Archives of Academic Emergency Medicine. 2022; 10(1): e42 OR I G I N A L RE S E A RC H An 18-Month Epidemiologic Survey of 3364 Deceased COVID-19 Cases; a Retrospective Cross-sectional Study Ayoub Tavakolian1, Seyed Hassan Ashrafi Shahri2, Mohammad Ali Jafari3, Elham Pishbin2, Hamid Zamani Moghaddam2, Mahdi Foroughian2, Hamidreza Reihani2∗ 1. Department of Emergency Medicine, Faculty of Medicine, Sabzevar University of Medical Sciences, Sabzevar, Iran. 2. Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. 3. Department of Emergency Medicine, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. Received: February 2022; Accepted: March 2022; Published online: 31 May 2022 Abstract: Introduction: The COVID-19 pandemic has been considered an international problem. This study aimed to survey the demographic and clinical characteristics of the deceased COVID-19 patients. Methods: The present cross-sectional study was performed on all deceased COVID-19 patients who died in Imam Reza Hospital, Mash- had, Iran, from March 20, 2020, to September 23, 2021. Their data, including age, gender, complaints, and clinical symptoms at the time of admission, as well as information at the time of death (hour, shift, holiday/non- holiday) were analyzed and reported. Results: 3364 deaths due to COVID-19 have been registered during the study period (60.46% male). The patients’ mean age was 66.99±16.97 (range: 1-101) years (92.7% of them were Iranian). The mortality at night shifts was less than day shifts (1643 vs. 1721). The average amount of deaths/day on holidays and workdays was (5.63 vs. 6.24). The number of deaths varied during the various hours of the day and night. Diabetes and cardiovascular diseases were the most common confounding factors, which were ob- served in 22.44% and 15.36% of the cases, respectively. Conclusion: Based on the findings of this series, COVID- 19 mortality was frequently observed in male patients, those with the mean age of 66.99 years, morning shifts, and workdays. Keywords: COVID-19; Hospital Mortality; Diabetes Mellitus; Cardiovascular Diseases Cite this article as: Tavakolian A, Ashrafi Shahri SH, Jafari MA, Pishbin E, Zamani Moghaddam H, Foroughian M, Reihani H. An 18-Month Epidemiologic Survey of 3364 Deceased COVID-19 Cases; a Retrospective Cross-sectional Study. Arch Acad Emerg Med. 2022; 10(1): e42. https://doi.org/10.22037/aaem.v10i1.1568. 1. Introduction SARS-COV-2, a member of the Coronaviridae family, caused a disease named COVID-19 in the late 2019, which became a widespread infection in world (1, 2). SARS-COV-2 can cause various ranges of the clinical symptoms from mild manifesta- tions to severe forms of disease requiring intensive care unit (ICU) admission (3-7). Acute respiratory distress syndrome (ARDS) is the main cause of death from COVID-19 (8, 9). Pooled analyses of mortality rates have demonstrated extensively higher rates of mortality among ICU admitted patients (40.5%) compared to ward admitted ones (11.5%) (10). Various studies are con- ∗Corresponding Author: Hamidreza Reihani; Emam Reza Hospital, Ibn-Sina Street, Mashhad, Iran. Email: reihanihr@mums.ac.ir, Tel: +98 9153173869, OR- CID: http://orcid.org/0000-0003-0617-9374. ducted to predict mortality rate and distinguish indices re- lated to severity of COVID-19 and its mortality, as well as to investigate biochemical, laboratory, clinical, and imag- ing characteristic of patients (11, 12). Additionally, some as- tounding findings have pointed to the significant effects of the spatiotemporal factors as well (13, 14). Zhang et al. re- ported that shift work at night was linked to a higher risk of mortality (14). But Morales et al. showed that being admitted to ICU at night does not correlate to higher mortality rate of COVID-19 patients (15). Understanding the impact of differ- ent times of the day on the quality of care, and finding other potentially influential factors would provide the opportunity for applying proper policies. So, this study aimed to evaluate the demographic and clinical findings of deceased COVID-19 cases, stratified by death time in a referral hospital in North- East of Iran. 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 A. Tavakolian et al. 2 2. Methods 2.1. Study design and setting In the present retrospective cross-sectional study, charac- teristics of 3364 deceased COVID-19 patients in Imam Reza Hospital, Mashhad, as one of the referral centers for COVID- 19 patients in North-East of Iran, from March 20, 2020, until September 23, 2021 (about 18 months), were reviewed. Af- ter obtaining approval from Mashhad University of Medical Sciences Ethics Committee (code: IR.MUMS.REC.1399.242), information about all deceased patients with confirmed COVID-19 diagnosis based on international guidelines was collected from the archives of the hospital using census method. Researchers adhered to confidentiality of patients’ information and ethical considerations stated in declaration of Helsinki. 