Isfahan COvid-19 REgistry (I-CORE): Design and methodology

COVID-19 Breakthrough Infections Among Patients with Cancer Receiving Sinopharm BBIBP-CorV Vaccine

Background: Patients with cancer are at an increased risk of mortality from COVID-19 infection. So, they are prioritized for vaccination. However, there is limited data about the immunogenicity, safety, and effectiveness of inactivated vaccines in preventing COVID-19 infection, hospitalization, and mortality in patients with cancer. Objectives: This study aimed to report the clinical characteristics of patients who had a positive PCR test after being fully vaccinated with the Sinopharm BBIBP-CorV Vaccine. Methods: In this retrospective study, the data of patients with cancer were extracted from the electronic health records of a cancer center in Isfahan, Iran. All COVID-19 data from Isfahan province also was collected by Isfahan COVID-19 Registry (I-CORE). We described the clinical characteristics of patients with cancer who have a positive test more than 14 days after the second dose. Results: Two hundred twenty-two patients with cancer had at least one positive PCR test after the start of the COVID-19 vaccination. Of these, 9 (4.1%) breakthrough infections have occurred. Six (67%) of them had hematological malignancies. Six (67%) were hospitalized and 3 (33%) patients died. Two of them had recent chemotherapy and have hematological malignancies. Conclusions: Vaccination is a good way to protect the population from COVID-19 complications and mortality, but it should be considered that fully-vaccinated patients with cancer are at risk of severe outcomes. Nevertheless, prioritizing cancer patients, especially those with hematological malignancies, or receiving chemotherapies for booster vaccines and studying the effectiveness of each COVID-19 vaccine for patients with cancer should be considered.

Vitamin D Level in Laboratory Confirmed COVID-19 and Disease Progression

OBJECTIVE

There is no conclusive evidence to suggest vitamin D level can prevent or treat infection with the new coronavirus disease 2019. This study aimed to investigate the effects of serum level of vitamin D in patients with coronavirus disease 2019 on death, severity, and hospitalization duration.

MATERIALS AND METHODS

Baseline characteristic of patients was extracted from the Isfahan coronavirus disease 2019 registry database (I-CORE). Blood samples were taken from all patients to measure the level of vitamin D (25-hydroxyvitamin D) and categorized. The effect of 25(OH) D on death, severity, and hospitalization duration was analyzed by logistic regression.

RESULTS

Among our study patients, 5.5% had a severe deficiency of vitamin D, 23.7% deficiency, and 24.8% insufficiency. Of the 107 patients who died, 7.5% were severely deficient in vitamin D. We found that vitamin D deficiency had no significant effect on death, disease severity, and hospitalization (P > .05). However, having at least one comorbidity increased the odds of death five times after adjusting age > 60 years and gender (P < .0001). The results showed that among all comorbidities, diabetes has the greatest impact on the outcomes as it raised the odds of death, disease severity, and length of hospital stay by 2.23,1.72, and 1.48, respectively, after controlling the age > 60 and gender (P = .0002, P=.08, P=.012).

CONCLUSIONS

The mortality, disease severity, and hospitalization of coronavirus disease 2019 patients seem to be not affected by the low levels of 25(OH)D. However, the synergy between vitamin D levels and comorbidities, age, and gender could affect the outcome of coronavirus disease 2019 patients.

Sex Differences in the Relation between Comorbidities and Prognosis in Hospitalized Patients with COVID-19

Purpose. There is a lack of information of the difference in sex-aggregated prevalence of comorbid noncommunicable disease (NCD) in patients hospitalized with COVID-19 in Iran. This study aimed to evaluate sex differences in the relation between medical comorbidities and subsequent death in patients hospitalized with COVID-19. Methods. All subsequently hospitalized patients with a diagnosis of moderate to severe COVID-19 since February 19th to June 14th, 2020, in Isfahan, Iran, were recruited in the ongoing I-CORE Registry. Real-time reverse-transcription polymerase chain reaction (RT-PCR) testing was done upon admission. Data on preexisting comorbid NCDs including hypertension, coronary heart disease (CHD), diabetes mellitus (DM), cancers, chronic renal disease (CRD), and chronic respiratory disease were collected through self-reported questionnaires. Results. Overall, 12,620 individuals were enrolled in this registry of which 4,356 were positive for the COVID-19 RT-PCR test. In the whole population, in women, DM, hypertension, and CHD, and in men, DM, CHD, and hypertension were, respectively, the most frequent comorbidities. The frequency of at least one NCD did not differ between men and women, but a greater proportion of women had two or more NCDs. Increasing the number of comorbidities was associated with higher death frequency and mortality risk in the unadjusted model but remained no longer significant after adjustment for age. There was no statistically significant difference in this regard between men and women. Conclusion. Overall, we found that DM, hypertension, and CHD were the most frequent comorbidities. Although comorbidities were more frequent among women, mortality risk did not significantly differ between men and women.

