Risk calculator for incident atrial fibrillation across a range of prediction horizons.

BACKGROUND: The increasing burden of atrial fibrillation (AF) emphasizes the need to identify high-risk individuals for enrolment in clinical trials of AF screening and primary prevention. We aimed to develop prediction models to identify individuals at high-risk of AF across prediction horizons from 6-months to 10-years. METHODS: We used secondary-care linked primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between January 2, 1998 and November 30, 2018; randomly divided into derivation (80%) and validation (20%) datasets. Models were derived using logistic regression from known AF risk factors for incident AF in prediction periods of 6 months, 1-year, 2-years, 5-years, and 10-years. Performance was evaluated using in the validation dataset with bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc and C2HEST scores. RESULTS: Of 2,081,139 individuals in the cohort (1,664,911 in the development dataset, 416,228 in the validation dataset), the mean age was 49.9 (SD 15.4), 50.7% were women, and 86.7% were white. New cases of AF were 7,386 (0.4%) within 6 months, 15,349 (0.7%) in 1 year, 38,487 (1.8%) in 5 years, and 79,997 (3.8%) by 10 years. Valvular heart disease and heart failure were the strongest predictors, and association of hypertension with AF increased at longer prediction horizons. The optimal risk models incorporated age, sex, ethnicity, and 8 comorbidities. The models demonstrated good-to-excellent discrimination and strong calibration across prediction horizons (AUROC, 95%CI, calibration slope: 6-months, 0.803, 0.789-0.821, 0.952; 1-year, 0.807, 0.794-0.819, 0.962; 2-years, 0.815, 0.807-0.823, 0.973; 5-years, 0.807, 0.803-0.812, 1.000; 10-years 0.780, 0.777-0.784, 1.010), and superior to the CHA2DS2-VASc and C2HEST scores. The models are available as a web-based FIND-AF calculator. CONCLUSIONS: The FIND-AF models demonstrate high discrimination and calibration across short- and long-term prediction horizons in 2 million individuals. Their utility to inform trial enrolment and clinical decisions for AF screening and primary prevention requires further study.

Post-COVID-19 Peripartum Cardiomyopathy: Experience from a Large Tertiary Referral Center.

BACKGROUND: Peripartum cardiomyopathy (PPCM) is a rare but potentially devastating complication of pregnancy. Although the pathophysiology of PPCM is not fully understood, there are known risk factors for developing PPCM, which are maternal and gestation related. In the first wave of the coronavirus disease 2019 (COVID-19) pandemic, we witnessed an elevated incidence of PPCM among COVID-19 survivors. OBJECTIVES: To present a single-center case series of three patients diagnosed with peripartum cardiomyopathy after recovered from COVID-19 during the index pregnancy. METHODS: In this single center case study, all patients diagnosed with PPCM at our institute during the examined time frame were included. Electronic medical records were studied. RESULTS: Three patients previously diagnosed with asymptomatic or mildly symptomatic COVID-19 disease during pregnancy presented with PPCM before or shortly after delivery. Patients underwent testing to rule out residual COVID-19 myocarditis, were treated pharmacologically and with wearable defibrillators as needed, and were examined in follow-up 1-9 months after delivery. CONCLUSIONS: Residual endothelial damage due to COVID-19 disease, even if originally mild in presentation, could predispose pregnant patients to PPCM and should be considered as a risk factor when assessing patients with new onset symptoms of heart failure. Further research is needed to confirm this hypothesis and fully determine the underlying pathophysiology. These preliminary findings warrant a high index of suspicion for PPCM in COVID-19 recoverers.

Peripheral Arterial Disease in Patients With Acute Coronary Syndrome: Results From a Large Real-World Registry.

