Mortality In COVID-19 Patients Research Articles

Predictive factors of mortality in COVID-19 patients: Analysis of an intensive care unit in Espirito Santo, Brazil

Background: Coronavirus disease (COVID-19) is a global health issue that keeps testing academic efforts to cease it. Many factors are involved in progression to severe disease including metabolic and inflammatory disorders. The aim of this study is to analyze the factors associated with mortality in those admitted for COVID-19 in the Intensive Care Unit (ICU) of a hospital in Espirito Santo, Brazil. Methods: This is a retrospective, cross-sectional study, with data collection from medical records. The primary outcome studied is mortality, categorized by length of stay in the ICU. A total of 163 patients were included in this study. The data of these patients where then separated in two groups, first with 93 discharges and second with 64 deaths. The parametric Student’s T-test and the nonparametric Mann–Whitney U test for continuous data and the χ2 and Fisher’s exact test for categorical data were used to compare the variables between both groups. Variables with a p-value < 0.05 (in the bivariate analysis) were submitted to the Cox Survival Hazard multivariate survival model. Results: Bivariate analysis identified as factors on admission associated with mortality: age > 60 years, high blood pressure, diabetes mellitus, heart disease, cerebrovascular disease thrombocytopenia, lactate dehydrogenase elevation, D-dimer elevation and use of supplemental oxygen. Complications while on ICU associated with higher mortality are: mechanical ventilation, mechanical ventilation> 14 days, acute renal failure, bacterial pneumonia, post COVID-19 acute arrhythmia, bloodstream infection, acute renal injury and anemia. To exclude possible interference, a multifactorial analysis was applied with the Cox Survival Hazard proportional risk model, showing that mechanical ventilation (OR: 17.254, 95%CI 4.35-68.43, p <0.0001) and anemia (OR: 2.17, 95%CI 1.15-4.09, p<0.016) are independent variables related to mortality. Conclusion: This study identified that anemia on admission and the need to provide mechanical ventilation during ICU stay are independent factors for predicting mortality.

Multi-center study to analyse outcome of integrated treatment approach in COVID-19 patients

Background: This study presents the outcome of integrated treatment approach based on government mandated standard allopathic treatment along with alternatives in COVID-19 patients. The aim of our study was to investigate the outcome of treatment strategy, co-morbid status, recovery and mortality rate of COVID-19 patients at Bhaktivedanta Hospital and Research Institute. Methods: Post ethics committee approval for multiple centers, data for 1049 COVID-19 patients (RTPCR confirmed cases) of all age groups and genders which were admitted in a dedicated covid hospital from March 2020 to November 2020 was analysed retrospectively. Results: This study highlights the management of COVID-19 patients with an integrated approach. In our cohort with 36.7%, 44.70 %, 18.58% of mild, moderate and severe cases respectively, mortality rate was only 3.43% of total positive patients admitted at our hospital. Conclusions: We emphasize that even in healthcare facilities with limited resource and poor infrastructure and lack of ICU facilities, clinical observation-based management can help to reduce mortality considerably. Unique features of our study include use of progesterone as an immune modulator, use of dual antiviral agents and use of age-related lower limit of oxygen saturation.

SARS-CoV-2 Vaccination and Clinical Presentation of COVID-19 in Patients Hospitalized during the Delta- and Omicron-Predominant Periods.

Evidence suggests that monovalent vaccine formulations are less effective against the Omicron SARS-CoV-2 than against previous variants. In this retrospective cohort study of hospitalized adults with PCR-confirmed COVID-19 during the Delta (October-November 2021) and Omicron (January-April 2022) variant predominant periods in Slovenia, we assessed the association between primary vaccination against SARS-CoV-2 and progression to critically severe disease (mechanical ventilation or death). Compared with the 529 patients hospitalized for acute COVID-19 during the Delta period (median age 65 years; 58.4% men), the 407 patients hospitalized during the Omicron period (median age 75 years; 50.6% men) were older, more often resided in long-term care facilities, and had higher Charlson comorbidity index scores. After adjusting for age, sex, the Charlson comorbidity index, the presence of immunocompromising conditions, and vaccination status, the patients admitted during the Omicron period had comparable odds of progressing to critically severe disease to those admitted during the Delta period. The 334/936 (35.7%) patients completing at least primary vaccination had lower odds of progression to critically severe disease and shorter hospital stay than unvaccinated patients; however, the protective effect of vaccination was less pronounced during the Omicron than during the Delta period. Although the Omicron variant appeared to better evade immunity induced by monovalent vaccines than the Delta variant, vaccination against SARS-CoV-2 remained an effective intervention to decrease morbidity and mortality in COVID-19 patients infected with the Omicron variant.

