Archives of Academic Emergency Medicine. 2022; 10(1): e65 OR I G I N A L RE S E A RC H Comparing Emergency Medical Services Processing Times for Stroke Patients Before and During COVID-19 Pan- demic; A Cross-sectional Study Thongpitak Huabbangyang1, Rossakorn Klaiangthong1∗, Krit Prasittichok2, Sutida Koikhunthod3, Jakkapan Wanna3, Nutthapong Sudajun3, Parichat Khaisri3, Anucha Kamsom4 1. Department of Disaster and Emergency Medical Operation, Faculty of Science and Health Technology, Navamindradhiraj University, Bangkok, Thailand. 2. Department of Research and Medical Innovation, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand. 3. Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand. 4. Division of Biostatistic, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand. Received: June 2022; Accepted: July 2022; Published online: 16 August 2022 Abstract: Introduction: Coronavirus disease 2019 (COVID-19) has directly affected global healthcare, especially the front- line of healthcare provision, including emergency medical services (EMS). The present study aimed to compare EMS processing times and the number of acute stroke patients serviced by EMS before and during COVID-19 pandemic. Methods: This is a retrospective observational review of Bangkok Surgico Medical Ambulance and Rescue Team (S.M.A.R.T.) EMS data from 2018 to 2021. The EMS processing times and the number of acute strokes were compared between pre-COVID-19 era ( January 1st, 2018, and December 31st, 2019) and during COVID-19 pandemic ( January 1st, 2020, and December 31st, 2021). Results: The number of stroke patients transported by EMS in one year, before and during COVID-19 pandemic was 128 and 150 cases, respectively (Change difference = 17.2%, 95% CI: 11.1–24.9). However, the average number of acute stroke patients per week was not significantly different (p = 0.386). The mean total EMS processing times before and during COVID-19 era were 25.59 ± 11.12 and 45.47 ± 14.61 minutes, respectively (mean difference of 19.88 (95% CI: 16.77–22.99) minutes; p < 0.001). The mean time from symptom onset to EMS arrival (p < 0.001), the mean call time (p < 0.001), the mean response time (p < 0.001), and the mean scene time (p < 0.001) were significantly higher during COVID-19 period. The mean transportation times for stroke patients was similar before and during COVID-19 pandemic (10.14 ± 6.28 and 9.41 ± 6.31 minutes, respectively; p = 0.338). Conclusion: During COVID-19 pan- demic, the number of acute stroke patients serviced by EMS increased substantially, but there was no difference in the average number of patients per week. During the pandemic, EMS processing times markedly increased. Keywords: Stroke; COVID-19; Emergency medical services Cite this article as: Huabbangyang T, Klaiangthong R, Prasittichok K, Koikhunthod S, Wanna J, Sudajun N, Khaisri P, Kamsom A. Comparing Emergency Medical Services Processing Times for Stroke Patients Before and During COVID-19 Pandemic; A Cross-sectional Study. Arch Acad Emerg Med. 2022; 10(1): e65. https://doi.org/10.22037/aaem.v10i1.1710. 1. Introduction Acute stroke is a severe neurological emergency that causes illness, mortality, and long-term morbidity. It is also an ∗Corresponding Author: Rossakorn Klaiaungthong; Department of Disas- ter and Emergency Medical Operation, Faculty of Science and Health Tech- nology, Navamindradhiraj University, Bangkok 10400, Thailand. Tel: +66 2- 244-3000, Email: rossakorn@nmu.ac.th, ORCID: https://orcid.org/0000-0002- 5846-5754. important global public health issue (1). Acute stroke is a time-sensitive condition. Prompt evaluation and manage- ment are crucial to patient outcomes (2). As the first re- sponders, emergency medical services (EMS) play an impor- tant role in this. EMS deliver patients to designated hospi- tals or stroke centers through a stroke fast track (3). Several previous studies have confirmed that EMS are important for rapid stroke center access, which increases treatment effi- ciency and positive outcomes in acute stroke patients (4, 5). COVID-19 not only affected stroke patients, but also led to an This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem T. Huabbangyang et al. 2 increase in the incidence of other emergency medical condi- tions, such as acute coronary syndrome, and delayed treat- ment in the context of EMS, reported in the