Journal of Occupational
Health and Epidemiology
Rafsanjan university Of medical sciences
Volume 12, Issue 1 (Winter 2023)
J Occup Health Epidemiol 2023, 12(1): 18-27 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Shabestan R, Amani B, Amani B, Khorramnia S, Zareei S, Parsaie M R, et al . Epidemiological Characteristics of COVID-19 Patients in Mazandaran, Iran, 2021. J Occup Health Epidemiol 2023; 12 (1) :18-27
URL: http://johe.rums.ac.ir/article-1-568-en.html
URL: http://johe.rums.ac.ir/article-1-568-en.html
Related article in
Google Scholar
Google Scholar
Similar articles
Rouhollah Shabestan *1 
, Bahman Amani2 , Behnam Amani2 , Saeed Khorramnia3 , Sara Zareei4 , Mohammad Reza Parsaie5 , Hormoz Kianian6 , Ali Charkameh6 , Arash Akbarzadeh7
, Bahman Amani2 , Behnam Amani2 , Saeed Khorramnia3 , Sara Zareei4 , Mohammad Reza Parsaie5 , Hormoz Kianian6 , Ali Charkameh6 , Arash Akbarzadeh7
1- M.Sc in Epidemiology, Dept. of Biostatistics and Epidemiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. , r-shabestan@alumnus.tums.ac.ir
2- M.Sc in Health Technology Assessment, Dept. of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
3- Assistant Prof., Dept. of Anesthesiology, School of Medicine, Rafsanjan University of Medical Sciences, Rafsanjan, Iran.
4- M.Sc in Biochemistry, Dept. of Cell & Molecular Biology, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran.
5- MD, Health Deputy, Mazandaran University of Medical Sciences, Sari, Iran.
6- B.Sc in Public Health, Health Deputy, Mazandaran University of Medical Sciences, Sari, Iran.
7- M.Sc in Biostatistics, Dept. of Biostatistics and Epidemiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
2- M.Sc in Health Technology Assessment, Dept. of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
3- Assistant Prof., Dept. of Anesthesiology, School of Medicine, Rafsanjan University of Medical Sciences, Rafsanjan, Iran.
4- M.Sc in Biochemistry, Dept. of Cell & Molecular Biology, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran.
5- MD, Health Deputy, Mazandaran University of Medical Sciences, Sari, Iran.
6- B.Sc in Public Health, Health Deputy, Mazandaran University of Medical Sciences, Sari, Iran.
7- M.Sc in Biostatistics, Dept. of Biostatistics and Epidemiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Article history
Received: 2022/03/12
Accepted: 2023/01/25
ePublished: 2023/03/27
Accepted: 2023/01/25
ePublished: 2023/03/27
Subject:
Epidemiology
Full-Text [PDF 514 kb]
(461 Downloads)
| Abstract (HTML) (1192 Views)
Table 1. Epidemiological features of patients with COVID-19 in Mazandaran province, Iran, 2021
Fig.1. The overall flow chart of the screening process
Fig. 2. Monthly morbidity and mortality cases in patients with COVID-19 in Mazandaran, Iran, 2021
Table 3. Morbidity and mortality cases by gender in Mazandaran province, Iran, 2021
Full-Text: (94 Views)
Introduction
In late December 2019, an unknown pneumonia disease was reported in Wuhan, China, for the first time [1-3]. This newly appeared infection, later called Covid-19, has now led to a global health emergency caused by a new type of coronavirus (SARS-CoV-2) [4]. COVID-19 is the third epidemic caused by coronaviruses in the last two decades, after SARS (Severe Acute Respiratory Syndrome) in 2002-2003 and MERS (Middle East Respiratory Syndrome-related coronavirus) in 2012 [5].
Compared with SARS and MERS, SARS-CoV-2 spreads more rapidly [6] among humans [7-10] and shows subsequent higher mortality and case fatality rates (CFR) different from country to country [11]. In this regard, hospital mortality has been reported in Egypt at 11.2% [12], Algeria at 15%, Netherlands at 11.35%, Qatar at 0.17%, Singapore at 0.2%, and the United Arab Emirates at 0.6%[13]. Moreover, crude CFR in Italy, China, Canada, and the United States were 3.2%, 7.2%, 4.9%, and 5.4%, respectively, while adjusted CFR in Canada and the USA were 5.5% and 6.1% on April 22, 2020 [14, 15], respectively.
In particular, there exist reports of CFR in Middle east countries: Egypt (7.1%), Iran (6.3%), Iraq (4.9%), Lebanon (3.4%), Pakistan (2.1%), Saudi Arabia (0.8%), United Arab Emirates 0.7%, Qatar (0.1%), and Kuwait (0.7%). Moreover, it has been established that Iran (76.3%) and Iraq (69.4 %) had the highest recovery rate in this region, followed by Pakistan (22.5%), the United Arab Emirates (19.2%), and Saudi Arabia (13.6%) [16].
COVID-19 is manifested in fever, dry cough, myalgia, fatigue, dyspnea, headache, and anorexia [17-19], with fever as the most frequent manifestation [20]. Multiple organ failure including renal [21], liver [22], and testicular tissue [21] damages are also seen in patients, and some cases show gastrointestinal symptoms such as [23-26] anorexia, diarrhea, abdominal pain, and nausea/vomiting [27]. Moreover, tinnitus, gingivitis, sudden hearing loss, Bell’s palsy, hoarseness [28], loss of smell, taste, hearing loss, and conjunctivitis problems [29, 30] have been barely reported. Hospitalized patients with COVID-19 may end up with stroke [31], cardiac injury [32, 33], thrombotic complications [34], and liver injury [35]. Since the global outbreak of COVID-19, various therapeutic options have been developed for treating COVID-19 [36-38]. Epidemiological studies play an essential role in identifying the factors that contribute to an infection and disease, including risk factors or protective factors related to the health status of the individual or population [39, 40]. Thus, this study was conducted to determine the epidemiological features of COVID-19 patients in the Mazandaran province.
Materials and Methods
The present descriptive study was performed in Mazandaran province, Iran, between February 20, 2020, and February 20, 2021. Data were collected from electronic medical records of 39 hospitals in
17 cities. The inclusion criteria were: 1) positive reverse transcription-polymerase chain reaction (RT-PCR) diagnostic test (of pharyngeal specimens). Infected patients were diagnosed according to national guidelines for the diagnosis and treatment of COVID-19; 2) Complete and available epidemiological, clinical, and outcome information. All patients' data remained confidential.
This study's variables included age, sex, symptoms and signs, underlying diseases, mortality and survival percent, treatments, and radiological findings. This study was approved by the ethics committee of Mazandaran University of Medical Sciences, Mazandaran, Iran, with the ethical code number of IR.MAZUMS..REC.1399.8260.
Descriptive analysis of the collected data was performed as mean (±SD: standard deviation) for continuous variables. Also, frequency, and percent were used for discrete variables. For categorized variables, Chi-square and Fisher's exact test were used. All analyzes were performed at a significance level of 5% using Statistical Package for Social Sciences (SPSS Inc., Chicago, Illinois, USA) version 24.0.