BACKGROUND: Limited data exist regarding the significance of peripheral arterial disease (PAD) in patients with acute coronary syndrome (ACS). METHODS: We evaluated 16,922 consecutive ACS patients who were prospectively included in a national ACS registry. The co-primary endpoint included 30 days major adverse cardiovascular event (MACE) (re-infarction, stroke, and/or cardiovascular death) and 1-year mortality. RESULTS: PAD patients were older (70±11 vs 63±13; p<0.01), male predominance (80% vs 77%; p=0.01), and more likely to sustain prior cardiovascular events. PAD patients were less likely to undergo coronary angiography (69% vs 83%; p<0.001) and revascularisation (80% vs 86%; p<0.001). Patients with PAD were more likely to sustain 30-day MACE (22% vs 14%; p<0.001) and mortality (10% vs 4.4%; p<0.001), as well as re-hospitalisation (23% vs 19%; p=0.001). After adjusting for potential confounders, PAD remained an independent predictor of 30-day MACE (odds ratio [OR], 1.6 [95% confidence interval (CI), 1.24-2.06]). Patients with compared to those without PAD had 2.5 times higher 1-year mortality rate (22% vs 9%; p<0.001). Co-existence of PAD remained an independent predictor of 1-year mortality after adjustment for potential confounders by multivariable regression analysis (OR, 1.62; 95% CI, 1.4-1.9). PAD was associated with a significant higher 1-year mortality rate across numerous sub-groups of patients including type of myocardial infarction (ST-elevation myocardial infarction vs non-ST-elevation myocardial infarction), and whether the patient underwent revascularisation. CONCLUSIONS: Acute coronary syndrome with concomitant PAD represents a high-risk subgroup that warrants special attention and a more tailored approach.

Lipoprotein(a) lowering by alirocumab reduces the total burden of cardiovascular events independent of low-density lipoprotein cholesterol lowering: ODYSSEY OUTCOMES trial.

AIMS: Lipoprotein(a) concentration is associated with first cardiovascular events in clinical trials. It is unknown if this relationship holds for total (first and subsequent) events. In the ODYSSEY OUTCOMES trial in patients with recent acute coronary syndrome (ACS), the proprotein convertase subtilisin/kexin type 9 inhibitor alirocumab reduced lipoprotein(a), low-density lipoprotein cholesterol (LDL-C), and cardiovascular events compared with placebo. This post hoc analysis determined whether baseline levels and alirocumab-induced changes in lipoprotein(a) and LDL-C [corrected for lipoprotein(a) cholesterol] independently predicted total cardiovascular events. METHODS AND RESULTS: Cardiovascular events included cardiovascular death, non-fatal myocardial infarction, stroke, hospitalization for unstable angina or heart failure, ischaemia-driven coronary revascularization, peripheral artery disease events, and venous thromboembolism. Proportional hazards models estimated relationships between baseline lipoprotein(a) and total cardiovascular events in the placebo group, effects of alirocumab treatment on total cardiovascular events by baseline lipoprotein(a), and relationships between lipoprotein(a) reduction with alirocumab and subsequent risk of total cardiovascular events. Baseline lipoprotein(a) predicted total cardiovascular events with placebo, while higher baseline lipoprotein(a) levels were associated with greater reduction in total cardiovascular events with alirocumab (hazard ratio Ptrend = 0.045). Alirocumab-induced reductions in lipoprotein(a) (median -5.0 [-13.6, 0] mg/dL) and corrected LDL-C (median -51.3 [-67.1, -34.0] mg/dL) independently predicted lower risk of total cardiovascular events. Each 5-mg/dL reduction in lipoprotein(a) predicted a 2.5% relative reduction in cardiovascular events. CONCLUSION: Baseline lipoprotein(a) predicted the risk of total cardiovascular events and risk reduction by alirocumab. Lipoprotein(a) lowering contributed independently to cardiovascular event reduction, supporting the concept of lipoprotein(a) as a treatment target after ACS.

Effects of the chymase inhibitor fulacimstat on adverse cardiac remodeling after acute myocardial infarction-Results of the Chymase Inhibitor in Adverse Remodeling after Myocardial Infarction (CHIARA MIA) 2 trial.

