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Predictive validity of different definitions of hypertension for type 2 diabetes
Martin C Gulliford1, Judith Charlton, Radoslav Latinovic
1Department of Public Health Sciences, Division of Health and Social Care Research, King's College London, UK. martin.gulliford@kcl.ac.uk
Insights
Different definitions of hypertension impact diabetes prediction accuracy. Using medical diagnoses or blood pressure medication prescriptions yielded varying sensitivities, highlighting the need for consistent hypertension definitions in predictive models.
Area of Science:
- Cardiology
- Endocrinology
- Health Services Research
Background:
- Predictive models for diabetes and pre-diabetes often include hypertension assessment.
- Inconsistent definitions of hypertension lead to varied classification outcomes.
- This study evaluates the impact of different hypertension definitions on diabetes prediction.
Purpose of the Study:
- To compare diabetes classification accuracy using distinct hypertension definitions.
- To assess the influence of diagnostic and treatment-based hypertension criteria.
- To identify variations in hypertension recording and prescribing practices across family practices.
Main Methods:
- A case-control study involving 5158 diabetes patients and 5158 matched controls.
- Hypertension classification compared using medical diagnoses, blood pressure-lowering drug prescriptions, or a combination.
- Analysis of variations in hypertension diagnosis and prescribing across 181 family practices.
Main Results:
- Hypertension diagnosis alone had 32.2% sensitivity for diabetes prediction.
- Prescription of blood pressure-lowering drugs showed 47.2% sensitivity.
- Combining diagnosis or prescription increased sensitivity to 52.8%.
- Sensitivity varied significantly based on family practice recording and prescribing rates.
Conclusions:
- Misclassification of hypertension is influenced by the definition used and its clinical implementation.
- Hypertension definitions reliant on healthcare access or quality can introduce bias.
- Standardized and consistent hypertension definitions are crucial for reliable diabetes prediction models.
Background:
Models to predict diabetes or pre-diabetes often incorporate the assessment of hypertension, but proposed definitions for 'hypertension' are inconsistent. We compared the classifications obtained using different definitions for 'hypertension'.
Methods:
We compared records for 5158 cases from 181 family practices, who were later diagnosed with diabetes and prescribed oral hypoglycaemic drugs, with 5158 controls, matched for age, sex and family practice, who were never diagnosed with diabetes. We compared classifications obtained using definitions of hypertension based on medical diagnoses, prescription of blood pressure lowering drugs or both. We compared family practices where diagnosis or prescribing varied systematically.
Results:
Classification of hypertension based on recorded medical diagnoses gave a sensitivity of 32.2% for diabetes (95% confidence interval from 30.4 to 34.1%). Prescription of blood pressure lowering drugs in the 12 months before diagnosis gave a sensitivity of 47.2% (45.7 to 48.7%). Combining either a medical diagnosis or a blood pressure lowering prescription gave a sensitivity of 52.8% (51.3 to 54.3%). In family practices where hypertension was least frequently recorded, a diagnosis of hypertension gave a sensitivity of 19.5% for diabetes (17.4 to 21.6%) compared with 50.8% (46.3 to 55.3%) in the highest quintile. Prescription of blood pressure lowering drugs gave a sensitivity of 36.1% (33.1 to 39.0%) in the lowest prescribing practices but 58.2% (55.5 to 61.0%) in the highest quintile.
Conclusions:
Misclassification errors depend on the definition of hypertension and its implementation in practice. Definitions of hypertension that depend on access or quality in health care should be avoided.
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