COVID-19: Diabetes Perspective—Pathophysiology and Management

Recent evidence relating to the impact of COVID-19 on people with diabetes is limited but continues to emerge. COVID-19 pneumonia is a newly identified illness spreading rapidly throughout the world and causes many disabilities and fatal deaths. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery have become prominent, along with the lingering effects of the virus on those directly infected. Diabetes is a commonly identified risk factor that contributes not only to the severity and mortality of COVID-19 patients, but also to the associated complications, including acute respiratory distress syndrome (ARDS) and multi-organ failure. Diabetic patients are highly affected due to increased viral entry into the cells and decreased immunity. Several hypotheses to explain the increased incidence and severity of COVID-19 infection in people with diabetes have been proposed and explained in detail recently. On the other hand, 20-50% of COVID-19 patients reported new-onset hyperglycemia without diabetes and new-onset diabetes, suggesting the two-way interactions between COVID-19 and diabetes. A systematic review is required to confirm diabetes as a complication in those patients diagnosed with COVID-19. Diabetes and diabetes-related complications in COVID-19 patients are primarily due to the acute illness caused during the SARS-CoV-2 infection followed by the release of glucocorticoids, catecholamines, and pro-inflammatory cytokines, which have been shown to drive hyperglycemia positively. This review provides brief insights into the potential mechanisms linking COVID-19 and diabetes, and presents clinical management recommendations for better handling of the disease.

The prognostic value of the Barthel Index for mortality in patients with COVID-19: A cross-sectional study.

This study aimed to analyze the association between the activity of daily living (ADL), coronavirus disease (COVID-19), and the value of the Barthel Index in predicting the prognosis of patients. This study included 398 patients with COVID-19, whose ADL at admission to hospital were assessed with the Barthel Index. The relationship between the index and the mortality risk of the patients was analyzed. Several regression models and a decision tree were established to evaluate the prognostic value of the index in COVID-19 patients. The Barthel Index scores of deceased patients were significantly lower than that of discharged patients (median: 65 vs. 90, P < 0.001), and its decrease indicated an increased risk of mortality in patients (P < 0.001). After adjusting models for age, gender, temperature, pulse, respiratory rate, mean arterial pressure, oxygen saturation, etc., the Barthel Index could still independently predict prognosis (OR = 0.809; 95% CI: 0.750-0.872). The decision tree showed that patients with a Barthel Index of below 70 had a higher mortality rate (33.3-40.0%), while those above 90 were usually discharged (mortality: 2.7-7.2%). The Barthel Index is of prognostic value for mortality in COVID-19 patients. According to their Barthel Index, COVID-19 patients can be divided into emergency, observation, and normal groups (0-70; 70-90; 90-100), with different treatment strategies.

Von Willebrand factor: from figurant to main character in the scene of inflammation

von Willebrand factor: from figurant to main character in the scene of inflammation

Decision Tree Prediction Model in Patient Mortality Rate based on Risk Factors

The Coronavirus disease (Covid-19) has become a global problem since WHO declared a pandemic in 2020. The number of deaths due to Covid-19 has increased significantly in many countries. This study aimed to implement decision tree modeling to represent the relationship between risk factors and the mortality rate of Covid-19 patients. This study analyzed secondary data of 83,024 Covid patients from January 2020 to June 2021. Data processing used data mining with the decision tree classification method. The results showed that comorbidity is the leading risk factor for death which is then influenced by age. The higher the age group with comorbidities, the higher the risk of death. Suggested that health services can utilize the results of this study to prevent the severity of Covid-19 infection. Such as the development of comorbid awareness programs and community-based education on managing patients with comorbidities.

