Case characteristics, clinical data, and outcomes of hospitalized COVID-19 patients in Qom province, Iran: a prospective cohort study

Background: The outbreak of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) dates back to December 2019 in China. Iran has been one of the most virus inicted countries of all in which the rst case of the disease was declared on 19th February, 2020 in Qom city. The aim of this study was to report demographics, signs and symptoms, laboratory ndings, therapeutic approaches, and outcomes. Methods: This observational cohort study was performed from 20 th February 2020 to 20 th July 2020. All patients were admitted due to WHO, CDC, and Iran’s National Guidelines. Their information was recorded in their medical les. Multivariable analysis was performed to assess demographics, signs and symptoms, paraclinical data, treatments, outcomes of disease, and nding the risk factors of death subject to COVID-19. Results: Of all 2468 participants, the mean age was 57.9±17.6 years and 56.8% of patients were male. The most signicant comorbidities were seen among those who have Hypertension and Diabetes Mellitus. Cough, Dyspnea, and Fever were the most frequent symptoms. 92.3% of patients received supplementary oxygen, 14.42% were admitted to ICU, and 17.2% died in hospital. The signicant risk factors of death related to COVID-19 were ageing, male gender, HTN, CHF, CVA, CKD, increasing ESR, PT, WBC, liver function tests, and decreasing Oxygen saturation. Conclusion: Incontinent results in the case of COVID-19 outcomes and death-related risk factors attribute to marked differences in demographics and health care systems. The patients with hazardous risk factors must be detected urgently and monitored closely to save more lives.

differences in demographics and health care systems. The patients with hazardous risk factors must be detected urgently and monitored closely to save more lives.

Background
Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) was discovered as an infectious pathologic agent following a widespread outbreak in Wuhan city, the capital of Hubei province of China, in December 2019. (1).
At the outset, fever and respiratory were deemed the major symptoms of this storage virus (2). As time went by, the virus caused other serious clinical manifestations ranging from asymptomatic or mild constitutional symptoms to life-threatening complications leading to hospitalization and even death (3).
The rapid spread of SARS-CoV-2 to other countries including Japan, USA, Italy, Russia, Iran, South Korea revealed that COVID-19 is a highly contagious disease in that it caused a pandemic (4).
Iran has been one of the most prone countries to the virus of all (2). It is approximately 1459370 identi ed COVID-19 patients by nasopharyngeal and oropharyngeal swabs polymerase chain reaction (PCR) test alongside with 58412 deaths (mortality rate: 4.00%) have been recorded in Iran until February 06, 2021 (3). The rst con rmed case of SARS-CoV-2 in Iran that was o cially reported belonged to Qom, a holy city in the north-central Iran, on 19th February, 2020. At the onset of coronavirus disease-2019  outburst, Qom proved to be not only the foremost city with regard to increasing number of patients and deaths among all cities in Middle East but also the source of virus transmission in this region without any and also a source of su cient and proper virus-related awareness and studies (4).
In an observational study from China, men gured the most hospitalized cases, with a median age of 56 years, a 26% intensive care unit (ICU) admission and 28% mortality rate (5). Whereas, an Iranian article reported different gures in that the mean age of 50.75 ± 19.33 years, ICU admission and mortality rate of 8% and 10.8%, respectively were recorded (6). De nitely, various information attributes to the differences between countries in population demographic data, genetic, prevalence of comorbidities, and health care systems (7). Reporting the clinical manifestations, risk factors, and outcomes of COVID-19 is essential to improve our knowledge and managerial skills related to the patients.
There was limited information to describe the characteristics and outcomes of Iranian hospitalized patients in relation to COVID-19-. This study aims to describe detailed demographics, comorbidities, signs and symptoms, paraclinical tests, therapeutic protocols, severity of disease, death risk factors, outcomes of the hospitalized patients, and the follow up of post-discharge COVID-19 cases .The data gathered from academic health care centers in Qom, Iran, at the outset of COVID-19 pandemic crisis.

