[Characteristics of peripheral blood leukocyte differential counts in patients with COVID-19]

Can the Cytokine Profile According to ABO Blood Groups Be Related to Worse Outcome in COVID-19 Patients? Yes, They Can

Severe status of coronavirus disease 2019 (COVID-19) is extremely associated to cytokine release. Moreover, it has been suggested that blood group is also associated with the prevalence and severity of this disease. However, the relationship between the cytokine profile and blood group remains unclear in COVID-19 patients. In this sense, we prospectively recruited 108 COVID-19 patients between March and April 2020 and divided according to ABO blood group. For the analysis of 45 cytokines, plasma samples were collected in the time of admission to hospital ward or intensive care unit and at the sixth day after hospital admission. The results show that there was a risk of more than two times lower of mechanical ventilation or death in patients with blood group O (log rank: p = 0.042). At first time, all statistically significant cytokine levels, except from hepatocyte growth factor, were higher in O blood group patients meanwhile the second time showed a significant drop, between 20% and 40%. In contrast, A/B/AB group presented a maintenance of cytokine levels during time. Hepatocyte growth factor showed a significant association with intubation or mortality risk in non-O blood group patients (OR: 4.229, 95% CI (2.064-8.665), p < 0.001) and also was the only one bad prognosis biomarker in O blood group patients (OR: 8.852, 95% CI (1.540-50.878), p = 0.015). Therefore, higher cytokine levels in O blood group are associated with a better outcome than A/B/AB group in COVID-19 patients.

New segmentation and feature extraction algorithm for classification of white blood cells in peripheral smear images

This article addresses a new method for the classification of white blood cells (WBCs) using image processing techniques and machine learning methods. The proposed method consists of three steps: detecting the nucleus and cytoplasm, extracting features, and classification. At first, a new algorithm is designed to segment the nucleus. For the cytoplasm to be detected, only a part of it located inside the convex hull of the nucleus is involved in the process. This attitude helps us overcome the difficulties of segmenting the cytoplasm. In the second phase, three shapes and four novel color features are devised and extracted. Finally, by using an SVM model, the WBCs are classified. The segmentation algorithm can detect the nucleus with a dice similarity coefficient of 0.9675. The proposed method can categorize WBCs in Raabin-WBC, LISC, and BCCD datasets with accuracies of 94.65%, 92.21%, and 94.20%, respectively. Besides, we show that the proposed method possesses more generalization power than pre-trained CNN models. It is worth mentioning that the hyperparameters of the classifier are fixed only with the Raabin-WBC dataset, and these parameters are not readjusted for LISC and BCCD datasets.

HGF, IL-1α, and IL-27 Are Robust Biomarkers in Early Severity Stratification of COVID-19 Patients

Pneumonia is the leading cause of hospital admission and mortality in coronavirus disease 2019 (COVID-19). We aimed to identify the cytokines responsible for lung damage and mortality. We prospectively recruited 108 COVID-19 patients between March and April 2020 and divided them into four groups according to the severity of respiratory symptoms. Twenty-eight healthy volunteers were used for normalization of the results. Multiple cytokines showed statistically significant differences between mild and critical patients. High HGF levels were associated with the critical group (OR = 3.51; p < 0.001; 95%CI = 1.95-6.33). Moreover, high IL-1α (OR = 1.36; p = 0.01; 95%CI = 1.07-1.73) and low IL-27 (OR = 0.58; p < 0.005; 95%CI = 0.39-0.85) greatly increased the risk of ending up in the severe group. This model was especially sensitive in order to predict critical status (AUC = 0.794; specificity = 69.74%; sensitivity = 81.25%). Furthermore, high levels of HGF and IL-1α showed significant results in the survival analysis (p = 0.033 and p = 0.011, respectively). HGF, IL-1α, and IL 27 at hospital admission were strongly associated with severe/critical COVID-19 patients and therefore are excellent predictors of bad prognosis. HGF and IL-1α were also mortality biomarkers.

Early hematological indicators of severe COVID-19 disease in hospitalized patients: Data from a South Asian population

Introduction

Outbreak of corona virus disease in 2019 (COVID‐19) has resulted in significant morbidity and mortality worldwide. Our aim is to document hematological parameters of patients with COVID‐19 during initial stage of diagnosis and to identify early hematological indicators of severe infection.