previous system- atic review and meta-analyses (6). Since late 2019, the world faced coronavirus disease 2019 (COVID-19). COVID-19 be- gan in Hubei, China, and then spread dramatically around the world. Thailand was one of the first countries outside of China to report infection. The first Thai patient was con- firmed on 13th January 2020 by Thailand’s Ministry of Pub- lic Health (7). Subsequently, COVID-19 continued to spread throughout Thailand, affecting every sector. The pandemic directly affected the healthcare system, especially EMS, as they are the first responders to emergency patients, including those with COVID-19 (8). EMS established improvements to their operations in response to COVID-19, including protocol development and the use of personal protective equipment (PPE) to prevent infection of EMS staff (9). The pandemic also affected EMS processing times. In the USA, the number of patients requesting EMS for conditions other than COVID- 19 markedly decreased compared to that in the same period in the previous year, and the total number of EMS requests decreased by 26.1% (10). Yet, despite this, EMS response times substantially increased during COVID-19 (11). An ob- servational study on the impact of COVID-19 on acute stroke patients serviced by EMS in Busan, South Korea, reported a decrease in the rate of acute stroke patients requesting EMS by 8.2% and a doubling of EMS processing times compared to that in the non-pandemic period (12). In Massachusetts, USA, the number of EMS callouts for acute stroke patients decreased by 12.3% during COVID-19 pandemic (13). In Cat- alonia, Spain, the number of EMS callouts for acute stroke patients decreased by 22.0% during COVID-19 (14). How- ever, data on changes in EMS callouts for acute stroke during COVID-19 has not yet been collated in Thailand. The present study aimed to compare EMS processing times and the number of acute stroke patients serviced by EMS be- fore and during COVID-19 pandemic. 2. Methods 2.1. Study design and setting This is a retrospective observational review of Bangkok Sur- gico Medical Ambulance and Rescue Team (S.M.A.R.T.) EMS data from 2018 to 2021. Data on acute stroke patients ser- viced by EMS in Bangkok were collected from EMS patient care reports and were used to compare EMS processing times and the number of acute stroke patients serviced by the EMS before and during COVID-19 pandemic. The area studied was that covered by the Surgico Medical Ambulance and Rescue Team, Faculty of Medicine, Vajira Hospital, Nava- mindradhiraj University, Bangkok. Data were obtained from the S.M.A.R.T. of the Faculty of Medicine at Vajira Hospi- tal, which is the primary EMS unit in area one of Bangkok’s nine areas. This team is dispatched by the Erawan Center in Bangkok, which has six public and private hospitals in its net- work and is responsible for an area of 50 km2, with a pop- ulation of 500,000 (15). The first COVID-19 patient in the study area was confirmed on 13th January 2020 by Thailand’s Ministry of Public Health. During the study period, there were 437,303 confirmed COVID-19 cases in the study area (16). During COVID-19 pandemic, the S.M.A.R.T. introduced additional protocols for the screening of patients under in- vestigation (PUI) by paramedics or emergency nurse practi- tioners (ENPs) via the emergency medical hotline, 1554, or from the Bangkok dispatch center. This required the emer- gency medical dispatcher (EMD) to gather a patient symp- tom report and assess the risk of COVID-19 infection. EMS staff transporting patients were required to wear PPE and to avoid aerosol-generating procedures such as advanced air- way management and mechanical cardiopulmonary resus- citation (CPR) in out-of-hospital cardiac arrest (OHCA) pa- tients. In the study area, at least three members of the S.M.A.R.T. staff attended each emergency. This could in- clude emergency physicians (EPs), paramedics, emergency nurse practitioners (ENPs), and emergency medical techni- cians (EMTs). 