The real-time reproduction number, impact of interventions and prediction of the epidemic size of COVID-19 in the center of Iran

Background:

The monitoring of reproduction number over time provides feedback on the effectiveness of interventions and on the need to intensify control efforts. Hence, we aimed to compute basic (R₀) and real-time (Rt) reproduction number and predict the trend and the size of the coronavirus disease 2019 (COVID-19) outbreak in the center of Iran.

Materials and Methods:

We used the 887 confirmed cases of COVID-19 from February 20, 2020, to April 17, 2020 in the center of Iran. We considered three scenarios for serial intervals (SIs) with gamma distribution. R_t was calculated by the sequential Bayesian and time-dependent methods. Based on a branching process using the Poisson distributed number of new cases per day, the daily incidence and cumulative incidence for the next 30 days were predicted. The analysis was applied in R packages 3.6.3 and STATA 12.0.

Results:

The model shows that the R_t of COVID-19 has been decreasing since the onset of the epidemic. According to three scenarios based on different distributions of SIs in the past 58 days from the epidemic, R_t has been 1.03 (0.94, 1.14), 1.05 (0.96, 1.15), and 1.08 (0.98, 1.18) and the cumulative incidence cases will be 360 (180, 603), 388 (238, 573), and 444 (249, 707) for the next 30 days, respectively.

Conclusion:

Based on the real-time data extracted from the center of Iran, R_t has been decreasing substantially since the beginning of the epidemic, and it is expected to remain almost constant or continue to decline slightly in the next 30 days, which is consequence of the schools and universities shutting down, reduction of working hours, mass screening, and social distancing.

Red Blood Cell Distribution Width (RDW) as a Predictor of In-Hospital Mortality in COVID-19 Patients; a Cross Sectional Study

INTRODUCTION

Red blood cell distribution width (RDW) has been introduced as a predictive factor for mortality in several critical illnesses and infectious diseases. This study aimed to assess the possible relationship between RDW on admission and COVID-19 in-hospital mortality.

METHOD

This cross-sectional study was performed using the Isfahan COVID-19 registry. Adult confirmed cases of COVID-19 admitted to four hospitals affiliated with Isfahan University of Medical Sciences in Iran were included. Age, sex, O2 saturation, RDW on admission, Intensive Care Unit admission, laboratory data, history of comorbidities, and hospital outcome were extracted from the registry. Cox proportional hazard regression was used to study the independent association of RDW with mortality.

RESULTS

4152 patients with the mean age of 61.1 ± 16.97 years were included (56.2% male). 597 (14.4%) cases were admitted to intensive care unit (ICU) and 477 (11.5%) cases died. The mortality rate of patients with normal and elevated RDW was 7.8% and 21.2%, respectively (OR= 3.1, 95%CI: 2.6-3.8), which remained statistically significant after adjusting for age, O2 saturation, comorbidities, and ICU admission (2.03, 95% CI: 1.68-2.44). Moreover, elevated RDW mortality Hazard Ratio in patients who were not admitted to ICU was higher than ICU-admitted patients (3.10, 95% CI: 2.35-4.09 vs. 1.47, 95% CI: 1.15-1.88, respectively).

CONCLUSION

The results support the presence of an association between elevated RDW and mortality in patients with COVID-19, especially those who were not admitted to ICU. It seems that elevated RDW can be used as a predictor of mortality in COVID-19 cases.

Psychological impact of COVID-19 on health-care workers: A multicenter cross-sectional study

BACKGROUND

Health-care workers (HCWs) as frontline soldiers are involved in the war against COVID-19. Not only their protection from COVID-19 is important but also their mental health is a concern. This study aimed to measure the psychological distress among HCWs in the time of COVID-19 in Isfahan, Iran.

MATERIALS AND METHODS

A cross-sectional study was conducted in the 2nd month of the spread of COVID-19 in Isfahan, Iran (March 16 to April 3). A total of 321 HCWs participated in an online survey and answered the General Health Questionnaire, the Insomnia Severity Index, and the Medical Outcomes Study Social Support Survey. t-test and ANOVA were used for comparing variables between groups. Multiple linear regression was used to evaluate the predictive factors of psychological distress.