Materials and methods

This retrospective study was conducted at Shifa International Hospital, Pakistan from April to November 2020. Patients hospitalized with COVID‐19, diagnosed on RT‐PCR and had a complete blood count (CBC) done within 48 hours of diagnosis were included. Data was analyzed using IBM^® SPSS Statistics.

Results

A total of 425 patients were included in this study out of whom 272(64%) were males. The mean age was 55.61 ± 17.84 years. 95 patients (22.4%) had normal blood counts within 48 hours of COVID‐19 diagnosis. Cytopenias were seen in 193(45.4%) patients. There were 75(17.6%) mortalities during the study period. Chi‐square test showed that thrombocytopenia, lymphopenia and neutrophilic leucocytosis were significantly associated with mortality (P = .037, P < .001, P < .001 respectively) and need for ventilator (P = .009, P < .001, P < .001, respectively). Neutrophilia was also associated with development of Acute Respiratory Distress Syndrome (P < .001). On ROC analysis, Neutrophil‐to‐Lymphocyte Ratio yielded an area under the curve (AUC) of 0.693 and 0.660 for the outcomes mortality and need for ventilator, respectively. For a subset of 288 patients who had D‐dimer levels checked within 48 hours of COVID‐19 diagnosis, the AUC for mortality and ventilator need was 0.708 and 0.671, respectively.

Conclusion

Hematological indices are vital indicators in the prognosis and risk stratification of COVID‐19 during initial stages of disease.

SARS-CoV-2 engages inflammasome and pyroptosis in human primary monocytes

Infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been associated with leukopenia and uncontrolled inflammatory response in critically ill patients. A better comprehension of SARS-CoV-2-induced monocyte death is essential for the identification of therapies capable to control the hyper-inflammation and reduce viral replication in patients with 2019 coronavirus disease (COVID-19). Here, we show that SARS-CoV-2 engages inflammasome and triggers pyroptosis in human monocytes, experimentally infected, and from patients under intensive care. Pyroptosis associated with caspase-1 activation, IL-1ß production, gasdermin D cleavage, and enhanced pro-inflammatory cytokine levels in human primary monocytes. At least in part, our results originally describe mechanisms by which monocytes, a central cellular component recruited from peripheral blood to respiratory tract, succumb to control severe COVID-19.

SARS-CoV-2 engages inflammasome and pyroptosis in human primary monocytes

Infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been associated with leukopenia and uncontrolled inflammatory response in critically ill patients. A better comprehension of SARS-CoV-2-induced monocyte death is essential for the identification of therapies capable to control the hyper-inflammation and reduce viral replication in patients with 2019 coronavirus disease (COVID-19). Here, we show that SARS-CoV-2 engages inflammasome and triggers pyroptosis in human monocytes, experimentally infected, and from patients under intensive care. Pyroptosis associated with caspase-1 activation, IL-1ß production, gasdermin D cleavage, and enhanced pro-inflammatory cytokine levels in human primary monocytes. At least in part, our results originally describe mechanisms by which monocytes, a central cellular component recruited from peripheral blood to respiratory tract, succumb to control severe COVID-19.

Pre-test probability for SARS-Cov-2-related infection score: The PARIS score

INTRODUCTION

In numerous countries, large population testing is impossible due to the limited availability of RT-PCR kits and CT-scans. This study aimed to determine a pre-test probability score for SARS-CoV-2 infection.

METHODS

This multicenter retrospective study (4 University Hospitals) included patients with clinical suspicion of SARS-CoV-2 infection. Demographic characteristics, clinical symptoms, and results of blood tests (complete white blood cell count, serum electrolytes and CRP) were collected. A pre-test probability score was derived from univariate analyses of clinical and biological variables between patients and controls, followed by multivariate binary logistic analysis to determine the independent variables associated with SARS-CoV-2 infection.

