Trend of Sudden Unexpected Death in Epilepsy Incidence Rate in Rural West China

Mortality of Epilepsy in Chinese Populations: A Comprehensive Review

BACKGROUND

Premature mortality is a significant part of the epilepsy burden and may vary across populations, especially between high-income and lower- and middle-income countries. People with epilepsy in China are approximately a fifth of the global population with epilepsy. Previous studies were unlikely to represent the situation in China due to limitations in design, methods, sample size, follow-up time, and other inherent population heterogeneity.

SUMMARY

By summarising the evidence on the mortality characteristics in Chinese populations with epilepsy in the last 6 decades, we found a median mortality rate of 14.7 (6.8-74.4)/1,000 person-years and a median standardised mortality ratio (SMR) of 4.4 (2.6-12.9) in population-based studies, and a median mortality rate of 12.3 (9.5-101.5)/1,000 person-years and a median SMR of 3.0 (1.5-5.1) in hospital-based studies. Vascular diseases, complications of diabetes, and accidental injuries were the leading causes of death. Risk factors for mortality were reported as older age, male, longer duration, and higher frequency of seizures. Case fatality ratios of status epilepticus in adults were higher than in children, and both increased with follow-up time. Mortality in people with symptomatic epilepsy was high and varied across different primary diseases.

KEY MESSAGES

The highest mortality rate and sudden unexpected death in epilepsy (SUDEP) incidence were reported from the least developed areas in China. Accidental injuries were the most common causes of epilepsy-related deaths, while the incidence of SUDEP may be underestimated in Chinese populations. Further research is warranted to improve the understanding of premature mortality risk so that preventative measures can be introduced to improve the situation.

[Incidence of sudden death in epilepsy (SUDEP): update and limitations]

BACKGROUND

Sudden unexpected death in epilepsy (SUDEP) is in most cases probably due to a fatal complication of tonic-clonic seizures and plays a significant role in the premature mortality of individuals with epilepsy. The reported risks of SUDEP vary considerably depending on the study population, so that an up-dated systematic review of SUDEP incidence including most recent studies is required to improve the estimated SUDEP risk and the counseling of individuals with epilepsy.

OBJECTIVE

To provide an overview of the current research landscape concerning SUDEP incidence across different patient populations and discuss potential conclusions and existing limitations.

MATERIAL AND METHODS

A systematic literature review on SUDEP incidence was conducted in MEDLINE and EMBASE, supplemented by a manual search in June 2023. Out of a total of 3324 publications, 50 were reviewed for this study.

RESULTS

The analyzed studies showed significant heterogeneity concerning cohorts, study design and data sources. Studies conducted without specific criteria and relying on comprehensive registers indicated an incidence of 0.78-1.2 per 1000 patient-years. Research providing incidences across various age groups predominantly show an increase with age, peaking in middle age.

DISCUSSION

Due to varying methods of data collection and incidence calculation, comparing between studies is challenging. The association with age might be due to an underrepresentation of children, adolescents and patients over 60 years.

CONCLUSION

Considering all age groups and types of epilepsy it is estimated that about 1 in 1000 individuals with epilepsy dies of SUDEP annually. With an assumed epilepsy prevalence of 0.6% in Germany, this could lead to more than one SUDEP case daily. Standardization of research methods is essential to gain more profound insights.

Premature mortality risk in individuals with convulsive epilepsy: Results from a longitudinal, prospective, population-based study

OBJECTIVE

To assess premature mortality and identify associated risk factors among individuals with convulsive epilepsy in resource-poor settings using a longitudinal, prospective, population-based approach.

METHOD

The study recruited people with convulsive epilepsy who underwent assessment and management of epilepsy at primary healthcare centers in rural Northwest China, including newly diagnosed individuals and previously identified prevalent cases. All participants were confirmed to have epilepsy by neurologists according to strict criteria and were followed up monthly by primary care physicians. Demographic data and cause of death (COD) were obtained from death certificates or verbal autopsies conducted by neurologists, following the International Classification of Diseases, 10th Edition. The standardized mortality ratio (SMR) and proportionate mortality ratio (PMR) for each cause of death were estimated using the Cause-Of-Death Surveillance Dataset of China (2020). Survival analysis was used to identify risk factors associated with all-cause mortality and death directly due to epilepsy.

RESULTS

During 5.9 years of follow-up with 40,947 person-years, there were 781 (11.2%) deaths among 6967 participants. The risk of premature death in people with convulsive epilepsy was 2.7-fold higher than that in the general population. Young participants had a significantly higher risk (standardized mortality ratio 26.5-52.5) of premature death. The proportionate mortality ratio was higher for cerebrovascular disease (15%), sudden unexpected death in epilepsy (SUDEP) (13.4%), cardiovascular disease (11.7%), status epilepsy (SE) (11.3%), and epilepsy-related accidents (14.0%) than other premature mortality cause of deaths. Additionally, the highest standardized proportional mortality ratio (SPMR) was observed from drowning in all cause of death (10.4, 95% confidence interval [CI]: 7.6-13.8), followed by burning (9.0, 95% CI: 3.7-18.9). Factors that increased the risk of all-cause mortality included male sex, late age of onset, short disease duration, high body mass index, monotherapy, and the frequency of generalized tonic-clonic seizures (GTCS). High frequency of generalized tonic-clonic seizures (> 3 attacks in the last year) was an independent risk factor for premature death directly due to epilepsy (including sudden unexpected death in epilepsy, status epilepsy, and epilepsy-related accidents), while early age of onset (≤ 14 years) and long duration of epilepsy (> 20 years) were independent risk factors for sudden unexpected death in epilepsy. In addition, short duration of epilepsy (≤ 20 years) was an independent risk factor for status epilepsy.

CONCLUSIONS

This study demonstrated that individuals with poorly controlled seizures are more likely to experience premature death, with most deaths being epilepsy-related and preventable. These findings underline the importance of effective seizure treatment and the potential impact on reducing premature mortality among people with convulsive epilepsy.

Annotation-Free Deep Learning-Based Prediction of Thyroid Molecular Cancer Biomarker BRAF (V600E) from Cytological Slides

Thyroid cancer is the most common endocrine cancer. Papillary thyroid cancer (PTC) is the most prevalent form of malignancy among all thyroid cancers arising from follicular cells. Fine needle aspiration cytology (FNAC) is a non-invasive method regarded as the most cost-effective and accurate diagnostic method of choice in diagnosing PTC. Identification of BRAF (V600E) mutation in thyroid neoplasia may be beneficial because it is specific for malignancy, implies a worse prognosis, and is the target for selective BRAF inhibitors. To the authors' best knowledge, this is the first automated precision oncology framework effectively predict BRAF (V600E) immunostaining result in thyroidectomy specimen directly from Papanicolaou-stained thyroid fine-needle aspiration cytology and ThinPrep cytological slides, which is helpful for novel targeted therapies and prognosis prediction. The proposed deep learning (DL) framework is evaluated on a dataset of 118 whole slide images. The results show that the proposed DL-based technique achieves an accuracy of 87%, a precision of 94%, a sensitivity of 91%, a specificity of 71% and a mean of sensitivity and specificity at 81% and outperformed three state-of-the-art deep learning approaches. This study demonstrates the feasibility of DL-based prediction of critical molecular features in cytological slides, which not only aid in accurate diagnosis but also provide useful information in guiding clinical decision-making in patients with thyroid cancer. With the accumulation of data and the continuous advancement of technology, the performance of DL systems is expected to be improved in the near future. Therefore, we expect that DL can provide a cost-effective and time-effective alternative tool for patients in the era of precision oncology.