Anti-inflammatory and antioxidant activities of Gymnema Sylvestre extract rescue acute respiratory distress syndrome in rats via modulating the NF-κB/MAPK pathway.

Acute respiratory distress syndrome (ARDS) is one of the major causes of mortality in COVID-19 patients, due to limited therapeutic options. This prompted us to explore natural sources to mitigate this condition. Gymnema Sylvestre (GS) is an ancient medicinal plant known to have various therapeutic effects. This investigation examined the therapeutic effect of hydroalcoholic extract of Gymnema Sylvestre (HAEGS) against lipopolysaccharide (LPS)-induced lung injury and ARDS in in vitro and in vivo models. UHPLC-HRMS/GC-MS was employed for characterizing the HAEGS and identified several active derivatives including gymnemic acid, gymnemasaponins, gymnemoside, gymnemasin, quercetin, and long fatty acids. Gene expression by RT-qPCR and DCFDA analysis by flow cytometry revealed that several inflammatory cytokine/chemokine, cell injury markers, and reactive oxygen species (ROS) levels were highly upregulated in LPS control and were significantly reduced upon HAEGS treatment. Consistent with the in vitro studies, we found that in LPS-induced ARDS model, pre-treatment with HAEGS significantly suppressed the LPS-induced elevation of inflammatory cell infiltrations, cytokine/chemokine marker expression, ROS levels, and lung injury in a dose-dependent manner. Further mechanistic studies demonstrated that HAEGS suppressed oxidative stress by modulating the NRF2 pathway and ameliorated the ARDS through the NF-κB/MAPK signalling pathway. Additional fractionation results revealed that fraction 6 which has the exclusive composition of gymnemic acid derivatives showed better anti-inflammatory effects (inhibition of IL-6 and IL-1β) at lower concentrations compared to HAEGS. Overall, HAEGS significantly mitigated LPS-induced lung injury and ARDS by targeting the NF-κB/MAPK signalling pathway. Thus, our work unravels the protective role of HAEGS for the first time in managing ARDS.

Evaluation of the Effect of Underlying Diseases on Mortality of COVID-19 Patients: A Study of 19,985 Cases

Background: The outbreak of a new coronavirus in China in 2019 (COVID-19) caused a global health crisis. Objectives: This study was performed to investigate the effect of different underlying diseases on mortality in patients with COVID-19. Methods: This retrospective cohort study was performed on COVID-19 patients admitted to the Shahid Rahimi and Sohada-ye Ashayer teaching hospitals in Khorramabad, Iran, from 2019 to 2021. Data on disease severity, clinical manifestations, mortality, and underlying disorders were collected and analyzed using the SPSS software version 22 at a 95% confidence interval and 0.05 significance level. Results: The study included 9653 men (48%) and 10332 women (52%). Patients with chronic kidney diseases, cancer, chronic obstructive pulmonary disease, hypertension, cardiovascular disease, and diabetes were at higher mortality risk than those without these underlying diseases, respectively. However, there was no significant relationship between asthma and mortality. Also, age &gt; 50 years, male gender, oxygen saturation &lt; 93 on admission, and symptoms lasting ≤ 5 days were associated with increased mortality. Conclusions: Since patients with underlying diseases are at higher mortality risk, they should precisely follow the advice provided by health authorities and receive a complete COVID-19 vaccination series.

Antithrombotic therapy in COVID-19 patients

Recently, there have been published the data of large randomized trials on the use of antithrombotic agents for reducing a risk of thromboembolic complications, multiple organ failure and mortality in COVID-19 patients. However, principles of selecting optimal therapy remain open. Strategies for the use of antithrombotic drugs in outpatient and inpatient settings, thromboprophylaxis in specific patient populations, and treatment of acute thrombosis in hospitalized COVID-19 patients are being developed. In October 2021, the International Society on Thrombosis and Hemostasis (ISTH) formed an interdisciplinary international panel of experts to develop recommendations for use of anticoagulants and antiplatelet agents in COVID-19 patients. Expert opinions are published. Here, we summarize all the publications available globally at the present time on this issue, obtained by using the principles of evidence-based medicine.