RESULTS

About 34% of our HCWs suffer from some levels of psychological distress. The result of multiple linear regression (R 2: 0.41) shows that the predictive variables with the highest value were insomnia, working as a medical resident, and lack of social support (standardized coefficient of beta: 0.51, 0.25, and 0.16, respectively; P < 0.05).

CONCLUSION

The result of our study shows that about one-third of HCWs in COVID-19 special hospitals have some psychological problems. Being a medical resident, suffering from insomnia, and lack of social support are predictive variables.

Co-infection between the severe acute respiratory syndrome coronavirus 2 and the influenza Type B in Isfahan, Iran

Background:

Some studies have been reported the rates of co-infection between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus in the different regions. In this study, we report the co-infection rates between SARS-CoV-2 and influenza type B in Isfahan, Iran.

Materials and Methods:

All patients with a definite diagnosis of coronavirus disease 2019 (COVID-19) from Isfahan COVID-19 registry (I-core) study were enrolled from February 2020.

Results:

Of the 1639 laboratory COVID-19 confirmed in Isfahan province, only two persons were positive for Influenza B from Isfahan COVID-19 registry (I-core). Both patients were symptom-free after 3 months' follow-up.

Conclusion:

During influenza season, differentiating other causes of respiratory illness from COVID-19 is difficult, because common clinical manifestations of COVID-19 mimic those of influenza. It seems that evaluating for co-infection with different types of influenza viruses in patients with specific settings should be considered.

A study to design minimum data set of COVID-19 registry system

BACKGROUND

From the beginning of the COVID-19 pandemic, the development of infrastructures to record, collect and report COVID-19‏ ‏data has become a fundamental necessity in the world. The disease registry system can help build an infrastructure to collect data systematically. The study aimed to design a minimum data set for the COVID-19 registry system.

METHODS

A qualitative study to design an MDS for the COVID-19 registry system was performed in five phases at Ahvaz University of Medical Sciences in Khuzestan Province in southwestern Iran, 2020-2021. In the first phase, assessing the information requirements was performed for the COVID-19 registry system. Data elements were identified in the second phase. In the third phase, the MDS was selected, and in the four phases, the COVID-19 registry system was implemented as a pilot study to test the MDS. Finally, based on the experiences gained from the COVID-19 registry system implementation, the MDS were evaluated, and corrections were made.

RESULTS

MDS of the COVID-19 registry system contains eight top groups including administrative (34 data elements), disease exposure (61 data elements), medical history and physical examination (138 data elements), findings of clinical diagnostic tests (101 data elements), disease progress and outcome of treatment (55 data elements), medical diagnosis and cause of death (12 data elements), follow-up (14 data elements), and COVID-19 vaccination (19 data elements) data, respectively.

CONCLUSION

Creating a standard and comprehensive MDS can help to design any national data dictionary for COVID-19 and improve the quality of COVID-19 data.

Model Prediction for In-Hospital Mortality in Patients with COVID-19: A Case-Control Study in Isfahan, Iran

The COVID-19 pandemic has now imposed an enormous global burden as well as a large mortality in a short time period. Although there is no promising treatment, identification of early predictors of in-hospital mortality would be critically important in reducing its worldwide mortality. We aimed to suggest a prediction model for in-hospital mortality of COVID-19. In this case-control study, we recruited 513 confirmed patients with COVID-19 from February 18 to March 26, 2020 from Isfahan COVID-19 registry. Based on extracted laboratory, clinical, and demographic data, we created an in-hospital mortality predictive model using gradient boosting. We also determined the diagnostic performance of the proposed model including sensitivity, specificity, and area under the curve (AUC) as well as their 95% CIs. Of 513 patients, there were 60 (11.7%) in-hospital deaths during the study period. The diagnostic values of the suggested model based on the gradient boosting method with oversampling techniques using all of the original data were specificity of 98.5% (95% CI: 96.8-99.4), sensitivity of 100% (95% CI: 94-100), negative predictive value of 100% (95% CI: 99.2-100), positive predictive value of 89.6% (95% CI: 79.7-95.7), and an AUC of 98.6%. The suggested model may be useful in making decision to patient's hospitalization where the probability of mortality may be more obvious based on the final variable. However, moderate gaps in our knowledge of the predictors of in-hospital mortality suggest further studies aiming at predicting models for in-hospital mortality in patients with COVID-19.

