Influenza A-associated severe pneumonia in hospitalized patients: Risk factors and NAI treatments

Clinical characteristics and assessment of risk factors in patients with influenza A-induced severe pneumonia after the prevalence of SARS-CoV-2

Purpose

The aim of this study is to describe the novel epidemiological and clinical characteristics of influenza A-induced severe pneumonia occurring after the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to further assess its potential risk factors for mortality.

Methods

We retrospectively studied the consecutive case series of 30 patients with confirmed influenza A-induced severe pneumonia treated in the intensive care unit at Dazhou Central Hospital in Sichuan, China, from March 1 to April 30, 2023. Logistic regression was used to analyze the independent risk factors, and receiver operating characteristic (ROC) curves were applied to evaluate the predictive efficacy of associated risk factors for mortality.

Results

The mortality rate was 33.3% in this study. Independent risk factors for mortality of patients were acute respiratory distress syndrome (ARDS) (p = 0.044) and septic shock (p = 0.012). ROC statistics for ARDS and septic shock to predict mortality in patients with influenza A-induced severe pneumonia demonstrated an area under the curve of 0.800 (sensitivity 80.0%, specificity 80.0%) and 0.825 (sensitivity 70.0%, specificity 95.0%), respectively.

Conclusion

ARDS and septic shock were the independent risk factors for mortality in patients with influenza A-induced severe pneumonia following the end of the SARS-CoV-2 pandemic. But high level of next generation sequencing reads Aspergillus coinfection, and comorbidities did not increase death risk of the study population.

Influenza vaccination for elderly, vulnerable and high-risk subjects: a narrative review and expert opinion

Influenza is associated with a substantial health burden, especially in high-risk subjects such as older adults, frail individuals and those with underlying chronic diseases. In this review, we summarized clinical findings regarding the impact of influenza in vulnerable populations, highlighted the benefits of influenza vaccination in preventing severe illness and complications and reviewed the main evidence on the efficacy, effectiveness and safety of the vaccines that are best suited to older adults among those available in Italy. The adverse outcomes associated with influenza infection in elderly and frail subjects and those with underlying chronic diseases are well documented in the literature, as are the benefits of vaccination (mostly in older adults and in patients with cardiovascular diseases, diabetes and chronic lung disease). High-dose and adjuvanted inactivated influenza vaccines were specifically developed to provide enhanced immune responses in older adults, who generally have low responses mainly due to immunosenescence, comorbidities and frailty. These vaccines have been evaluated in clinical studies and systematic reviews by international immunization advisory boards, including the European Centre for Disease Prevention and Control. The high-dose vaccine is the only licensed influenza vaccine to have demonstrated greater efficacy versus a standard-dose vaccine in preventing laboratory-confirmed influenza in a randomized controlled trial. Despite global recommendations, the vaccination coverage in high-risk populations is still suboptimal. All healthcare professionals (including specialists) have an important role in increasing vaccination rates.

Viral Pneumonia: From Influenza to COVID-19

Respiratory viruses are increasingly recognized as a cause of community-acquired pneumonia (CAP). The implementation of new diagnostic technologies has facilitated their identification, especially in vulnerable population such as immunocompromised and elderly patients and those with severe cases of pneumonia. In terms of severity and outcomes, viral pneumonia caused by influenza viruses appears similar to that caused by non-influenza viruses. Although several respiratory viruses may cause CAP, antiviral therapy is available only in cases of CAP caused by influenza virus or respiratory syncytial virus. Currently, evidence-based supportive care is key to managing severe viral pneumonia. We discuss the evidence surrounding epidemiology, diagnosis, management, treatment, and prevention of viral pneumonia.

Effects of Glycemic Variability in Critically Ill Patients with Coronavirus Disease 2019: A Retrospective Observational Study

Aim and background

Hyperglycemia is considered an adaptive metabolic manifestation of stress and is associated with poor outcomes. Herein, we analyzed the association between glycemic variability (GV) and hospital mortality in patients with coronavirus disease 2019 (COVID-19) admitted to the intensive care unit (ICU), and the association between GV and mechanical ventilation (MV), ICU stay, length of hospital stays, renal replacement therapy (RRT), hypoglycemia, nosocomial infections, insulin use, and corticosteroid class.

Materials and methods

In this retrospective observational study, we collected information on blood glucose levels during the first 10 days of hospitalization in a cohort of ICU patients with COVID-19 and its association with outcomes.

Results

In 239 patients, an association was observed between GV and hospital mortality between the first and last quartiles among patients without diabetes [odds ratio (OR), 3.78; confidence interval, 1.24-11.5]. A higher GV was associated with a greater need for RRT (p = 0.002), regular insulin (p < 0.001), and episodes of hypoglycemia (p < 0.001). Nosocomial infections were associated with intermediate GV quartiles (p = 0.02). The corticosteroid class had no association with GV (p = 0.21).

Conclusion

Glycemic variability was associated with high mortality in patients with COVID-19 and observed in the subgroup of patients without diabetes.

Clinical significance

Glycemic control in critically ill patients remains controversial and hyperglycemia is associated with worse outcomes. Diabetes mellitus (DM) is one of the most prevalent comorbidities in patients with COVID-19. In addition, they require corticosteroids due to pulmonary involvement, representing a challenge and an opportunity to better understand how glycemic changes can influence the outcome of these patients.

How to cite this article

Boschi E, Friedman G, Moraes RB. Effects of Glycemic Variability in Critically Ill Patients with Coronavirus Disease 2019: A Retrospective Observational Study. Indian J Crit Care Med 2024;28(4):381-386.

Analysis of viral pneumonia and risk factors associated with severity of influenza virus infection in hospitalized patients from 2012 to 2016

BACKGROUND

Influenza viruses cause pneumonia in approximately one-third of cases, and pneumonia is an important cause of death. The aim was to identify risk factors associated with severity and those that could predict the development of pneumonia.

METHODS

This retrospective, observational study included all adult patients with confirmed influenza virus infection admitted to Son Espases University Hospital during four influenza seasons in Spain (October to May) from to 2012-2016.