Patients and study design
This prospective cohort study was conducted at four hospitals (Kamkar, Forghani, Beheshti, and Imam Reza) a liated with the Qom University of Medical Sciences. Kamkar hospital was the rst center in the Qom to admit the rst case of COVID-19 in Iran.
We prospectively traced patients who were admitted to all four hospitals from February 20 to July 20, 2020 the infectious cases were diagnosed by nasopharyngeal or oropharyngeal swab PCR tests and also chest high resolution computed tomography (HRCT) scan if indicated. All patients were admitted subject to world health organization (WHO), Centers for Disease Control and Prevention (CDC) and Iran's national guidelines. Furthermore, hypoxemia Patients received different types of therapeutic agents and respiratory facilities includednasal cannula, simple face mask, face mask with reserve bag, and intubation based on the severity of hypoxemia during hospitalization. Serious patients were admitted to ICUs while those who are required non-invasive oxygen therapy were admitted to general wards.
This cohort study was approved by the Qom University of medical sciences ethics committee (IR.MUQ.REC.1399.013). Informed contest was taken from all participants.

Data collection
Patients were con rmed based on their PCR test, HRCT-scan ndings, and clinical presentations. Second con rming PCR tests were performed on either highly suspicious clinical presentations patients or those with false-negative PCR tests coming from insu cient sample collection. There were no cases transfer among hospitals. For readmission cases, the rst admission data were recorded. The data were collected only from COVID-19 cases whose full-length hospital stay (died or discharged) was available during the study.
Two criteria including 1.O2sat≥93% without Oxygen support, and 2. Normal body temperature for 2-3 days without any anti-pyretic drugs were considered for discharging patients.
Patients' demographics, comorbidities, exposure history, signs and symptoms, vital signs, laboratory data, radiological ndings, therapeutic approaches, duration of hospitalization, and outcomes were documented in their paper medical records. Afterwards, these data were collected as the standard data collection form and then rechecked by both a physician and a statistician. In case of any disagreements, they were reassessed by a third physician. A 30-day telephone investigation of post-discharged patients was taken into account after patients' discharge. Patients were asked about the existence of symptoms, relapse of symptoms, the requirement of readmission and the occurrence of death By the telephone investigation.
Symptoms, vital signs, radiological ndings, laboratory data and type of respiratory facilities were de ned within the rst day of admission.

Procedures
All data regarding demographics, exposure history, co-morbidities, signs and symptoms, Chest HRCT-scan and laboratory ndings were collected within 24 hours of admission. Plus, concentrations of biomarkers of blood samples including complete blood count (CBC) diff, C-reactive protein (CRP), Erythrocyte sedimentation rate (ESR), high-sensitivity troponin, Serum Creatinine and liver function tests were documented. Additionally, the data with respect to therapeutic interventions including supplemental oxygen (simple face mask, face mask with reserve bag, intubation), administration of anti-viral agents, anti-bacterial agents, immunomodulatory agents, Dialysis and plasmapheresis were recorded. Finally, data from post-discharge follow up was recorded

Laboratory investigations
All diagnostic real-time reverse-transcriptase-polymerase chain-reaction (RT-PCR) tests of nasopharyngeal and oropharyngeal specimens were performed in all of these four hospitals.

Outcomes
The main outcome of this study was to de ne the rate of death and survive in hospitalized patients. The secondary outcomes were frequency of demographics, comorbidities, signs and symptoms, respiratory facilities (invasive or non-invasive), drugs, laboratory data, and their association with the severity of disease and mortality.

