Prevalence of burnout among health care workers during coronavirus disease (COVID-19) pandemic: A systematic review and meta-analysis

The aim of this systematic review and meta-analysis study was to estimate the pooled prevalence of burnout among health care workers (HCWs), who worked in health centers during the coronavirus disease (COVID-19) outbreak, based on the Maslach Burnout Inventory (MBI) Questionnaire. A comprehensive search based on specific terms was performed through the online studies of Pubmed, Scopus, Web of Science, and ProQuest, until January 2022. The methodological quality of included studies was assessed using the National Institutes of Health (NIH) tool. Data analysis was carried out through the random-effects model, and the heterogeneity was investigated by I2 statistic using the software STATA Version 16. In total, seven articles with 5,022 participants were included in the final analysis. Four studies with 4,419 participants reported the prevalence of burnout as percent in moderate and severe types for all three components of burnout syndrome. Our results showed that the 45% of pooled moderate and 37% of severe levels of emotional exhaustion, 49% of pooled moderate and 18% of severe levels of depersonalization, 38% of pooled moderate and 51% of pooled severe levels of reduced personal accomplishment. Whereas six studies with 4,838 sample size reported the mean prevalence of MBI-based burnout syndrome and the mean pooled prevalence of emotional exhaustion, depersonalization, and accomplishment was 21.57, 7.47, and 33.48, respectively. Based on our findings, HCWs who worked in health centers during COVID-19 outbreak, experienced significant burnout. Therefore, it is necessary to design and implement programs to deal with burnout among this populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved) Impact Statement What is the public health significance of this article? This study suggests that health care workers (HCWs) who worked in health centers during the outbreak of COVID-19 and were in direct and/or indirect contact with COVID-19 patients experienced significant burnout. Burnout among HCWs is an important issue because it not only has an impact on their quality of life, but it can potentially affect the quality of care provided, increase medical errors, reduce patient safety, and even the influence on the mental health of their families and society. Therefore, it is necessary to design and implement programs to deal with burnout among this populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Efficacy of ozone adjuvant therapy in COVID-19 patients: A meta-analysis study.

Introduction: Using ozone therapy to manage COVID-19 patients has been accompanied by conflicting results in prior studies. Therefore, we aimed to widely assess the effects of ozone as adjuvant therapy in COVID-19 patients. Methods: PubMed, Scopus, Web of Science, Cochrane, ProQuest, Springer, and Sage journals were searched systematically until April 2022. Mortality rate, ICU admission, hospital-length stay, negative PCR, pulmonary, renal, and hepatic functions, as well as inflammatory and blood systems were pooled to compare the efficacy of ozone as adjacent therapy (OZ) and standard treatment (ST). Analyses were run with the random/fixed models, sub-group analysis, funnel plot, and sensitivity analysis using comprehensive meta-analysis (CMA) software version 2.0. Results: The results of four randomized clinical trials (RCTs) and four case-control studies with a total of 371 COVID-19 positive patients were analyzed. The OZ group patients had a shorter length of hospital stay (P > 0.05), lower ICU admissions (P > 0.05), and lower mortality rates (P < 0.05) than the ST group cases. After treatment, 41% more COVID-19 patients had negative PCR tests than the ST group (P < 0.05). Serum creatinine and urea levels were not modified in either group (P > 0.05). Moreover, except for albumin serum levels, which decreased significantly in the OZ group, serum bilirubin, ALT, and AST were not modified in either group (P > 0.05). Both arms did not show a decrease in C-reactive protein blood levels (P > 0.05), but the OZ group showed a significant modification in LDH serum levels (P < 0.05). Unlike the d-dimer and WBC serum levels (P > 0.05), platelet levels were increased in the OZ group (P < 0.05). No negative side effects were demonstrated in either group. Conclusion: Ozone therapy was effective significantly on PCR test and LDH serum levels, as well as mortality based on overall estimation. Concerning the length of hospital stay and ICU admissions, although the results were insignificant, their effect sizes were notable clinically. More RCT studies are needed to show the efficacy of ozone therapy on other studied variables.

The feasibility of using acoustic measures for predicting the Total Opacity Scores of chest computed tomography scans in patients with COVID-19.

