Change Point Analysis for Detecting Vaccine Safety Signals

Investigation of spontaneous abortion and stillbirth adverse events in epilepsy patients treated with levetiracetam: A pharmacovigilance study

BACKGROUND

The prescription of levetiracetam during pregnancy has become more common due to its lower teratogenic risk profile. However, due to a lack of data about its association with stillbirth and spontaneous abortion, worries remain.

OBJECTIVE

To investigate information on any possible association of spontaneous abortion and stillbirth adverse events with levetiracetam in women with epilepsy.

METHODS

This retrospective pharmacovigilance study used disproportionality analysis to detect signals of adverse reaction of interest reported with Levetiracetam in FAERS, the FDA Adverse Event Reporting System. The ratio of reporting odds (ROR) and information component (IC) indices were used to undertake disproportionality analyses, and change point analyses were carried out to identify variations in the frequency of reporting of relevant adverse events. Sensitivity analyses included subgroup analyses by indication, treatment regimen, and reporting region.

RESULTS

Overall, 2870 cases of spontaneous abortion and stillbirth with commonly used antiseizure medications were analyzed. A total of 65.5 % of these cases had epilepsy as the indication. In the entire dataset, we observed disproportionality signals of spontaneous abortion for 6 ASMs (levetiracetam, carbamazepine, lamotrigine, oxcarbazepine, topiramate, valproic acid) and disproportionality signals of stillbirth for 4 ASMs (levetiracetam, carbamazepine, lamotrigine, oxcarbazepine). In the epileptic population, disproportionality signals for stillbirth (ROR0.25 = 4.60; IC0.25 = 1.30) and spontaneous abortion (ROR0.25 = 3.98; IC0.25 = 1.20) in levetiracetam was identified. These disproportionality signals have been consistently robust over the past years, according to a temporal assessment of them. Sensitivity studies proved how reliable the findings were.

CONCLUSION

Using validated pharmacovigilance methods, we found significant disproportional signals for spontaneous abortion and stillbirth associated with levetiracetam. Of these, the signals for spontaneous abortion were observed after 2011 and for stillbirth after 2014, which may be related to the rise in levetiracetam prescriptions during pregnancy in recent years. The association of spontaneous abortion and stillbirth adverse events with levetiracetam and potential biases confounding this association merit further investigation.

Signal detection of COVID-19 vaccines adverse events using spontaneous reports from South Korea

PURPOSE

Studies on the detection of COVID-19 vaccine signals in South Korea are insufficient. Therefore, to investigate adverse events (AEs) that might be associated with COVID-19 vaccines, signals were detected using spontaneous reports from South Korea. We compared the signals with the vaccine insert lists of the regulators in the four countries.

METHODS

Spontaneous reports from 62 sites were collected by the National Medical Center between January 2013 and May 2022. A descriptive analysis of AEs associated with COVID-19 vaccines (Pfizer, Moderna, AstraZeneca, and Janssen) was performed, and the proportional reporting ratio, reporting odds ratio, and information component were calculated. We performed five analyses, with five cases and one control group.

RESULTS

During the study period, 68 355 cases were reported, of which 12 485 were COVID-19 vaccine AEs. Injection site pain (2198 cases, 17.6%), myalgia (1552 cases, 12.4%), headache (1145 cases, 9.2%), pyrexia (1003 cases, 8.0%), and fatigue (735 cases, 5.9%) were frequently reported. When comparing all COVID-19 vaccines with other viral vaccines, 20 signals were detected, of which cachexia, dyspepsia, abdominal discomfort, and mood swings were not listed on the vaccine inserts in all four countries. Overall, 20, 17, 29, and 9 signals were detected in vaccines developed by Pfizer, Moderna, AstraZeneca, and Janssen, respectively.

CONCLUSIONS

Based on a disproportionate analysis of COVID-19 vaccine AEs using spontaneous reports from South Korea, different signals were detected for each vaccine manufacturer.

COVID-19 case-fatality variations with application to the Middle East countries

During a pandemic outbreak, it is important for health officials to know the proportions of deaths among infected individuals and to understand how these proportions change overtime, to accurately predict the impact of the pandemic and to implement effectively new intervention policies and health protocols and to adjust them accordingly. However, most studies where efforts have been made to estimate accurately the case fatality rates did not address the issue of measuring the dynamics of the pandemic deadliness during its course. Daily data on COVID-19 cases and deaths were collected from selected MENA countries. In this paper, two new measures of the pandemic fatality are developed based on the estimated time it takes hospitalized infected patients to eventually die from the disease. The first measure assigns COVID-19 deaths to its most significant lagged number of cases based on a fixed-effects panel data model. The second fatality measure relates pandemic deaths and cases based on their respective change points. The results find notable variations of the pandemic lethality between the Middle East countries, likely due to the difference in the quality of health care. Although crude case-fatality rate does not identify the pandemic lethality variations during the ongoing of the disease, this paper develops two novel measures for COVID-19 case fatality which can identify the dynamics and the variations of the pandemic deadliness.

A Proportional Digital Controller to Monitor Load Variation in Wind Turbine Systems

Monitoring the variation of the loading blades is fundamental due to its importance in the behavior of the wind turbine system. Blade performance can be affected by different loads that alter energy conversion efficiency and cause potential safety hazards. An example of this is icing on the blades. Therefore, the main objective of this work is to propose a proportional digital controller capable of detecting load variations in wind turbine blades together with a fault detection method. An experimental platform is then built to experimentally validate the main contribution of the article. This platform employs an automotive throttle device as a blade system emulator of a wind turbine pitch system. In addition, a statistical fault detection algorithm is established based on the point change methodology. Experimental data support our approach.