Longitudinal Assessment of Plasma Syndecan-1 Predicts 60-Day Mortality in Patients with COVID-19.

Endotheliopathy is a common pathologic finding in patients with acute and long COVID-19. It may be associated with disease severity and predispose patients to long-term complications. Plasma levels of a proteoglycan, syndecan-1, are found to be significantly elevated in patients with COVID-19, but its roles in assessing disease severity and predicting long-term outcome are not fully understood. A total of 124 consecutive hospitalized patients with SARS-CoV-2 infection were prospectively enrolled and blood samples were collected on admission (T1), 3-4 days following treatment (T2), and 1-2 days prior to discharge or death (T3). Plasma levels of syndecan-1 were determined using an immunosorbent assay; various statistical analyses were performed to determine the association between plasma syndecan-1 levels and disease severity or the 60-day mortality rate. Compared with those in the healthy controls, plasma levels of syndecan-1 in patients with critical COVID-19 were significantly higher (p &lt; 0.0001). However, there was no statistically significant difference among patients with different disease severity (p &gt; 0.05), resulting from large individual variability. Longitudinal analysis demonstrated that while the levels fluctuated during hospitalization in all patients, plasma syndecan-1 levels were persistently elevated from baseline in critical COVID-19 patients. Cox proportional hazard regression analyses revealed that elevated plasma levels of syndecan-1 (&gt;260 ng/mL at T1, &gt;1018 ng/mL at T2, and &gt;461 ng/mL at T3) were significantly associated with the 60-day mortality rate. Endotheliopathy, marked by glycocalyx degradation and elevated plasma syndecan-1, occurs in nearly all hospitalized patients with SARS-CoV-2 infection; elevated plasma syndecan-1 is associated with increased mortality in COVID-19 patients.

Prevaccination Glucose Time in Range Correlates With Antibody Response to SARS-CoV-2 Vaccine in Type 1 Diabetes.

Poor glucose control has been associated with increased mortality in COVID-19 patients with type 1 diabetes (T1D). This work aimed to assess the effect of prevaccination glucose control on antibody response to the SARS-CoV-2 vaccine BNT162b2 in T1D. We studied 26 patients with T1D scheduled to receive 2 doses, 21 days apart, of BNT162b2, followed prospectively for 6 months with regular evaluation of SARS-CoV-2 antibodies and glucose control. Immunoglobulin G (IgG) to spike glycoprotein were assessed by enzyme-linked immunosorbent assay, and serum neutralization by a live SARS-CoV-2 assay (Vero E6 cells system). Glycated hemoglobin A1c (HbA1c) and continuous glucose monitoring (CGM), including time in range (TIR) and above range (TAR), were collected. The primary exposure and outcome measures were prevaccination glucose control, and antibody response after vaccination, respectively. Prevaccination HbA1c was unrelated to postvaccine spike IgG (r = -0.33; P = .14). Of note, the CGM profile collected during the 2 weeks preceding BNT162b2 administration correlated with postvaccine IgG response (TIR: r = 0.75; P = .02; TAR: r = -0.81; P = .008). Patients meeting the recommended prevaccination glucose targets of TIR (≥ 70%) and TAR (≤ 25%) developed stronger neutralizing antibody titers (P < .0001 and P = .008, respectively), regardless of HbA1c. Glucose control along the study time frame was also associated with IgG response during follow-up (TIR: r = 0.93; P < .0001; TAR: r = -0.84; P < .0001). In T1D, glucose profile during the 2 weeks preceding vaccination is associated with stronger spike antibody binding and neutralization, highlighting a role for well-controlled blood glucose in vaccination efficacy.