BACKGROUND: Adverse cardiac remodeling is a major risk factor for the development of post myocardial infarction (MI) heart failure (HF). This study investigates the effects of the chymase inhibitor fulacimstat on adverse cardiac remodeling after acute ST-segment-elevation myocardial infarction (STEMI). METHODS: In this double-blind, randomized, placebo-controlled trial patients with first STEMI were eligible. To preferentially enrich patients at high risk of adverse remodeling, main inclusion criteria were a left-ventricular ejection fraction (LVEF) ≤45% and an infarct size >10% on day 5 to 9 post MI as measured by cardiac MRI. Patients were then randomized to 6 months treatment with either 25 mg fulacimstat (n = 54) or placebo (n = 53) twice daily on top of standard of care starting day 6 to 12 post MI. The changes in LVEF, LV end-diastolic volume index (LVEDVI), and LV end-systolic volume index (LVESVI) from baseline to 6 months were analyzed by a central blinded cardiac MRI core laboratory. RESULTS: Fulacimstat was safe and well tolerated and achieved mean total trough concentrations that were approximately tenfold higher than those predicted to be required for minimal therapeutic activity. Comparable changes in LVEF (fulacimstat: 3.5% ±â€¯5.4%, placebo: 4.0% ±â€¯5.0%, P = .69), LVEDVI (fulacimstat: 7.3 ±â€¯13.3 mL/m2, placebo: 5.1 ±â€¯18.9 mL/m2, P = .54), and LVESVI (fulacimstat: 2.3 ±â€¯11.2 mL/m2, placebo: 0.6 ±â€¯14.8 mL/m2, P = .56) were observed in both treatment arms. CONCLUSION: Fulacimstat was safe and well tolerated in patients with left-ventricular dysfunction (LVD) after first STEMI but had no effect on cardiac remodeling.

Real-World Use of Novel P2Y12 Inhibitors in Patients with Acute Myocardial Infarction: A Treatment Paradox.

OBJECTIVE: To assess the real-world use, clinical outcomes, and adherence to novel P2Y12 inhibitors. METHODS: We evaluated 1,093 consecutive acute myocardial infarction patients undergoing a percutaneous intervention. Patients were derived from a prospective, multicenter, nationwide registry and were followed for 30 days; 381 patients (35%) received clopidogrel, 468 (43%) received prasugrel, and 244 (22%) received ticagrelor. Patients treated with clopidogrel were older and more likely to suffer from chronic renal failure and stroke and/or present with non-ST-elevation myocardial infarction (NSTEMI) (p < 0.01 for all). Independent predictors of undertreatment with novel P2Y12 inhibitors included: older age (OR 0.17; 95% CI 0.1-0.27, p < 0.0001), a prior stroke (OR 0.41; 95% CI 0.2-0.68, p = 0.008), and NSTEMI (OR 0.37; 95% CI 0.26-0.54, p < 0.0001). RESULTS: Novel P2Y12 inhibitors were associated with a lower incidence of cardiovascular events, major bleeding, and/or death (7.6 vs.11%, HR 0.67; 95% CI 0.43-1, p = 0.05). However, after a multivariate analysis this trend was not statistically significant. Patients discharged with ticagrelor versus thienopyridines demonstrated a higher rate of crossover to other P2Y12 inhibitors (11 vs. 5%, p = 0.03). CONCLUSIONS: In a real-world cohort, there was an underutilization of novel P2Y12 inhibitors which was more pronounced in higher-risk subsets that might benefit from novel P2Y12 inhibitors at least as much as other patients.

High-frequency QRS analysis in the evaluation of chest pain in the emergency department.

OBJECTIVES: High frequency QRS (HFQRS) analysis has been shown to be an accurate marker for myocardial ischemia. Our objective was to test the use of HFQRS in diagnosing ACS in the emergency department. METHODS: 324 patients presenting to the ED with chest pain were enrolled. Resting ECG was recorded and later analyzed by an HFQRS algorithm. Results were compared to the conventional ECG diagnosis by 3 independent interpretations: treating physician, expert cardiologist and an automated computer program. RESULTS: The HFQRS analysis demonstrated improved sensitivity (67.5%) for the NSTE-ACS group compared to the human interpreters (59.7% and 53.2% for the treating physician and cardiologist respectively) with similar specificity. The automatic program had significantly lower sensitivity (31%) with a higher specificity (77%). CONCLUSIONS: HFQRS which has shown great promise in diagnosing stable CAD may also be helpful in the ED for diagnosing ACS.

Predictors of high-risk angiographic findings in patients with non-ST-segment elevation acute coronary syndrome.