Results
Among 34036 patients admitted due to Covid-19, 12977 patients diagnosed by other clinical techniques but PCR tests and 53 patients with insufficient data were excluded from the final samples with the remaining 21007 patients. The epidemiological features of patients with COVID-19 are shown in Table 1. The patients comprised 48.6% of males and 51.4% of females, with a ratio of 0.94. The mean age was 55.79 ± 18.23 years, with 56.41 ± 18.86 years and 55.21 ± 17.59 years for males and females, respectively. Most cases were in the age group 60-70 (19.9%) years, and the lowest of cases were in the age group 10-20 (0.8%) years.
The mean age of death was 68.54± 15.51 years; this quantity was 69.46 ± 15.71 years for males and 67.49 ± 15.22 years for females. The overall mortality was 2431 (11.6%), and the number of male mortality was higher, 1292 (53.1%), compared to females 1139 (46.9%). The frequency of morbidity, however, was higher in women than men (Table 1). Moreover, the highest mortality rate was observed among the age group of 70-80 (26.2%).
In late December 2019, an unknown pneumonia disease was reported in Wuhan, China, for the first time [1-3]. This newly appeared infection, later called Covid-19, has now led to a global health emergency caused by a new type of coronavirus (SARS-CoV-2) [4]. COVID-19 is the third epidemic caused by coronaviruses in the last two decades, after SARS (Severe Acute Respiratory Syndrome) in 2002-2003 and MERS (Middle East Respiratory Syndrome-related coronavirus) in 2012 [5].
Compared with SARS and MERS, SARS-CoV-2 spreads more rapidly [6] among humans [7-10] and shows subsequent higher mortality and case fatality rates (CFR) different from country to country [11]. In this regard, hospital mortality has been reported in Egypt at 11.2% [12], Algeria at 15%, Netherlands at 11.35%, Qatar at 0.17%, Singapore at 0.2%, and the United Arab Emirates at 0.6%[13]. Moreover, crude CFR in Italy, China, Canada, and the United States were 3.2%, 7.2%, 4.9%, and 5.4%, respectively, while adjusted CFR in Canada and the USA were 5.5% and 6.1% on April 22, 2020 [14, 15], respectively.
In particular, there exist reports of CFR in Middle east countries: Egypt (7.1%), Iran (6.3%), Iraq (4.9%), Lebanon (3.4%), Pakistan (2.1%), Saudi Arabia (0.8%), United Arab Emirates 0.7%, Qatar (0.1%), and Kuwait (0.7%). Moreover, it has been established that Iran (76.3%) and Iraq (69.4 %) had the highest recovery rate in this region, followed by Pakistan (22.5%), the United Arab Emirates (19.2%), and Saudi Arabia (13.6%) [16].
COVID-19 is manifested in fever, dry cough, myalgia, fatigue, dyspnea, headache, and anorexia [17-19], with fever as the most frequent manifestation [20]. Multiple organ failure including renal [21], liver [22], and testicular tissue [21] damages are also seen in patients, and some cases show gastrointestinal symptoms such as [23-26] anorexia, diarrhea, abdominal pain, and nausea/vomiting [27]. Moreover, tinnitus, gingivitis, sudden hearing loss, Bell’s palsy, hoarseness [28], loss of smell, taste, hearing loss, and conjunctivitis problems [29, 30] have been barely reported. Hospitalized patients with COVID-19 may end up with stroke [31], cardiac injury [32, 33], thrombotic complications [34], and liver injury [35]. Since the global outbreak of COVID-19, various therapeutic options have been developed for treating COVID-19 [36-38]. Epidemiological studies play an essential role in identifying the factors that contribute to an infection and disease, including risk factors or protective factors related to the health status of the individual or population [39, 40]. Thus, this study was conducted to determine the epidemiological features of COVID-19 patients in the Mazandaran province.
Materials and Methods
The present descriptive study was performed in Mazandaran province, Iran, between February 20, 2020, and February 20, 2021. Data were collected from electronic medical records of 39 hospitals in
17 cities. The inclusion criteria were: 1) positive reverse transcription-polymerase chain reaction (RT-PCR) diagnostic test (of pharyngeal specimens). Infected patients were diagnosed according to national guidelines for the diagnosis and treatment of COVID-19; 2) Complete and available epidemiological, clinical, and outcome information. All patients' data remained confidential.
This study's variables included age, sex, symptoms and signs, underlying diseases, mortality and survival percent, treatments, and radiological findings. This study was approved by the ethics committee of Mazandaran University of Medical Sciences, Mazandaran, Iran, with the ethical code number of IR.MAZUMS..REC.1399.8260.
Descriptive analysis of the collected data was performed as mean (±SD: standard deviation) for continuous variables. Also, frequency, and percent were used for discrete variables. For categorized variables, Chi-square and Fisher's exact test were used. All analyzes were performed at a significance level of 5% using Statistical Package for Social Sciences (SPSS Inc., Chicago, Illinois, USA) version 24.0.
Results
Among 34036 patients admitted due to Covid-19, 12977 patients diagnosed by other clinical techniques but PCR tests and 53 patients with insufficient data were excluded from the final samples with the remaining 21007 patients. The epidemiological features of patients with COVID-19 are shown in Table 1. The patients comprised 48.6% of males and 51.4% of females, with a ratio of 0.94. The mean age was 55.79 ± 18.23 years, with 56.41 ± 18.86 years and 55.21 ± 17.59 years for males and females, respectively. Most cases were in the age group 60-70 (19.9%) years, and the lowest of cases were in the age group 10-20 (0.8%) years.
The mean age of death was 68.54± 15.51 years; this quantity was 69.46 ± 15.71 years for males and 67.49 ± 15.22 years for females. The overall mortality was 2431 (11.6%), and the number of male mortality was higher, 1292 (53.1%), compared to females 1139 (46.9%). The frequency of morbidity, however, was higher in women than men (Table 1). Moreover, the highest mortality rate was observed among the age group of 70-80 (26.2%).
