Cardiac Arrest and Subsequent Hospitalization–Induced Posttraumatic Stress Is Associated With 1-Year Risk of Major Adverse Cardiovascular Events and All-Cause Mortality

Abstract Background Key dimensions of cardiac arrest-induced posttraumatic stress disorder (PTSD) symptoms include reexperiencing, avoidance, numbing, and hyperarousal. It remains unknown which dimensions are most predictive of outcome. Purpose To determine which dimensions of cardiac arrest-induced PTSD are predictive of clinical outcome within 13 months posthospital discharge. Methods PTSD symptoms were assessed in survivors of cardiac arrest who were able to complete psychological screening measures at hospital discharge via the PTSD Checklist-Specific scale, which queries for 17 symptoms using five levels of severity. Responses on items for each symptom dimension of the four-factor numbing model (reexperiencing, avoidance, numbing, and hyperarousal) were converted to Z-scores and treated as continuous predictors. The combined primary endpoint was all-cause mortality (ACM) or major adverse cardiovascular events (MACE; hospitalization for myocardial infarction, unstable angina, heart failure, emergency coronary revascularization, or urgent defibrillator/pacemaker placements) within 13 months postdischarge. Four bivariate Cox proportional hazards survival models evaluated associations between individual symptom dimensions and ACM/MACE. A multivariable model then evaluated whether significant bivariate predictors remained independent predictors of the primary outcome after adjusting for age, sex, comorbidities, premorbid psychiatric diagnoses, and initial cardiac rhythm. Results A total of 114 patients (59.6% men, 52.6% white, mean age: 54.6 ± 13 years) were included. In bivariate analyses, only hyperarousal was significantly associated with ACM/MACE. In a fully adjusted model, 1 standard deviation increase in hyperarousal symptoms corresponded to a two-times increased risk of experiencing ACM/MACE. Conclusions Greater level of hyperarousal symptoms was associated with a higher risk of ACM/MACE within 13 months postcardiac arrest. This initial evidence should be further investigated in a larger sample.

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Abstract 13: Cardiac Arrest-Induced Posttraumatic Stress Increases 1-Year Risk of Major Adverse Cardiovascular Events and All-Cause Mortality

Circulation ◽

10.1161/circ.138.suppl_2.13 ◽

2018 ◽

Vol 138 (Suppl_2) ◽

Author(s):

Sachin Agarwal ◽

Alex Presciutti ◽

Talea Cornelius ◽

Jeffrey L Birk ◽

David J Roh ◽

...

Keyword(s):

Cardiac Arrest ◽

Posttraumatic Stress ◽

Hospital Discharge ◽

Cardiovascular Events ◽

Cox Regression ◽

Tertiary Care ◽

Self Report ◽

Ptsd Symptoms ◽

Risk Of Death ◽

All Cause Mortality

Importance: Many cardiac arrest (CA) survivors develop posttraumatic stress disorder (PTSD) symptoms (i.e., CA-induced PTSD). The association of CA-induced PTSD with secondary mortality and cardiovascular risk is unknown. Methods: A prospective, observational, cohort study of adults with return of spontaneous circulation after in-hospital or out-of-hospital CA at a tertiary-care center between September 2015 and September 2017. A consecutive sample of survivors with sufficient mental status to self-report CA-induced PTSD symptoms at hospital discharge were included. The combined primary end point was all-cause mortality (ACM) or a major adverse cardiovascular event (MACE)—hospitalization for nonfatal MI, unstable angina, congestive heart failure (CHF), urgent/emergency coronary revascularization procedures, or urgent implantable defibrillators/pacemaker (ICDs/PPM) placements within 12 months of discharge. In-person assessments for CA-induced PTSD were performed within 24 hours of hospital discharge. PTSD symptomatology was assessed via the PTSD Checklist - Specific (PCL-S) scale; a suggested diagnostic cut-off of 36 for specialized medical settings was adopted. Outcomes for patients meeting (vs. not meeting) this cutoff were compared using Cox regression with adjustment for demographic and clinical covariates. Results: Of 114 included patients, 36 (31.6%) screened positive for CA-induced PTSD at discharge (median 21 days post-CA; interquartile range 11-36). During the follow-up period (median = 12.4 months, range 10.2-13.5), 10 (8.8%) died and 29 (25.4%) experienced a recurrent MACE: rehospitalizations due to MI (n=4, 13.8%), UA (n=8, 27.6%), CHF exacerbations (n=4, 13.8%), emergency revascularizations (n=5, 17.2%), and ICDs/PPM placements (n=8, 27.6%). CA-induced PTSD was associated with ACM/MACE in univariate (Hazard Ratio [HR] =3.19; 95% confidence interval [CI], 1.7-6.0) and in models adjusted for age, sex, charlson comorbidity index and nonshockable initial rhythms (HR=3.2; CI, 1.7-6.1). Conclusions: PTSD is common after CA, and survivors with CA-induced PTSD had significantly higher risk of death and cardiovascular events. Further inquiry into underlying mechanisms is warranted.