BACKGROUND: Current risk assessment of patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) may fail to identify some patients with severe coronary artery disease (CAD). We aimed to identify predictors of the angiographic extent and severity of CAD in patients with NSTE-ACS undergoing early angiography and to evaluate its impact on prognosis. METHODS: We evaluated 923 patients with NSTE-ACS who underwent coronary angiography. High-risk coronary anatomy (HRCA) was defined as left main disease > 50%, proximal LAD lesion > 70%, or 2- to 3-vessel disease involving the LAD. Clinical characteristics, in-hospital, and 30-day outcome and 1-year mortality were compared between the high-risk (N = 370) and the low-risk groups (N = 553). RESULTS: Proportion of patients with elevated cardiac biomarkers was similar in both groups. The presence of peripheral vascular disease (OR = 1.88, 95% confidence interval [CI] = 1.62-5.80, P < 0.001) and a GRACE score of >140 (OR = 1.88, 95% CI = 1.29-2.75, P < 0.001) were the strongest predictors of HRCA. Patients with HRCA were prone to more complications during hospitalization and at 30 days (11.9% vs. 6%, P < 0.01) and increased 1-year mortality (6.7% vs. 0.9%, P < 0.001). HRCA was the strongest predictor for 30-day MACCE (OR = 2.32, 95% CI = 1.42-3.79, P < 0.001). HRCA (OR = 8.36, 95% CI = 1.01-69.4, P = 0.049; OR = 3.64, 95% CI = 1.2-11.07, P = 0.02) and GRACE score of >140 (OR = 6.86, 95% CI = 1.68-27.9, P = 0.007; OR = 4.84, 95% CI = 1.74-13.5, P = 0.002) were significant predictors of 30-day and 1-year mortality, respectively. CONCLUSIONS: HRCA is predicted by clinical parameters and was not associated with elevated cardiac biomarkers. These patients fared worse when compared with those with low-risk anatomy. We suggest that HRCA predictors should be included in the risk stratification of patients with NSTE-ACS.

High-frequency QRS analysis in patients with acute myocardial infarction: a preliminary study.

BACKGROUND: The 12-lead electrocardiogram (ECG) is a primary tool in the evaluation and risk stratification of patients with suspected acute myocardial infarction (AMI), even though the initial ECG of these patients is often normal or nondiagnostic. Myocardial ischemia induces depolarization changes that can be quantified by analysis of high-frequency QRS (HFQRS) components. We aimed to demonstrate the potential usefulness of HFQRS analysis in diagnosing myocardial ischemia by characterizing the morphological patterns of the HFQRS signals in patients with AMI before and following reperfusion. METHODS: Five-minute high-resolution ECG was acquired from 30 patients with AMI (age 55 ± 11 years, 26 men) upon their admission to the intensive coronary care unit (ICCU). Serial ECGs were acquired following coronary revascularization and after additional 24 hours (24h). High-frequency morphology index (HFMI), quantifying the extent of ischemic patterns was computed by a custom software, and its values were compared between the serial ECG measurements. RESULTS: HFMI values were significantly higher on the admission ECG as compared to the post intervention ECG (4.6 ± 2.9% vs 3.4 ± 2.3%, P < 0.05) and to the 24h ECG (4.6 ± 2.9% vs 2.8 ± 2.1%, P < 0.01). In 79% of the patients who were successfully revascularized HFMI value decreased from admission ECG to 24h ECG. CONCLUSIONS: Analysis of HFQRS morphology in patients with AMI provides information about the existence and severity of myocardial ischemia. HFQRS analysis may aid in risk stratification of patients with suspected myocardial ischemia, complementarily to conventional ECG.

Incident cardiovascular, renal, metabolic diseases and death in individuals identified for risk-guided atrial fibrillation screening: a nationwide cohort study.

OBJECTIVE: Risk-guided atrial fibrillation (AF) screening may be an opportunity to prevent adverse events in addition to stroke. We compared events rates for new diagnoses of cardio-renal-metabolic diseases and death in individuals identified at higher versus lower-predicted AF risk. METHODS: From the UK Clinical Practice Research Datalink-GOLD dataset, 2 January 1998-30 November 2018, we identified individuals aged ≥30 years without known AF. The risk of AF was estimated using the FIND-AF (Future Innovations in Novel Detection of Atrial Fibrillation) risk score. We calculated cumulative incidence rates and fit Fine and Gray's models at 1, 5 and 10 years for nine diseases and death adjusting for competing risks. RESULTS: Of 416 228 individuals in the cohort, 82 942 were identified as higher risk for AF. Higher-predicted risk, compared with lower-predicted risk, was associated with incident chronic kidney disease (cumulative incidence per 1000 persons at 10 years 245.2; HR 6.85, 95% CI 6.70 to 7.00; median time to event 5.44 years), heart failure (124.7; 12.54, 12.08 to 13.01; 4.06), diabetes mellitus (123.3; 2.05, 2.00 to 2.10; 3.45), stroke/transient ischaemic attack (118.9; 8.07, 7.80 to 8.34; 4.27), myocardial infarction (69.6; 5.02, 4.82 to 5.22; 4.32), peripheral vascular disease (44.6; 6.62, 6.28 to 6.98; 4.28), valvular heart disease (37.8; 6.49, 6.14 to 6.85; 4.54), aortic stenosis (18.7; 9.98, 9.16 to 10.87; 4.41) and death from any cause (273.9; 10.45, 10.23 to 10.68; 4.75). The higher-risk group constituted 74% of deaths from cardiovascular or cerebrovascular causes (8582 of 11 676). CONCLUSIONS: Individuals identified for risk-guided AF screening are at risk of new diseases across the cardio-renal-metabolic spectrum and death, and may benefit from interventions beyond ECG monitoring.