Table 1. Epidemiological features of patients with COVID-19 in Mazandaran province, Iran, 2021
| Variable | Total (%) (n=21007) |
Death (%) (n=2431) |
Live (%) (n=18576) |
|
| Age (Year) |
0-10 | 305(1.5) | 3(0.1) | 302(1.6) |
| 10-20 | 168(0.8) | 8(0.3) | 160(0.9) | |
| 20-30 | 944(4.5) | 34(1.4) | 910(4.9) | |
| 30-40 | 2799(13.3) | 94(3.9) | 2705(14.6) | |
| 40-50 | 3432(16.3) | 140(5.8) | 3292(17.7) | |
| 50-60 | 4082(19.4) | 312(12.8) | 3770(20.3) | |
| 60-70 | 4173(19.9) | 579(23.8) | 3594(19.3) | |
| 70-80 | 3036(14.5) | 636(26.2) | 2400(12.9) | |
| 80 | 2068(9.8) | 625(25.7) | 1443(7.8) | |
| p-value* | <0.001 | <0.001* | <0.001 | |
| Sex |
Female | 10788(51.4) | 1139(46.9) | 9649(51.9) |
| Male | 10219(48.6) | 1292(53.1) | 8927(48.1) | |
| p-value* | <0.001 | 0.002 | <0.001 | |
| Underlying Disease |
Without background disease | 9639(45.88) | 1151(47.35) | 8487(45.69) |
| Cancer | 160(0.76) | 24(0.99) | 136(0.73) | |
| Chronic heart disease | 1840(8.76) | 166(6.83) | 1674(9.01) | |
| Chronic blood | 133(0.63) | 15(0.62) | 118(0.64) | |
| Chronic kidney | 242(1.15) | 43(1.77) | 199(1.07) | |
| Chronic pulmonary disease | 387(1.84) | 68(2.80) | 318(1.71) | |
| immunodeficiency disorders | 157(0.75) | 12(0.49) | 145(0.78) | |
| Diabetes | 1872(8.91) | 205(8.43) | 1666(8.97) | |
| Hypertension | 1342(6.39) | 119(4.90) | 1223(6.58) | |
| Chronic neurological disease | 330(1.57) | 41(1.69) | 289(1.56) | |
| Chronic Liver | 63(0.30) | 7(0.29) | 56(0.30) | |
| Severe obesity | 51(0.24) | 7(0.29) | 44(0.24) | |
| Pregnancy | 129(0.61) | 19(0.78) | 110(0.59) | |
| Diabetes and Hypertension | 1085(5.16) | 84(3.46) | 1001(5.39) | |
| Chronic heart disease and Hypertension | 543(2.58) | 59(2.43) | 484(2.61) | |
| Chronic heart disease and Diabetes | 705(3.36) | 108(4.44) | 597(3.21) | |
| Diabetes Hypertension, and Chronic heart disease | 530(2.52) | 49(2.02) | 481(2.59) | |
| Chronic kidney and Diabetes | 93(0.44) | 14(0.58) | 79(0.43) | |
| Chronic kidney and Hypertension | 71(0.34) | 10(0.41) | 61(0.33) | |
| Chronic kidney and Chronic heart disease | 81(0.39) | 15(0.62) | 66(0.36) | |
| Chronic pulmonary disease and Diabetes | 66(0.31) | 7(0.29) | 59(0.32) | |
| Chronic pulmonary disease and Hypertension | 57(0.27) | 7(0.29) | 50(0.27) | |
| Chronic pulmonary disease and Chronic heart disease | 103(0.49) | 21(0.86) | 82(0.44) | |
| Chronic neurological disease and Diabetes | 59(0.28) | 10(0.41) | 49(0.26) | |
| Chronic neurological disease and Hypertension | 57(0.27) | 11(0.45) | 46(0.25) | |
| Chronic neurological disease and Chronic heart disease | 41(0.20) | 7(0.29) | 34(0.18) | |
| Several diseases | 1160(5.52) | 149(6.13) | 1011(5.44) | |
| Other | 14(0.07) | 3(0.12) | 11(0.06) | |
| Symptoms | Fever | 9025(43.00) | 961(39.53) | 8064(43.41) |
| Sore throat | 3771((18.00) | 327(13.45) | 3444(18.54) | |
| Difficult breathing | 2311(11.00) | 149(6.13) | 2162(11.64) | |
| Hemoptysis | 5911(28.10) | 537(22.09) | 5374(28.93) | |
| Chest pain | 945(4.50) | 96(3.95) | 849(4.57) | |
| Low blood pressure | 3626(17.30) | 395(16.25) | 3231(17.39) | |
| Treatment | Standard of care (SOC) | 8381(39.90) | 858(35.29) | 7523(45.50) |
| Antiretroviral Therapy | 1005(4.78) | 124(5.10) | 881(4.74) | |
| Antibiotic Therapy | 6804(32.39) | 815(33.53) | 5989(32.24) | |
| Combination therapy | 4083(19.44) | 546(22.46) | 3537(19.04) | |
| Antimalarial | 734(3.49) | 88(3.62) | 646(3.48) | |
* Chi-square; ** Fisher`s exact test
The screening process of admitted patients is shown in Fig. 1. The most common symptoms in patients were fever (43%), followed by hemoptysis (28.10%), sore throat (18%), difficulty breathing (11%), and low blood pressure (17.30%). The least common symptom was chest pain (4.50%).
Fig.1. The overall flow chart of the screening process
The result showed that diabetes (8.91%), chronic heart disease (8.76%), hypertension (6.39%), chronic pulmonary disease (1.84%), chronic kidney disease (1.15%), chronic neurological disease (1.57%) were the most frequent underlying diseases. Some patients also had coincident diseases, among which diabetes and hypertension (5.16%), chronic heart disease and hypertension (2.58%), chronic heart disease and diabetes (3.36%), diabetes and hypertension and chronic heart disease (2.52%), and several diseases (5.52%) were the most prevalent ones.
The assessment of clinical records showed that most of the deaths occurred in cases with no clinical background. Among the underlying disease, the highest mortality rate belonged to patients with diabetes (8.43%), while chronic liver (0.29%) and severe obesity (0.29%) conditions caused the lowest mortality. This suggests the probable high and low potentials of diabetes as long as liver and obesity in death rate, respectively. It was also observed that the risk of death in diabetes patients with other underlying diseases like hypertension, hypertension and chronic heart disease, chronic kidney, and chronic pulmonary disease was lower than in diabetes. This matter is true for hypertension and chronic pulmonary disease simultaneously with another condition (Table 1).
The symptom was the next clinical manifestation monitored and recorded to evaluate its probable relationship with the death rate. The results showed that patients with fever (39.53%) had the highest mortality rate, and the least mortality rate was related to Chest pain (3.95%). Regarding the therapeutic approaches, most patients received treatments based on Standard of Care (SOC) guidelines (39.90%) followed by antibiotic therapy (32.39%) and Combination therapy (19.44%), all of which showed the highest mortality values suggesting their ineffective prescription in COVID-19. On the other hand, antiretroviral (4.78%) and antimalarial (hydroxychloroquine) (3.49%) therapies seemed to successfully prevent the death toll as their lower levels of mortality rate indicate.
The assessment of clinical records showed that most of the deaths occurred in cases with no clinical background. Among the underlying disease, the highest mortality rate belonged to patients with diabetes (8.43%), while chronic liver (0.29%) and severe obesity (0.29%) conditions caused the lowest mortality. This suggests the probable high and low potentials of diabetes as long as liver and obesity in death rate, respectively. It was also observed that the risk of death in diabetes patients with other underlying diseases like hypertension, hypertension and chronic heart disease, chronic kidney, and chronic pulmonary disease was lower than in diabetes. This matter is true for hypertension and chronic pulmonary disease simultaneously with another condition (Table 1).
The symptom was the next clinical manifestation monitored and recorded to evaluate its probable relationship with the death rate. The results showed that patients with fever (39.53%) had the highest mortality rate, and the least mortality rate was related to Chest pain (3.95%). Regarding the therapeutic approaches, most patients received treatments based on Standard of Care (SOC) guidelines (39.90%) followed by antibiotic therapy (32.39%) and Combination therapy (19.44%), all of which showed the highest mortality values suggesting their ineffective prescription in COVID-19. On the other hand, antiretroviral (4.78%) and antimalarial (hydroxychloroquine) (3.49%) therapies seemed to successfully prevent the death toll as their lower levels of mortality rate indicate.