RESULTS

Overall, 666 patients with laboratory-confirmed influenza were included, 93 (14%) of which were severe; 73 (10.9%) were admitted to Intensive Care Unit (ICU), 39 (5.8%) died, and 185 (27.7%) developed pneumonia. Compared to less severe cases, patients with severe disease: were less vaccinated (40% vs. 28%, p = 0.021); presented with more confusion (26.9% vs. 6.8%), were more hypoxemic (Horowitz index (PaO2/FiO2) 261 vs. 280), had higher C-reactive protein (CRP) (12.3 vs. 4.0), had more coinfections (26.8% vs. 6.3%) and had more pleural effusion (14% vs. 2.6%) (last six all p < 0.001). Risk factors significantly associated with severity were pneumonia [OR (95% CI) = 4.14 (2.4-7.16)], history of heart disease (1.84, 1.03-3.28), and confusion at admission (4.99, 2.55-9.74). Influenza vaccination was protective (0.53, 0.28-0.98). Compared to those without pneumonia, the pneumonia group had higher CRP (11.3 vs. 4.0, p < 0.001), lower oxygen saturation (92% vs. 94%, p < 0.001), were more hypoxic (PaO2/FiO2 266 vs. 281, p < 0.001), and incurred more mechanical ventilation, septic shock, admission to the ICU, and deaths (all four p < 0.001). Higher CRP and lower oxygen saturation were independent variables for predicting the development of pneumonia.

CONCLUSIONS

Pneumonia, history of heart disease, confusion and no influenza vaccination were independent variables to present complications in patients admitted with influenza infection.

Incident infection risks depending on oral antidiabetic exposure in insulin-treated type 2 diabetes patients

Dipeptidyl peptidase-4 inhibitors (DPP4is) and sodium glucose cotransporter-2 inhibitors (SGLT2is) have been speculated to have a potential to increase infection risks in type 2 diabetes mellitus (T2DM) patients. We performed a cohort study using the Korean health insurance data to investigate infection risks with each drug class relative to metformin in insulin-treated T2DM patients. After propensity score matching, we included 1,498 and 749 patients in DPP4i + insulin vs metformin + insulin and 300 and 549 patients in SGLT2i + insulin vs metformin + insulin, respectively. In stratified analyses per patient factor, none of the odds ratios (ORs) were associated with a statistical significance across respiratory, genital, and urinary tract infections (UTIs), except that of the male stratum for respiratory infections (OR 0.77, p = 0.04). With regard to SGLT2is, a higher risk of genital infections was analyzed with their use than with metformin therapy (OR 1.76, p = 0.03). In stratified analyses, the OR for genital infections remained significant in the baseline cardiovascular disease stratum (OR 2.29, p = 0.01). No increased UTI risk was detected with SGLT2is compared against metformin. In this study on insulin-receiving T2DM patients, DPP4is were not associated with increased infection risks, whereas SGLT2is led to a higher risk for genital infections, but not for UTIs, relative to metformin.

Influenza: Diabetes as a risk factor for severe related-outcomes and the effectiveness of vaccination in diabetic population. A meta-analysis of observational studies

AIMS

In order to better define the need for influenza vaccination in people with diabetes (DM), we collected all available evidence on the effect of DM as a risk factor for complications of both seasonal and pandemic influenza, and on the specific effectiveness of vaccines in patients with DM.

DATA SYNTHESIS

Two distinct systematic searches on MEDLINE, Cochrane, ClinicalTrials.gov and Embase databases were performed, one for each metanalysis, collecting all observational studies and randomized clinical trials performed on humans up to May 31st, 2022. We retrieved 34 observational studies comparing risk for influenza complications in people with or without diabetes, and 13 observational studies assessing vaccine effectiveness on preventing such complications. Mortality for influenza and hospitalization for influenza and pneumonia resulted significantly higher in individuals with versus without DM, both when unadjusted and adjusted data are analyzed. In diabetic individuals vaccinated for influenza overall hospitalization, hospitalization for influenza or pneumonia and overall mortality are significantly lower in comparison with not vaccinated DM subjects, both when unadjusted and adjusted data were analyzed.

CONCLUSION

This systematic review and meta-analysis shows that: 1) influenza is associated with more severe complications in diabetic versus not diabetic individuals and 2) influenza vaccination is effective in preventing clinically relevant outcomes in adults with DM with a NNT (number needed to treat) of 60, 319, and 250 for all-cause hospitalization, specific hospitalization, and all-cause mortality, respectively. The identification of diabetic patients as the target of vaccination campaigns for influenza appears to be justified by available clinical evidence.

Risk factors for in-hospital mortality and secondary bacterial pneumonia among hospitalized adult patients with community-acquired influenza: a large retrospective cohort study

BACKGROUND

Secondary bacterial pneumonia is an important complication of seasonal influenza, but little data is available about impact on death and risk factors. This study identified risk factors for all-cause in-hospital mortality and secondary bacterial pneumonia among hospitalized adult patients with community-acquired influenza.

METHODS

A retrospective cohort study was performed at a tertiary teaching hospital in southwest China. The study cohort included all adult hospitalized patients with a laboratory-confirmed, community-acquired influenza virus infection during three consecutive influenza seasons from 2017 to 2020. Cause-specific Cox regression was used to analyze risk factors for mortality and secondary bacterial pneumonia, respectively, accounting for competing events (discharge alive and discharge alive or death without secondary bacterial pneumonia, respectively).

RESULTS

Among 174 patients enrolled in this study, 14.4% developed secondary bacterial pneumonia and 11.5% died during hospitalization. For all-cause in-hospital mortality, time-varying secondary bacterial pneumonia was a direct risk factor of death (cause-specific hazard ratio [csHR] 3.38, 95% confidence interval [CI] 1.25-9.17); underlying disease indirectly increased death risk through decreasing the hazard of being discharged alive (csHR 0.55, 95% CI 0.39-0.77). For secondary bacterial pneumonia, the final model only confirmed direct risk factors: age ≥ 65 years (csHR 2.90, 95% CI 1.27-6.62), male gender (csHR 3.78, 95% CI 1.12-12.84) and mechanical ventilation on admission (csHR 2.96, 95% CI 1.32-6.64).

CONCLUSIONS

Secondary bacterial pneumonia was a major risk factor for in-hospital mortality among adult hospitalized patients with community-acquired influenza. Prevention strategies for secondary bacterial pneumonia should target elderly male patients and critically ill patients under mechanical ventilation.

