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Post-marketing vaccine safety surveillance aims to detect adverse events following immunization in a population. Whether certain methods of surveillance are more precise and unbiased in generating safety signals is unclear. Here, we synthesized information from existing literature to provide an overview of the strengths, weaknesses, and clinical applications of epidemiologic and analytical methods used in vaccine monitoring, focusing on cohort, case-control and self-controlled designs. These designs are proposed to be evaluated in the EUMAEUS (Evaluating Use of Methods for Adverse Event Under Surveillance-for vaccines) study because of their widespread use and potential utility. Over the past decades, there have been an increasing number of epidemiological study designs used for vaccine safety surveillance. While traditional cohort and case-control study designs remain widely used, newer, novel designs such as the self-controlled case series and self-controlled risk intervals have been developed. Each study design comes with its strengths and limitations, and the most appropriate study design will depend on availability of resources, access to records, number and distribution of cases, and availability of population coverage data. Several assumptions have to be made while using the various study designs, and while the goal is to mitigate any biases, violations of these assumptions are often still present to varying degrees. In our review, we discussed some of the potential biases (i.e., selection bias, misclassification bias and confounding bias), and ways to mitigate them. While the types of epidemiological study designs are well established, a comprehensive comparison of the analytical aspects (including method evaluation and performance metrics) of these study designs are relatively less well studied. We summarized the literature, reporting on two simulation studies, which compared the detection time, empirical power, error rate and risk estimate bias across the above-mentioned study designs. While these simulation studies provided insights on the analytic performance of each of the study designs, its applicability to real-world data remains unclear. To bridge that gap, we provided the rationale of the EUMAEUS study, with a brief description of the study design; and how the use of real-world multi-database networks can provide insights into better methods evaluation and vaccine safety surveillance.

BACKGROUND: Despite the improved medical and surgical managements, still there is a significant risk of developing acute cerebrovascular strokes after coronary artery bypass grafting (CABG). Our objectives were to study the immediate and long-term outcomes after CABG and to identify the possible predictors of post-CABG strokes.

RESULTS: Between January 2016 and August 2020, 410 adult patients, mostly males (82.2%), were retrospectively enrolled after CABG. Acute postoperative strokes occurred in 31 (7.5%) patients; of them, 30 (96.8%) patients had ischemic stroke, while 1 (3.2%) had hemorrhagic stroke. Mechanical thrombectomy was done in two cases. The patients who developed acute cerebral stroke had significantly higher admission (p = 0.02) and follow-up (p < 0.001) SOFA scores, higher arterial blood lactate level (p < 0.001), longer hospitalization (p < 0.001) and more hospital mortality (p < 0.001) compared with the patients who did not develop stroke. Kaplan-Meier curves for 5-year mortality showed increased risk in those patients with postoperative stroke (HR: 23.03; 95% CI: 6.10-86.92, p < 0.001). After multivariate regression, the predictors of early postoperative stroke were carotid artery stenosis (CAS), postoperative atrial fibrillation, cardiopulmonary bypass time, prior cerebral stroke, admission SOFA score and chronic kidney disease (CKD). The predictors of late cerebrovascular stroke were CAS, combined CABG and valve surgery, CKD, atrial fibrillation, prior stroke and HbA1c.

CONCLUSIONS: The development of post-CABG acute cerebrovascular stroke is associated with longer hospitalization, multiple morbidities and increased mortality. Careful assessment and management of risk factors especially atrial fibrillation and carotid artery stenosis should be implemented to decrease this substantial complication after CABG.

BACKGROUND: The left ventricular assist devices (LVADs) are increasingly used for advanced heart failure as a bridge to heart transplantation or as a destination therapy. The aim of this study was to investigate the changes of diastolic pulmonary gradient (DPG), pulmonary vascular resistance (PVR) and transpulmonary gradient (TPG) after LVAD implantation and their impact on survival after LVAD and heart transplantation.

RESULTS: A total of 73 patients who underwent LVAD (HeartMate III) implantation between 2016 and 2022 were retrospectively studied. According to pre-LVAD catheterization, 49 (67.1%) patients had DPG < 7 mmHg and 24 (32.9%) patients had DPG ≥ 7 mmHg. The patients with a pre-VAD DPG ≥ 7 mmHg had higher frequencies of right ventricular (RV) failure (p < 0.001), RVAD insertion (p < 0.001), need for renal replacement therapy (p = 0.002), total mortality (p = 0.036) and on-VAD mortality (p = 0.04) with a longer ICU stay (p = 0.001) compared to the patients with DPG < 7 mmHg. During the follow-up period of 38 (12-60) months, 24 (32.9%) patients died. Pre-LVAD DPG ≥ 7 mmHg (adjusted HR 1.83, 95% CI 1.21-6.341, p = 0.039) and post-LVAD DPG ≥ 7 mmHg (adjusted HR 3.824, 95% CI 1.482-14.648, p = 0.002) were associated with increased risks of mortality. Neither pre-LVAD TPG ≥ 12 (p = 0.505) nor post-LVAD TPG ≥ 12 mmHg (p = 0.122) was associated with an increased risk of death. Pre-LVAD PVR ≥ 3 WU had a statistically insignificant risk of mortality (HR 2.35, 95% CI 0.803-6.848, p = 0.119) while post-LVAD PVR ≥ 3 WU had an increased risk of death (adjusted HR 2.37, 95% CI 1.241-7.254, p = 0.038). For post-transplantation mortality, post-LVAD DPG ≥ 7 mmHg (p = 0.55), post-LVAD TPG ≥ 12 mmHg (p = 0.85) and PVR ≥ 3 WU (p = 0.54) did not have statistically increased risks. The logistic multivariable regression showed that post-LVAD PVR ≥ 3 WU (p = 0.013), post-LVAD DPG ≥ 7 mmHg (p = 0.026) and RVF (p = 0.018) were the predictors of mortality after LVAD implantation. Pre-LVAD DPG ≥ 7 mmHg (p < 0.001) and pre-LVAD PVR ≥ 3 WU (p = 0.036) were the predictors of RVF after LVAD implantation.

CONCLUSIONS: Persistently high DPG was associated with right ventricular failure and mortality after LVAD implantation rather than after heart transplantation. DPG is a better predictor of pulmonary vascular remodeling compared to TPG and PVR. Further larger prospective studies are required in this field due to the growing numbers of patients with advanced heart failure, as possible candidates for LVAD implantation, and limitations of heart transplantation.