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Abstract 15895: Machine Learning Algorithms to Predict Major Adverse Cardiovascular Events in Patients Undergoing Orthotopic Liver Transplantation: A Retrospective Cohort Study

Circulation ◽

10.1161/circ.142.suppl_3.15895 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

vardhmaan jain ◽

Vikram Sharma ◽

Agam Bansal ◽

Cerise Kleb ◽

Chirag Sheth ◽

...

Keyword(s):

Machine Learning ◽

Random Forest ◽

Cardiovascular Events ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Major Adverse Cardiovascular Events ◽

Support Vector ◽

Post Transplant ◽

Extreme Gradient Boosting ◽

All Cause Mortality

Background: Post-transplant major adverse cardiovascular events (MACE) are amongst the leading cause of death amongst orthotopic liver transplant(OLT) recipients. Despite years of guideline directed therapy, there are limited data on predictors of post-OLT MACE. We assessed if machine learning algorithms (MLA) can predict MACE and all-cause mortality in patients undergoing OLT. Methods: We tested three MLA: support vector machine, extreme gradient boosting(XG-Boost) and random forest with traditional logistic regression for prediction of MACE and all-cause mortality on a cohort of consecutive patients undergoing OLT at our center between 2008-2019. The cohort was randomly split into a training (80%) and testing (20%) cohort. Model performance was assessed using c-statistic or AUC. Results: We included 1,459 consecutive patients with mean ± SD age 54.2 ± 13.8 years, 32% female who underwent OLT. There were 199 (13.6%) MACE and 289 (20%) deaths at a mean follow up of 4.56 ± 3.3 years. The random forest MLA was the best performing model for predicting MACE [AUC:0.78, 95% CI: 0.70-0.85] as well as mortality [AUC:0.69, 95% CI: 0.61-0.76], with all models performing better when predicting MACE vs mortality. See Table and Figure. Conclusion: Random forest machine learning algorithms were more predictive and discriminative than traditional regression models for predicting major adverse cardiovascular events and all-cause mortality in patients undergoing OLT. Validation and subsequent incorporation of MLA in clinical decision making for OLT candidacy could help risk stratify patients for post-transplant adverse cardiovascular events.

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A Bayesian network meta-analysis of PCSK9 inhibitors, statins and ezetimibe with or without statins for cardiovascular outcomes

European Journal of Preventive Cardiology ◽

10.1177/2047487318766612 ◽

2018 ◽

Vol 25 (8) ◽

pp. 844-853 ◽

Cited By ~ 21

Author(s):

Safi U Khan ◽

Swapna Talluri ◽

Haris Riaz ◽

Hammad Rahman ◽

Fahad Nasir ◽

...