To study the possibility of using acoustic parameters, i.e., Acoustic Voice Quality Index (AVQI) and Maximum Phonation Time (MPT) for predicting the degree of lung involvement in COVID-19 patients. This cross-sectional case-control study was conducted on the voice samples collected from 163 healthy individuals and 181 patients with COVID-19. Each participant produced a sustained vowel/a/, and a phonetically balanced Persian text containing 36 syllables. AVQI and MPT were measured using Praat scripts. Each patient underwent a non-enhanced chest computed tomographic scan and the Total Opacity score was rated to assess the degree of lung involvement. The results revealed significant differences between patients with COVID-19 and healthy individuals in terms of AVQI and MPT. A significant difference was also observed between male and female participants in AVQI and MPT. The results from the receiver operating characteristic curve analysis and area under the curve indicated that MPT (0.909) had higher diagnostic accuracy than AVQI (0.771). A significant relationship was observed between AVQI and TO scores. In the case of MPT, however, no such relationship was observed. The findings indicated that MPT was a better classifier in differentiating patients from healthy individuals, in comparison with AVQI. The results also showed that AVQI can be used as a predictor of the degree of patients' and recovered individuals' lung involvement. A formula is suggested for calculating the degree of lung involvement using AVQI.

Evaluation the efficacy and safety of N-acetylcysteine inhalation spray in controlling the symptoms of patients with COVID-19: An open-label randomized controlled clinical trial.

The aim of this study was to evaluate the effect and safety of N-acetylcysteine (NAC) inhalation spray in the treatment of patients with coronavirus disease 2019 (COVID-19). This randomized controlled clinical trial study was conducted on patients with COVID-19. Eligible patients (n = 250) were randomly allocated into the intervention group (routine treatment + NAC inhaler spray one puff per 12 h, for 7 days) or the control group who received routine treatment alone. Clinical features, hemodynamic, hematological, biochemical parameters and patient outcomes were assessed and compared before and after treatment. The mortality rate was significantly higher in the control group than in the intervention group (39.2% vs. 3.2%, p < 0.001). Significant differences were found between the two groups (intervention and control, respectively) for white blood cell count (6.2 vs. 7.8, p < 0.001), hemoglobin (12.3 vs. 13.3, p = 0.002), C-reactive protein (CRP: 6 vs. 11.5, p < 0.0001) and aspartate aminotransferase (AST: 32 vs. 25.5, p < 0.0001). No differences were seen for hospital length of stay (11.98 ± 3.61 vs. 11.81 ± 3.52, p = 0.814) or the requirement for intensive care unit (ICU) admission (7.2% vs. 11.2%, p = 0.274). NAC was beneficial in reducing the mortality rate in patients with COVID-19 and inflammatory parameters, and a reduction in the development of severe respiratory failure; however, it did not affect the length of hospital stay or the need for ICU admission. Data on the effectiveness of NAC for Severe Acute Respiratory Syndrome Coronavirus-2 is limited and further research is required.

Efficacy of ozone adjuvant therapy in COVID-19 patients: A meta-analysis study

Introduction Using ozone therapy to manage COVID-19 patients has been accompanied by conflicting results in prior studies. Therefore, we aimed to widely assess the effects of ozone as adjuvant therapy in COVID-19 patients. Methods PubMed, Scopus, Web of Science, Cochrane, ProQuest, Springer, and Sage journals were searched systematically until April 2022. Mortality rate, ICU admission, hospital-length stay, negative PCR, pulmonary, renal, and hepatic functions, as well as inflammatory and blood systems were pooled to compare the efficacy of ozone as adjacent therapy (OZ) and standard treatment (ST). Analyses were run with the random/fixed models, sub-group analysis, funnel plot, and sensitivity analysis using comprehensive meta-analysis (CMA) software version 2.0. Results The results of four randomized clinical trials (RCTs) and four case-control studies with a total of 371 COVID-19 positive patients were analyzed. The OZ group patients had a shorter length of hospital stay (P > 0.05), lower ICU admissions (P > 0.05), and lower mortality rates (P < 0.05) than the ST group cases. After treatment, 41% more COVID-19 patients had negative PCR tests than the ST group (P < 0.05). Serum creatinine and urea levels were not modified in either group (P > 0.05). Moreover, except for albumin serum levels, which decreased significantly in the OZ group, serum bilirubin, ALT, and AST were not modified in either group (P > 0.05). Both arms did not show a decrease in C-reactive protein blood levels (P > 0.05), but the OZ group showed a significant modification in LDH serum levels (P < 0.05). Unlike the d-dimer and WBC serum levels (P > 0.05), platelet levels were increased in the OZ group (P < 0.05). No negative side effects were demonstrated in either group. Conclusion Ozone therapy was effective significantly on PCR test and LDH serum levels, as well as mortality based on overall estimation. Concerning the length of hospital stay and ICU admissions, although the results were insignificant, their effect sizes were notable clinically. More RCT studies are needed to show the efficacy of ozone therapy on other studied variables.