Statistical analysis
Descriptive statistics were regarded as mean±SD or median (interquartile range) for continuous data and frequency (percentage) for categorical data. The chi-square independent was used to determine whether there is a signi cant relationship between categorical variables. The independent t-test and Mann-Whitney U test were applied to compare differences of continuous variables between groups. Graphs including Euler diagram and Heat map were utilized to represent the relationship between groups and the different frequencies respectively.
The death outcome as the event of interest for survival analysis was considered the time interval between hospitalization and event (death or discharged) was deemed as the survival time. Discharged Patients were regarded as the censored cases. The single and multiple Cox regression were used to evaluate the single and adjusted effect of risk factors on the survival time. Adjusted model was chosen with the help of stepwise selection method with forward approach. Kaplan-Meier survival curve was applied to illustrate cumulative probability of occurring event of interest. All analyzes were performed by R 3.6.2. P-values less than 0.05 were considered as the statistically signi cant.
Results based on Iran's national guidelines, were admitted to the hospitals between February 20 and July 20, 2020. Table 1 summarized the baseline characteristics and their association with disease outcome (death or survive) and severity. The mean age of patients was 57.9 ± 17.6 years while the mean age of the dead was signi cantly higher than survivors (66.8 ± 15.0 vs 56.0 ± 17.6, p-value < 0.001). Although all age groups probable infected with SARS-CoV-2, the highest rate of infection belonged to 60-69 years age group. The mean BMI of patients was 25.4 ± 3.2 kg/m 2 of which 55.2% were overweight and obese, 1402 (56.8%) were men, 2291(92.9%) were Iranian and 2354 (95.4%) were non-smokers while 2167(87.8%) of cases were reported none or unknown history of exposure. 5.4% of cases had misused Antibiotics before admission.     19 (18 -20) 19 (18 -21) 19 (18 -20) 0.002 b 19 (18 -20) 19 (18 -21) <0 between survivor and non-survivor cases using independent t-test, b) the mean rank difference of variables between survivor and non-survivor using Mann Whitney test, and c) the relation between baseline variables and survivor/non-survivor patients using Pearson chi-squared. * Pregnancy percentage was calculated among females.
The most remarkable adverse events and outcomes of COVID-19 is presented in Table 3. Weight loss (9.3%) de ned as ≥ 5% in comparison to initial weight, myocardial injuries (   Note: Data were expressed as mean (standard deviation) and median (IQR) for symmetric and asymmetric numeric variables. Categorical variables were shown as No. (%). P-values denoted a) the comparison of mean variables between survivor and non-survivor cases using independent t-test, b) the mean rank difference of variables between survivor and non-survivor using Mann Whitney test, and c) the relation between baseline variables and survivor/non-survivor patients using Pearson chi-squared. * All deaths out of hospital were occurred between discharge patients; ** all weight loss cases are related to patients who survived. *** The denominator is the summation of CPR cases and number of deaths; **** the denominator is those who were discharged from the hospital and did not die outside the hospital for a month. ICU = intensive care unit, CVA = cerebrovascular accident, DVT = deep venous thrombosis, CPR = cardiopulmonary resuscitation On single and multiple Cox regression model, the signi cant risk factors of death due to COVID-19 like: age, gender, a number of comorbidities, symptoms, paraclinical data and treatment protocols were found, presented in detail in Appendix 1.
The analysis of the nal Cox regression model (Fig. 2) Figure 3 showed the Kaplan-Meier survival curve with the 95% con dence interval and representation of the censoring time. Accordingly, the survival probability was 0.14 and 0.12 in the two groups of 59 and 59 years, respectively, after thirty days of hospitalization.