Respiratory viruses: their importance and lessons learned from COVID-19

Respiratory virus infection can cause severe illnesses capable of inducing acute respiratory failure that can progress rapidly to acute respiratory distress syndrome (ARDS). ARDS is related to poor outcomes, especially in individuals with a higher risk of infection, such as the elderly and those with comorbidities, i.e. obesity, asthma, diabetes mellitus and chronic respiratory or cardiovascular disease. Despite this, effective antiviral treatments available for severe viral lung infections are scarce. The coronavirus disease 2019 (COVID-19) pandemic demonstrated that there is also a need to understand the role of airborne transmission of respiratory viruses. Robust evidence supporting this exists, but better comprehension could help implement adequate measures to mitigate respiratory viral infections. In severe viral lung infections, early diagnosis, risk stratification and prognosis are essential in managing patients. Biomarkers can provide reliable, timely and accessible information possibly helpful for clinicians in managing severe lung viral infections. Although respiratory viruses highly impact global health, more research is needed to improve care and prognosis of severe lung viral infections. In this review, we discuss the epidemiology, diagnosis, clinical characteristics, management and prognosis of patients with severe infections due to respiratory viruses.

Network pharmacology-based strategy for predicting therapy targets of Sanqi and Huangjing in diabetes mellitus

BACKGROUND

A comprehensive literature search shows that Sanqi and Huangjing (SQHJ) can improve diabetes treatment in vivo and in vitro, respectively. However, the combined effects of SQHJ on diabetes mellitus (DM) are still unclear.

AIM

To explore the potential mechanism of Panax notoginseng (Sanqi in Chinese) and Polygonati Rhizoma (Huangjing in Chinese) for the treatment of DM using network pharmacology.

METHODS

The active components of SQHJ and targets were predicted and screened by network pharmacology through oral bioavailability and drug-likeness filtration using the Traditional Chinese Medicine Systems Pharmacology Analysis Platform database. The potential targets for the treatment of DM were identified according to the DisGeNET database. A comparative analysis was performed to investigate the overlapping genes between active component targets and DM treatment-related targets. We constructed networks of the active component-target and target pathways of SQHJ using Cytoscape software and then analyzed the gene functions. Using the STRING database to perform an interaction analysis among overlapping genes and a topological analysis, the interactions between potential targets were identified. Gene Ontology (GO) function analyses and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted in DAVID.

RESULTS

We screened 18 active components from 157 SQHJ components, 187 potential targets for active components and 115 overlapping genes for active components and DM. The network pharmacology analysis revealed that quercetin, beta-sitosterol, baicalein, etc. were the major active components. The mechanism underlying the SQHJ intervention effects in DM may involve nine core targets (TP53, AKT1, CASP3, TNF, interleukin-6, PTGS2, MMP9, JUN, and MAPK1). The screening and enrichment analysis revealed that the treatment of DM using SQHJ primarily involved 16 GO enriched terms and 13 related pathways.

CONCLUSION

SQHJ treatment for DM targets TP53, AKT1, CASP3, and TNF and participates in pathways in leishmaniasis and cancer.

Perceived Changes in Emotions, Worries and Everyday Behaviors in Children and Adolescents Aged 5-18 Years with Type 1 Diabetes during the COVID-19 Pandemic

The COVID-19 pandemic and the consequent restrictive measures may be related to increased stress and anxiety and to changes in daily behaviors. Children with type 1 diabetes (T1D) are a vulnerable group due to their difficulties in achieving glycemic control and to their medical and psychological comorbidities. The purpose of the current study was to the investigate the changes on emotional and behavioral parameters in children with T1D due to the Coronavirus crisis. A total of 152 children and adolescents, aged 5−18, were studied: 114 (62 boys) with T1D and 38 (19 boys) healthy volunteers (HV) (controls). The study was performed at the Diabetes Center, Aghia Sofia Children’s Hospital, during the first national lockdown in Greece. The CRISIS questionnaire was completed by parents/caregivers. The data were collected in May 2020 and referred to two time-points: three months prior (before the pandemic), and the past two weeks. During the lockdown, it was observed significant aggravation in the “Emotion/Worries (EW)” symptoms in both groups (logEW-before vs. logEW-during the crisis, T1D: 2.66 ± 0.23 vs. 3.00 ± 0.21, p < 0.001 and HV: 2.62 ± 0.16 vs. 2.83 ± 0.18, p < 0.001). Deterioration of “ΕW” was recorded for 93.0% of those with T1D and 92.1% of the HV. “EW” during the lockdown were affected by: previous psychological condition, COVID-related concerns, and “Life Changes due to the COVID-19 crisis in the past two weeks (LC)”. Deterioration was observed in the “daily behaviors” and “use of digital media” for all of the children. The crisis and the associated restrictions negatively affected both the lifestyle parameters and the behavioral and emotional variables of the children with T1D.

COVID-19 Risk Prediction for Diabetic Patients Using Fuzzy Inference System and Machine Learning Approaches

Individuals with pre-existing diabetes seem to be vulnerable to the COVID-19 due to changes in blood sugar levels and diabetes complications. As observed globally, around 20-50% of individuals affected by coronavirus had diabetes. However, there is no recent finding that diabetic patients are more prone to contract COVID-19 than nondiabetic patients. However, a few recent findings have observed that it could be at least twice as likely to die from complications of diabetes. Considering the multifold mortality rate of COVID-19 in diabetic patients, this study proposes a COVID-19 risk prediction model for diabetic patients using a fuzzy inference system and machine learning approaches. This study aimed to estimate the risk level of COVID-19 in diabetic patients without a medical practitioner's advice for timely action and overcoming the multifold mortality rate of COVID-19 in diabetic patients. The proposed model takes eight input parameters, which were found as the most influential symptoms in diabetic patients. With the help of the various state-of-the-art machine learning techniques, fifteen models were built over the rule base. CatBoost classifier gives the best accuracy, recall, precision, F1 score, and kappa score. After hyper-parameter optimization, CatBoost classifier showed 76% accuracy and improvements in the recall, precision, F1 score, and kappa score, followed by logistic regression and XGBoost with 75.1% and 74.7% accuracy. Stratified k-fold cross-validation is used for validation purposes.

Integrated Nutritional Supports for Diabetic Patients During COVID-19 Infection: A Comprehensive Review

BACKGROUND

Diabetes mellitus is an endocrine metabolic disorder, which affects the major organs in human and comorbid with others. Besides, diabetic patients are more prone to various infectious diseases as well as COVID-19 sporadic infection which is a high risk for patients with diabetes mellitus. To combat these infections and comorbid situations, an integrated balanced nutritional supportive could help in maintaining sound health and increase immunity for prevention and management of such type of viral infections.