Prevalence of burnout among health care workers during coronavirus disease (COVID-19) pandemic: A systematic review and meta-analysis

The aim of this systematic review and meta-analysis study was to estimate the pooled prevalence of burnout among health care workers (HCWs), who worked in health centers during the coronavirus disease (COVID-19) outbreak, based on the Maslach Burnout Inventory (MBI) Questionnaire. A comprehensive search based on specific terms was performed through the online studies of Pubmed, Scopus, Web of Science, and ProQuest, until January 2022. The methodological quality of included studies was assessed using the National Institutes of Health (NIH) tool. Data analysis was carried out through the random-effects model, and the heterogeneity was investigated by I-2 statistic using the software STATA Version 16. In total, seven articles with 5,022 participants were included in the final analysis. Four studies with 4,419 participants reported the prevalence of burnout as percent in moderate and severe types for all three components of burnout syndrome. Our results showed that the 45% of pooled moderate and 37% of severe levels of emotional exhaustion, 49% of pooled moderate and 18% of severe levels of depersonalization, 38% of pooled moderate and 51% of pooled severe levels of reduced personal accomplishment. Whereas six studies with 4,838 sample size reported the mean prevalence of MBI-based burnout syndrome and the mean pooled prevalence of emotional exhaustion, depersonalization, and accomplishment was 21.57, 7.47, and 33.48, respectively. Based on our findings, HCWs who worked in health centers during COVID-19 outbreak, experienced significant burnout. Therefore, it is necessary to design and implement programs to deal with burnout among this populations. Public Significance Statement What is the public health significance of this article? This study suggests that health care workers (HCWs) who worked in health centers during the outbreak of COVID-19 and were in direct and/or indirect contact with COVID-19 patients experienced significant burnout. Burnout among HCWs is an important issue because it not only has an impact on their quality of life, but it can potentially affect the quality of care provided, increase medical errors, reduce patient safety, and even the influence on the mental health of their families and society. Therefore, it is necessary to design and implement programs to deal with burnout among this populations.

A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes.

There is still an urgent need to develop effective treatments to help minimize the cases of severe COVID-19. A number of tools have now been developed and applied to address these issues, such as the use of non-contrast chest computed tomography (CT) for evaluation and grading of the associated lung damage. Here we used a deep learning approach for predicting the outcome of 1078 patients admitted into the Baqiyatallah Hospital in Tehran, Iran, suffering from COVID-19 infections in the first wave of the pandemic. These were classified into two groups of non-severe and severe cases according to features on their CT scans with accuracies of approximately 0.90. We suggest that incorporation of molecular and/or clinical features, such as multiplex immunoassay or laboratory findings, will increase accuracy and sensitivity of the model for COVID-19 -related predictions.

Is there any association between plasma lipid profile and severity of COVID-19?

BACKGROUND: COVID-19 is an infectious disease which caused a pandemic with many diseases and fatalities. This new variant of coronavirus called SARS-CoV-2 and is primarily characterized by respiratory symptoms. There are some data indicating that LDL-cholesterol (LDL-C) as well as HDL-cholesterol (HDL-C) levels are inversely correlated to disease severity and could act as a predictor for disease progression and unfavorable prognosis. However, the results of some other studies do not confirm this. This current study aimed to provide an answer to this question. METHODS: This prospective, single-center study analyzed 367 confirmed COVID-19 patients to find whether there are any differences in plasma lipoproteins between survivors and non-survivors patients or between the patients with a "duration of ≤10 days intensive unit care (ICU) stay" and patients with a "duration of >10 days ICU stay". RESULTS: No association between any lipid/lipoprotein parameter and the severity of COVID-19 could be found but survivors and non-survivors did differ concerning total cholesterol and LDL-C levels. CONCLUSION: Multivariate cox regression analysis could not prove any association between lipids/lipoproteins and severe events in COVID-19 patients. Significantly less non-survivors with COVID-19 were taking atorvastatin than survivors which is consistent with the majority of previous findings.