2.2. Participants Patient data were collected with the assistance of the S.M.A.R.T. of the Faculty of Medicine at Vajira Hospital, Nava- mindradhiraj University. The data were obtained from EMS patient care reports using the response code (RC) for acute stroke, which was “18 code red 1 - red 9.” The period be- tween January 1st, 2018, and December 31st, 2019, was de- fined as pre-COVID-19 era, while the period between Jan- uary 1st, 2020, and December 31st, 2021, was defined as dur- ing COVID-19 pandemic. Patients with a final diagnosis of acute stroke, RC code 18 with level red severity (18 red 1 - red 9), aged > 18 years and assisted by the S.M.A.R.T. of the Fac- ulty of Medicine, Vajira Hospital, Navamindradhiraj Univer- sity were included in our study. Patients who refused treat- ment or transportation to hospital, those with incomplete data, and those treated with end-of-life or palliative care were excluded. 2.3. Data gathering Patient data were collected from EMS patient care reports. These reports are recorded on a form that consists of EMS operation unit data, patient data, and all treatments given by the EMS team. The reports are recorded by the EMD and the EMS staff responsible for the patient. The primary pur- pose of the reports is the evaluation of EMS service require- ments when assigning healthcare funding for EMS units. The forms filled out from 2018 to 2021 were retrospectively col- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 3 Archives of Academic Emergency Medicine. 2022; 10(1): e65 Table 1: Comparing the baseline characteristics of acute stroke patients as well as their EMS processing times before and during the coron- avirus disease 2019 (COVID-19) pandemic Characteristics COVID-19 era P value Before (N = 128) During (N = 150) Number of patients per week Mean ± SD 1.96 ± 1.15 2.17 ± 1.22 0.386 Gender Male 77 (60.2) 85 (56.7) 0.556 Female 51 (39.8) 65 (43.3) Age (year) Mean ± SD 66.88 ± 14.33 66.11 ± 13.20 0.642 Underlying disease Yes 71 (55.5) 102 (68.0) 0.032 Vital signs (Prehospital) Systolic blood pressure 157.22 ± 39.05 163.62 ± 35.15 0.152 Diastolic blood pressure 92.68 ± 23.89 93.12 ± 23.15 0.876 Heart rate 88.34 ± 21.87 93.14 ± 19.99 0.057 Oxygen saturation 96.58 ± 3.03 97.05 ± 2.10 0.142 Glasgow coma score 11.55 ± 3.40 12.51 ± 2.89 0.011 EMS processing times (minutes) Symptom to EMS 13.52 ± 11.58 56.27 ± 76.6 < 0.001 Call time 1.48 ± 0.77 3.62 ± 1.89 < 0.001 Response time 2.75 ± 2.45 16.54 ± 8.86 < 0.001 Scene time 12.23 ± 5.54 19.68 ± 7.81 < 0.001 Transportation time 10.14 ± 6.28 9.41 ± 6.31 0.338 Total 25.59 ± 11.12 45.47 ± 14.61 < 0.001 Data are presented as number (%) and mean ± standard deviation (SD). EMS: emergency medical services. Figure 1: The average number per week of acute stroke patients, who were transported to hospital by emergency medical services (EMS) before and during COVID-19 period. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem T. Huabbangyang et al. 4 Figure 2: The average number per week of acute stroke patients, who were transported to hospital by emergency medical services (EMS) before and during COVID-19 period. lected, with the period from January 1st, 2018, to December 31st, 2019, defined as pre-COVID-19; and the period from January 1st, 2020, to December 31st, 2021, defined as dur- ing COVID-19. The data from EMS patient care reports for all acute stroke patients meeting our criteria were recorded and saved in Microsoft Excel. This included patient demographic and clinical characteristics, including gender, age, underly- ing diseases, prehospital systolic blood pressure, prehospital diastolic blood pressure, prehospital heart rate, prehospital oxygen saturation, prehospital Glasgow coma score, and time from symptom onset to EMS arrival (in min); and EMS pro- cessing time, including call time (in minutes), response time (in min), scene time (in min), transportation time (in min- utes), and total processing time (in min). 2.4. Definitions - The period between January 1st, 2018, and December 31st, 2019, was defined as pre-COVID-19, while the period be- tween January 1st, 2020, and December 31st, 2021, was de- fined as during COVID-19. - EMS processing time was the total time from the beginning of the call to emergency services to the arrival of the patient (by ambulance) at the designated hospital. - Call time was the time from the beginning of the emergency call to the order for ambulance dispatch. - Response time was the time from the end of the emergency call to ambulance arrival at the scene. - Scene time was the time from ambulance arrival at the scene to ambulance departure from the scene. - Transportation time was the time from ambulance depar- ture from the scene to ambulance arrival at the designated hospital. - The response code (RC) “RC 18 red 1 - RC 18 red 9” was the code for acute ischemic or hemorrhagic stroke with a high severity level. 