OBJECTIVES

While information regarding nutritional supports in COVID-19 pandemic in diabetic patients is not available, this review aimed to accumulate the evidence from previous publications where studied about nutrition-based supports or interventions for viral diseases with special emphasis on respiratory infections.

METHODS

For reviewing, searches are done for getting journal articles into Google Scholar, Pub Med/Medline, Database of Open Access Journal and Science Direct for relevant data and information.

RESULTS

Integrated nutritional supports of both macronutrients and micronutrients guidelines, including home-based physical exercise schedule, is summarized in this comprehensive review for possible prevention and management of diabetic patients in COVID-19 infections. The immuneboosting benefits of some vitamins, trace elements, nutraceuticals and probiotics in viral infections of diabetic patients are also included.

CONCLUSION

There is an urgent need for a healthy diet and integrated nutritional supports with home-based physical activities for diabetic patients during the self-isolation period of COVID-19 Infection.

Serum level of testosterone predicts disease severity of male COVID-19 patients and is related to T-cell immune modulation by transcriptome analysis

Background

Severe disease of COVID-19 and mortality occur more frequently in male patients than that in female patients may be related to testosterone level. However, the diagnostic value of changes in the level of testosterone in predicting severe disease of male COVID-19 patients has not been determined yet.

Methods

Sixty-one male COVID-19 patients admitted to the First Affiliated Hospital of Zhejiang University School of Medicine were enrolled. Serum samples at different stages of the patients after admission were collected and testosterone levels were detected to analyze the correlation between testosterone level and disease severity. Transcriptome analysis of PBMC was performed in 34 patients.

Results

Testosterone levels at admission in male non-ICU COVID-19 patients (3.7 nmol/L, IQR: 1.5 ∼ 4.7) were significantly lower than those in male ICU COVID-19 patients (6.7 nmol/L, IQR: 4.2 ∼ 8.7). Testosterone levels in the non-ICU group increased gradually during the progression of the disease, while those in the ICU group remained low. In addition, testosterone level of enrolled patients in the second week after onset was significantly correlated with the severity of pneumonia, and ROC curve showed that testosterone level in the second week after onset was highly effective in predicting the severity of COVID-19. Transcriptome studies have found that testosterone levels of COVID-19 patients were associated with immune response, including T cell activation and regulation of lymphocyte activation. In addition, CD28 and Inositol Polyphosphate-4-Phosphatase Type II B (INPP4B) were found positively correlated with testosterone.

Conclusions

Serum testosterone is an independent risk factor for predicting the severity of COVID-19 in male patients, and the level of serum testosterone in the second week after onset is valuable for evaluating the severity of COVID-19. Testosterone level is associated with T cell immune activation. The monitoring of serum testosterone should be highlighted in clinical treatment and the related mechanism should be further studied.

The severity and risk factors for mortality in immunocompromised adult patients hospitalized with influenza-related pneumonia

Objective

To explore disease severity and risk factors for 30-day mortality of adult immunocompromised (IC) patients hospitalized with influenza-related pneumonia (Flu-p).

Method

A total of 122 IC and 1191 immunocompetent patients hospitalized with Flu-p from January 2012 to December 2018 were recruited retrospectively from five teaching hospitals in China.

Results

After controlling for confounders, multivariate logistic regression analysis showed that immunosuppression was associated with increased risks for invasive ventilation [odds ratio: (OR) 2.475, 95% confidence interval (CI): 1.511–4.053, p < 0.001], admittance to the intensive care unit (OR: 3.247, 95% CI 2.064–5.106, p < 0.001), and 30-day mortality (OR: 3.206, 95% CI 1.926–5.335, p < 0.001) in patients with Flu-p. Another multivariate logistic regression model revealed that baseline lymphocyte counts (OR: 0.993, 95% CI 0.990–0.996, p < 0.001), coinfection (OR: 5.450, 95% CI 1.638–18.167, p = 0.006), early neuraminidase inhibitor therapy (OR 0.401, 95% CI 0.127–0.878, p = 0.001), and systemic corticosteroid use at admission (OR: 6.414, 95% CI 1.348–30.512, p = 0.020) were independently related to 30-day mortality in IC patients with Flu-p. Based on analysis of the receiver operating characteristic curve (ROC), the optimal cutoff for lymphocyte counts was 0.6 × 10⁹/L [area under the ROC (AUROC) = 0.824, 95% CI 0.744—0.887], sensitivity: 97.8%, specificity: 73.7%].

Conclusions

IC conditions are associated with more severe outcomes in patients with Flu-p. The predictors for mortality that we identified may be valuable for the management of Flu-p among IC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12941-021-00462-7.

Comorbidities and in-hospital death of viral pneumonia adults admitted to SUS (2002-2015)

OBJECTIVE

To identify demographic and clinical characteristics of adult patients hospitalized in the Brazilian Unified Health System (SUS) due to viral pneumonia and investigate the association between some comorbidities and death during hospitalization.

METHODS

This retrospective cohort study was conducted with secondary data of adults admitted to SUS due to viral pneumonia between 2002 and 2015. Patient profile was characterized based on demographic and clinical variables. The association between the ten Elixhauser comorbidities and in-hospital death was investigated using Poisson regression models with robust standard errors. Results were quantified as incidence rate ratio (IRR) with 95% confidence intervals (CI), and we built five models using successive inclusion of variables blocks.

RESULTS

Hospital admissions for viral pneumonias decreased throughout the study period, and it was observed that 5.8% of hospitalized patients had an in-hospital death. We observed significant differences in demographic and clinical characteristics by comparing individuals who died during hospitalization with those who did not, with the occurrence of one or more comorbidities being more expressive among patients who died. Although not considered risk factors for in-hospital death, chronic pulmonary disease and congestive heart failure were the most common comorbidities. Conversely, IRR for in-hospital death increased with other neurological disorders, diabetes, cancer, obesity, and especially with HIV/AIDS.

CONCLUSIONS

Individuals presenting with pulmonary and cardiovascular diseases require proper attention during hospitalization, as well as those with other neurological diseases, diabetes, cancer, obesity, and especially HIV/AIDS. Understanding the influence of chronic diseases on viral infections may support the healthcare system in achieving better outcomes.