A novel scoring system for early assessment of the risk of the COVID-19-associated mortality in hospitalized patients: COVID-19 BURDEN

BackgroundCorona Virus Disease 2019 (COVID-19) presentations range from those similar to the common flu to severe pneumonia resulting in hospitalization with significant morbidity and/or mortality. In this study, we made an attempt to develop a predictive scoring model to improve the early detection of high risk COVID-19 patients by analyzing the clinical features and laboratory data available on admission.MethodsWe retrospectively included 480 consecutive adult patients, aged 21–95, who were admitted to Faghihi Teaching Hospital. Clinical and laboratory features were collected from the medical records and analyzed using multiple logistic regression analysis. The final data analysis was utilized to develop a simple scoring model for the early prediction of mortality in COVID-19 patients. The score given to each associated factor was based on the coefficients of the regression analyses.ResultsA novel mortality risk score (COVID-19 BURDEN) was derived, incorporating risk factors identified in this cohort. CRP (> 73.1 mg/L), O2 saturation variation (greater than 90%, 84–90%, and less than 84%), increased PT (> 16.2 s), diastolic blood pressure (≤ 75 mmHg), BUN (> 23 mg/dL), and raised LDH (> 731 U/L) were the features constituting the scoring system. The patients are triaged to the groups of low- (score < 4) and high-risk (score ≥ 4) groups. The area under the curve, sensitivity, and specificity for predicting mortality in patients with a score of ≥ 4 were 0.831, 78.12%, and 70.95%, respectively.ConclusionsUsing this scoring system in COVID-19 patients, the patients with a higher risk of mortality can be identified which will help to reduce hospital care costs and improve its quality and outcome.

The Value of Interleukin-17A as a Prognostic Indicator in COVID-19 Patients

Background: SARS-CoV-2 infections (COVID-19) first occurred in Wuhan, China, in December 2019 and spread worldwide, causing significant mortality and morbidity. IL-17A may mediate numerous immunopathological effects secondary to cytokine release syndrome during SARS-CoV-2 infection. However, there has not been enough research on its effect on prognosis. Objectives: This study evaluated the predictive power of serum interleukin (IL)-17A level as a prognostic marker in COVID-19. Methods: The study included 152 patients diagnosed with COVID-19 by real-time polymerase chain reaction analysis of nasopharyngeal swab samples in the infectious diseases department and intensive care unit of our hospital between October 1 and December 31, 2020. The control group consisted of 40 asymptomatic healthcare workers who had negative RT-PCR results during routine COVID-19 screening in our hospital. Samples were collected in anticoagulant-free tubes and left at room temperature for 30 minutes. Afterward, it was centrifuged at 1000 × g for 15 minutes at 4°C per the instructions provided with the enzyme-linked immunoassay (ELISA) kit. Serum IL-17A levels were measured using the Human Interleukin 17A ELISA Kit. Results: Serum IL-17A levels were significantly higher in COVID-19 patients than in controls (P &lt; 0.001). IL-17A levels increased significantly in association with disease severity in patients with the moderate, severe, and critical disease, with a less pronounced difference between severe and critical patients (moderate vs. severe, P &lt; 0.001; severe vs. critical, P = 0.048). IL-17A levels at hospital admission and day 7 were significantly higher in non-surviving patients (P &lt; 0.001). At a cut-off value of 210.25 ng/L, IL-17A at admission had a predictive power of 0.792 (P &lt; 0.001). Compared to baseline, IL-17A values on day seven were significantly increased in non-survivors (P = 0.004) and decreased in survivors (P = 0.014). An increase of 26.17 ng/L or more on day 7 had a predictive mortality power of 0.634 (P = 0.005). Conclusions: The results of this study suggest that IL-17A, an important part of the immune system previously shown to be useful in the treatment and follow-up of COVID-19, may also help predict mortality in COVID-19 patients.

Perbandingan Angka Kematian Terapi Antiviral Favipiravir dan Remdesivir pada Pasien COVID-19 Di RSUP Dr. Sardjito Yogyakarta