Associastion of In-hospital Use of Statins, Aspirin, and Renin-Angiotensin-Aldosterone Inhibitors with Mortality and ICU Admission Due to COVID-19.

The exaggerated host response to Sars-CoV-2 plays an important role in COVID-19 pathology but provides a therapeutic opportunity until definitive virus targeted therapies and vaccines become available. Given a central role of endothelial dysfunction and systemic inflammation, repurposing ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), statins, and aspirin has been of interest. In this retrospective, single-center study, we evaluated the primary outcomes of mortality and ICU admission in 587 hospitalized patients with documented COVID-19 with or without ACEIs, ARBs, statins, and aspirin. Atorvastatin was associated with reduced mortality, which persisted after adjusting for age, lockdown status, and other medications (OR: 0.18. 95% CI: 0.06-0.49, P = 0.001). ACEIs were also associated with reduced mortality in the crude model (OR: 0.20, CI: 0.06-0.66, P = 0.008), as ACEIs and ARBs were combined as a single group (OR: 0.35, CI: 0.16-0.75, P = 0.007), although ARBs alone did not reach statistical significance. There was no association between any medications and risk of ICU admission. Aspirin only achieved a significant association of reduced mortality in a subgroup of patients with diabetes in the crude model (OR: 0.17, CI: 0.04-0.80, P = 0.02). The reduced mortality observed with atorvastatin is consistent with other literature, and consideration should be given to atorvastatin as a COVID-19 treatment. While there was suggested benefit of ACEIs and ARBs in the present study, other studies are varied and further studies are warranted to recommend employing these medications as a treatment strategy. Nevertheless, this study combined with others continues to give credibility that ACEIs and ARBs are safe to continue in the setting of COVID-19.

Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.

This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voices. Twenty-five acoustic parameters were extracted from voice samples of 203 COVID-19 patients and 171 healthy individuals who produced a sustained vowel, i.e., /a/, as long as they could after a deep breath. The selected acoustic parameters were from different categories including fundamental frequency and its perturbation, harmonicity, vocal tract function, airflow sufficiency, and periodicity. After the feature extraction, different machine learning methods were tested. A leave-one-subject-out validation scheme was used to tune the hyper-parameters and record the test set results. Then the models were compared based on their accuracy, precision, recall, and F1-score. Based on accuracy (89.71%), recall (91.63%), and F1-score (90.62%), the best model was the feedforward neural network (FFNN). Its precision function (89.63%) was a bit lower than the logistic regression (90.17%). Based on these results and confusion matrices, the FFNN model was employed in the software. This screening tool could be practically used at home and public places to ensure the health of each individual's respiratory system. If there are any related abnormalities in the test taker's voice, the tool recommends that they seek a medical consultant.

Effectiveness of Curcumin on Outcomes of Hospitalized COVID-19 Patients: A Systematic Review of Clinical Trials.

Despite the ongoing vaccination efforts, there is still an urgent need for safe and effective treatments to help curb the debilitating effects of COVID-19 disease. This systematic review aimed to investigate the efficacy of supplemental curcumin treatment on clinical outcomes and inflammation-related biomarker profiles in COVID-19 patients. We searched PubMed, Scopus, Web of Science, EMBASE, ProQuest, and Ovid databases up to 30 June 2021 to find studies that assessed the effects of curcumin-related compounds in mild to severe COVID-19 patients. Six studies were identified which showed that curcumin supplementation led to a significant decrease in common symptoms, duration of hospitalization and deaths. In addition, all of these studies showed that the intervention led to amelioration of cytokine storm effects thought to be a driving force in severe COVID-19 cases. This was seen as a significant (p < 0.05) decrease in proinflammatory cytokines such as IL1ß and IL6, with a concomitant significant (p < 0.05) increase in anti-inflammatory cytokines, including IL-10, IL-35 and TGF-α. Taken together, these findings suggested that curcumin exerts its beneficial effects through at least partial restoration of pro-inflammatory/anti-inflammatory balance. In conclusion, curcumin supplementation may offer an efficacious and safe option for improving COVID-19 disease outcomes. We highlight the point that future clinical studies of COVID-19 disease should employ larger cohorts of patients in different clinical settings with standardized preparations of curcumin-related compounds.