Fig. 2. Monthly morbidity and mortality cases in patients with COVID-19 in Mazandaran, Iran, 2021
Table 2. Mortality of patients with COVID-19 by ward in Mazandaran province, Iran, 2021
| Place of death | Number of Cases | Percent |
| ICU | 2803 | 85.7 |
| CCU | 80 | 3.3 |
| Infectious | 85 | 3.5 |
| Internal | 109 | 4.5 |
| Emergency | 35 | 1.4 |
| Outside the hospital | 14 | 0.6 |
| Other (gastroenterology, NICU, PICU) | 25 | 1.0 |
| Total | 2431 | 100 |
Our results showed that the highest morbidity of Covid-19 occurred in cold months, July, January, December, and February, during the one year. Also, Monthly mortality was higher in January, August, and July. The assessment of the place of death showed that the highest mortality occurred in the intensive care unit (ICU), with a mortality rate of 85.7% (Table 2(. The morbidity and mortality cases were reported for each city and by gender in Table 3. The highest rate of mortality and morbidity was 19 in Sari City.
Table 3. Morbidity and mortality cases by gender in Mazandaran province, Iran, 2021
| City | Population | Morbidity | Mortality | ||||||
| Total | Male | Female | Total (Per 10000) | Male (Per 10000) | Female (Per 10000) | Total (Per 10000) | Male (Per 10000) | Female (Per 10000) | |
| Amol | 411221 | 208516 | 202700 | 4189 (101.87) | 1723 (82.63) | 2466 (121.66) | 366 (8.90) | 105 (5.04) | 261 (12.88) |
| Babolsar | 145176 | 73231 | 71945 | 187 (12.88) | 76 (10.38) | 111 (15.43) | 22 (1.52) | 11 (1.50) | 11 (1.53) |
| Behshahr | 168978 | 84868 | 84110 | 1840 (108.89) | 973 (114.65) | 867 (103.08) | 234 (13.85) | 159 (18.73) | 75 (8.92) |
| Tonekabon | 162155 | 81548 | 80605 | 992 (61.18) | 498 (61.07) | 494 (61.29) | 92 (5.67) | 30 (3.68) | 62 (7.69) |
| Juybar | 81666 | 41744 | 39921 | 323 (39.55) | 137 (32.82) | 186 (46.59) | 36 (4.41) | 29 (6.95) | 7 (1.75) |
| Chalus | 103237 | 51691 | 51546 | 973 (34.25) | 458 (88.60) | 515 (99.91) | 148 (14.34) | 67 (12.96) | 81 (15.71) |
| Ramsar | 75306 | 37772 | 37534 | 846 (112.34) | 380 (100.60) | 466 (124.15) | 129 (17.13) | 60 (15.88) | 69 (18.38) |
| Sari | 514757 | 258436 | 256316 | 5001(97.15) | 2376 (91.94) | 2625 (102.41) | 612 (11.89) | 385 (14.90) | 227 (8.86) |
| Savadkuh | 33160 | 16729 | 16431 | 479 (144.45) | 241 (114.06) | 238 (144.85) | 44 (13.27) | 3 (1.79) | 41 (24.95) |
| Abbasabad | 53957 | 27806 | 26151 | 108 (20.02) | 81 (29.13) | 27 (10.32) | 33 (6.12) | 29 (10.43) | 4 (1.53) |
| Fereydunkenar | 63838 | 32574 | 31263 | 473 (74.09) | 252 (77.36) | 221 (70.69) | 66 (10.34) | 55 (16.88) | 11 (3.52) |
| Qaem Shahr | 308165 | 154289 | 153872 | 3291 (106.79) | 1699 (110.12) | 1592 (103.46) | 386 (12.53) | 208 (13.48) | 178 (11.57) |
| Galugah | 38381 | 19354 | 19027 | 99 (25.79) | 51 (26.35) | 48 (25.23) | 9 (2.34) | 6 (3.10) | 3 (1.58) |
| Mahmudabad | 102607 | 52201 | 50406 | 344 (33.53) | 183 (35.06) | 161 (31.94) | 60 (5.85) | 43 (8.24) | 17 (3.37) |
| Neka | 116846 | 58749 | 58097 | 644 (55.12) | 353 (60.09) | 291 (50.09) | 76 (6.50) | 44 (7.49) | 32 (5.51) |
| Nur | 122956 | 62270 | 60686 | 665 (54.08) | 348 (55.89) | 317 (52.24) | 66 (5.37) | 39 (6.26) | 27 (4.45) |
| Nowshahr | 131596 | 66376 | 65220 | 553 (42.02) | 390 (58.76) | 163 (24.99) | 52 (3.95) | 19 (2.86) | 33 (5.06) |
Discussion
This study aimed to evaluate the risk of COVID-19 mortality and the involved factors using one-year clinical records of more than 21000 COVID-19 patients from 39 hospitals in 21 cities in the north of Iran.
Based on the results, the estimated case fatality rate in hospitalized cases was approximately 11.6%, consistent with the previously reported range of 4% to 15.4% in Iranian populations and [41-47] and the highest mortality rate of 15.4% in northeast Iran [45]. One reason for the different mortality rates might be the smaller sample size of previous studies. To date, the largest sample size of 8252 was studied by Zali et al. [46] in Tehran, with a mortality rate of 13.52% which is also in line with our findings.
In our study, a significant association was observed between greater age and increased mortality risk in COVID-19 patients. The highest mortality rate was observed in the age group of 70-80. Similar to our findings, a large cohort study showed that patients ≥75 years old were at higher mortality risk than those <65 years [48]. The results of some meta-analyses [49, 50] revealed that older age is associated with higher death among hospitalized COVID-19 patients. More particularly, there was a positive correlation between Hypertension, weak immunity, poor lung function, and comorbidities that were suggested as the reasons for the increased risk of death in older COVID-19 cases [48, 49].
According to the present findings, the mortality rate in males was significantly higher than in females, consistent with some studies [51-53] in which higher death in male patients was reported. Moreover, a large-scale meta-analysis [50, 54] revealed that the male gender is a risk factor for death. This difference can be attributed to gender discrepancies in immune response [55-57] as long as biological, psychosocial, and behavioral factors [58, 59].
In the present study, the most common symptoms among hospitalized cases were fever, hemoptysis, sore throat, and difficulty breathing. The highest death was observed in patients who had a fever. In complete agreement with our results, fever has been proposed as a predictive factor of COVID-19 mortality [60], and Tharakan et al. [61] showed that there is a significant increase in the mortality rate for every 0.5 °C increase in body temperature in COVID-19 patients.