Ivabradine for Uncontrolled Sinus Tachycardia in Thyrotoxic Cardiomyopathy - Case Report.

BACKGROUND: Beta-blockers, mainly propranalol, are usually administered to control heart rate in patients with thyrotoxicosis, especially when congestive heart failure presents. However, when thyrotoxicosis is not controlled, heart rate may be difficult to control even with maximal doses of propranolol. This presentation alerts physicians to the possibility of using ivabradine, a selective inhibitor of the sinoatrial pacemaker, for the control of heart rate. CASE PRESENTATION: We present a 37-year-old woman with thyrotoxicosis and congestive heart failure whose heart rate was not controlled with a maximal dose of beta blockers during a thyroid storm. The addition of ivabradine, a selective inhibitor of the sinoatrial pacemaker, controlled her heart rate within 48 hours. CONCLUSION: Ivabradine should be considered in patients with thyrotoxicosis, including those with heart failure, in whom beta blockers are insufficient to control heart rate.

Nonobstructive coronary atherosclerosis is associated with adverse prognosis among patients diagnosed with myocardial infarction without obstructive coronary arteries.

BACKGROUND AND AIMS: The prognostic impact of nonobstructive coronary artery disease (CAD), as opposed to normal coronary arteries, on long-term outcomes of patients with myocardial infarction with no obstructive coronary arteries (MINOCA) is unclear. We aimed to address the association between nonobstructive-CAD and major adverse events (MAE) following MINOCA. METHODS: We conducted a retrospective cohort study of consecutive MINOCA patients admitted to a large referral medical center between 2005 and 2018. Patients were classified according to coronary angiography as having either normal-coronaries or nonobstructive-CAD. The primary outcome was MAE, defined as the composite of all-cause mortality and recurrent acute coronary syndrome (ACS). RESULTS: Of the 1544 MINOCA patients, 651 (42%) had normal coronaries, and 893 (58%) had CAD. The mean age was 61.2 ± 12.6 years, and 710 (46%) were females. Nonobstructive-CAD patients were older and less likely to be females, with higher rates of diabetes, hypertension, dyslipidemia, atrial fibrillation, and chronic renal-failure (p < 0.05). At a median follow-up of 7 years, MAE occurred in 203 (23%) patients and 67 (10%) patients in the nonobstructive-CAD and normal-coronaries groups, respectively (p < 0.01). In multivariable models, nonobstructive -CAD was significantly associated with long-term MAE [adjusted-hazard-ratio (aHR):1.67, 95% confidence-interval (95%CI):1.25-2.23; p < 0.001]. Other factors associated with a higher MAE-risk were older-age (aHR:1.05,95%CI:1.03-1.06; p < 0.001) and left ventricular ejection-fraction<40% (aHR:3.04,95%CI:2.03-4.57; p < 0.001), while female-sex (aHR:0.72, 95%CI: 0.56-0.94; p=0.014) and sinus rhythm at presentation (aHR:0.66, 95%CI: 0.44-0.98; p=0.041) were associated with lower MAE-risk. CONCLUSIONS: In MINOCA, nonobstructive-CAD is independently associated with a higher MAE-risk than normal-coronaries. This finding may promote risk-stratification of patients with nonobstructive-CAD-MINOCA who require tighter medical follow-up and treatment optimization.

Risk of atrial fibrillation and association with other diseases: protocol of the derivation and international external validation of a prediction model using nationwide population-based electronic health records.