The Effect of Exogenous Surfactant on Moderate and Severe Stages of COVID-19 Induced ARDS: the Pilot Study of a Clinical Trial

COVID-19 pandemic has created a global health challenge. Many pharmaceuticals have been repurposed as potential treatments, though many have not been promising. Due to the inflammatory and destructive effects of the virus on alveolar cells, the effect of exogenous surfactant was assessed as a potential treatment of lung dysfunction in COVID-19 patients. In this pilot study of the clinical trial, 49 patients aged 35-80 years with COVID-19 admitted in ICU entered the study (22 patients intubated and 23 had face masks; 4 patients in the control arm). The treatment arm patients received two consecutive doses of surfactant. P/F ratio (based on serial blood gas analyses before and 12 hours after 2 doses of surfactant) and also, clinical outcomes were assessed.in COVID-19 adult patients, surfactant significantly improved pulmonary P/F ratio both in intubated and face mask COVID-19 patients (increasing from 119.2 ± 51.7 to 179.4 ± 115.5). The rate of extubation was much better than similar country-wide studies. Surfactant significantly alleviates the respiratory status in moderate to severe COVID-19 ARDS with two consecutive 100 mg doses of surfactant (with 6 hours' interval) though previous studies have been controversial, regarding the effect of surfactant in general forms of ARDS. Higher doses might have better effects, mandating more trials.

Assessment of mental health, knowledge, and attitude of patients with multiple sclerosis and neuromyelitis optica spectrum disorder in response to 2019 novel coronavirus

Background

With the recent pandemic of the novel coronavirus disease (COVID-19), multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) patients for their compromised immune system have been in significant concern. Awareness and attitude about this virus have an important impact on infection prevention and coping with stress and anxiety. So we conducted this study to assess knowledge, attitude, and mental health status in MS and NMOSD patients within the COVID-19 pandemic.

Method

In this cross-sectional study, the link of Depression Anxiety Stress Scales-21 (DASS-21) and a self-administered structured questionnaire were sent through social media to MS and NMOSD patients and two control groups consisting of healthy and migraine individuals.

Results

A total of 223 MS patients, 41 NMOSD, 29 migraine, and 245 healthy subjects participated in this study. MS patients had higher total DASS scores compared to healthy participants (p = 0.012). There were no significant differences among the study groups regarding knowledge and attitude. In MS patients, physical comorbidity was associated with a total score of attitude (OR 1.59, 95% CI 0.53, 2.66, p = 0.004). We did not find association between other demographic and clinical variables with DASS scores, attitude, and knowledge in MS patients.

Conclusion

The current data highlight the necessity of attitude, knowledge, and mental health assessment among MS and NMOSD patients. Further studies in other countries need to be carried to assess these points among MS and NMOSD patients.

Development of minimal basic data set to report COVID-19

Background: Effective surveillance of COVID-19 highlights the importance of rapid, valid, and standardized information to crisis monitoring and prompts clinical interventions. Minimal basic data set (MBDS) is a set of metrics to be collated in a standard approach to allow aggregated use of data for clinical purposes and research. Data standardization enables accurate comparability of collected data, and accordingly, enhanced generalization of findings. The aim of this study is to establish a core set of data to characterize COVID-19 to consolidate clinical practice. Methods: A 3-step sequential approach was used in this study: (1) an elementary list of data were collected from the existing information systems and data sets; (2) a systematic literature review was conducted to extract evidence supporting the development of MBDS; and (3) a 2-round Delphi survey was done for reaching consensus on data elements to include in COVID-19 MBDS and for its robust validation. Results: In total, 643 studies were identified, of which 38 met the inclusion criteria, where a total of 149 items were identified in the data sources. The data elements were classified by 3 experts and validated via a 2-round Delphi procedure. Finally, 125 data elements were confirmed as the MBDS. Conclusion: The development of COVID-19 MBDS could provide a basis for meaningful evaluations, reporting, and benchmarking COVID-19 disease across regions and countries. It could also provide scientific collaboration for care providers in the field, which may lead to improved quality of documentation, clinical care, and research outcomes.

Neutrophil-to-Lymphocyte ratio as a potential biomarker for disease severity in COVID-19 patients

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Controlling age and sex, NLR>6.5 increases the chance of disease severity by 4 times.

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NLR>6.5 increases the chance of death about 1.8 times after age and sex adjustments.

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The average value of WBC among severe patients was higher than non-severe.

Toward Controlling Coronavirus Disease 2019 (COVID-19) Pandemic by Integrated Registry Systems

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