Why the study?
Approximately 50% of out-of-hospital sudden cardiac arrests occur in people with unrecognized risk and no prior cardiologic care records, including individuals with type 2 diabetes.
Routine primary care data can identify risk factors for sudden cardiac arrest in patients with type 2 diabetes, such as high fasting glucose, albuminuria, and a history of cardiovascular disease.
May enable SCA risk stratification from routine T2D data; hypothesis-generating pending prospective validation.
Background Approximately 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. Methods This 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). Results We 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. Conclusions The 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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Harms et al. (2024) studied this question.
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