INTRODUCTION: Atrial fibrillation (AF) is a major public health issue and there is rationale for the early diagnosis of AF before the first complication occurs. Previous AF screening research is limited by low yields of new cases and strokes prevented in the screened populations. For AF screening to be clinically and cost-effective, the efficiency of identification of newly diagnosed AF needs to be improved and the intervention offered may have to extend beyond oral anticoagulation for stroke prophylaxis. Previous prediction models for incident AF have been limited by their data sources and methodologies. METHODS AND ANALYSIS: We will investigate the application of random forest and multivariable logistic regression to predict incident AF within a 6-month prediction horizon, that is, a time-window consistent with conducting investigation for AF. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation, and the Clalit Health Services (CHS) dataset will be used for international external geographical validation. Analyses will include metrics of prediction performance and clinical utility. We will create Kaplan-Meier plots for individuals identified as higher and lower predicted risk of AF and derive the cumulative incidence rate for non-AF cardio-renal-metabolic diseases and death over the longer term to establish how predicted AF risk is associated with a range of new non-AF disease states. ETHICS AND DISSEMINATION: Permission for CPRD-GOLD was obtained from CPRD (ref no: 19_076). The CPRD ethical approval committee approved the study. CHS Helsinki committee approval 21-0169 and data usage committee approval 901. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences. TRIAL REGISTRATION NUMBER: A systematic review to guide the overall project was registered on PROSPERO (registration number CRD42021245093). The study was registered on ClinicalTrials.gov (NCT05837364).

Prediction of short-term atrial fibrillation risk using primary care electronic health records.

OBJECTIVE: Atrial fibrillation (AF) screening by age achieves a low yield and misses younger individuals. We aimed to develop an algorithm in nationwide routinely collected primary care data to predict the risk of incident AF within 6 months (Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF)). METHODS: We used primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between 2 January 1998 and 30 November 2018, randomly divided into training (80%) and testing (20%) datasets. We trained a random forest classifier using age, sex, ethnicity and comorbidities. Prediction performance was evaluated in the testing dataset with internal bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc (Congestive heart failure, Hypertension, Age >75 (2 points), Stroke/transient ischaemic attack/thromboembolism (2 points), Vascular disease, Age 65-74, Sex category) and C2HEST (Coronary artery disease/Chronic obstructive pulmonary disease (1 point each), Hypertension, Elderly (age ≥75, 2 points), Systolic heart failure, Thyroid disease (hyperthyroidism)) scores. Cox proportional hazard models with competing risk of death were fit for incident longer-term AF between higher and lower FIND-AF-predicted risk. RESULTS: Of 2 081 139 individuals in the cohort, 7386 developed AF within 6 months. FIND-AF could be applied to all records. In the testing dataset (n=416 228), discrimination performance was strongest for FIND-AF (area under the receiver operating characteristic curve 0.824, 95% CI 0.814 to 0.834) compared with CHA2DS2-VASc (0.784, 0.773 to 0.794) and C2HEST (0.757, 0.744 to 0.770), and robust by sex and ethnic group. The higher predicted risk cohort, compared with lower predicted risk, had a 20-fold higher 6-month incidence rate for AF and higher long-term hazard for AF (HR 8.75, 95% CI 8.44 to 9.06). CONCLUSIONS: FIND-AF, a machine learning algorithm applicable at scale in routinely collected primary care data, identifies people at higher risk of short-term AF.

Predictors of Adverse Outcome in High-Risk Percutaneous Coronary Interventions Patients.