The present results showed that diabetes, hypertension, and chronic heart disease were significantly associated with more deaths in COVID-19 patients. These findings are supported by other studies conducted on primary and secondary data [49, 62-66] and the meta-analysis by Corona et al. [67], in which diabetes was the most prevalent comorbidity associated with COVID-19 deaths. In these patients, an increased death rate seems to be connected with decreased lymphocyte count, lactate dehydrogenase, hsCRP, and interleukin levels [68]. Although some studies proved that diabetic patients receiving insulin are at higher risk of exacerbation of the disease and death [69, 70], other studies showed that controlling blood glucose reduces the mortality rate of Covid-19 diabetic cases [71]. Anti-diabetic drugs such as metformin, iDPP4, and pioglitazone are beneficial for COVID-19 treatment [72].
Our results showed that ICU witnessed the highest mortality rate, the quantity of which hinges on disease severity, gender, ethnicity, age, comorbidity, blood type, respiratory support, and availability of trained staff [73]. Moreover, bacterial
and fungal nosocomial infections, which are common complications in ICU, are shown to be associated with high mortality and longer ICU stays [74]. Moreover, It is undeniable that higher ICU capacity strain causes an increase in mortality rate of Covid-19 [75].
The potential influence of the temperature was another factor that was evaluated. The results showed that both infection and mortality rate increased in the cold seasons. On one hand, there are several studies consistent with our data highlighting the reducing effect of tempresture on COVID-19 infection and death rates. Haklai et al. showed that the incidence of COVID-19 decreases as the temperature increases [76] as the same results were obtained in European countries where the spread of COVID-19 decreased between March and May [77]. Comparing various countries with different climates, it has been found that the average number of COVID-cases was lower in countries with hot weather [78]. This is corroborated by another study indicating that cold countries, despite of having improved economic and social parameters, experienced higher prevalence of COVID-19 and rapid outbreak of the disease is associated with moderate high and low tempreatures [79]. on the other hand, several studies showed that there is no evidence that the number of COVID-19 cases decreases in warm seasons [80, 81] particularly in Iran [82]. Therefore, the temperature-based results should be interpreted with caution.
Our study is the largest multicenter study conducted in Iran on the mortality rate and its risk factors. There are several limitations to our study. Due to insufficient laboratory data, we could not estimate the mortality rate according to the severity of COVID-19 disease. Generalizability can be the next limitation since our study was conducted in the north of Iran and therefore our finding may fail to be generalized to the whole population in Iran.
Conclusion
Our study showed that the case fatality rate of COVID-19 was higher in northern Iran than in other regions. Therefore, greater healthcare resources and facilities would help reduce the mortality rate in this area. Older age, male gender, comorbidities such as diabetes, chronic heart disease, hypertension, and admission to ICU are significant death risk factors in hospitalized COVID-19 patients. The findings of this study would assist health policymakers in developing appropriate management strategies and stratifying the patients according to risk for giving proper treatments and nursing services.
Acknowledgement
The authors would like to appreciate the Research Committee of Mazandaran University of Medical Sciences and all the nurses, physicians, and patients who contributed to this project.
Conflict of interest: None declared.
This study aimed to evaluate the risk of COVID-19 mortality and the involved factors using one-year clinical records of more than 21000 COVID-19 patients from 39 hospitals in 21 cities in the north of Iran.
Based on the results, the estimated case fatality rate in hospitalized cases was approximately 11.6%, consistent with the previously reported range of 4% to 15.4% in Iranian populations and [41-47] and the highest mortality rate of 15.4% in northeast Iran [45]. One reason for the different mortality rates might be the smaller sample size of previous studies. To date, the largest sample size of 8252 was studied by Zali et al. [46] in Tehran, with a mortality rate of 13.52% which is also in line with our findings.
In our study, a significant association was observed between greater age and increased mortality risk in COVID-19 patients. The highest mortality rate was observed in the age group of 70-80. Similar to our findings, a large cohort study showed that patients ≥75 years old were at higher mortality risk than those <65 years [48]. The results of some meta-analyses [49, 50] revealed that older age is associated with higher death among hospitalized COVID-19 patients. More particularly, there was a positive correlation between Hypertension, weak immunity, poor lung function, and comorbidities that were suggested as the reasons for the increased risk of death in older COVID-19 cases [48, 49].
According to the present findings, the mortality rate in males was significantly higher than in females, consistent with some studies [51-53] in which higher death in male patients was reported. Moreover, a large-scale meta-analysis [50, 54] revealed that the male gender is a risk factor for death. This difference can be attributed to gender discrepancies in immune response [55-57] as long as biological, psychosocial, and behavioral factors [58, 59].
In the present study, the most common symptoms among hospitalized cases were fever, hemoptysis, sore throat, and difficulty breathing. The highest death was observed in patients who had a fever. In complete agreement with our results, fever has been proposed as a predictive factor of COVID-19 mortality [60], and Tharakan et al. [61] showed that there is a significant increase in the mortality rate for every 0.5 °C increase in body temperature in COVID-19 patients.
The present results showed that diabetes, hypertension, and chronic heart disease were significantly associated with more deaths in COVID-19 patients. These findings are supported by other studies conducted on primary and secondary data [49, 62-66] and the meta-analysis by Corona et al. [67], in which diabetes was the most prevalent comorbidity associated with COVID-19 deaths. In these patients, an increased death rate seems to be connected with decreased lymphocyte count, lactate dehydrogenase, hsCRP, and interleukin levels [68]. Although some studies proved that diabetic patients receiving insulin are at higher risk of exacerbation of the disease and death [69, 70], other studies showed that controlling blood glucose reduces the mortality rate of Covid-19 diabetic cases [71]. Anti-diabetic drugs such as metformin, iDPP4, and pioglitazone are beneficial for COVID-19 treatment [72].
Our results showed that ICU witnessed the highest mortality rate, the quantity of which hinges on disease severity, gender, ethnicity, age, comorbidity, blood type, respiratory support, and availability of trained staff [73]. Moreover, bacterial
and fungal nosocomial infections, which are common complications in ICU, are shown to be associated with high mortality and longer ICU stays [74]. Moreover, It is undeniable that higher ICU capacity strain causes an increase in mortality rate of Covid-19 [75].
The potential influence of the temperature was another factor that was evaluated. The results showed that both infection and mortality rate increased in the cold seasons. On one hand, there are several studies consistent with our data highlighting the reducing effect of tempresture on COVID-19 infection and death rates. Haklai et al. showed that the incidence of COVID-19 decreases as the temperature increases [76] as the same results were obtained in European countries where the spread of COVID-19 decreased between March and May [77]. Comparing various countries with different climates, it has been found that the average number of COVID-cases was lower in countries with hot weather [78]. This is corroborated by another study indicating that cold countries, despite of having improved economic and social parameters, experienced higher prevalence of COVID-19 and rapid outbreak of the disease is associated with moderate high and low tempreatures [79]. on the other hand, several studies showed that there is no evidence that the number of COVID-19 cases decreases in warm seasons [80, 81] particularly in Iran [82]. Therefore, the temperature-based results should be interpreted with caution.
Our study is the largest multicenter study conducted in Iran on the mortality rate and its risk factors. There are several limitations to our study. Due to insufficient laboratory data, we could not estimate the mortality rate according to the severity of COVID-19 disease. Generalizability can be the next limitation since our study was conducted in the north of Iran and therefore our finding may fail to be generalized to the whole population in Iran.
