Browsing by Author "Batty, G David"

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    Anaemia, haemoglobin level and cause-specific mortality in people with and without diabetes
    (Public Library of Science, 2012) Kengne, Andre Pascal; Czernichow, Sébastien; Hamer, Mark; Batty, G David; Stamatakis, Emmanuel
    BACKGROUND: Both anaemia and cardiovascular disease (CVD) are common in people with diabetes. While individually both characteristics are known to raise mortality risk, their combined influence has yet to be quantified. In this pooling project, we examined the combined impact of baseline haemoglobin levels and existing CVD on all-cause and CVD mortality in people with diabetes. We draw comparison of these effects with those apparent in diabetes-free individuals. Methods/Principal FINDINGS: A combined analyses of 7 UK population-based cohorts resulted in 26,480 study members. There were 946 participants with physician-diagnosed diabetes, 2227 with anaemia [haemoglobin<13 g/dl (men) or <12 (women)], 2592 with existing CVD (stroke, ischaemic heart disease), and 21,396 with none of the conditions. Across diabetes and anaemia subgroups, and using diabetes-free, non-anaemic participants as the referent group, the adjusted hazard ratios (HR) were 1.46 (95% CI: 1.30-1.63) for anaemia, 1.67 (1.45-1.92) for diabetes, and 2.10 (1.55-2.85) for diabetes and anaemia combined. Across combined diabetes, anaemia and CVD subgroups, and compared with non-anaemic, diabetes-free and CVD-free participants, HR (95% CI) for all-cause mortality were 1.49 (1.32-1.69) anaemia, 1.60 (1.46-1.76) for existing CVD, and 1.66 (1.39-1.97) for diabetes alone. Equivalents were 2.13 (1.48-3.07) for anaemia and diabetes, 2.68 (2.14-3.36) for diabetes and existing CVD, and 3.25 (1.88-5.62) for the three combined. Patterns were similar for CVD mortality. Conclusions/Significance Individually, anaemia and CVD confer similar mortality risks in people with diabetes, and are excessively fatal in combination. Screening for anaemia would identify vulnerable diabetic patients whose outcomes can potentially be improved.
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    Risk models to predict hypertension: a systematic review
    (Public Library of Science, 2013) Echouffo-Tcheugui, Justin B; Batty, G David; Kivimäki, Mika; Kengne, Andre P
    BACKGROUND: As well as being a risk factor for cardiovascular disease, hypertension is also a health condition in its own right. Risk prediction models may be of value in identifying those individuals at risk of developing hypertension who are likely to benefit most from interventions. Methods and FINDINGS: To synthesize existing evidence on the performance of these models, we searched MEDLINE and EMBASE; examined bibliographies of retrieved articles; contacted experts in the field; and searched our own files. Dual review of identified studies was conducted. Included studies had to report on the development, validation, or impact analysis of a hypertension risk prediction model. For each publication, information was extracted on study design and characteristics, predictors, model discrimination, calibration and reclassification ability, validation and impact analysis. Eleven studies reporting on 15 different hypertension prediction risk models were identified. Age, sex, body mass index, diabetes status, and blood pressure variables were the most common predictor variables included in models. Most risk models had acceptable-to-good discriminatory ability (C-statistic>0.70) in the derivation sample. Calibration was less commonly assessed, but overall acceptable. Two hypertension risk models, the Framingham and Hopkins, have been externally validated, displaying acceptable-to-good discrimination, and C-statistic ranging from 0.71 to 0.81. Lack of individual-level data precluded analyses of the risk models in subgroups. CONCLUSIONS: The discrimination ability of existing hypertension risk prediction tools is acceptable, but the impact of using these tools on prescriptions and outcomes of hypertension prevention is unclear.