Using routine primary care data to assess Sudden Cardiac Arrest risk in people with type 2 diabetes: a proof-of-concept case-control study
Harms, P. P.; van Dongen, L. H.; Oosterbaan, N.; Bennis, F. C.; Beulens, J. W. J.; Swart, K. M. A.; Hoogendoorn, M.; Tan, H. L.; Elders, P. P. J. M.; Blom, M. T.; RESCUED investigators,
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BackgroundApproximately 50% of out-of-hospital Sudden Cardiac Arrest (SCA) occurs in people with unrecognized SCA-risk and no preceding cardiologic care records. General practitioner (GP) records include these people, specifically people with type 2 diabetes (T2D) with increased SCA-risk. We aimed to provide a proof-of-concept for using routine primary care data to study SCA-risk in people with T2D. MethodsThis case-control study, identified SCA cases through the AmsteRdam REsuscitation STudies (ARREST) registry of out-of-hospital SCA in the Dutch region of Noord-Holland (2005-2019). We included cases with presumed cardiac cause and T2D registered at participating GP practices from the PHARMO Data Network and the academic network of general practice Amsterdam UMC (ANHA). Cases were matched (age, sex, T2D, GP-practice) with up to five non-SCA controls. From their GP files, we collected clinical measurements, medication use and medical history. Associations with SCA were analysed using univariable and multivariable conditional logistic regression (Odds Ratios, 95% confidence intervals). ResultsWe included 247 cases and 1,143 controls. In the multivariable model, high fasting glucose (1.08 (1.01-1.16) per 1 mmol/L), high cholesterol ratio (1.17 (1.03-1.34)), moderate albuminuria (2.77 (1.84-4.16)), severe albuminuria (2.96 (1.44-6.08)), dyslipidaemia (0.53 (0.33-0.86)) and a history of cardiovascular disease (1.72 (1.23-2.17)) were significantly associated with SCA. Current smoking behaviour, decreased eGFR, insulin use, hypertension and microvascular complications were close to significantly associated with SCA. ConclusionsThe relatively strong associations in our small sample are consistent with those found in cardiologic care populations, indicating that GP file data can be useful to study SCA-risk.
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