2.2. Participants The present study includes all cases of hospital mortalities due to COVID-19 during the study period. All cases of mor- talities attributed to COVID-19 by an infectious disease spe- cialist was considered in this study, even cases with under- lying health conditions. Records of patients who were trans- ferred from other centers were also included. Patients who did not meet the ICD-10 criteria for COVID-19 diagnosis were excluded. Patients who had died after being transmitted to other hospitals were not included. Ethnicity was not consid- ered when gathering data and refugees were also included. 2.3. Data gathering The collected data include age, gender, postal address, com- plaints and clinical symptoms, O2 saturation at the time of admission, as well as information on the time of death (hour, shift, holiday/workdays). A checklist of the mentioned fac- tors was provided by researchers and filled out, retrospec- tively, by reviewing hospital records. Only records containing a positive PCR result for COVID-19 were recruited. 2.4. Statistical analysis The collected data were analyzed using SPSS software ver- sion 26. Descriptive statistics for qualitative variables were reported in the form of frequency and frequency distribution and those of quantitative variables were reported as mean and standard deviation. The normality of quantitative vari- ables was confirmed using the Kolmogorov-Smirnov test. 3. Results 3364 deaths due to COVID-19 were recorded during the study period (2034 (60.46%) male and 1330 (39.54%) female). The mean age was 66.99 ± 16.97 (range: 1 -101; median: 68) years with normal distribution (50% > 67 and 25% < 56 years). Table 1 shows the baseline characteristics of studied patients. The most common complaint was shortness of breath (74.23%) followed by cough (34.0%). 88.59% of patients had a decrease in O2 saturation at the time of admission to the hospital. 1321/2015 (65.56%) patients with complete clinical informa- tion had at least one underlying disease. (15.36% heart dis- ease and 22.44% diabetes mellitus). 3.1. Mortality peaks Figure 1 shows a comparison of the total number of COVID- 19-associated deaths during each peak. During the study pe- riod, five mortality peaks was observed. During the first one (from March 20, 2020, up to June 3, 2020), which occurred in the first month of the COVID-19 pandemic, a total of 309 people died and the average daily death rate was 4.07±2.91 deaths/day. In the second peak ( June 11 up to August 26, 2020), during which 911 COVID-19 deaths was recorded, the average daily number of deaths was 11.99±8.06 deaths/day. The third and fourth waves of death due to coronavirus oc- curred at the end of 2020 and the first half of 2021. The fifth wave occurred from July 7, 2021, until September 20, 2021, in which 1042 COVID-19 deaths were recorded with a daily average number of 13.71± 8.28. At the same time, the high- est mortality rate was recorded, with 34 deaths in one day. This peak was larger than the other peaks in terms of inten- sity and extent. The second and fifth peaks were more severe and there were a higher number of patients with worse con- ditions compared to the other waves. 3.2. Age distribution Figure 2 shows the age distribution of deceased cases strati- fying study periods to 3-month parts. Least deaths were re- ported in individuals less than 20 years old with 59 (1.75%) cases, followed by twenty- to forty-year-old subjects with 281 (8.35%) cases. The highest number of death reports, 1516 (45.07%) cases, belonged to those 60 to 80 years old followed by those 40 to 60 years old and over 80 years old with 732 (21.76%) and 776 (23.07%) cases, respectively (p < 0.001). 3.3. Time distribution The lowest death rate is recorded in the early hours of the morning with 103(3.06%) deaths and the highest death rate is recorded in 11-12 AM with 170 (5.05%) deaths (figure 3). In the morning shift, 884 patients died with an average of 1.61 ± 2.41 deaths/day, and in the evening shift, 837 people died with an average of 1.52±2.25 deaths/day. By a division of the night shift into two shifts from 19 in the evening till 1 in the morning and the other shift from 1 AM till 7 AM an av- erage death rate of 1.58 ±2.38/day and 1.41± 2.08/day were recorded, respectively (figure 4). 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): e42 3.4. Day Distribution The present study period covers a total of 115 holidays and 435 workdays. The average COVID-19 mortality rate was 5.58 deaths/day (642 cases) on holidays and 6.27 deaths/day (2722 deaths) on workdays. 4. Discussion Based on the findings of this series, the COVID-19 mortalities were frequently observed in males, patients with the mean age of 66.99 years, morning shifts, and workdays. Preliminary reports of COVID-19 epidemiology in China show that the mortality rate of males (2.8%) is higher than females (1.7%) (16). Mir Jalili et al. reviewed the risk factors of COVID-19 patients’ mortality in a case-cohort study and reported that 56.1% of the deceased patients are male, and their mean age is 71 years (17). Another study on COVID-19 mortality in ten major European countries reported that men had a higher death rate than women. COVID-19-related death risk ranged from RR = 1.11 in Portugal to RR = 1.54 in France (18). Hannah et al., in a large meta-analysis of more than three million COVID-19 patients in 44 countries, indicate that gen- der does not play a role in COVID-19 infection, but in the case of COVID-19, male patients have three times more chance of ICU admission and death (OR = 1.39,95% CL = 1.31,1.47) (19). In the present study, similar to most studies, males ac- counted for more deaths (60.46%) than females. Ghasemian et al. reviewed the medical files of deceased COVID-19 cases and found that their mean age was 63.36 years with a standard deviation of 15.26 years. 