Behavior of hospitalized severe influenza cases according to the outcome variable in Catalonia, Spain, during the 2017-2018 season

Influenza is an important cause of severe illness and death among patients with underlying medical conditions and in the elderly. The aim of this study was to investigate factors associated with ICU admission and death in patients hospitalized with severe laboratory-confirmed influenza during the 2017–2018 season in Catalonia. An observational epidemiological case-to-case study was carried out. Reported cases of severe laboratory-confirmed influenza requiring hospitalization in 2017–2018 influenza season were included. Mixed-effects regression analysis was used to estimate the factors associated with ICU admission and death. A total of 1306 cases of hospitalized severe influenza cases were included, of whom 175 (13.4%) died and 217 (16.6%) were ICU admitted. Age 65–74 years and ≥ 75 years and having ≥ 2 comorbidities were positively associated with death (aOR 3.19; 95%CI 1.19–8.50, aOR 6.95, 95%CI 2.76–1.80 and aOR 1.99; 95%CI 1.12–3.52, respectively). Neuraminidase inhibitor treatment and pneumonia were negatively associated with death. The 65–74 years and ≥ 75 years age groups were negatively associated with ICU admission (aOR 0.41; 95%CI 0.23–0.74 and aOR 0.30; 95%CI 0.17–0.53, respectively). A factor positively associated with ICU admission was neuraminidase inhibitor treatment. Our results support the need to investigate the worst outcomes of hospitalized severe cases, distinguishing between death and ICU admission.

Analysis of Pneumonia Occurrence in Relation to Climate Change in Tanga, Tanzania

In 2018, 70% of global fatalities due to pneumonia occurred in about fifteen countries, with Tanzania being among the top eight countries contributing to these deaths. Environmental and individual factors contributing to these deaths may be multifaceted, but they have not yet been explored in Tanzania. Therefore, in this study, we explore the association between climate change and the occurrence of pneumonia in the Tanga Region, Tanzania. A time series study design was employed using meteorological and health data of the Tanga Region collected from January 2016 to December 2018 from the Tanzania Meteorological Authority and Health Management Information System, respectively. The generalized negative binomial regression technique was used to explore the associations between climate indicators (i.e., precipitation, humidity, and temperature) and the occurrence of pneumonia. There were trend differences in climate indicators and the occurrence of pneumonia between the Tanga and Handeni districts. We found a positive association between humidity and increased rates of non-severe pneumonia (incidence rate ratio (IRR) = 1.01; 95% CI: 1.01–1.02; p ≤ 0.05) and severe pneumonia (IRR = 1.02; 95% CI: 1.01–1.03; p ≤ 0.05). There was also a significant association between cold temperatures and the rate of severe pneumonia in Tanga (IRR = 1.21; 95% CI: 1.11–1.33; p ≤ 0.001). Other factors that were associated with pneumonia included age and district of residence. We found a positive relationship between humidity, temperature, and incidence of pneumonia in the Tanga Region. Policies focusing on prevention and control, as well as promotion strategies relating to climate change-related health effects should be developed and implemented.

CANPT Score: A Tool to Predict Severe COVID-19 on Admission

Background and Aims: Patients with critical coronavirus disease 2019 (COVID-19) have a mortality rate higher than 50%. The purpose of this study was to establish a model for the prediction of the risk of severe disease and/or death in patients with COVID-19 on admission.

Materials and Methods: Patients diagnosed with COVID-19 in four hospitals in China from January 22, 2020 to April 15, 2020 were retrospectively enrolled. The demographic, laboratory, and clinical data of the patients with COVID-19 were collected. The independent risk factors related to the severity of and death due to COVID-19 were identified with a multivariate logistic regression; a nomogram and prediction model were established. The area under the receiver operating characteristic curve (AUROC) and predictive accuracy were used to evaluate the model's effectiveness.

Results: In total, 582 patients with COVID-19, including 116 patients with severe disease, were enrolled. Their comorbidities, body temperature, neutrophil-to-lymphocyte ratio (NLR), platelet (PLT) count, and levels of total bilirubin (Tbil), creatinine (Cr), creatine kinase (CK), and albumin (Alb) were independent risk factors for severe disease. A nomogram was generated based on these eight variables with a predictive accuracy of 85.9% and an AUROC of 0.858 (95% CI, 0.823–0.893). Based on the nomogram, the CANPT score was established with cut-off values of 12 and 16. The percentages of patients with severe disease in the groups with CANPT scores <12, ≥12, and <16, and ≥16 were 4.15, 27.43, and 69.64%, respectively. Seventeen patients died. NLR, Cr, CK, and Alb were independent risk factors for mortality, and the CAN score was established to predict mortality. With a cut-off value of 15, the predictive accuracy was 97.4%, and the AUROC was 0.903 (95% CI 0.832, 0.974).

Conclusions: The CANPT and CAN scores can predict the risk of severe disease and mortality in COVID-19 patients on admission.

CANPT Score: A Tool to Predict Severe COVID-19 on Admission

Background and Aims: Patients with critical coronavirus disease 2019 (COVID-19) have a mortality rate higher than 50%. The purpose of this study was to establish a model for the prediction of the risk of severe disease and/or death in patients with COVID-19 on admission. Materials and Methods: Patients diagnosed with COVID-19 in four hospitals in China from January 22, 2020 to April 15, 2020 were retrospectively enrolled. The demographic, laboratory, and clinical data of the patients with COVID-19 were collected. The independent risk factors related to the severity of and death due to COVID-19 were identified with a multivariate logistic regression; a nomogram and prediction model were established. The area under the receiver operating characteristic curve (AUROC) and predictive accuracy were used to evaluate the model's effectiveness. Results: In total, 582 patients with COVID-19, including 116 patients with severe disease, were enrolled. Their comorbidities, body temperature, neutrophil-to-lymphocyte ratio (NLR), platelet (PLT) count, and levels of total bilirubin (Tbil), creatinine (Cr), creatine kinase (CK), and albumin (Alb) were independent risk factors for severe disease. A nomogram was generated based on these eight variables with a predictive accuracy of 85.9% and an AUROC of 0.858 (95% CI, 0.823-0.893). Based on the nomogram, the CANPT score was established with cut-off values of 12 and 16. The percentages of patients with severe disease in the groups with CANPT scores <12, ≥12, and <16, and ≥16 were 4.15, 27.43, and 69.64%, respectively. Seventeen patients died. NLR, Cr, CK, and Alb were independent risk factors for mortality, and the CAN score was established to predict mortality. With a cut-off value of 15, the predictive accuracy was 97.4%, and the AUROC was 0.903 (95% CI 0.832, 0.974). Conclusions: The CANPT and CAN scores can predict the risk of severe disease and mortality in COVID-19 patients on admission.