Conclusion
Our study showed that the case fatality rate of COVID-19 was higher in northern Iran than in other regions. Therefore, greater healthcare resources and facilities would help reduce the mortality rate in this area. Older age, male gender, comorbidities such as diabetes, chronic heart disease, hypertension, and admission to ICU are significant death risk factors in hospitalized COVID-19 patients. The findings of this study would assist health policymakers in developing appropriate management strategies and stratifying the patients according to risk for giving proper treatments and nursing services.
Acknowledgement
The authors would like to appreciate the Research Committee of Mazandaran University of Medical Sciences and all the nurses, physicians, and patients who contributed to this project.
Conflict of interest: None declared.
References
1. Lu H, Stratton CW, Tang YW. Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle. J Med Virol. 2020;92(4):401-2. [DOI] [PMID] [PMCID]
2. Hui DS, Azhar EI, Madani TA, Ntoumi F, Kock R, Dar O, et al. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health - The latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis. 2020;91:264-6. [DOI] [PMID] [PMCID]
3. Paules CI, Marston HD, Fauci AS. Coronavirus Infections - More Than Just the Common Cold. JAMA. 2020;323(8):707-8. [DOI] [PMID]
4. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727-33. [DOI] [PMID] [PMCID]
5. Yang Y, Peng F, Wang R, Yange M, Guan K, Jiang T, et al. The deadly coronaviruses: The 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China. J Autoimmun. 2020;109:102434. [DOI] [PMID] [PMCID]
6. Peeri NC, Shrestha N, Rahman MS, Zaki R, Tan Z, Bibi S, et al. The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned? Int J Epidemiol. 2020;49(3):717-26. [DOI] [PMID] [PMCID]
7. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. N Engl J Med. 2020;382(13):1199-207. [DOI] [PMID] [PMCID]
8. Riou J, Althaus CL. Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Euro surveill. 2020;25(4):2000058. [DOI] [PMID] [PMCID]
9. The Lancet. Emerging understandings of 2019-nCoV. Lancet. 2020;395(10221):311. [DOI]
10. Dargahi A, Gholizadeh H, Poursadeghiyan M, Hamidzadeh Arbabi Y, Hamidzadeh Arbabi MH, Hosseini J. Health - promoting behaviors in staff and students of Ardabil University of Medical Sciences. J Educ Health Promot. 2022;11:283. [DOI]
11. Elrashdy F, Redwan EM, Uversky VN. Why COVID-19 Transmission Is More Efficient and Aggressive Than Viral Transmission in Previous Coronavirus Epidemics? Biomolecules. 2020;10(9):1312 [DOI] [PMID] [PMCID]
12. Asem N, Hassany M, Taema K, Masoud H, Elassal G, Kamal E, et al. Demographic and clinical features associated with in-hospital mortality in Egyptian COVID-19 patients: A retrospective cohort study. Open Access Maced J Med Sci. 2021:21253577. [DOI]
13. Noor AU, Maqbool F, Bhatti ZA, Khan AU. Epidemiology of CoViD-19 Pandemic: Recovery and mortality ratio around the globe. Pak J Med Sci. 2020;36(COVID19-S4):S79-84. [DOI] [PMID] [PMCID]
14. Onder G, Rezza G, Brusaferro S. Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. JAMA. 2020;323(18):1775-6. [DOI] [PMID]
15. Abdollahi E, Champredon D, Langley JM, Galvani AP, Moghadas SM. Temporal estimates of case-fatality rate for COVID-19 outbreaks in Canada and the United States. CMAJ. 2020;192(25):E666-70. [DOI] [PMID] [PMCID]
16. Dil S, Dil N, Maken ZH. COVID-19 Trends and Forecast in the Eastern Mediterranean Region with a Particular Focus on Pakistan. Cureus. 2020;12(6):e8582. [DOI] [PMID] [PMCID]
17. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China. JAMA. 2020;323(11):1061-9. [DOI] [PMID] [PMCID]
18. Adhikari SP, Meng S, Wu Y-J, Mao Y-P, Ye R-X, Wang Q-Z, et al. Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: a scoping review. Infect Dis Poverty. 2020;9(1):29. [DOI] [PMID] [PMCID]
19. Soltaninejad M, Babaei-Pouya A, Poursadeqiyan M, Feiz Arefi M. Ergonomics factors influencing school education during the COVID-19 pandemic: A literature review. Work. 2021;68(1):69-75. [DOI] [PMID]
20. Hu Y, Sun J, Dai Z, Deng H, Li X, Huang Q, et al. Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis. J Clin Virol. 2020:104371. [DOI] [PMID] [PMCID]
21. Fan C, Lu W, Li K, Ding Y, Wang J. ACE2 Expression in Kidney and Testis May Cause Kidney and Testis Infection in COVID-19 Patients. Front Med (Lausanne). 2021;7:56893. [DOI] [PMID] [PMCID]
22. Chai X, Hu L, Zhang Y, Han W, Lu Z, Ke A, et al. Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV Infection. bioRxiv. 2020:2020-02. [DOI]
23. Kumar VCS, Mukherjee S, Harne PS, Subedi A, Ganapathy MK, Patthipati VS, et al. Novelty in the gut: a systematic review and meta-analysis of the gastrointestinal manifestations of COVID-19. BMJ Open Gastroenterol. 2020;7(1):e000417. [DOI] [PMID] [PMCID]
24. Parasa S, Desai M, Chandrasekar VT, Patel HK, Kennedy KF, Roesch T, et al. Prevalence of Gastrointestinal Symptoms and Fecal Viral Shedding in Patients with Coronavirus Disease 2019: A Systematic Review and Meta-analysis. JAMA Netw Open. 2020;3(6):e2011335. [DOI] [PMID] [PMCID]
25. Merola E, Armelao F, de Pretis G. Prevalence of gastrointestinal symptoms in coronavirus disease 2019: a meta-analysis. Acta Gastroenterol Belg. 2020;83(4):603-15. [PMID]
26. Poursadeqiyan M, Kasiri N, Khedri B, Ghalichi Zaveh Z, Babaei Pouya A, Barzanouni S, et al. The Fear of COVID-19 Infection one Year After Business Reopening in Iranian Society. J Health Sci Surveill Syst. 2022;10(3):284-92. [DOI]
27. Akin H, Kurt R, Tufan F, Swi A, Ozaras R, Tahan V, et al. Newly Reported Studies on the Increase in Gastrointestinal Symptom Prevalence with COVID-19 Infection: A Comprehensive Systematic Review and Meta-Analysis. Diseases. 2020;8(4):41. [DOI] [PMID] [PMCID]
