods (backwards elimination and a new proposal called stepdown) for simplifying full models. Simulation studies based on two medical data sets suggest that simplified models can be found that perform nearly as well as, or sometimes even better than, full models. Optimizing the Akaike information criterion appears to be appropriate for choosing the degree of simplification.

Aortic Aneurysm, Abdominal↗