National retrospective cohort study to identify risk factors for in-hospital 30-day lethality in laboratory-confirmed cases of influenza

OBJECTIVE

To identify factors associated with the risk of death in adolescent and adult inpatients with laboratory-positive (reverse-transcription polymerase chain reaction) influenza in Mexico during consecutive influenza seasons (2018-2020).

PATIENTS AND METHODS

A retrospective cohort study used national surveillance system data, enrolling 3422 individuals. The association between various risk factors and 30-day in-hospital lethality were evaluated through risk ratios (RR) and 95% confidence intervals (CI).

RESULTS

The lethality rate was 18.1%. Flu vaccination history (RR = 0.56, 95% CI 0.42-0.78), early antiviral drug administration (≤ two days from symptom onset [reference ≥ 5 days], RR = 0.68, 95% CI 0.58-0.81), and a history of asthma (RR = 0.66, 95% CI 0.47-0.95) showed protective effects against influenza-attributable death. Mechanical ventilator support produced the highest increase in death risk (RR = 3.31, 95% CI 2.89-3.79). Male sex, older age, AH1N1 subtype, and other chronic diseases were also associated with fatal in-hospital influenza-related outcomes.

CONCLUSIONS

Our findings highlight the major relevance of promoting immunization in high-risk individuals, together with ensuring early and effective antiviral management in suspected influenza cases.

Covid 19 death analysis in Colombia

Introduction: This article shows an analysis of the evolution up until date (May 4-2021), of official coronavirus cases statistics (CC) and the total number of deaths (TND) due to SARS-CoV-2 in Colombia. Additionally, said information is shown in correlation to other variables such as Case Fatality Rate (CFR), age range of persons, their typical reported co-morbidities and the cities where there has been highest concentration of cases. Materials and Methods: From March 16 2020 until today, information regarding the daily number of new confirmed cases (DNC) and daily confirmed deaths (DD) was registered in a database with the purpose of estimating the evolution of CC, TND and CFR. The age of deceased was also registered, as well as their gender, prior co-morbidities and city of death. The evolution of TND with the time of other countries were compared to that of Colombia. A mathematical equation that represents the epidemiological curve of TND evolution of different countries across time was defined. Results: In Colombia, the average age of people who die due to COVID-19 is of 69.5±14.7 years (median and mode of 71 and 80 years, respectively), and the virus is less lethal amongst a population under the age of 40. The greater part of deaths have taken place in people with prior co-morbidities and of the male gender. Conclusion: Most of the persons that have deceased are those of senior age, mainly with prior co-morbidities, and predominantly of male gender. Epidemiological peaks of COVID-19 are consistent with the rainy and winter seasons, and with the traditional epidemiological peaks of flu or influenza.

National retrospective cohort study to identify risk factors for in-hospital 30-day lethality in laboratory-confirmed cases of influenza

OBJECTIVE

To identify factors associated with the risk of death in adolescent and adult inpatients with laboratory-positive (reverse-transcription polymerase chain reaction) influenza in Mexico during consecutive influenza seasons (2018-2020).

METHODS

A retrospective cohort study used national surveillance system data, enrolling 3.422 individuals. The association between various risk factors and 30-day in-hospital lethality were evaluated through risk ratios (RRs) and 95% confidence intervals (CIs).

RESULTS

The lethality rate was 18.1%. Flu vaccination history (RR=0.56, 95% CI 0.42-0.78), early antiviral drug administration (≤2 days from symptom onset [reference ≥5 days], RR=0.68, 95% CI 0.58-0.81), and a history of asthma (RR=0.66, 95% CI 0.47-0.95) showed protective effects against influenza-attributable death. Mechanical ventilator support produced the highest increase in death risk (RR=3.31, 95% CI 2.89-3.79). Male sex, older age, AH1N1 subtype, and other chronic diseases were also associated with fatal in-hospital influenza-related outcomes.

CONCLUSIONS

Our findings highlight the major relevance of promoting immunization in high-risk individuals, together with ensuring early and effective antiviral management in suspected influenza cases.

Diabetic patients with COVID-19 need more attention and better glycemic control

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a pandemic disease spreading all over the world and has aroused global concerns. The increasing mortality has revealed its severity. It is important to distinguish severe patients and provide appropriate treatment and care to prevent damages. Diabetes is reported to be a common comorbidity in COVID-19 patients and associated with higher mortality. We attempted to clarify the relationship between diabetes and COVID-19 patients' severity.

AIM

To determine the role of type 2 diabetes in COVID-19 patients.

METHODS

To study the relationship between diabetes and COVID-19, we retrospectively collected 61 patients' data from a tertiary medical center in Wuhan. All the patients were diagnosed with laboratory-confirmed COVID-19 and admitted to the center from February 13 to March 1, 2020. Patients' age, sex, laboratory tests, chest computed tomography findings, capillary blood glucose (BG), and treatments were collected and analyzed. Fisher exact test was used for categorical data. Univariate and multivariate logistic regressions were used to explore the relationship between clinical characteristics and patients' severity.

RESULTS

In the 61 patients, the comorbidity of type 2 diabetes, hypertension, and heart diseases were 24.6% (15 out of 61), 37.7% (23 out of 61), and 11.5% (7 out of 61), respectively. The diabetic group was related to more invasive treatments (P = 0.02) and severe status (P = 0.003). In univariate logistic regression, histories of diabetes (OR = 7.13, P = 0.003), hypertension (OR = 3.41, P = 0.039), and hepatic dysfunction (OR = 7.69, P = 0.002) were predictors of patients' severity while heart disease (OR = 4.21, P = 0.083) and large lung involvement (OR = 2.70, P = 0.093) also slightly exacerbated patients' conditions. In the multivariate analysis, diabetes (OR = 6.29, P = 0.016) and hepatic dysfunction (OR = 5.88, P = 0.018) were risk factors for severe patients. Diabetic patients showed elevated BG in 61.7% of preprandial tests and 33.3% of postprandial tests, revealing the limited control of glycemia in COVID-19 patients.

CONCLUSION

A history of type 2 diabetes is correlated with invasive treatments and severe status. Suboptimal glycemic control and hepatic dysfunction have negative effects on severity status and may lead to the exacerbation of COVID-19 patients.

A Nomogram-Based Prediction for Severe Pneumonia in Patients with Coronavirus Disease 2019 (COVID-19)

Background

The outbreak of a novel coronavirus disease 2019 (COVID-19) is currently ongoing worldwide. A proportion of COVID-19 patients progress rapidly to acute respiratory failure.