28. Elibol E. Otolaryngological symptoms in COVID-19. Eur Arch Otorhinolaryngol. 2021;278(4):1233-6. [DOI] [PMID] [PMCID]
29. Pascarella G, Strumia A, Piliego C, Bruno F, Del Buono R, Costa F, et al. COVID‐19 diagnosis and management: a comprehensive review. J Intern Med. 2020;288(2):192-206. [DOI] [PMID] [PMCID]
30. Savtale S, Hippargekar P, Bhise S, Kothule S. Prevalence of Otorhinolaryngological Symptoms in Covid 19 Patients. Indian J Otolaryngol Head Neck Surg. 2022;74(Suppl 2):3378-84. [DOI] [PMID] [PMCID]
31. Oxley TJ, Mocco J, Majidi S, Kellner CP, Shoirah H, Singh IP, et al. Large-Vessel Stroke as a Presenting Feature of Covid-19 in the Young. N Engl J Med. 2020;382(20):e60. [DOI] [PMID] [PMCID]
32. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, et al. Association of Cardiac Injury with Mortality in Hospitalized Patients with COVID-19 in Wuhan, China. JAMA Cardiol. 2020;5(7):802-10. [DOI] [PMID] [PMCID]
33. Kochi AN, Tagliari AP, Forleo GB, Fassini GM, Tondo C. Cardiac and arrhythmic complications in patients with COVID‐19. J Cardiovasc Electrophysiol. 2020;31(5):1003-8 [DOI] [PMID] [PMCID]
34. Klok FA, Kruip MJHA, van der Meer NJM, Arbous MS, Gommers DAMPJ, Kant KM, et al. Incidence of thrombotic complications in critically ill ICU patients with COVID-19. Thromb Res. 2020;191:145-7. [DOI] [PMID] [PMCID]
35. Cai Q, Huang D, Yu H, Zhu Z, Xia Z, Su Y, et al. COVID-19: Abnormal liver function tests. J Hepatol. 2020;73(3):566-74. [DOI] [PMID] [PMCID]
36. Amani B, Amani B, Zareei S, Zareei M. Efficacy and safety of arbidol (umifenovir) in patients with COVID‐19: A systematic review and meta‐analysis. Immun Inflamm Dis. 2021;9(4):1197-208. [DOI] [PMID] [PMCID]
37. Amani B, Zareei S, Amani B, Zareei M, Zareei N, Shabestan R, et al. Artesunate, imatinib, and infliximab in COVID‐19: A rapid review and meta‐analysis of current evidence. Immun Inflamm Dis. 2022;10(6):e628 [DOI] [PMID] [PMCID]
38. Amani B, Zareei S, Amani B. Rapid Review and Meta‐Analysis of Adverse Events Associated with Molnupiravir in Patients with COVID‐19. Br J Clin Pharmacol. 2022;88(10):4403-11. [DOI] [PMID] [PMCID]
39. Krämer A, Kretzschmar M, Krickeberg K. Principles of Infectious Disease Epidemiology. Mod Infect Dis Epidemiol. 2010:85-99. [DOI] [PMCID]
40. Khajehnasiri F, Zaroushani V, Poursadeqiyand M. Macro ergonomics and health workers during the COVID-19 pandemic. Work. 2021;69(3):713-4. [DOI] [PMID]
41. Asghari E, Rahmani F, Hosseinzadeh M, Mahdavi N, Praskova A, Targhaq S, et al. The Clinical Characteristics of Early Cases with 2019 Novel Coronavirus Disease in Tabriz, Iran. Iran J Health Sci. 2021;9(1):1-11. [Article] [DOI]
42. Jalili Khoshnood R, Ommi D, Zali A, Ashrafi F, Vahidi M, Azhide A, et al. Epidemiological Characteristics, Clinical Features, and Outcome of COVID-19 Patients in Northern Tehran, Iran; a Cross-Sectional Study. Front Emerg Med. 2021;5(1):e11. [Article]
43. Nikpouraghdam M, Jalali Farahani A, Alishiri GH, Heydari S, Ebrahimnia M, Samadinia H, et al. Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study. J Clin Virol. 2020;127:104378 [DOI] [PMID] [PMCID]
44. Rezabeigi-Davarani E, Bokaie S, Mashayekhi V, Sharifi L, Faryabi R, Alian Samakkhah S, et al. Epidemiological and Clinical Characteristics of COVID-19 Patients Studied by Jiroft University of Medical Sciences: Southeast of Iran. J Adv Med Biomed Res. 2021;29(136):302-8. [DOI]
45. Sobhani S, Aryan R, Kalantari E, Soltani S, Malek N, Pirzadeh P, et al. Association between Clinical Characteristics and Laboratory Findings with Outcome of Hospitalized COVID-19 Patients: A Report from Northeast Iran. Interdiscip Perspect Infect Dis. 2021;2021:5552138. [DOI] [PMID] [PMCID]
46. Zali A, Gholamzadeh S, Mohammadi G, azizmohammad Looha M, Akrami F, Zarean E, et al. Baseline Characteristics and Associated Factors of Mortality in COVID-19 Patients; An Analysis of 16000 Cases in Tehran, Iran. Arch Acad Emerg Med. 2020;8(1):e70. [PMID] [PMCID]
47. Arefi MF, Babaei AP, Barzanouni S, Ebrahimi S, Salehi AR, Khajehnasiri F, et al. Risk Perception in the COVID-19 pandemic; a health promotion approach. J Educ Health Promot. 2022;11:118. [DOI] [PMID] [PMCID]
48. Ho FK, Petermann-Rocha F, Gray SR, Jani BD, Katikireddi SV, Niedzwiedz CL, et al. Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants. PLoS One. 2020;15(11):e0241824. [DOI] [PMID] [PMCID]
49. Biswas M, Rahaman S, Biswas TK, Haque Z, Ibrahim B. Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis. Intervirology. 2020:1-12. [DOI] [PMID] [PMCID]
50. Noor FM, Islam MM. Prevalence and Associated Risk Factors of Mortality Among COVID-19 Patients: A Meta-Analysis. J Community Health. 2020;45(6):1270-82. [DOI] [PMID] [PMCID]
51. Gomez JMD, Du-Fay-de-Lavallaz JM, Fugar S, Sarau A, Simmons JA, Clark B, et al. Sex Differences in COVID-19 Hospitalization and Mortality. J Womens Health (Larchmt). 2021;30(5):646-53. [DOI] [PMID]
52. Green MS, Nitzan D, Schwartz N, Niv Y, Peer V. Sex differences in the case-fatality rates for COVID-19—A comparison of the age-related differences and consistency over seven countries. Plos One. 2021;16(4):e0250523. [DOI] [PMID] [PMCID]
53. Jin JM, Bai P, He W, Wu F, Liu XF, Han DM, et al. Gender Differences in Patients with COVID-19: Focus on Severity and Mortality. Front Public Health. 2020;8:152. [DOI] [PMID] [PMCID]
54. Peckham H, de Gruijter NM, Raine C, Radziszewska A, Ciurtin C, Wedderburn LR, et al. Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission. Nat Commun. 2020;11(1):6317. [DOI] [PMID] [PMCID]
55. Bienvenu LA, Noonan J, Wang X, Peter K. Higher mortality of COVID-19 in males: sex differences in immune response and cardiovascular comorbidities. Cardiovasc Res. 2020;116(14):2197-206. [DOI] [PMID] [PMCID]