Antiviral treatment for SARS-CoV2 (Severe Acute Respiratory Syndrome Coronavirus-2) is still being studied for its effectivity. The antivirals in the July 3, 2021 edition of the COVID-19 management guidelines, namely favipiravir and remdesivir, are used for moderate, severe and critical degrees. The study compares the mortality rate of COVID-19 patients taking the antivirals favipiravir and remdesivir. This research is a retrospective cohort study conducted at RSUP Dr. Sardjito Yogyakarta. The data was from the medical records of patients diagnosed with moderate, severe, and critical degrees of COVID-19 treated during the January-December 2021 period. Ninety-nine patients (50.8%) used favipiravir, while 97 patients (49.5%) used remdesivir. Chi-square analysis and multiple logistic regression were used to determine the relationship between research variables. Study subjects with the highest percentage of age 46-65 years (65%), male sex (54,6%), comorbid diabetes mellitus and hypertension (13,3%), severe degree of severity (60,7%), and viral load CT value ≤ 29 (80,1%), the patient went home alive (61,2%), and died (38,8%). The antivirals did not affect on mortality (p &gt; 0,05). Further research is needed with the same characteristics of the two groups involving factors of degree severity of the disease, co-morbidity, and other medication therapy.

Upper Gastrointestinal Tract Bleeding as a Predictor of Mortality in COVID-19 Patients Admitted to RSUP Dr. Sardjito, Yogyakarta, Indonesia

This retrospective cohort study explored the association between Upper Gastrointestinal Tract Bleeding (UGIB) and mortality in adult COVID-19 patients admitted to RSUP Dr. Sardjito Yogyakarta hospital from January 2021 to October 2022. Data, sourced from electronic medical records (EMRs) and analyzed using R Studio, aimed to discern if UGIB could predict mortality in COVID-19 patients, considering other relevant comorbidities. The univariate analysis identified several significant mortality-associated factors. Notably, UGIB presented an odds ratio (OR) of 2.14 (95% CI 1.48-3.11, p &lt; 0.001) for increased mortality. Type 2 diabetes mellitus (OR 1.56, 95% CI 1.34-1.81), hypoalbuminemia (OR 2.05, 95% CI 1.70-2.48), hyperkalemia (OR 3.35, 95% CI 2.44-4.67), and renal impairment (OR 2.91, 95% CI 2.41-3.53) also exhibited significant associations. In contrast, being female reduced mortality risk (OR 0.78, 95% CI 0.69-0.90). The multivariate analysis, after adjusting for influential factors, indicated UGIB as an independent predictor with an OR of 1.68 (95% CI 1.022.79, p = 0.042). The results underscore UGIB’s significance in predicting COVID-19 patient mortality, suggesting the need for proactive interventions to enhance patient management and outcomes.

Inflammation-based Indices Predicting Mortality in COVID-19.

Efficiency of various inflammation-based indices, including neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), C-reactive protein/lymphocyte ratio (CLR), albumin/globulin ratio (AGR), haemoglobin, albumin, lymphocyte, and platelet (HALP), systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI), was examined in predicting mortality in COVID-19 patients. The study population consisted of 827 COVID-19 patients, including 733 survivors and 94 non-survivors. Compared with the survivor group, the NLR, PLR, CLR, and SII values of the non-survivor group were markedly higher; however, the LMR, PNI, HALP and AGR values were markedly lower. Multivariate analysis identified PNI, NLR, CLR, older age, male gender and dyslipidemia as independent factors for mortality in COVID-19 patients. PNI had the largest area under the curve to predict mortality, followed by CLR, NLR, and other indexes. This data revealed that PNI, NLR, and CLR are independent factors of mortality in COVID-19 patients among inflammation-based indexes. Key Words: COVID-19 mortality, Prognostic nutritional index, C-reactive protein/lymphocyte ratio, Neutrophil/lymphocyte ratio.

Association of Metformin with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis

Studies have demonstrated high prevalence of mortality in coronavirus disease (COVID-19) patients with type 2 diabetes mellitus; however, the effects of antidiabetic pharmacotherapy on COVID-19 complications need further exploration. The aim of the study was to explore the association of metformin use and mortality in COVID-19 patients. A literature search was conducted using the databases Medline (via PubMed) and Cochrane Central Register of Controlled Trials until February 09, 2021. Nine studies were included in the meta-analysis, including 12,684 COVID-19 patients. The meta-analysis suggested 37% lower risk of mortality in patients receiving metformin (risk ratio: 0.63; 95% confidence interval: 0.50–0.78; p &lt; 0.001). However, no significant difference in hospitalization days between the two groups (p = 0.197) was observed. The analysis revealed significantly lower risk of having obesity (p &lt; 0.001), hypertension (p &lt; 0.001), heart failure (p &lt; 0.001), and cerebrovascular disease (p = 0.015) in the group receiving metformin. The analysis also demonstrated significantly lower risk of using anticoagulants (p = 0.015), diuretics (p &lt; 0.001), and antiplatelets (p = 0.010) in patients receiving metformin. Our findings suggest that metformin use decreases mortality in COVID-19 patients. However, randomized studies demonstrating the consequences of metformin use are needed to understand the magnitude of the beneficial effects of metformin.