2.5. Sample size determination For the primary objectives, mean values of each category were compared between before and during the pandemic (17). For the sample size calculation, we referred to statisti- cal data from a previous study (18). The mean EMS process- ing times for acute stroke patients before and during COVID- 19 were 31.3 and 35.4 min, respectively, and the interquartile ranges (IQRs) were 23–37 and 25–41. The standard deviations (SDs) were 10.37 and 11.85, respectively (12). The ratio of the sample size compared to the studied groups was defined as 1. We set the significance level as p > 0.05 and the power as 80%. The calculated minimum sample size was determined to be 116 per group. In the present study, the sample comprised acute stroke This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 5 Archives of Academic Emergency Medicine. 2022; 10(1): e65 patients serviced by the EMS of the S.M.A.R.T., Faculty of Medicine Vajira Hospital, Navamindradhiraj University, who matched our eligibility criteria over the 4 years. The number of patients during the pre-COVID-19 period was 128, and the number during COVID-19 was 150. Thus, our total sample size was 278, which was sufficient for analysis. 2.6. Statistical analysis To examine the distribution of variables, we converted the raw data to descriptive statistics. Continuous variables were presented as the mean ± SD or the median and IQR. Categor- ical variables were presented as frequencies and proportions. We compared the two groups using independent t-tests or Mann–Whitney U tests for numeric variables and chi-square or Fisher’s exact tests for categorical variables. The differ- ences between means before and during COVID-19 were re- ported with 95% confidence intervals (CIs). To compare the number of acute stroke patients serviced by EMS before and during COVID-19, data were described as frequency distributions and difference percentages between the two periods, with 95% CI. An interrupted time-series analysis with a linear first-order autoregressive model was used to compare the number of patients before and during COVID-19 (change in the number of events per week to eval- uate the change in the number of weekly EMS stroke cases). Statistical analyses were performed using SPSS Statistics for Windows, version 28.0. (IBM Corp., Armonk, NY, USA). A p- value < 0.05 was considered statistically significant. 2.7. Ethical statement This study was conducted in accordance with the tenets of the Declaration of Helsinki 1975 and its revisions in 2000. It was approved by the Institutional Review Board of the Fac- ulty of Medicine Vajira Hospital, Navamindradhiraj Univer- sity (COA no. 099/2565). The informed consent requirement was waived due to the retrospective nature and anonymity of all patient data. 3. Results 3.1. Baseline characteristics of studied patients Table 1 compares the baseline characteristics of stroke pa- tients before and during COVID-19 pandemic. The number of stroke patients transported by EMS in one year, before and during COVID-19 pandemic was 128 and 150 cases, respec- tively (Change difference = 17.2%, 95% CI: 11.1–24.9). How- ever, the average number of acute stroke patients per week was not significantly different (1.96 ± 1.15 cases before and 2.17 ± 1.22 during COVID-19; p = 0.386; Figure 1). The mean age of patients before and during the pandemic were 66.11 ± 13.20 and 66.88 ± 14.33 years, respectively (p = 0.642). The proportions of male patients before and during COVID-19 were 56.7% and 60.2%, respectively (p = 0.556). The mean systolic blood pressure (p = 0.152), diastolic blood pressure (p = 0.876), heart rate (p = 0.057), and oxygen saturation (p = 0.142) of stroke patients in prehospital setting was same before and during COVID-19 era. The mean Glasgow coma scale of patients was significantly higher during COVID-19 pandemic (12.51 ± 2.89 vs. 11.55 ± 3.40; p = 0.011). In addi- tion, the prevalence of underlying diseases during COVID-19 era was higher than before the pandemic (68.0% vs. 55.5%; p = 0.032). 