RESULTS

605 patients were included between March 10th and April 30th, 2020 (200 patients for the training cohort, 405 consecutive patients for the validation cohort). In the multivariate analysis, lymphocyte (<1.3 G/L), eosinophil (<0.06 G/L), basophil (<0.04 G/L) and neutrophil counts (<5 G/L) were associated with high probability of SARS-CoV-2 infection but no clinical variable was statistically significant. The score had a good performance in the validation cohort (AUC = 0.918 (CI: [0.891-0.946]; STD = 0.014) with a Positive Predictive Value of high-probability score of 93% (95%CI: [0.89-0.96]). Furthermore, a low-probability score excluded SARS-CoV-2 infection with a Negative Predictive Value of 98% (95%CI: [0.93-0.99]). The performance of the score was stable even during the last period of the study (15-30th April) with more controls than infected patients.

CONCLUSIONS

The PARIS score has a good performance to categorize the pre-test probability of SARS-CoV-2 infection based on complete white blood cell count. It could help clinicians adapt testing and for rapid triage of patients before test results.

Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data

BACKGROUND

Reverse Transcription-Polymerase Chain Reaction (RT-PCR) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) diagnosis currently requires quite a long time span. A quicker and more efficient diagnostic tool in emergency departments could improve management during this global crisis. Our main goal was assessing the accuracy of artificial intelligence in predicting the results of RT-PCR for SARS-COV-2, using basic information at hand in all emergency departments.

METHODS

This is a retrospective study carried out between February 22, 2020 and March 16, 2020 in one of the main hospitals in Milan, Italy. We screened for eligibility all patients admitted with influenza-like symptoms tested for SARS-COV-2. Patients under 12 years old and patients in whom the leukocyte formula was not performed in the ED were excluded. Input data through artificial intelligence were made up of a combination of clinical, radiological and routine laboratory data upon hospital admission. Different Machine Learning algorithms available on WEKA data mining software and on Semeion Research Centre depository were trained using both the Training and Testing and the K-fold cross-validation protocol.

RESULTS

Among 199 patients subject to study (median [interquartile range] age 65 [46-78] years; 127 [63.8%] men), 124 [62.3%] resulted positive to SARS-COV-2. The best Machine Learning System reached an accuracy of 91.4% with 94.1% sensitivity and 88.7% specificity.

CONCLUSION

Our study suggests that properly trained artificial intelligence algorithms may be able to predict correct results in RT-PCR for SARS-COV-2, using basic clinical data. If confirmed, on a larger-scale study, this approach could have important clinical and organizational implications.

Routine laboratory testing to determine if a patient has COVID-19

BACKGROUND

Specific diagnostic tests to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and resulting COVID-19 disease are not always available and take time to obtain results. Routine laboratory markers such as white blood cell count, measures of anticoagulation, C-reactive protein (CRP) and procalcitonin, are used to assess the clinical status of a patient. These laboratory tests may be useful for the triage of people with potential COVID-19 to prioritize them for different levels of treatment, especially in situations where time and resources are limited.

OBJECTIVES

To assess the diagnostic accuracy of routine laboratory testing as a triage test to determine if a person has COVID-19.

SEARCH METHODS

On 4 May 2020 we undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions.

SELECTION CRITERIA

We included both case-control designs and consecutive series of patients that assessed the diagnostic accuracy of routine laboratory testing as a triage test to determine if a person has COVID-19. The reference standard could be reverse transcriptase polymerase chain reaction (RT-PCR) alone; RT-PCR plus clinical expertise or and imaging; repeated RT-PCR several days apart or from different samples; WHO and other case definitions; and any other reference standard used by the study authors.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data from each included study. They also assessed the methodological quality of the studies, using QUADAS-2. We used the 'NLMIXED' procedure in SAS 9.4 for the hierarchical summary receiver operating characteristic (HSROC) meta-analyses of tests for which we included four or more studies. To facilitate interpretation of results, for each meta-analysis we estimated summary sensitivity at the points on the SROC curve that corresponded to the median and interquartile range boundaries of specificities in the included studies.