Objective

We aimed to build a model to predict the risk of developing severe pneumonia in patients with COVID-19 in the early stage.

Methods

Data from patients who were confirmed to have COVID-19 and were admitted within 7 days from the onset of respiratory symptoms were retrospectively collected. The patients were classified into severe and non-severe groups according to the presence or absence of severe pneumonia during 1–2 weeks of follow-up. The clinical characteristics and laboratory indicators were screened by cross-validation based on LASSO regression to build a prediction model presented by a nomogram. The discrimination and stability, as well as the prediction performance of the model, were analysed.

Results

The neutrophil–lymphocyte ratio, monocyte counts, eosinophil percentage, serum lactate dehydrogenase level and history of diabetes mellitus were collected for the model. Bootstrap resampling showed the apparent C-statistics, and the brier scores were 0.929 and 0.098. The optimism of the C-statistics and brier score was 0.0172 and −0.019, respectively. The adjusted C-statistics and brier score were 0.9108 and 0.1169, respectively. The optimal cut-off value of the total nomogram score was determined to be 119 according to the maximal Youden index. The sensitivity, specificity, positive predictive value, and negative predictive value for differentiating the presence and absence of severe pneumonia were 83%, 89%, 74%, and 94%, respectively.

Conclusion

In our study, the neutrophil–lymphocyte ratio, monocyte counts, eosinophil percentage, serum lactate dehydrogenase level and history of diabetes mellitus showed great discrimination and stability for the prediction of the presence of severe pneumonia and were selected for the model.

The Effects of Diabetes and Hypertension on the Severity of COVID-19 - Yichang, Hubei Province, 2020

What is already known on this topic?

COVID-19 has become a serious public health issue. A higher proportion of severe patients were senior patients with underlying diseases such as diabetes and hypertension and had a lack of statistical evidence so far.

What is added by this report?

When severe illness was compared with non-severe illness, senior patients were at a greater risk (4.71) than young and middle-aged patients, as well as the odds ratio was about 2.99 patients with diabetes compared to patients without diabetes and hypertension. COVID-19-infectious senior patients with diabetes were inclined to suffer severe illness.

What are the implications for public health practice?

Much more attention should be provided for the elderly and individuals with diabetes, for which a community-based education and surveillance program could be considered.

Newly diagnosed diabetes is associated with a higher risk of mortality than known diabetes in hospitalized patients with COVID-19

AIM

To evaluate the association between different degrees of hyperglycaemia and the risk of all-cause mortality among hospitalized patients with COVID-19.

MATERIALS AND METHODS

In a retrospective study conducted from 22 January to 17 March 2020, 453 patients were admitted to Union Hospital in Wuhan, China, with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection. Patients were classified into four categories: normal glucose, hyperglycaemia (fasting glucose 5.6-6.9 mmol/L and/or HbA1c 5.7%-6.4%), newly diagnosed diabetes (fasting glucose ≥7 mmol/L and/or HbA1c ≥6.5%) and known diabetes. The major outcomes included in-hospital mortality, intensive care unit (ICU) admission and invasive mechanical ventilation (IMV).

RESULTS

Patients with newly diagnosed diabetes constituted the highest percentage to be admitted to the ICU (11.7%) and require IMV (11.7%), followed by patients with known diabetes (4.1%; 9.2%) and patients with hyperglycaemia (6.2%; 4.7%), compared with patients with normal glucose (1.5%; 2.3%), respectively. The multivariable-adjusted hazard ratios of mortality among COVID-19 patients with normal glucose, hyperglycaemia, newly diagnosed diabetes and known diabetes were 1.00, 3.29 (95% confidence interval [CI] 0.65-16.6), 9.42 (95% CI 2.18-40.7) and 4.63 (95% CI 1.02-21.0), respectively.

CONCLUSION

We showed that COVID-19 patients with newly diagnosed diabetes had the highest risk of all-cause mortality compared with COVID-19 patients with known diabetes, hyperglycaemia and normal glucose. Patients with COVID-19 need to be kept under surveillance for blood glucose screening.

Exposure to dipeptidyl-peptidase 4 inhibitors and the risk of pneumonia among people with type 2 diabetes: Retrospective cohort study and meta-analysis

AIM

Concerns have been raised that dipeptidyl-peptidase 4 inhibitors (DPP-4i) may increase the risk of pneumonia. We analysed observational data and clinical trials to explore whether use of DPP-4i modifies the risk of pneumonia.

METHODS

We identified patients with diabetes in the Veneto region administrative database and performed propensity score matching between new users of DPP-4 inhibitors and new users of other oral glucose-lowering medications (OGLMs). We compared the rate of hospitalization for pneumonia between matched cohorts using the Cox proportional hazard model. The same analysis was repeated using the database of a local diabetes outpatient clinic. We retrieved similar observational studies from the literature to perform a meta-analysis. Results from trials reporting pneumonia rates among patients randomized to DPP-4 inhibitors versus placebo/active comparators were also meta-analysed.

RESULTS

In the regional database, after matching 6495 patients/group, new users of DPP-4 inhibitors had a lower rate of hospitalization for pneumonia than new users of other OGLMs (HR 0.76; 95% CI 0.61-0.95). In the outpatient database, after matching 867 patients/group, new users of DPP-4 inhibitors showed a non-significantly lower rate of hospitalization for pneumonia (HR 0.65; 95% CI 0.41-1.04). The meta-analysis of observational studies yielded an overall non-significant lower risk of hospitalization for pneumonia among DPP-4 inhibitor users (RR 0.81; 95% CI 0.65-1.01). The meta-analysis of randomized controlled trials showed no overall effect of DPP-4 inhibitors on pneumonia risk (RR 1.06; 95% CI 0.93-1.20).

CONCLUSION

The use of DPP-4 inhibitors can be considered as safe with regard to the risk of pneumonia.

Coronavirus disease 2019 (COVID-19) and obesity. Impact of obesity and its main comorbidities in the evolution of the disease

The COVID-19 pandemic is posing a great challenge worldwide. Its rapid progression has caused thousands of deaths worldwide. Although multiple aspects remain to be clarified, some risk factors associated with a worse prognosis have been identified. These include obesity and some of its main complications, such as diabetes and high blood pressure. Furthermore, although the possible long-term complications and psychological effects that may appear in survivors of COVID-19 are not well known yet, there is a concern that those complications may be greater in obese patients. In this manuscript, we review some of the data published so far and the main points that remain to be elucidated are emphasized.