Assessing sex differential in COVID-19 mortality rate by age and polymerase chain reaction test results: an Iranian multi-center study.

BACKGROUND: The aim of this study is to evaluate the sex differential effect in the COVID-19 mortality by different age groups and polymerase chain reaction (PCR) test results. RESEARCH DESIGN: In a multicenter cross-sectional study from 55 hospitals in Tehran, Iran, patients were categorized as positive, negative, and suspected cases. RESULTS: A total of 25,481 cases (14,791 males) were included in the study with a mortality rate of 12.0%. The mortality rates in positive, negative, and suspected cases were 20.55%, 9.97%, and 7.31%, respectively. Using a Cox regression model, sex had a significant effect on the hazard of death due to COVID-19 in adult and senior male patients having positive and suspected PCR test results. However, sex was not found as significant factor for mortality in patients with a negative PCR test in different age groups. CONCLUSIONS: Regardless of other risk factors, we found that the effect of sex on COVID-19 mortality varied significantly in different age groups. Therefore, appropriate strategies should be designed to protect adult and senior males from this deadly infectious disease. Furthermore, owing to the considerable death rate of COVID-19 patients with negative test results, new policies should be launched to increase the accuracy of diagnosis tests.

Improved COVID-19 Outcomes following Statin Therapy: An Updated Systematic Review and Meta-analysis.

BACKGROUND: Although vaccine rollout for COVID-19 has been effective in some countries, there is still an urgent need to reduce disease transmission and severity. We recently carried out a meta-analysis and found that pre- and in-hospital use of statins may improve COVID-19 mortality outcomes. Here, we provide an updated meta-analysis in an attempt to validate these results and increase the statistical power of these potentially important findings. METHODS: The meta-analysis investigated the effect of observational and randomized clinical studies on intensive care unit (ICU) admission, tracheal intubation, and death outcomes in COVID-19 cases involving statin treatment, by searching the scientific literature up to April 23, 2021. Statistical analysis and random effect modeling were performed to assess the combined effects of the updated and previous findings on the outcome measures. Findings. The updated literature search led to the identification of 23 additional studies on statin use in COVID-19 patients. Analysis of the combined studies (n = 47; 3,238,508 subjects) showed no significant effect of statin treatment on ICU admission and all-cause mortality but a significant reduction in tracheal intubation (OR = 0.73, 95% CI: 0.54-0.99, p = 0.04, n = 10 studies). The further analysis showed that death outcomes were significantly reduced in the patients who received statins during hospitalization (OR = 0.54, 95% CI: 0.50-0.58, p < 0.001, n = 7 studies), with no such effect of statin therapy before hospital admission (OR = 1.06, 95% CI = 0.82-1.37, p = 0.670, n = 29 studies). CONCLUSION: Taken together, this updated meta-analysis extends and confirms the findings of our previous study, suggesting that in-hospital statin use leads to significant reduction of all-cause mortality in COVID-19 cases. Considering these results, statin therapy during hospitalization, while indicated, should be recommended.

Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into two groups of critical and non-critical according to their CT features. Methods This was carried out as a retrospective study from March to April 2020 in Baqiyatallah Hospital, Tehran, Iran. From total of 1078 patients with COVID-19 pneumonia who underwent chest CT, 169 were critical cases and 909 were non-critical. Deep learning neural networks were used to classify samples into critical or non-critical ones according to the chest CT results. Results The best accuracy of prediction was seen by the presence of diffuse opacities and lesion distribution (both=0.91, 95% CI: 0.83-0.99). The largest sensitivity was achieved using lesion distribution (0.74, 95% CI: 0.55-0.93), and the largest specificity was for presence of diffuse opacities (0.95, 95% CI: 0.9-1). The total model showed an accuracy of 0.89 (95% CI: 0.79-0.99), and the corresponding sensitivity and specificity were 0.71 (95% CI: 0.51-0.91) and 0.93 (95% CI: 0.87-0.96), respectively. Conclusions The results showed that CT scan can accurately classify and predict critical and non-critical COVID-19 cases.

The Experiences of Recovered COVID-19 Patients in Baqiyatallah Hospital: A Qualitative Study.