MAIN RESULTS

We included 21 studies in this review, including 14,126 COVID-19 patients and 56,585 non-COVID-19 patients in total. Studies evaluated a total of 67 different laboratory tests. Although we were interested in the diagnotic accuracy of routine tests for COVID-19, the included studies used detection of SARS-CoV-2 infection through RT-PCR as reference standard. There was considerable heterogeneity between tests, threshold values and the settings in which they were applied. For some tests a positive result was defined as a decrease compared to normal vaues, for other tests a positive result was defined as an increase, and for some tests both increase and decrease may have indicated test positivity. None of the studies had either low risk of bias on all domains or low concerns for applicability for all domains. Only three of the tests evaluated had a summary sensitivity and specificity over 50%. These were: increase in interleukin-6, increase in C-reactive protein and lymphocyte count decrease. Blood count Eleven studies evaluated a decrease in white blood cell count, with a median specificity of 93% and a summary sensitivity of 25% (95% CI 8.0% to 27%; very low-certainty evidence). The 15 studies that evaluated an increase in white blood cell count had a lower median specificity and a lower corresponding sensitivity. Four studies evaluated a decrease in neutrophil count. Their median specificity was 93%, corresponding to a summary sensitivity of 10% (95% CI 1.0% to 56%; low-certainty evidence). The 11 studies that evaluated an increase in neutrophil count had a lower median specificity and a lower corresponding sensitivity. The summary sensitivity of an increase in neutrophil percentage (4 studies) was 59% (95% CI 1.0% to 100%) at median specificity (38%; very low-certainty evidence). The summary sensitivity of an increase in monocyte count (4 studies) was 13% (95% CI 6.0% to 26%) at median specificity (73%; very low-certainty evidence). The summary sensitivity of a decrease in lymphocyte count (13 studies) was 64% (95% CI 28% to 89%) at median specificity (53%; low-certainty evidence). Four studies that evaluated a decrease in lymphocyte percentage showed a lower median specificity and lower corresponding sensitivity. The summary sensitivity of a decrease in platelets (4 studies) was 19% (95% CI 10% to 32%) at median specificity (88%; low-certainty evidence). Liver function tests The summary sensitivity of an increase in alanine aminotransferase (9 studies) was 12% (95% CI 3% to 34%) at median specificity (92%; low-certainty evidence). The summary sensitivity of an increase in aspartate aminotransferase (7 studies) was 29% (95% CI 17% to 45%) at median specificity (81%) (low-certainty evidence). The summary sensitivity of a decrease in albumin (4 studies) was 21% (95% CI 3% to 67%) at median specificity (66%; low-certainty evidence). The summary sensitivity of an increase in total bilirubin (4 studies) was 12% (95% CI 3.0% to 34%) at median specificity (92%; very low-certainty evidence). Markers of inflammation The summary sensitivity of an increase in CRP (14 studies) was 66% (95% CI 55% to 75%) at median specificity (44%; very low-certainty evidence). The summary sensitivity of an increase in procalcitonin (6 studies) was 3% (95% CI 1% to 19%) at median specificity (86%; very low-certainty evidence). The summary sensitivity of an increase in IL-6 (four studies) was 73% (95% CI 36% to 93%) at median specificity (58%) (very low-certainty evidence). Other biomarkers The summary sensitivity of an increase in creatine kinase (5 studies) was 11% (95% CI 6% to 19%) at median specificity (94%) (low-certainty evidence). The summary sensitivity of an increase in serum creatinine (four studies) was 7% (95% CI 1% to 37%) at median specificity (91%; low-certainty evidence). The summary sensitivity of an increase in lactate dehydrogenase (4 studies) was 25% (95% CI 15% to 38%) at median specificity (72%; very low-certainty evidence).

AUTHORS' CONCLUSIONS

Although these tests give an indication about the general health status of patients and some tests may be specific indicators for inflammatory processes, none of the tests we investigated are useful for accurately ruling in or ruling out COVID-19 on their own. Studies were done in specific hospitalized populations, and future studies should consider non-hospital settings to evaluate how these tests would perform in people with milder symptoms.

COVID-19 in two severe asthmatics receiving benralizumab: busting the eosinophilia myth

Amidst the current pandemic there is only little clinical evidence regarding COVID-19 infections in asthma patients. Chinese data suggests that asthma patients might not be at an elevated risk of severe infections [1, 2]. A recent article by Carliet al. [3] hypothesises that asthma might even have a protective effect in COVID-19 infections. It is important to point out that this is purely theoretical. Eosinophils from healthy probands have antiviral activity against respiratory syncytial virus and influenza virus, but not eosinophils collected from asthma patients [4]. Eosinopenia, alongside lymphopenia has been seen in COVID-19 patients [2]. Both eosinopenia and lymphopenia are more common in patients with COVID-19 pneumonitis compared with patients with non-COVID-19 viral pneumonitis [5]. Azkuret al. [6] attribute this to an overwhelming type 1 response.

