key: cord-0967499-nvl31v3s
authors: Sirikarn, Prapassara; Tiamkao, Siriporn; Tiamkao, Somsak
title: The effects of COVID‐19 measures on the hospitalization of patients with epilepsy and status epilepticus in Thailand: An interrupted time series analysis
date: 2022-04-19
journal: Epilepsia Open
DOI: 10.1002/epi4.12600
sha: 6e551fe0d7fcc7e078edc326bdc1316eb6738ba8
doc_id: 967499
cord_uid: nvl31v3s

OBJECTIVE: To investigate the effect of Coronavirus disease 2019 (COVID‐19) measures on the hospitalization of patients with epilepsy and status epilepticus (SE). METHODS: This interrupted time series design included data from the Thai Universal Coverage Scheme electronic database between January 2017 and September 2020. The monthly hospitalization rate of epilepsy and SE was calculated by the number of hospitalizations divided by the midyear population. Segmented regression fitted by ordinary least squares (OLS) was used to detect the immediate and overtime effects of COVID‐19 measures on the hospitalization rate. RESULTS: During January 2017 and September 2020, the numbers of epilepsy and SE patients admitted to the hospital were 129 402 and 15 547 episodes, respectively. The monthly trend of the hospitalization rate in epilepsy decreased immediately after the COVID‐19 measure (0.739 per 100 000 population [95% CI: 0.219 to 1.260]). In particular, the number of children declined to 1.178 per 100 000 population, and the number of elderly individuals dropped to 0.467 per 100 000 population, while there was a nonstatistically significant change in SE. SIGNIFICANCE: COVID‐19 measures reduced the hospital rate in epilepsy, particularly in children and adults. However, there was no change in SE patients.

coronavirus disease, hospital admission, noncommunicable diseases, public measures, seizure cluster in Bangkok that mostly tract to boxing stadium and nightclubs. Thus, the public places were closed (e.g., mall, market, and school), and the partial lockdown was implemented in and outside Bangkok. However, the cases spread widely throughout the country within March due to the workers in Bangkok returned to their hometowns. Then, a curfew, restriction of movement, and active case finding were implemented in April across the country. 5, 6 The measures not only slowed down COVID-19 cases 7-9 but also affected the number of other public health issues, such as drug overdose, 10-12 accidents, 13,14 respiratory diseases, [15] [16] [17] respiratory tract infection, 18, 19 and mental health. 20, 21 Moreover, as a consequence of the growing number of COVID-19 cases and established measures, health care resources have been conserved for COVID-19 patients. Thus, hospitals have restricted or delayed treatment for nonessential cases, causing the hospitalization of inpatients with noncommunicable diseases to decrease. [22] [23] [24] Epilepsy and status epilepticus (SE) are neurological disorders that affect disability and mortality. The discontinuation of antiseizures medications in epilepsy patients is a common etiology of SE; continuous therapy is required to reduce the frequency and severity of the seizure. 25 Given the consequences of the COVID-19 outbreak and implemented measures, patients ranging from 4% to 35% had worse seizure control because of sleep problems, depression, and anxiety factors. In addition, 14.5% to 61.0% of those were postponed neurological tests. 26 Previous studies have shown that COVID-19 decreased the number of seizure-related admissions in children, 27 while there was no change in adult SE patients. 28 However, previous reports have studied children and adults. Therefore, this study aimed to investigate the effect of COVID-19 measures on the hospitalization of all patients with epilepsy and SE.

This study was an interrupted time series (ITS) design and conducted the data on the Thai Universal Coverage Scheme electronic database, which is an insurance of Thai citizens and covers over 75% of the Thai population.

Patients who were admitted to the hospital and had a primary diagnosis of epilepsy and SE from January 2017 to September 2020 were included. The database search was performed by using guidelines described in the International Statistical Classification of Diseases and Related Health Problems -10th Revision (ICD-10) with codes G40 (epilepsy) and G41 (SE). Epilepsy and SE diagnosis were followed by the guideline of the International League Against Epilepsy. 29, 30 There were no restrictions on age, sex, or epilepsy and SE type. Patients with missing date of admission were also excluded.

The COVID-19 outbreak in Thailand began in January 2020 and the number of newly cases peaked in March which were mainly cause form local transmission cluster in Bangkok. Thus, the state of emergency announced on 26 March to impose the partial lockdown which was a nighttime curfew and a ban on gatherings of more than five people in and around Bangkok. As a result of state of emergency announcement, the public venues were closed and working from home was encouraged. However, the cases continuously rose and widely spread throughout the country because the workers migrated to countryside. Then, a nationwide curfew was implemented on April 3, 2020. In addition, restriction of movement, and active case finding were established in several provinces. 5

The monthly hospitalization rate of epilepsy and SE was calculated by the number of hospitalizations divided by the midyear population.