3.2. EMS processing times Figure 2 and table 1 compare the total EMS processing times for acute stroke patients before and during COVID-19 pan- demic. The mean total EMS processing times before and during COVID-19 pandemic were 25.59 ± 11.12 and 45.47 ± 14.61 minutes, respectively (mean difference of 19.88 (95% CI: 16.77–22.99) minutes; p < 0.001). The mean duration from symptom onset to EMS arrival (p < 0.001), the mean call time (p < 0.001), the mean response time (p < 0.001), and the mean scene time (p < 0.001) were significantly higher during COVID-19 period (table 1 and figure 2). The mean transportation times for stroke patients was similar before and during COVID-19 pandemic (10.14 ± 6.28 and 9.41 ± 6.31 minutes, respectively; p = 0.338). 4. Discussion The number of acute stroke patients serviced by EMS in- creased by 17.2% during COVID-19 pandemic. The mean EMS processing times, call times, response times, and scene times were all significantly higher during COVID-19 pan- demic compared to before, but there was no significant change in the transportation times. The present study supported the findings of previous sys- tematic reviews and meta-analyses that have reported an in- crease in the incidence and risk of acute stroke in COVID- 19 patients. Several factors may increase the risk of acute stroke in COVID-19 patients. These include abnormal coag- ulation, inflammation, platelet activation, and abnormal en- dothelial alterations (19, 20). Velasco et al. found a 53.0% increase in EMS callouts for acute stroke during COVID-19 pandemic, most of which were in urban areas (21). It is likely that most EMS callouts for all conditions, at all times, are in urban areas as they are more densely populated. How- ever, this finding conflicted with those of several observa- tional studies in other countries, including South Korea (12), the USA (13), and Spain (14), all of which found a decrease in incidence of acute stroke during COVID-19. Reasons pos- tulated by the authors of these studies for this reduced in- cidence of stroke EMS callouts are broad explanations for a general reduction in the number of patients accessing EMS This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem T. Huabbangyang et al. 6 during COVID-19 era, including the declaration of a state of emergency, social restrictions (11), stay-at-home measures, social distancing measures, and self-isolation (10). In the present study, we found that the number of acute stroke pa- tients serviced by EMS in Bangkok, Thailand, increased by 17.2% during COVID-19. This is likely to have been because people were more inclined to call out EMS in medical emer- gencies rather than traveling to hospitals themselves or being taken by relatives, because the emergency departments of Bangkok hospitals had to temporarily close during COVID-19 pandemic to prevent co-mingling of COVID-19 patients and medically vulnerable non-COVID-19 patients. Also, because of the frequent presentation of COVID-19 patients in emer- gency departments, there was a need to ensure thorough dis- infection of these departments and to quarantine high-risk staff. Therefore, EMS were often the sole means of access to hospital emergency departments. In addition, the declara- tion of a state of emergency by the Thai government was ac- companied by the implementation of a 22.00–04.00 curfew, effective between March 26th and June 30th, 2020. This pro- vided an additional reason for people choosing EMS rather than delivering patients to hospitals themselves, at least dur- ing the curfew hours. The increase in acute stroke patients seen by EMS during COVID-19 pandemic was also observed in a study by Ikenberg et al., who reported an 86% increase in EMS stroke RC during the lockdown (22). EMS processing times, call times, response times, and scene times markedly increased during COVID-19 pandemic. This result was compatible with those of previous studies that had found increased EMS processing times during the pan- demic (12, 14, 23, 24). The greatest increases in EMS pro- cessing times in this study occurred during a period in which Bangkok EMS experienced a huge increase in callouts, both for COVID-19 patients and other medical emergencies, with a greater frequency of calls to the emergency hotline 1669 than ever before, leading to many callers reaching a busy signal. Moreover, the new COVID-19 protocols required the EMD at the Bangkok dispatch center to gather PUI medi- cal histories and assess the COVID-19 risk to attending EMS staff. This