Experience with very mild #COVID19 disease courses in two severe eosinophilic asthmatics with complete eosinophil depletion due to benralizumab treatment counters the recent theories that eosinophilia is protective in COVID-19 infectionshttps://bit.ly/3cnEFvg

Clinical, laboratory and radiological characteristics and outcomes of novel coronavirus (SARS-CoV-2) infection in humans: A systematic review and series of meta-analyses

New evidence on the COVID-19 pandemic is being published daily. Ongoing high-quality assessment of this literature is therefore needed to enable clinical practice to be evidence-based. This review builds on a previous scoping review and aimed to identify associations between disease severity and various clinical, laboratory and radiological characteristics. We searched MEDLINE, CENTRAL, EMBASE, Scopus and LILACS for studies published between January 1, 2019 and March 22, 2020. Clinical studies including ≥10 patients with confirmed COVID-19 of any study design were eligible. Two investigators independently extracted data and assessed risk of bias. A quality effects model was used for the meta-analyses. Subgroup analysis and meta-regression identified sources of heterogeneity. For hospitalized patients, studies were ordered by overall disease severity of each population and this order was used as the modifier variable in meta-regression. Overall, 86 studies (n = 91,621) contributed data to the meta-analyses. Severe disease was strongly associated with fever, cough, dyspnea, pneumonia, any computed tomography findings, any ground glass opacity, lymphocytopenia, elevated C-reactive protein, elevated alanine aminotransferase, elevated aspartate aminotransferase, older age and male sex. These variables typically increased in prevalence by 30-73% from mild/early disease through to moderate/severe disease. Among hospitalized patients, 30-78% of heterogeneity was explained by severity of disease. Elevated white blood cell count was strongly associated with more severe disease among moderate/severe hospitalized patients. Elevated lymphocytes, low platelets, interleukin-6, erythrocyte sedimentation rate and D-dimers showed potential associations, while fatigue, gastrointestinal symptoms, consolidation and septal thickening showed non-linear association patterns. Headache and sore throat were associated with the presence of disease, but not with more severe disease. In COVID-19, more severe disease is strongly associated with several clinical, laboratory and radiological characteristics. Symptoms and other variables in early/mild disease appear non-specific and highly heterogeneous. Clinical Trial Registration: PROSPERO CRD42020170623.

Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis

INTRODUCTION

Since December 2019, a novel coronavirus (SARS-CoV-2) has triggered a world-wide pandemic with an enormous medical and societal-economic toll. Thus, our aim was to gather all available information regarding comorbidities, clinical signs and symptoms, outcomes, laboratory findings, imaging features, and treatments in patients with coronavirus disease 2019 (COVID-19).

METHODS

EMBASE, PubMed/Medline, Scopus, and Web of Science were searched for studies published in any language between December 1st, 2019 and March 28th, 2020. Original studies were included if the exposure of interest was an infection with SARS-CoV-2 or confirmed COVID-19. The primary outcome was the risk ratio of comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatments, outcomes, and complications associated with COVID-19 morbidity and mortality. We performed random-effects pairwise meta-analyses for proportions and relative risks, I2, T2, and Cochrane Q, sensitivity analyses, and assessed publication bias.

RESULTS

148 studies met the inclusion criteria for the systematic review and meta-analysis with 12'149 patients (5'739 female) and a median age of 47.0 [35.0-64.6] years. 617 patients died from COVID-19 and its complication. 297 patients were reported as asymptomatic. Older age (SMD: 1.25 [0.78-1.72]; p < 0.001), being male (RR = 1.32 [1.13-1.54], p = 0.005) and pre-existing comorbidity (RR = 1.69 [1.48-1.94]; p < 0.001) were identified as risk factors of in-hospital mortality. The heterogeneity between studies varied substantially (I2; range: 1.5-98.2%). Publication bias was only found in eight studies (Egger's test: p < 0.05).

CONCLUSIONS

Our meta-analyses revealed important risk factors that are associated with severity and mortality of COVID-19.