We used the monthly hospitalization rate during January 2017 to September 2020 to perform an ITS analysis for

• The COVID-19 measures impacted the hospitalization rate differently in each age group.

• The hospitalization of epilepsy decreased after COVID-19 measure implementation in children and elderly

• There was a nonstatistically significant change of hospitalization rate after COVID-19 measure implementation in SE evaluating the impact of COVID-19 measures. Thus, there were 36-time points before and nine points after established measures which had an adequate sample size for ITS analysis. 31

Segmented regression fitted by ordinary least squares (OLS) was used to detect the immediate and overtime effect of COVID-19 measures in April 2020 (curfew, movement restriction, and active case finding) on the hospitalization rate. The equation of segmented regression model was represented as follows:

When Y t is the hospitalization rate at time t, time indicate time in month from the start (January 2017) to end (September 2020) of the observation, intervention is the indicator for time t occurring before (intervention = 0) or after (intervention = 1) the implementation of the COVID-19 measures, 0 estimate the baseline level of hospitalization rate at t 0 , 1 represent hospitalization trend before introducing the COVID-19 measures, 2 is the level change of hospitalization rate immediately after measures implementation, 3 show the trend change between before and after establishing the COVID-19 measures, and 1 + 3 estimate the trend of post-intervention. Autocorrelation was examined by the Cumby-Huizinga test, and the Newey-West standard error was used to account for autocorrelation. The seasonal effect was controlled by including it as a covariate in the model. 32, 33 All statistical analyses were performed by STATA 15.0. The study protocol was approved by the ethics committee in human research, Khon Kaen University, Khon Kaen, Thailand (HE641589).

During January 2017 and September 2020, the numbers of epilepsy and SE patients admitted to the hospital were 129 402 and 15 547 episodes, respectively. Most of the patients were men, and the median age was 36 (interquartile range [IQR] = 35) for epilepsy and 42 (IQR = 45) for SE patients ( Table 1 ). The hospitalization rate of epilepsy before the COVID-19 spread peaked in the early year and fluctuated over the year, the rate in 2020 presented dramatically dropped from January to April. While SE was high at early of the year and gradually decreased until it returned to high again in the midyear (Figure 1) . Thus, the effect of seasonality was controlled to consider the effect of COVID-19 measures on the hospitalization of epilepsy and SE.

The trend of hospitalization rate for overall epilepsy before the implementation of the measures increased 0.010 per 100 000 population in each month and it dropped to 0.739 per 100 000 population immediately after the first month of the COVID-19 measure was implemented. In particular, the hospitalization rate in elderly individuals declined to 0.467 per 100 000 population, and that in children declined to 1.178 per 100 000 population. However, the monthly trend after measures increased in children ( Table 2 ).

The immediate and overtime effects of measures on the hospitalization rate of SE were not statistically significant for all age groups (Table 2) . 

The first COVID-19 case in Thailand was reported in January 2020, and the number of cases rose continually. Thus, the curfew, movement restriction, and active case finding measures were established in April 2020 to control the spread of COVID-19. These measures affected the reduction in hospitalization of epilepsy in pediatric (0.129 per 100 000 population), which was similar to previous studies that reported a 59% decrease. 27 Moreover, our findings found that the hospitalization in the elderly also declined after the first month of measures (0.467 per 100 000 population). Due to concern about COVID-19 infection, medical appointments were canceled or postponed, 34 and the results found that increasing age was an important factor associated with experiencing a delay. 35 In particular, worry in caregivers or parents was a reason for delayed hospitalization in children. 36 Furthermore, the measures (e.g., lockdown and social isolation) were another cause for canceling appointments scheduled at medical care. 37, 38 Although the hospitalization rate of epilepsy in pediatric and elderly after the first month of implemented measures decreased, the overall trend after measures increased in pediatric patients because of therapy discontinuation in the early COVID-19 period and measure implementation.

In contrast to epilepsy, our SE results showed there was no change in the immediate and overtime effects of COVID-19 measures on the hospitalization rate, which was consistent with the latest study. 28 Because seizures are more severe in SE patients, patients require rapid treatment. Thus, the hospitalization rate of SE was not different between before and after establishing COVID-19 measures.

In addition, our study showed that the seasonal pattern increased the hospitalization of epilepsy (rainy: 0.379 per 100 000 population [95% CI: 0.200 to 0.558] and winter: 0.491 per 100 000 population [95% CI: 0.308 to 0.674]) and SE (rainy: 0.060 per 100 000 population [95% CI: 0.034 to 0.085] and winter: 0.061 per 100 000 population [95% CI: 0.035 to 0.087]), which was in accordance with previous research reporting that seasonality affected the number of epileptic seizures. [39] [40] [41] Preferably in a country with a generally hot temperature, the turning from hot to cold weather is one of the triggers to increase the risk of seizures.