increased call times and response times, despite the planning and implementation of strategies to stabilize operations during the pandemic. The primary strategy used to decrease call times was a computer-assisted triage sys- tem that separated and directed calls about COVID-19 pa- tients from those concerned with other medical emergen- cies. Nonetheless, call and response times were still signif- icantly increased during the pandemic in the present study. Because of the risk of infection, the S.M.A.R.T. staff attend- ing callouts were required to wear PPE to every emergency attended, leading to increased response times. The period during which staff were required to wear PPE was directly correlated with the increased response times (24). An ad- ditional protocol implemented during the pandemic was an en route call to the person who requested the service by the leader of the attending S.M.A.R.T. This was to evaluate the pa- tient’s symptom severity and COVID-19 risk, with questions about recent travel to high-risk areas for COVID-19 infection and COVID-19 symptoms such as an abnormal sense of taste or smell. This may have had additional effects on response times. During the pandemic, the attending EMS staff faced diffi- culties in the evaluation and management of emergency pa- tients, with contact precautions and PPE use interfering with communication and treatment. In the region studied, the EMS team leaders are responsible for decisions about hos- pital delivery of acute stroke patients. However, before deliv- ery, they must coordinate the reporting of patient symptoms and stroke fast track activation with EMD at the Bangkok dis- patch center who, in turn, is required to pass on this infor- mation to the emergency department equipped for stroke patient management closest to the scene. During the pan- demic, Bangkok hospital emergency departments were over- crowded with both COVID-19 and other emergency patients. As a result, some emergency departments were unable to ad- mit new acute stroke patients, resulting in further increases in scene times. Previous research indicated that this was also an issue in Okayama during COVID-19 pandemic, with de- lays in the delivery of emergency patients to hospitals due to overcrowded emergency departments with insufficient re- sources to deal with the increased number of patients (25). No difference was found between the mean EMS transporta- tion times before and during the pandemic. We posit that this is because, in the study location, most patients would not have been far from the designated hospital, and traffic conditions were not noticeably altered by the pandemic, with heavy congestion in the capital city, even during COVID-19 pandemic. 4.1. Strengths and limitations of this study A strength of the present study was its comparison of pro- cessing times and the number of acute stroke patients ser- viced by EMS before and during COVID-19. Our results offer considerable potential benefits to EMS in developing coun- tries. The information on the effects of a medical crisis on EMS treatment of time-sensitive diseases such as acute stroke can be utilized to improve the efficacy of EMS and streamline their crisis response practices. There were sev- eral limitations in the present study. Firstly, and most impor- tantly, the only data obtained on acute stroke patients was prehospital information from the ambulance operation re- port. We did not have access to any information regarding their treatment in the emergency department or the admin- istration of anticoagulants or other medications. Secondly, due to the retrospective nature of our study, the data of some This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 7 Archives of Academic Emergency Medicine. 