European Society of Cardiology quality indicators for the cardiovascular pre-operative assessment and management of patients considered for non-cardiac surgery. Developed in collaboration with the European Society of Anaesthesiology and Intensive Care.

AIMS: To establish a set of quality indicators (QIs) for the cardiovascular (CV) assessment and management of patients undergoing non-cardiac surgery (NCS). METHODS AND RESULTS: The Quality Indicator Committee of the European Society of Cardiology (ESC) and European Society of Anaesthesiology and Intensive Care (ESAIC) in collaboration with Task Force members of the 2022 ESC Guidelines on CV assessment and management of patients undergoing NCS followed the ESC methodology for QI development. This included (1) identification, by constructing a conceptual framework of care, of domains of the CV assessment, and management of patients with risk factors or established cardiovascular disease (CVD) who are considered for or undergoing NCS, (2) development of candidate QIs following a systematic literature review, (3) selection of the final set of QIs using a modified Delphi method, and (4) evaluation of the feasibility of the developed QIs. In total, eight main and nine secondary QIs were selected across six domains: (1) structural framework (written policy), (2) patient education and quality of life (CV risk discussion), (3) peri-operative risk assessment (indication for diagnostic tests), (4) peri-operative risk mitigation (use of hospital therapies), (5) follow-up (post-discharge assessment), and (6) outcomes (major CV events). CONCLUSION: We present the 2022 ESC/ESAIC QIs for the CV assessment and management of patients with risk factors or established CVD who are considered for or are undergoing NCS y. These indicators are supported by evidence from the literature, underpinned by expert consensus, and align with the 2022 ESC Guidelines on CV assessment and management of patients undergoing NCS.

Association between income and control of cardiovascular risk factors after acute coronary syndromes: an observational study.

BACKGROUND: The role of income in cardiovascular disease prevention after an acute coronary syndrome (ACS) remains unclear. We aimed to assess the association between income and control of cardiovascular risk factors one year after an ACS in a country with universal health insurance. METHODS: Between 2013 and 2014, we studied 255 consecutive patients with ACS in an observational study in a university hospital in Switzerland in which self-reported household income was assessed. We classified patients into two categories based on the median income in Switzerland: higher than CHF 6000 (€ 5300) or less than or equal to CHF 6000 (€ 5300) per month. One year after discharge, patients were evaluated for the achievement of lipid and blood pressure targets, smoking cessation and drug adherence. Multivariate odds ratios (OR) were adjusted for age, sex, education, living status and working status. RESULTS: Overall, 52.2% (n = 133) of patients with ACS were in the low-income category and 47.8% (n = 122) were in the high-income category. One year after discharge, high-income patients had higher rates of smoking cessation (64.2 vs 30.1%, multivariate-adjusted odds ratio (OR) 3.82, 95% confidence interval (CI) 1.58–9.24) and blood pressure target achievement (78.6 vs 60.2%, multivariate-adjusted OR 2.19, 95% CI 1.09–4.41) compared to those in the low-income category. There were no differences regarding adherence to drugs or lipid control between the two income groups. CONCLUSION: A high household income was associated with a higher rate of smoking cessation and better control of blood pressure one year after ACS, independently of education, living status and working status.

Prevalence and management of familial hypercholesterolaemia in patients with acute coronary syndromes.

AIMS: We aimed to assess the prevalence and management of clinical familial hypercholesterolaemia (FH) among patients with acute coronary syndrome (ACS). METHODS AND RESULTS: We studied 4778 patients with ACS from a multi-centre cohort study in Switzerland. Based on personal and familial history of premature cardiovascular disease and LDL-cholesterol levels, two validated algorithms for diagnosis of clinical FH were used: the Dutch Lipid Clinic Network algorithm to assess possible (score 3-5 points) or probable/definite FH (>5 points), and the Simon Broome Register algorithm to assess possible FH. At the time of hospitalization for ACS, 1.6% had probable/definite FH [95% confidence interval (CI) 1.3-2.0%, n = 78] and 17.8% possible FH (95% CI 16.8-18.9%, n = 852), respectively, according to the Dutch Lipid Clinic algorithm. The Simon Broome algorithm identified 5.4% (95% CI 4.8-6.1%, n = 259) patients with possible FH. Among 1451 young patients with premature ACS, the Dutch Lipid Clinic algorithm identified 70 (4.8%, 95% CI 3.8-6.1%) patients with probable/definite FH, and 684 (47.1%, 95% CI 44.6-49.7%) patients had possible FH. Excluding patients with secondary causes of dyslipidaemia such as alcohol consumption, acute renal failure, or hyperglycaemia did not change prevalence. One year after ACS, among 69 survivors with probable/definite FH and available follow-up information, 64.7% were using high-dose statins, 69.0% had decreased LDL-cholesterol from at least 50, and 4.6% had LDL-cholesterol ≤1.8 mmol/L. CONCLUSION: A phenotypic diagnosis of possible FH is common in patients hospitalized with ACS, particularly among those with premature ACS. Optimizing long-term lipid treatment of patients with FH after ACS is required.

Electrocardiographic Screening for Prolonged QT Interval to Reduce Sudden Cardiac Death in Psychiatric Patients: A Cost-Effectiveness Analysis.

IMPORTANCE: Sudden cardiac death is a leading cause of mortality in psychiatric patients. Long QT (LQT) is common in this population and predisposes to Torsades-de-Pointes (TdP) and subsequent mortality. OBJECTIVE: To estimate the cost-effectiveness of electrocardiographic screening to detect LQT in psychiatric inpatients. DESIGN, SETTING, AND PARTICIPANTS: We built a decision analytic model based on a decision tree to evaluate the cost-effectiveness and utility of LQT screening from a health care perspective. LQT proportion parameters were derived from an in-hospital cross-sectional study. We performed experts' elicitation to estimate the risk of TdP, given extent of QT prolongation. A TdP reduction of 65% after LQT detection was based on positive drug dechallenge rate and through adequate treatment and electrolyte adjustments. The base-case model uncertainty was assessed with one-way and probabilistic sensitivity analyses. Finally, the TdP related mortality and TdP avoidance parameters were varied in a two-way sensitivity analysis to assess their effect on the Incremental Cost-Effectiveness Ratio (ICER). MAIN OUTCOMES AND MEASURES: Costs, Quality Ajusted Life Year (QALY), ICER, and probability of cost effectiveness thresholds ($ 10,000, $25,000, and $50,000 per QALY). RESULTS: In the base-case scenario, the numbers of patients needed to screen were 1128 and 2817 to avoid one TdP and one death, respectively. The ICER of systematic ECG screening was $8644 (95%CI, 3144-82 498) per QALY. The probability of cost-effectiveness was 96% at a willingness-to-pay of $50,000 for one QALY. In sensitivity analyses, results were sensitive to the case-fatality of TdP episodes and to the TdP reduction following the diagnosis of LQT. CONCLUSION AND RELEVANCE: In psychiatric hospitals, performing systematic ECG screening at admission help reduce the number of sudden cardiac deaths in a cost-effective fashion.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result

Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score.

BACKGROUND: Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. METHODS: Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. RESULTS: The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increasing with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774) revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81) with a sensitivity of 85.6% and a specificity of 47.2%. CONCLUSIONS: This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.