BACKGROUND: Identifying high-risk percutaneous coronary intervention (PCI) patients is challenging. We aimed to evaluate which high-risk patients are prone to adverse events. METHODS: We performed a retrospective study including consecutive high-risk PCIs from 2005 to 2018 in a large tertiary medical centre. Patients with unprotected left main (LM) disease, last patent coronary vessel, or 3-vessel coronary artery disease with left ventricular ejection fraction < 35% were included. A predictive 30-day major adverse cardiac events (MACE) score consisting of any myocardial infarction, all-cause death, or target-vessel revascularisation was constructed. RESULTS: From 2005 to 2018, a total of 1890 patients who underwent PCI met the predefined high-risk PCI criteria. Mortality rate was 8.8% at 30 days and 20.7% at 1 year, and 30-day MACE rate was 14.2% and 33.5% at 1 year. Predictors of short-term MACE were New York Heart Association functional class (NYHA) 4 (hazard ratio [HR] 6.65; P < 0.001), systolic blood pressure (SBP) < 90 mm Hg (HR 4.93; P < 0.001), creatinine > 1.3 mg/dL (HR 3.57; P < 0.001), hemoglobin < 11.0 g/dL (HR 3.07; P < 0.001), pulmonary artery systolic pressure > 50 mm Hg (HR 2.06; P < 0.001), atrial fibrillation (HR 1.74; P < 0.001), and LM disease (HR 2.04; P < 0.001) or last patent vessel (HR 1.70; P = 0.002). A score constructed from these parameters reached a sensitivity of 90% and a specificity of 81% with areas under the receiver operating characteristic curve of 0.92 for MACE and 0.94 with 89% sensitivity and 87% specificity for all-cause mortality. CONCLUSIONS: Specific features such as LM lesion or last patent conduit, pulmonary hypertension, atrial fibrillation, anemia, and renal failure, along with low SBP and NYHA 4, aid risk stratification and consideration of further treatment measures.

Development of saliva-based cardiac troponin I point-of-care test using alpha-amylase depletion: a feasibility study.

INTRODUCTION: Cardiac troponin (cTn) is the biomarker of choice for detection of myocardial injury. There is a great need for simple point-of-care (POC) troponin testing among patients with chest pain, mainly in the prehospital setting. The purpose of this study was to evaluate the presence of cardiac troponin I (cTnI) in saliva of patients with myocardial injury using alpha-amylase depletion technique. METHODS: Saliva samples were collected from 40 patients with myocardial injury who were tested positive for conventional high-sensitivity cardiac troponin T (cTnT) blood tests, and from 66 healthy volunteers. Saliva samples were treated for the removal of salivary alpha-amylase. Treated and untreated samples were tested with blood cTnI Rapid Diagnostic Test. Salivary cTnI levels were compared to blood cTnT levels. RESULTS: Thirty-six of 40 patients with positive blood cTnT had positive salivary samples for cTnI following alpha-amylase depletion treatment (90.00% sensitivity). Moreover, three of the four negative saliva samples were obtained from patients with relatively low blood cTnT levels of 100 ng/L or less (96.88% sensitivity for 100 ng/L and above). The negative predictive value was 93.65% and rose up to 98.33% considering the 100 ng/L cutoff. Positive predictive values were 83.72% and 81.58%, respectively. Among 66 healthy volunteers and 7 samples yielded positive results (89.39% specificity). CONCLUSION: In this preliminary work, the presence of cTnI in saliva was demonstrated for the first time to be feasibly identified by a POC oriented assay. The specific salivary alpha-amylase depletion technique was shown to be crucial for the suggested assay.

Prediction models for heart failure in the community: A systematic review and meta-analysis.

AIMS: Multivariable prediction models can be used to estimate risk of incident heart failure (HF) in the general population. A systematic review and meta-analysis was performed to determine the performance of models. METHODS AND RESULTS: From inception to 3 November 2022 MEDLINE and EMBASE databases were searched for studies of multivariable models derived, validated and/or augmented for HF prediction in community-based cohorts. Discrimination measures for models with c-statistic data from ≥3 cohorts were pooled by Bayesian meta-analysis, with heterogeneity assessed through a 95% prediction interval (PI). Risk of bias was assessed using PROBAST. We included 36 studies with 59 prediction models. In meta-analysis, the Atherosclerosis Risk in Communities (ARIC) risk score (summary c-statistic 0.802, 95% confidence interval [CI] 0.707-0.883), GRaph-based Attention Model (GRAM; 0.791, 95% CI 0.677-0.885), Pooled Cohort equations to Prevent Heart Failure (PCP-HF) white men model (0.820, 95% CI 0.792-0.843), PCP-HF white women model (0.852, 95% CI 0.804-0.895), and REverse Time AttentIoN model (RETAIN; 0.839, 95% CI 0.748-0.916) had a statistically significant 95% PI and excellent discrimination performance. The ARIC risk score and PCP-HF models had significant summary discrimination among cohorts with a uniform prediction window. 77% of model results were at high risk of bias, certainty of evidence was low, and no model had a clinical impact study. CONCLUSIONS: Prediction models for estimating risk of incident HF in the community demonstrate excellent discrimination performance. Their usefulness remains uncertain due to high risk of bias, low certainty of evidence, and absence of clinical effectiveness research.