2022; 10(1): e65 acute stroke patients were incomplete, and these patients had to be excluded. Thirdly, data were derived from only one medical facility (S.M.A.R.T., Faculty of Medicine, Vajira Hos- pital, Navamindradhiraj University). Hence, while our out- comes can be considered representative of effects on EMS in equivalent or similar settings substantially affected by the COVID-19 pandemic, they cannot be applied more broadly to other contexts. Fourthly, the period between January 1st, 2018, and December 31st, 2019, was defined as pre-COVID- 19, while the period between January 1st, 2020, and Decem- ber 31st, 2021, was defined as the COVID-19 pandemic pe- riod. This provided a study period of four years. However, strictly speaking, the COVID-19 pandemic remained ongo- ing at the time this paper was written ( June 2022). Lastly, the present study was observational. Consequently, the effects of COVID-19 on EMS processing times and the number of acute stroke patients serviced by EMS could not be comprehen- sively evaluated, and valid and reliable causality could not be inferred with certainty from the relationships between vari- ables. Future qualitative, prospective, and population-based studies are needed for the accurate attribution of causality. 5. Conclusion During the 2 years of the COVID-19 pandemic, the number of acute stroke patients serviced by EMS substantially in- creased. However, there were no significant changes in the average number of acute stroke patients treated by EMS per week. During the pandemic period, all EMS processing times significantly increased. 6. Declarations 6.1. Acknowledgments We would like to thank the paramedics at the S.M.A.R.T. Divi- sion of Emergency Medical Services and Disasters, Faculty of Medicine, Vajira Hospital, Navamindradhiraj University, for facilitating data access and collection for the present study. Our thanks also to Dr. Krit Prasittichok and Dr. Rossakorn Klaiaungthong for their research development suggestions. Thanks to Dr. Chunlanee Sangketchon, the Chief of the De- partment of Disasters and Emergency Medical Operations, Faculty of Science and Health Technology, Navamindradhiraj University, for his support and research development sugges- tions. Thanks to Anucha Kamsom of the Division of Biostatis- tics, Faculty of Medicine, Vajira Hospital, Navamindradhiraj University, for her advice on statistical analyses. Finally, our thanks to Dr. Aniwat Berpan for his role in this study as an English language consultant. 6.2. Authors’ contributions Conceptualization: Thongpitak Huabbangyang, Sutida Koikhunthod, Jakkapan Wanna, Nutthapong Sudajun and Parichat Khaisri; Methodology: Thongpitak Huab- bangyang, Rossakorn Klaiaungthong and Krit Prasittichok; Software: Thongpitak Huabbangyang and Anucha Kam- som; Validation: Thongpitak Huabbangyang, Rossakorn Klaiaungthong and Krit Prasittichok; Formal analysis: Thongpitak Huabbangyang and Anucha Kamsom; Investi- gation: Thongpitak Huabbangyang, Sutida Koikhunthod, Jakkapan Wanna, Nutthapong Sudajun and Parichat Khaisri; Resources: Thongpitak Huabbangyang, Suthida Koikhuntod, Jakkapan Wanna, Nutthapong Sudajun, Parichat Khaisri and Rossakorn Klaiaungthong; Data Curation: Thongpitak Huab- bangyang and Anucha Kamsom; Writing – Original Draft: Thongpitak Huabbangyang, Rossakorn Klaiaungthong and Krit Prasittichok; Writing - Review & Editing: Thongpitak Huabbangyang; Visualization: Thongpitak Huabbangyang and Rossakorn Klaiaungthong; Supervision: Krit Prasitti- chok; Project administration: Thongpitak Huabbangyang; Funding acquisition: Rossakorn Klaiaungthong 6.3. Funding and supports The authors are grateful to the Navamindradhiraj University Research Fund for Pub. Funding acquisition: Rossakorn Kla- iaungthong. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for- profit sectors. 6.4. Conflict of interest The authors have no conflicting interests to declare 6.5. Data availability The datasets generated and analyzed during the current study are available from the corresponding author on reason- able request. References 1. Prabhakaran S, Ruff I, Bernstein RA. Acute stroke inter- vention: a systematic review. Jama. 2015;313(14):1451- 62. 2. Zubair AS, Sheth KN. Emergency Care of Patients with Acute Ischemic Stroke. Neurol Clin. 2021;39(2):391-404. 3. Ardebili ME, Naserbakht M, Bernstein C, Alazmani- Noodeh F, Hakimi H, Ranjbar H. Healthcare providers ex- perience of working during the COVID-19 pandemic: a qualitative study. Am J Infect Control. 2021;49(5):547-54. 4. Abdullah AR, Smith EE, Biddinger PD, Kalenderian D, Schwamm LH. Advance hospital notification by EMS in acute stroke is associated with shorter door-to- computed tomography time andIncreased likelihood of This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem T. Huabbangyang et al. 8 administration of tissue-plasminogen activator. Prehosp Emerg Care. 2008;12(4):426-31. 5. Morris DL, Rosamond W, Madden K, Schultz C, Hamil- ton S. Prehospital and emergency department delays af- ter acute stroke: the Genentech Stroke Presentation Sur- vey. Stroke. 