Discussion
To the extent of our knowledge, this is the rst cohort study of COVID-19 in the case of gathered precise information from admitted patients in the rst center of SARS-CoV-19 in Iran. 2468 COVID-19 patients were admitted to four hospitals of Qom during the rst months of the Iran's COVID-19 outbreak. Our ndings provided informative and stringent demographic data, paraclinical ndings, therapeutic approaches, disease outcomes, and post-discharge follow-up in details. However, multivariable analysis were performed to de ne the risk factors of death subject to COVID-19.
The majority of patients were men having the mean age of 57.9 ± 17.6 years and hypertension and diabetes, nearly half of which had Upper than normal weight, which was in line with China (8) and USA pattern (5). The most prevalent symptoms were dyspnea(78.8%), cough (75.7%), and fever (58.3%), which are consistent with Ashraf et al (2) and Guan et al (9). These data may represent fever as a minor symptom of COVID-19, whilst cough and dyspnea are major ones. 92.3% of patients received respiratory facilities while 14.42% of whom were admitted to ICU. In the course of the study, 17.2% and 1.2% of patients died in hospital and out of hospital, respectively, which is similar to Germany and France (7), but lower than UK with 39% of mortality (10). Surely, the inconsistency result ascribes insigni cant differences between countries in population demographic data and health care systems. The mortality rate was reported 2.3% at the onset of COVID-19 epidemic (11). This controversy may result from investigating the patients until 30-days after discharge, and just admitted patients were participated.
356 (14.42%) out of 2468 participants were critically ill and admitted to ICU, which is similar to reports from china (9,12), Italy (13), and New York City (14). 92.3% of patients required respiratory facilities which is consistent with Italy reports, but it is higher than China (8,9,12,15), New York (14), and Washington state (16). These high rates of critically ill patients requiring respiratory support and ICU admission, emphasizes the severity of the disease in  (14). The abnormal level of Prothrombin might result from procoagulant state in COVID-19 (17). Abnormal serum Creatinine levels might be secondary to direct kidney injury or uid imbalance, and also higher levels of WBC might be a clue of bacterial super-infection.
Similarly to data from China (12) and Italy (18), Hypertension was associated with poor in-hospital outcomes. In consistent with CVA as a risk factor of death in our study, an analysis of Aggawal G et al revealed a 2.5-fold increase in severity of COVID-19 illness among patients with underlying cerebrovascular disease (19).
55.2% of admitted patients were overweight while critically deceased cases had higher BMI mean in comparison with the survivors. These data are similar to UK (20) and USA (14), where obesity has been related with higher rates of ICU admission and mortality. Although obesity is an exacerbating factor for many diseases including HTN, DM, CVA, liver and renal dysfunctions, con rming studies needs to be performed to approve that association.
Non-survivors had higher range of Blood pressure, Temperature, Pulse rate, Respiratory rate, and lower Oxygen saturation compared to These ndings illustrates that patients' abnormal vital signs might be prognostic factors of severity.
Anti-viral agents were administered to all patients. Lopinavir/Ritonavir and Remdisivir played a signi cant role in patients' survival. Ashraf et al reported the positive effect of Kaletra on patients' outcomes (2). It should be noted that the US National Institute of Allergy and Infectious Diseases approved an emergency administration of Remdesivir for critical cases of COVID-19 inpatients. The e cacy of administrating Hydroxychlorquine with respect to COVID-19 patients remains to be understood. The revealed information from the USA have not disclosed the bene cial effect of Hydroxychlorquine for COVID-19 inpatients (21). Interferon was one of the immunomodulators with remarkable effects on COVID-19 patients' survival in our study. Interferons (IFN) strengthen the immune system by antiviral and immunomodulatory activities (22). Nile et al reported the bene ts of IFNs against SARS-CoV-2, alone or in combination with the other anti-viral agents (23).The most challenging therapeutic agent would be Plasmaphresis, which increases the hazard of death on the contrary with other studies in which it has reported the bene cial effect of a COVID-19 convalescent plasma transfusion on the treatment of critically ill COVID-19 cases through neutralization of SARS-CoV-2 and inhibition of cytokine storm (24)(25)(26). However, we evaluated this effect beside other co-factors, and just 1.1% of the participants underwent Plasmaphresis, therefore, it requires further studies with larger study population.
One of the most striking features of this study would be a 30-day post-discharge follow-up indicated 6.0% readmission, 1.2% post-discharge death, the median of 14 days of recovery of symptoms, and existence of symptoms in 5.3% of patients after 30 days of discharge. Similarly, Ashraf et al reported 8.6% of readmission and 4.3% of death after discharge (2). These data emphasizes the symptoms relapse and the importance of close follow-up after discharge.

Conclusion
To our knowledge, this study is the rst study of COVID-19 with detailed information of participants in Qom, the main source of SARS-CoV-19 transmission in the Middle-East.
To wrap up, various outcomes of COVID-19 among different countries attribute to different demographic data and health care systems. This disease has the potential to aggravate with regard to identi ed risk factors. As a result, atrisk patients need to be looked after speci cally in favor of saving more lives.  Kaplan-Meier based survival curve according to hospital admission due to COVID-19 among two age groups.

Supplementary Files
This is a list of supplementary les associated with this preprint. Click to download. Appendix1.docx