To our knowledge, this study reported the effect of COVID-19 measures on the hospitalization rate of epilepsy and SE and conducted data with a large sample size based on multicentre data collection. Additionally, we performed subgroup analysis by age, which was classified into children, adults, and elderly. These results provided information to plan for preventing the hospitalization of a specific age group, for instance, the physicians need to provide the information on continued medication intake to caregivers of pediatric and elderly patients in the outbreak situation because discontinuation of antiseizures medications leads to worse seizure control and eventually hospital admission. However, this study examined the effect of COVID-19 measures only in the first wave in Thailand because the time duration and measures in the first wave could obviously identify. Furthermore, living in different COVID-19 zoning areas, especially the red zone that is the area with the continued surge in cases and the maximum control, can impact decisions to go to the hospital. Moreover, the database did not contain information about antiseizure medications which are the important factor associated with hospital admission in epilepsy and SE. Thus, further studies are needed to evaluate the effect of COVID-19 measures on the hospitalization rate of epilepsy and SE in various COVID-19 zoning areas and performing subgroup analysis in with and without continuous antiseizure medications.

In conclusion, the COVID-19 measures impacted the reduced hospitalization rate in epilepsy, especially children and adults, but there was a nonsignificant decrease in SE patients.

WHO declares COVID-19 a pandemic

Social distancing during the COVID-19 pandemic: staying home save lives

Isolation, quarantine, social distancing and community containment: pivotal role for oldstyle public health measures in the novel coronavirus (2019-nCoV) outbreak

Mask wearing to complement social distancing and save lives during COVID-19

Coronavirus disease 2019 (COVID-19) WHO Thailand situation report

Social impact assessment of COVID-19 in Thailand

The effect of lockdown on the COVID-19 epidemic in Brazil: evidence from an interrupted time series design

Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries

Effect of social distancing on COVID-19 incidence and mortality in Iran since

Signal of increased opioid overdose during COVID-19 from emergency medical services data

Impact of COVID-19 pandemic on drug overdoses in Indianapolis

How emergency department visits for substance use disorders have evolved during the early COVID-19 pandemic

Impact of COVID-19 on accident and emergency attendances and emergency and planned hospital admissions in Scotland: an interrupted time-series analysis

Initial impact of COVID-19's stay-at-home order on motor vehicle traffic and crash patterns in Connecticut: an interrupted time series analysis

Impact of COVID-19 lockdown on the incidence and mortality of acute exacerbations of chronic obstructive pulmonary disease: national interrupted time series analyses for Scotland and Wales

Impact of COVID-19 lockdown on emergency asthma admissions and deaths: national interrupted time series analyses for Scotland and Wales

Impact of COVID-19 national lockdown on asthma exacerbations: interrupted time-series analysis of English primary care data

Early impact of school closure and social distancing for COVID-19 on the number of inpatients with childhood non-COVID-19 acute infections in Japan

Changes in infection-related hospitalizations in children following pandemic restrictions: an interrupted timeseries analysis of total population data

Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a populationbased study

Acute mental health presentations before and during the COVID-19 pandemic

Trends of follow-up clinic visits and admissions three-months before and during COVID-19 pandemic at Tikur Anbessa specialized hospital

Disruption in essential health services in Mexico during COVID-19: an interrupted time series analysis of health information system data

Impact of the COVID-19 pandemic and response on the utilisation of health services in public facilities during the first wave in Kinshasa, The Democratic Republic of the Congo

Etiological assessment of status epilepticus

The impact of the COVID-19 pandemic on people with epilepsy. An Italian survey and a global perspective

Where have the children with epilepsy gone? An observational study of seizure-related accesses to emergency department at the time of COVID-19

Status epilepticus admissions during the COVID-19 pandemic in Salzburg-a population-based study

ILAE official report: a practical clinical definition of epilepsy

A definition and classification of status epilepticus -report of the ILAE task force on classification of status epilepticus

Use of interrupted time series analysis in evaluating health care quality improvements

Conducting interrupted time-series analysis for single-and multiple-group comparisons

Segmented regression analysis of interrupted time series studies in medication use research

Epilepsy care in the time of COVID-19 pandemic in Italy: risk factors for seizure worsening

Characterizing health care delays and interruptions in the United States during the COVID-19 pandemic: internet-based, cross-sectional survey study

Caregiver-reported delay in presentation to pediatric emergency departments for fear of contracting COVID-19: a multi-national cross-sectional study

Outcome predictors for status epilepticus--what really counts

Status epilepticus: an independent outcome predictor after cerebral anoxia

Seasonal pattern of epileptic seizures: a single-center experience

Seasonality in epileptic seizures

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: a population-based timeseries study

None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

https://orcid. org/0000-0001-5887-6716