2000;31(11):2585-90. 6. Mogharab V, Ostovar M, Ruszkowski J, Hussain SZM, Shrestha R, Yaqoob U, et al. Global burden of the COVID- 19 associated patient-related delay in emergency health- care: a panel of systematic review and meta-analyses. Glob Health. 2022;18(1):58. 7. Wongtanasarasin W, Srisawang T, Yothiya W, Phinyo P. Impact of national lockdown towards emergency depart- ment visits and admission rates during the COVID-19 pandemic in Thailand: A hospital-based study. Emerg Med Australas. 2021;33(2):316-23. 8. Stirparo G, Oradini-Alacreu A, Migliori M, Villa G, Botteri M, Fagoni N, et al. Public health impact of the COVID-19 pandemic on the emergency healthcare system. J Public Health (Oxf ). 2022;44(1):e149-e52. 9. Kovacs G, Sowers N, Campbell S, French J, Atkin- son P. Just the facts: airway management during the coronavirus disease 2019 (COVID-19) pandemic. CJEM. 2020;22(4):440-4. 10. Lerner EB, Newgard CD, Mann NC. Effect of the coro- navirus disease 2019 (COVID-19) pandemic on the US emergency medical services system: a preliminary re- port. Acad Emerg Med. 2020;27(8):693-9. 11. Laukkanen L, Lahtinen S, Liisanantti J, Kaakinen T, Ehrola A, Raatiniemi L. Early impact of the COVID-19 pandemic and social restrictions on ambulance mis- sions. Eur J Public Health. 2021;31(5):1090-5. 12. Kim J, Kim C, Park SY. Impact of COVID-19 on Emergency Medical Services for Patients with Acute Stroke Presenta- tion in Busan, South Korea. J Clin Med. 2021;11(1):94. 13. Goldberg SA, Cash RE, Peters G, Weiner SG, Gree- nough PG, Seethala R. The impact of COVID-19 on statewide EMS use for cardiac emergencies and stroke in Massachusetts. J Am Coll Emerg Physicians Open. 2021;2(1):e12351. 14. Ramos-Pachón A, García-Tornel Á, Millán M, Ribó M, Amaro S, Cardona P, et al. Bottlenecks in the acute stroke care system during the COVID-19 pandemic in Catalo- nia. Cerebrovasc Dis. 2021;50(5):551-9. 15. Huabbangyang T, Soion T, Promdee A, Nguanjinda K, Chamchan A, Chaisorn R, et al. Factors associated with successful resuscitation during out-of-hospital cardiac arrest performed by Surgico Medical Ambulance and Rescue Team (SMART), Division of Emergency Medical Service and Disaster, Faculty of Medicine Vajira Hos- pital, Navamindradhiraj University. J Med Assoc Thai. 2021;104:1488-96. 16. Ministry of Public Health DoDC. Data COVID- 19. 2021 [cited 2022 1 April]. Available from: https://media.thaigov.go.th/uploads/public_img/source/311264.pdf 17. Rosner B. Fundamentals of biostatistics. Fifth edition ed: Duxbury: Thomson learning; 2000. 18. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, me- dian, range and/or interquartile range. BMC Med Res Methodol. 2014;14(1):135. 19. Nannoni S, de Groot R, Bell S, Markus HS. Stroke in COVID-19: a systematic review and meta-analysis. Int J Stroke. 2021;16(2):137-49. 20. Stein LK, Mayman NA, Dhamoon MS, Fifi JT. The emerg- ing association between COVID-19 and acute stroke. Trends Neurosci. 2021;44(7):527-37. 21. Velasco C, Wattai B, Buchle S, Richardson A, Padmana- ban V, Morrison KJ, et al. Impact of COVID-19 pandemic on the incidence, prehospital evaluation, and presenta- tion of ischemic stroke at a nonurban comprehensive stroke center. Stroke Res Treat. 2021;2021:6624231. 22. Ikenberg B, Hemmer B, Dommasch M, Kanz K-G, Wunderlich S, Knier B. Code stroke patient refer- ral by emergency medical services during the public COVID-19 pandemic lockdown. J Stroke Cerebrovasc Dis. 2020;29(11):105175. 23. Lee S-H, Mun YH, Ryoo HW, Jin S-C, Kim JH, Ahn JY, et al. Delays in the management of patients with acute ischemic stroke during the COVID-19 outbreak period: a multicenter study in Daegu, Korea. Emerg Med Int. 2021;2021:6687765. 24. Melaika K, Sveikata L, Wiśniewski A, Jaxybayeva A, Ekkert A, Jatužis D, et al. Changes in prehospital stroke care and stroke mimic patterns during the COVID-19 lockdown. Int J Environ Res Public Health. 2021;18(4):2150. 25. Ageta K, Naito H, Yorifuji T, Obara T, Nojima T, Yamada T, et al. Delay in emergency medical service transporta- tion responsiveness during the COVID-19 pandemic in a minimally affected region. Acta Med Okayama. 2020;74(6):513-20. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem Introduction Methods Results Discussion Conclusion Declarations References