56. Takahashi T, Ellingson MK, Wong P, Israelow B, Lucas C, Klein J, et al. Sex differences in immune responses that underlie COVID-19 disease outcomes. Nature. 2020;588(7837):315-20. [DOI] [PMID] [PMCID]
57. Zhao G, Xu Y, Li J, Cui X, Tan X, Zhang H, et al. Sex differences in immune responses to SARS-CoV-2 in patients with COVID-19. Biosci Rep. 2021;41(1):BSR20202074. [DOI] [PMID] [PMCID]
58. Bronfman N, Repetto P, Cordón P, Castañeda J, Cisternas P. Gender Differences on Psychosocial Factors Affecting COVID-19 Preventive Behaviors. Sustainability. 2021;13(11):6148. [DOI]
59. Griffith DM, Sharma G, Holliday CS, Enyia OK, Valliere M, Semlow AR, et al. Men and COVID-19: A Biopsychosocial Approach to Understanding Sex Differences in Mortality and Recommendations for Practice and Policy Interventions. Prev Chronic Dis. 2020;17:E63. [DOI] [PMID] [PMCID]
60. Choron RL, Butts CA, Bargoud C, Krumrei NJ, Teichman AL, Schroeder ME, et al. Fever in the ICU: A Predictor of Mortality in Mechanically Ventilated COVID-19 Patients. J Intensive Care Med. 2021;36(4):484-93. [DOI] [PMID] [PMCID]
61. Tharakan S, Nomoto K, Miyashita S, Ishikawa K. Body temperature correlates with mortality in COVID-19 patients. Crit Care. 2020;24(1):298. [DOI] [PMID] [PMCID]
62. de Almeida-Pititto B, Dualib PM, Zajdenverg L, Dantas JR, De Souza FD, Rodacki M, et al. Severity and mortality of COVID 19 in patients with diabetes, hypertension and cardiovascular disease: a meta-analysis. Diabetol Metab Syndr. 2020;12:75. [DOI] [PMID] [PMCID]
63. Harrison SL, Fazio-Eynullayeva E, Lane DA, Underhill P, Lip GYH. Comorbidities associated with mortality in 31,461 adults with COVID-19 in the United States: A federated electronic medical record analysis. PLoS Med. 2020;17(9):e1003321. [DOI] [PMID] [PMCID]
64. Kim DW, Byeon KH, Kim J, Cho KD, Lee N. The Correlation of Comorbidities on the Mortality in Patients with COVID-19: An Observational Study Based on the Korean National Health Insurance Big Data. J Korean Med Sci. 2020;35(26):e243. [DOI] [PMID] [PMCID]
65. Posso M, Comas M, Román M, Domingo L, Louro J, González C, et al. Comorbidities and Mortality in Patients With COVID-19 Aged 60 Years and Older in a University Hospital in Spain. Arch Bronconeumol (Engl Ed). 2020;56(11):756-8. [DOI] [PMID] [PMCID]
66. Ng WH, Tipih T, Makoah NA, Vermeulen JG, Goedhals D, Sempa JB, et al. Comorbidities in SARS-CoV-2 Patients: A Systematic Review and Meta-Analysis. mBio. 2021;12(1):e03647-20. [DOI] [PMID] [PMCID]
67. Corona G, Pizzocaro A, Vena W, Rastrelli G, Semeraro F, Isidori AM, et al. Diabetes is most important cause for mortality in COVID-19 hospitalized patients: Systematic review and meta-analysis. Rev Endocr Metab Disord. 2021;22(2):275-96. [DOI] [PMID] [PMCID]
68. Hui Y, Li Y, Tong X, Wang Z, Mao X, Huang L, et al. The risk factors for mortality of diabetic patients with severe COVID-19: A retrospective study of 167 severe COVID-19 cases in Wuhan. PLoS One. 2020;15(12):e0243602. [DOI] [PMID] [PMCID]
69. Yu B, Li C, Sun Y, Wang DW. Insulin Treatment is Associated with Increased Mortality in Patients with COVID-19 and Type 2 Diabetes. Cell Metab. 2021;33(1):65-77.e2. [DOI] [PMID] [PMCID]
70. Shang J, Wang Q, Zhang H, Wang X, Wan J, Yan Y, et al. The Relationship Between Diabetes Mellitus and COVID-19 Prognosis: A Retrospective Cohort Study in Wuhan, China. Am J Med. 2021;134(1):e6-14. [DOI] [PMID] [PMCID]
71. Zhu L, She ZG, Cheng X, Qin JJ, Zhang XJ, Cai J, et al. Association of Blood Glucose Control and Outcomes in Patients with COVID-19 and Pre-Existing Type 2 Diabetes. Cell Metab. 2020;31(6):1068-77. e3. [DOI] [PMID] [PMCID]
72. Santos A, Magro DO, Evangelista-Poderoso R, Saad MJA. Diabetes, obesity, and insulin resistance in COVID-19: molecular interrelationship and therapeutic implications. Diabetol Metabol Syndr. 2021;13(1):23. [DOI] [PMID] [PMCID]
73. Gupta S, Hayek SS, Wang W, Chan L, Mathews KS, Melamed ML, et al. Factors Associated With Death in Critically Ill Patients with Coronavirus Disease 2019 in the US. JAMA Intern Med. 2020;180(11):1436-47. [DOI] [PMID] [PMCID]
74. Bardi T, Pintado V, Gomez-Rojo M, Escudero-Sanchez R, Azzam Lopez A, Diez-Remesal Y, et al. Nosocomial infections associated to COVID-19 in the intensive care unit: clinical characteristics and outcome. Eur J Clin Microbiol Infect Dis. 2021;40(3):495-502. [DOI] [PMID] [PMCID]
75. Bravata DM, Perkins AJ, Myers LJ, Arling G, Zhang Y, Zillich AJ, et al. Association of Intensive Care Unit Patient Load and Demand With Mortality Rates in US Department of Veterans Affairs Hospitals During the COVID-19 Pandemic. JAMA Netw Open. 2021;4(1):e2034266. [DOI] [PMID] [PMCID]
76. Shi P, Dong Y, Yan H, Zhao C, Li X, Liu W, et al. Impact of temperature on the dynamics of the COVID-19 outbreak in China. Sci Total Environ. 2020;728:138890. [DOI] [PMID] [PMCID]
77. Kifer D, Bugada D, Villar-Garcia J, Gudelj I, Menni C, Sudre C, et al. Effects of Environmental Factors on Severity and Mortality of COVID-19. Front Med (Lausanne). 2021;7:607786. [DOI] [PMID] [PMCID]
78. Caspi G, Shalit U, Kristensen SL, Aronson D, Caspi L, Rossenberg O, et al. Climate effect on COVID-19 spread rate: an online surveillance tool. MedRxiv. 2020. [DOI]
79. Iqbal MM, Abid I, Hussain S, Shahzad N, Waqas MS, Iqbal MJ. The effects of regional climatic condition on the spread of COVID-19 at global scale. Sci Total Environ. 2020;739:140101. [DOI] [PMID] [PMCID]
80. Prata DN, Rodrigues W, Bermejo PH. Temperature significantly changes COVID-19 transmission in (sub) tropical cities of Brazil. Sci Total Environ. 2020;729:138862. [DOI] [PMID] [PMCID]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