The emerging COVID-19 disease affects not only the physical health but also the emotional and psychological health of patients. This study aimed to explain the experiences of 22 recovered COVID-19 patients in Baqiyatallah hospital, Tehran, Iran. Data were collected through in-depth semi-structured interviews. All interviews were recorded and transcribed and then analyzed using the conventional content analysis method. This resulted in emergence of 3 themes "emotional-sensational paradox", "spiritual growth", and "experienced mental-psychological effects", with 11 main categories and 33 subcategories. The results of the study can be used to develop instructions and guidelines for the families of patients as well as healthcare teams to provide effective measures and interventions to minimize the suffering of patients and the damage to mental health.

Improved COVID-19 ICU admission and mortality outcomes following treatment with statins: a systematic review and meta-analysis.

INTRODUCTION: Approximately 1% of the world population has now been infected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). With cases still rising and vaccines just beginning to rollout, we are still several months away from seeing reductions in daily case numbers, hospitalisations, and mortality. Therefore, there is a still an urgent need to control the disease spread by repurposing existing therapeutics. Owing to antiviral, anti-inflammatory, immunomodulatory, and cardioprotective actions, statin therapy has been considered as a plausible approach to improve COVID-19 outcomes. MATERIAL AND METHODS: We carried out a meta-analysis to investigate the effect of statins on 3 COVID-19 outcomes: intensive care unit (ICU) admission, tracheal intubation, and death. We systematically searched the PubMed, Web of Science, Scopus, and ProQuest databases using keywords related to our aims up to November 2, 2020. All published observational studies and randomised clinical trials on COVID-19 and statins were retrieved. Statistical analysis with random effects modelling was performed using STATA16 software. RESULTS: The final selected studies (n = 24 studies; 32,715 patients) showed significant reductions in ICU admission (OR = 0.78, 95% CI: 0.58-1.06; n = 10; I 2 = 58.5%) and death (OR = 0.70, 95% CI: 0.55-0.88; n = 21; I 2 = 82.5%) outcomes, with no significant effect on tracheal intubation (OR = 0.79; 95% CI: 0.57-1.11; n = 7; I 2= 89.0%). Furthermore, subgroup analysis suggested that death was reduced further by in-hospital application of stains (OR = 0.40, 95% CI: 0.22-0.73, n = 3; I 2 = 82.5%), compared with pre-hospital use (OR = 0.77, 95% CI: 0.60-0.98, n = 18; I 2 = 81.8%). CONCLUSIONS: These findings call attention to the need for systematic clinical studies to assess both pre- and in-hospital use of statins as a potential means of reducing COVID-19 disease severity, particularly in terms of reduction of ICU admission and total mortality reduction.

Effect of COVID-19 on Mortality of Pregnant and Postpartum Women: A Systematic Review and Meta-Analysis.

BACKGROUND: Based on what is known at this time, pregnant women are at an increased risk of severe illness from COVID-19 compared to nonpregnant women. Additionally, pregnant women with COVID-19 might have an increased risk of adverse pregnancy outcomes. To investigate the effects of coronavirus disease 2019 (COVID-19) on mortality of pregnant and postpartum women, we performed a systematic review of available published literature on pregnancies affected by COVID-19. METHODS: Web of Science, SCOPUS, and MEDLINE- databases were searched for original studies concerning the effect of COVID-19 on mortality of pregnant and postpartum women published by July 10, 2020. Meta-analyses of proportions were used to combine data and report pooled proportions. RESULTS: 117 studies with a total of 11758 pregnant women were included. The age ranged between 15 and 48 years. Most subjects were infected with SARS-CoV-2 in the third trimester. Disease severity was not reported in 1125 subjects. Maternal mortality was 1.3%. In 100% of fatal cases with adequate data, fever alone or with cough was one of the presenting symptoms. Also, dyspnea (58.3%) and myalgia (50%) were the most common symptoms. Sore throat (8.3%) and gastrointestinal symptoms (anorexia, nausea) (8.3%) were rare. The rate of comorbidities was 20% among COVID-19 deaths. The majority of COVID-19-infected women who died had cesarean section (58.3%), 25% had a vaginal delivery, and 16.7% of patients were not full term. CONCLUSION: COVID-19 infection in pregnant women was associated with higher rates (and pooled proportions) of cesarean section and mortality. Because new data are continuously being generated and published, the findings of this study can be complete and updated with new researches. The results of this study can guide and improve prenatal counseling of COVID-19-infected pregnant women.