Keyword(s):

Myocardial Infarction ◽

Bayesian Network ◽

Cardiovascular Mortality ◽

Cardiovascular Events ◽

Meta Analysis ◽

Credible Interval ◽

Major Adverse Cardiovascular Events ◽

Pcsk9 Inhibitors ◽

Adverse Cardiovascular Event ◽

All Cause Mortality

Background The comparative effects of statins, ezetimibe with or without statins and proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors remain unassessed. Design Bayesian network meta-analysis was conducted to compare treatment groups. Methods Thirty-nine randomized controlled trials were selected using MEDLINE, EMBASE, and CENTRAL (inception – September 2017). Results In network meta-analysis of 189,116 patients, PCSK9 inhibitors were ranked as the best treatment for prevention of major adverse cardiovascular events (Surface Under Cumulative Ranking Curve (SUCRA), 85%), myocardial infarction (SUCRA, 84%) and stroke (SUCRA, 80%). PCSK9 inhibitors reduced the risk of major adverse cardiovascular events compared with ezetimibe + statin (odds ratio (OR): 0.72; 95% credible interval (CrI), 0.55–0.95; Grading of Recommendation Assessment, Development and Evaluation (GRADE) criteria: moderate), statin (OR: 0.78; 95% CrI: 0.62–0.97; GRADE: moderate) and placebo (OR: 0.63; 95% CrI: 0.49–0.79; GRADE: high). The PCSK9 inhibitors were consistently superior to groups for major adverse cardiovascular event reduction in secondary prevention trials (SUCRA, 95%). Statins had the highest probability of having lowest rates of all-cause mortality (SUCRA, 82%) and cardiovascular mortality (SUCRA, 84%). Compared with placebo, statins reduced the risk of all-cause mortality (OR: 0.88; 95% CrI: 0.83–0.94; GRADE: moderate) and cardiovascular mortality (OR: 0.84; 95% CrI: 0.77–0.90; GRADE: high). For cardiovascular mortality, PCSK9 inhibitors were ranked as the second best treatment (SUCRA, 78%) followed by ezetimibe + statin (SUCRA, 50%). Conclusion PCSK9 inhibitors were ranked as the most effective treatment for reducing major adverse cardiovascular events, myocardial infarction and stroke, without having major safety concerns. Statins were ranked as the most effective therapy for reducing mortality.

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Plasma Trimethylamine N-Oxide and Risk of Cardiovascular Events in Patients With Type 2 Diabetes

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgaa188 ◽

2020 ◽

Vol 105 (7) ◽

pp. 2371-2380 ◽

Cited By ~ 1

Author(s):

Mikael Croyal ◽

Pierre-Jean Saulnier ◽

Audrey Aguesse ◽

Elise Gand ◽

Stéphanie Ragot ◽

...

Keyword(s):

Type 2 Diabetes ◽

Cardiovascular Events ◽

Tumor Necrosis Factor Receptor ◽

Density Lipoprotein ◽

Major Adverse Cardiovascular Events ◽

Cox Models ◽

Increased Risk ◽

All Cause Mortality ◽

Design And Methods

Abstract Objective Even though trimethylamine N-oxide (TMAO) has been demonstrated to interfere with atherosclerosis and diabetes pathophysiology, the association between TMAO and major adverse cardiovascular events (MACE) has not been specifically established in type 2 diabetes (T2D). Research Design and Methods We examined the association of plasma TMAO concentrations with MACE and all-cause mortality in a single-center prospective cohort of consecutively recruited patients with T2D. Results The study population consisted in 1463 SURDIENE participants (58% men), aged 65 ± 10 years. TMAO concentrations were significantly associated with diabetes duration, renal function, high-density lipoprotein cholesterol, soluble tumor necrosis factor receptor 1 (sTNFR1) concentrations (R2 = 0.27) and were significantly higher in patients on metformin, even after adjustment for estimated glomerular filtration rate (eGFR): 6.7 (8.5) vs 8.5 (13.6) µmol/L, respectively (PeGFR-adjusted = 0.0207). During follow-up (median duration [interquartile range], 85 [75] months), 403 MACE and 538 deaths were registered. MACE-free survival and all-cause mortality were significantly associated with the quartile distribution of TMAO concentrations, patients with the highest TMAO levels displaying the greatest risk of outcomes (P < 0.0001). In multivariate Cox models, compared with patients from the first 3 quartiles, those from the fourth quartile of TMAO concentration had an independently increased risk for MACE: adjusted hazard ratio (adjHR) 1.32 (1.02-1.70); P = 0.0325. Similarly, TMAO was significantly associated with mortality in multivariate analysis: adjHR 1.75 (1.17-2.09); P = 0.0124, but not when sTNFR1 and angiopoietin like 2 were considered: adjHR 1.16 (0.95-1.42); P = 0.1514. Conclusions We revealed an association between higher TMAO concentrations and increased risk of MACE and all-cause mortality, thereby opening some avenues on the role of dysbiosis in cardiovascular risk, in T2D patients.