Effects and safety of Tanreqing injection on viral pneumonia: A protocol for systematic review and meta-analysis

BACKGROUND

Influenza-related viral pneumonia is a severe threat to human health, which has caused high morbidity and mortality each year. The objective of this study was to assess the efficacy and safety of Tanreqing Injection therapy in patients with viral pneumonia.

MATERIALS AND METHODS

This protocol established in this study has been reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Web of Science, PubMed, EMBASE and the Cochrane Library were searched for clinical randomized trials in cases with viral pneumonia until 1st of July 2020. We will use a combination of Medical Subject Heading and free-text terms with various synonyms to search based on the Eligibility criteria. Two investigators independently reviewed the included studies and extracted relevant data. The relative risk (RR) and 95% confidence intervals (CIs) of were used as effect estimate. I-square (I) test, substantial heterogeneity, sensitivity analysis and publication bias assessment will be performed accordingly. Stata 14.0 and Review Manger 5.3 are used for meta-analysis and systematic review.

RESULTS

The results will be published in a peer-reviewed journal.

CONCLUSION

The results of this review will be widely disseminated through peer-reviewed publications and conference presentations. This evidence may also provide helpful evidence of whether Tanreqing Injection therapy was efficient and safe in patients with viral pneumonia.

PROSPERO REGISTRATION NUMBER

CRD42020164164.

Diabetes and CoViD-19: Experience from the frontline of Internal Medicine wards in Italy

Available data suggest that the issue of CoViD-19 is particularly critical in patients with diabetes. In Italy, Internal Medicine (IM) wards have played a pivotal role in contrasting the spread of SARS-Cov2. During this pandemic, FADOI submitted a brief questionnaire to a group of its members acting as Head of IM units. Considering 38 units, 58% of beds dedicated to CoViD patients in CoViD Hospitals were in charge of IM, and globally cared for 6650 patients during a six-week period. Of these patients, 1264 (19%) had diabetes. Mortality rate in CoViD patients with or without diabetes were 20.5% and 14%, respectively (p < 0.001). Our survey seems to confirm that diabetes is a major comorbidity of CoViD-19, but it does not support an increased incidence of CoViD-19 infection in people with diabetes, if compared with the figures of patients with diabetes and hospitalized before the outbreak. On the other side, patients with diabetes appeared at a significantly increased risk of worse outcome. This finding underlines the importance of paying special attention to this patient population and its management.

Practical recommendations for the management of diabetes in patients with COVID-19

Diabetes is one of the most important comorbidities linked to the severity of all three known human pathogenic coronavirus infections, including severe acute respiratory syndrome coronavirus 2. Patients with diabetes have an increased risk of severe complications including Adult Respiratory Distress Syndrome and multi-organ failure. Depending on the global region, 20-50% of patients in the coronavirus disease 2019 (COVID-19) pandemic had diabetes. Given the importance of the link between COVID-19 and diabetes, we have formed an international panel of experts in the field of diabetes and endocrinology to provide some guidance and practical recommendations for the management of diabetes during the pandemic. We aim to briefly provide insight into potential mechanistic links between the novel coronavirus infection and diabetes, present practical management recommendations, and elaborate on the differential needs of several patient groups.

COVID-19 in diabetic patients: Related risks and specifics of management

Diabetes is among the most frequently reported comorbidities in patients infected with COVID-19. According to current data, diabetic patients do not appear to be at increased risk of contracting SARS-CoV-2 compared to the general population. On the other hand, diabetes is a risk factor for developing severe and critical forms of COVID-19, the latter requiring admission to an intensive care unit and/or use of invasive mechanical ventilation, with high mortality rates. The characteristics of diabetic patients at risk for developing severe and critical forms of COVID-19, as well as the prognostic impact of diabetes on the course of COVID-19, are under current investigation. Obesity, the main risk factor for incident type 2 diabetes, is more common in patients with critical forms of COVID-19 requiring invasive mechanical ventilation. On the other hand, COVID-19 is usually associated with poor glycemic control and a higher risk of ketoacidosis in diabetic patients. There are currently no recommendations in favour of discontinuing antihypertensive medications that interact with the renin-angiotensin-aldosterone system. Metformin and SGLT2 inhibitors should be discontinued in patients with severe forms of COVID-19 owing to the risks of lactic acidosis and ketoacidosis. Finally, we advise for systematic screening for (pre)diabetes in patients with proven COVID-19 infection.

Risk-adapted Treatment Strategy For COVID-19 Patients

•

There are no clear expert consensus or guidelines on how to treat COVID-19.

•

We developed a risk-adapted treatment approach according to the illness severity.

•

This strategy was effective in symptoms alleviation and chest CT recovery.

•

This strategy is a useful and efficient approach for COVID-19 patients.

Background

There are no clear expert consensus or guidelines on how to treat 2019 coronavirus disease (COVID-19). The objective of this study is to investigate the short-term effect of risk-adapted treatment strategy on patients with COVID-19.

Methods

We collected the medical records of 55 COVID-19 patients for analysis. We divided these patients into mild, moderate and severe groups, and risk-adapted treatment approaches were given according to the illness severity.

Results

Twelve patients were in mild group and 22 were in moderate group (non-severe group, n = 34), and 21 patients were in severe group. At the end of the first two weeks after admission, clinical manifestations had completely despeared in 31(91.2%)patients in non-severe group, and 18(85.7%) patients in severe group (p = 0.85). Both groups had a satisfied chest CT imaging recovery, which includes 22(64.7%) patients in non-severe group and 12(57.1%) patients in severe group recovered at least 50% of the whole leisions in the first week, and 28(82.4%) and 16(76.2%) recovered at least 75% in the second week, respectively. There were no significant differences in SARS-CoV-2 nucleic acid negativity (p = 0.92). There were also no significant differences in the levels of SARS-CoV-2-IgM and IgG antibody production between the two groups (p = 0.13, 0.62). There were 45 cases were discharged from the hospital, and no patients died at the time of this clinical analysis.

Conclusions

Risk-adapted treatment strategy was associated with significant clinical manifestations alleviation and clinical imaging recovery. In severe COVID-19 patients, early and short-term use of low-dose methylprednisolone was beneficial and did not delay SARS-CoV-2 nucleic acid clearance and influence IgG antibody production.