43% of pa- tients were under 60 years old and 42.3% of patients were in the age group of 60-80 years (20). In the present study, the mean age of the patients was 67 and their median age was 68 years. 71.7% of patients were over 60 years old. In the age range of 60-69 years, total death count equaled 25.6%. During our study, the top five mortality peaks occurred. The fifth peak occurred from July 7, 2021 until September 20, 2021, in which 1042 COVID-19 patients died (a daily aver- age mortality rate of 17.31 patients/day). In the twenty- third epidemiological report of COVID-19 disease in Fars province, published by Shiraz University of Medical Sciences, five peaks in mortality rate due to coronavirus were reported. The second and fifth peaks were more extensive, which con- form with our study (21). The results of a study conducted in Canada indicated that in the case of some medical emergencies, the mortality rate of patients admitted to the emergency room on holidays is sig- nificantly higher (22). Also, based on the results of a study conducted in Japan on 1134 patients, it was found that if the patient is admitted on workdays of the week, the prognosis of the disease will be better (23). In the present study, the mortality rate reported in the morning shifts was significantly higher compared to other shifts. In our study, COVID-19 death counts varied at various times during the day and night. According to our study, 2722 COVID-19 deaths were reported on workdays (mean 6.27 ± 6.5), while 642 deaths were con- firmed on holidays (mean 5.58 ± 6.05). This result was in con- trast to other studies and needs further investigation. According to our study, the most common patient complaint was shortness of breath. 5. Limitations Our study was a retrospective review of hospital records, in some of which data were missing, and we could not examine more detailed hypotheses. Also, the records were registered by different persons, each of which might have their own def- inition for the different concepts used in the study as well as symptoms. 6. Conclusion Based on the findings of this series, the COVID-19 mortalities were frequently observed in males, patients with mean age of 66.99 years, morning shifts, and workdays. 7. Declarations 7.1. Acknowledgments The present review is a portion of Dr. Seyed Hassan Ashrafi Shahri’s thesis, with an approved code of ethics IR.MUMS.REC.1399.242. The financial support, guidance, and advice of the Clinical Research Development Unit of Imam Reza Hospital are appreciated. 7.2. Authors’ contributions This study was designed and registered by SHAS, MJ, and MF. EP, HZM, MF, and HR participated in data collection. Data preprocess was performed by HZM and SHAS. Data analysis was performed by MF and SHAS. All authors contributed to literature review and manuscript writing as well as the revi- sions. 7.3. Funding and supports This study was supported by Mashhad University of Medical Sciences. 7.4. Conflict of interest The researchers claim no conflicts of interest. 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 A. Tavakolian et al. 4 References 1. 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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): e42 Figure 1: The frequency of death per day during the five peaks of COVID-19 referrals in the studied hospital. Figure 2: Distribution of COVID-19 mortalities based on different age groups. 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 A. Tavakolian et al. 6 Figure 3: Distribution of COVID-19 mortalities based on the different hours of the day. Figure 4: Distribution of COVID-19 mortalities based on different working shifts. 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): e42 Table 1: Baseline characteristics of deceased COVID-19 cases Variables Number * Value Age (year) Mean ± SD 3364 66.99 ± 16.97 Gender 3364 male 2034 2034 (60.46) Female 1330 1330 (39.54) Presenting sign/symptoms Fever 2340 530 (22.65) Chills 2340 212 (9.06) Cough 2340 796 (34.02) Sore throat 2340 19 (0.81) Dyspnea 2340 1737 (74.23) General weakness 2340 666 (28.46) Diarrhea 2340 26 (1.11) Nausea/vomiting 1725 61 (3.54) Headache 1725 63 (3.65) Abdominal pain 1725 37 (2.14) Smell disorder 1725 10 (0.58) Taste disorder 1725 10 (0.58) Saturation O2 < 93% 1954 1731 (88.59) Respiratory rate >23/minutes 1827 344 (18.83) Data are presented as mean ± standard deviation (SD) or frequency (%). *: number of available data. 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 Limitations Conclusion Declarations References