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Sodium glucose cotransporter 2 inhibitors and risk of major adverse cardiovascular events: multi-database retrospective cohort study

BMJ ◽

10.1136/bmj.m3342 ◽

2020 ◽

pp. m3342 ◽

Cited By ~ 2

Author(s):

Kristian B Filion ◽

Lisa M Lix ◽

Oriana HY Yu ◽

Sophie Dell’Aniello ◽

Antonios Douros ◽

...

Keyword(s):

Myocardial Infarction ◽

Cardiovascular Events ◽

Retrospective Cohort ◽

Meta Analysis ◽

Cardiovascular Death ◽

Sglt2 Inhibitors ◽

Major Adverse Cardiovascular Events ◽

Site Specific ◽

Sodium Glucose Cotransporter ◽

All Cause Mortality

Abstract Objective To compare the risk of cardiovascular events between sodium glucose cotransporter 2 (SGLT2) inhibitors and dipeptidyl peptidase-4 (DPP-4) inhibitors among people with type 2 diabetes in a real world context of clinical practice. Design Multi-database retrospective cohort study using a prevalent new user design with subsequent meta-analysis. Setting Canadian Network for Observational Drug Effect Studies (CNODES), with administrative healthcare databases from seven Canadian provinces and the United Kingdom, 2013-18. Population 209 867 new users of a SGLT2 inhibitor matched to 209 867 users of a DPP-4 inhibitor on time conditional propensity score and followed for a mean of 0.9 years. Main outcome measures The primary outcome was major adverse cardiovascular events (MACE, a composite of myocardial infarction, ischaemic stroke, or cardiovascular death). Secondary outcomes were the individual components of MACE, heart failure, and all cause mortality. Cox proportional hazards models were used to estimate site specific adjusted hazards ratios and 95% confidence intervals, comparing use of SGLT2 inhibitors with use of DPP-4 inhibitors in an as treated approach. Site specific results were pooled using random effects meta-analysis. Results Compared with DPP-4 inhibitors, SGLT2 inhibitors were associated with decreased risks of MACE (incidence rate per 1000 person years: 11.4 v 16.5; hazard ratio 0.76, 95% confidence interval 0.69 to 0.84), myocardial infarction (5.1 v 6.4; 0.82, 0.70 to 0.96), cardiovascular death (3.9 v 7.7; 0.60, 0.54 to 0.67), heart failure (3.1 v 7.7; 0.43, 0.37 to 0.51), and all cause mortality (8.7 v 17.3; 0.60, 0.54 to 0.67). SGLT2 inhibitors had more modest benefits for ischaemic stroke (2.6 v 3.5; 0.85, 0.72 to 1.01). Similar benefits for MACE were observed with canagliflozin (0.79, 0.66 to 0.94), dapagliflozin (0.73, 0.63 to 0.85), and empagliflozin (0.77, 0.68 to 0.87). Conclusions In this large observational study conducted in a real world clinical practice context, the short term use of SGLT2 inhibitors was associated with a decreased risk of cardiovascular events compared with the use of DPP-4 inhibitors. Trial registration ClinicalTrials.gov NCT03939624 .

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