The significant role of Carbapenems-resistant Acinetobacter Baumannii in mortality rate of patients with COVID-19

Background: Infections caused by Acinetobacter baumannii, especially carbapenem-resistant (CR) strains, pose important challenges in patients with COVID-19 infection. Therefore, in the present study, we investigated co-infection and antimicrobial resistance patterns, as well as the role of A. baumannii in the outcome of patients with COVID-19.Materials and methods: Between February 2019 and January 2021, 141 patients with A. baumannii infections were detected from seven different hospitals (A to G) in Arak, Iran, and the antibacterial susceptibility pattern of these isolates was evaluated using disk diffusion and E-test methods. Forty-seven of these patients were co-infected with COVID-19. During the study, the data about the clinical course, demographic data, and the role of A. baumannii infections in the mortality rate of COVID-19 patients were collected.Results: Hospitals A and B reported the most patients, with 53 (38%) and 47 (33%), respectively. Additionally, most cases (105 cases, 75%) were reported from surgical and general ICUs. Mechanical ventilators were detected as predisposing factors in 95 (67%) patients, and infection was detected in 20% of patients on the 10th day after intubation. All of the A. baumannii isolates were resistant to different classes of antibiotics, such as carbapenems. Notably, 33% (47 patients) were also positive for COVID-19, and 68% (32 patients) died due to the infection. Statistical analysis showed a significant role of A. baumannii co-infection in the mortality rate of COVID-19 patients (p-value 0.05).Conclusion: co-infection with A. baumannii is one of the most important challenges in COVID-19 patients. Our results showed that all isolated bacteria were CR and significantly increased mortality rates in COVID-19 patients.

Comorbid Diseases, Decreased PaO2/FiO2 Ratio, Increased Ferritin, Decreased Liver and Kidney Function as Risk Factors for Mortality in COVID-19 Patients

Background: Comorbid disease, a ratio of partial pressure of oxygen (PaO2) to a fraction of inspired oxygen (FiO2) (P/F ratio), ferritin serum, liver function, and kidney function correlate with mortality; hence, these factors are suggested as the prognostic markers in COVID -19. This study aims to analyze comorbid diseases, decreased PaO2/FiO2 ratio, increased ferritin, and decreased liver and kidney function as risk factors for mortality in COVID-19 patients. Methods: An analytic observational study with a match case-control design. Analysis was performed univariate, bivariate with the chi-squared test, and multivariate analysis using binary logistic regression analysis. Results: The subjects of the study were 220 people. The comorbid disease and the mortality of COVID-19 patients (p=0.038, OR=2.737, 95% CI 1.020 to 7.342), PaO2/FiO2 ratio to COVID-19 patient mortality (p=0.000, OR=43.1 95% CI 19.461 to 95.478), ferritin serum levels to COVID-19 patient mortality (p=0.000, OR=53.3, 95% CI 21.014 to 135.110), decreased liver function to COVID-19 patient mortality (p=0.000, OR=62.4 95% CI 25.323 to 153.567), decreased kidney function to COVID-19 patient mortality (p=0.000, OR=1389.7 95% CI 170.8 to 11307.2). The most dominant variable related to the death of COVID-19 patients is the decreased kidney function with an OR value of 722.447 (95% CI 33.356 to 15647.243). Conclusion: Risk factors of mortality of COVID-19 patients are comorbid disease, decrease in PaO2/FiO2 ratio, increase in ferritin, decrease in liver function, and decrease in kidney function. Of all these, the most dominant risk factor related to the highest mortality rate among COVID-19 patients is the decrease in kidney function.