The underlying changes and predicting role of peripheral blood inflammatory cells in severe COVID-19 patients: A sentinel?

BACKGROUND

The underlying changes of peripheral blood inflammatory cells (PBICs) in COVID-19 patients are little known. Moreover, the risk factors for the underlying changes of PBICs and their predicting role in severe COVID-19 patients remain uncertain.

MATERIAL AND METHODS

This retrospective study including two cohorts: the main cohort enrolling 45 patients of severe type serving as study group, and the secondary cohort enrolling 12 patients of no-severe type serving as control group. The PBICs analysis was based on blood routine and lymphocyte subsets. The inflammatory cell levels were compared among patients according to clinical classifications, disease-associated phases, as well as one-month outcomes.

RESULTS

Compared with patients of non-severe type, the patients of severe type suffered from significantly decreased counts of lymphocytes, eosinophils, basophils, but increased counts of neutrophils. These PBICs alterations got improved in recovery phase, but persisted or got worse in aggravated phase. Compared with patients in discharged group, the patients in un-discharged/died group suffered from decreased counts of total T lymphocytes, CD4 + T lymphocytes, CD8 + T lymphocytes, as well as NK cells at 2 weeks after treatment. Clinical classification-critically severe was the independently risk factor for lymphopenia (OR = 7.701, 95%CI:1.265-46.893, P = 0.027), eosinopenia (OR = 5.595, 95%CI:1.008-31.054, P = 0.049), and worse one-month outcome (OR = 8.984; 95%CI:1.021-79.061, P = 0.048).

CONCLUSION

Lymphopenia and eosinopenia may serve as predictors of disease severity and disease progression in COVID-19 patients, and enhancing the cellular immunity may contribute to COVID-19 treatment. Thus, PBICs might become a sentinel of COVID-19, and it deserves attention during COVID-19 treatment.

Safe and informed prescribing of psychotropic medication during the COVID-19 pandemic

Treatment with psychotropic medication may sometimes be jeopardised because of the COVID-19 pandemic. One underlying reason is the lack of COVID-19-specific psychopharmacology guidelines. Here, we discuss five considerations arising from our clinical experience and pharmacological background knowledge to enable safe and well-informed psychopharmacotherapy during the COVID-19 pandemic.

The Novel Coronavirus Disease (COVID-19): A PRISMA Systematic Review and Meta-Analysis of Clinical and Paraclinical Characteristics

An outbreak of pneumonia, caused by a novel coronavirus (SARS-CoV-2), was identified in China in December 2019. This virus expanded worldwide, causing global concern. Although clinical, laboratory, and imaging features of COVID-19 are characterized in some observational studies, we undertook a systematic review and meta-analysis to assess the frequency of these features. We did a systematic review and meta-analysis using three databases to identify clinical, laboratory, and computerized tomography (CT) scanning features of rRT-PCR confirmed cases of COVID-19. Data for 3420 patients from 30 observational studies were included. Overall, the results showed that fever (84.2%, 95% CI 82.6-85.7), cough (62%, 95% CI 60-64), and fatigue (39.4%, 95% CI 37.2-41.6%) are the most prevalent symptoms in COVID-19 patients. Increased CRP level, decreased lymphocyte count, and increased D-dimer level were the most common laboratory findings. Among COVID-19 patients, 92% had a positive CT finding, most prevalently ground-glass opacification (GGO) (60%, 95% CI 58-62) and peripheral distribution opacification (64%, 95% CI 60-69). These results demonstrate the clinical, paraclinical, and imaging features of COVID-19.

The role of Chinese medicine in COVID-19 pneumonia: A systematic review and meta-analysis

INTRODUCTION

Chinese medicine (CM) has been used to treat Novel Coronavirus 2019 (COVID-19) pneumonia in China. This meta-analysis was conducted to evaluate the clinical efficacy and safety of CM in the treatment of COVID-19 pneumonia.

METHODS

Randomized controlled trials (RCTs) involving CM in the treatment of COVID-19 pneumonia were identified from Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Chinese National Knowledge Infrastructure, Chinese Biomedical Database, Wanfang Database and VIP Information Database. The methodological quality of trials was evaluated with Cochrane Hanadbook criteria, and the Cochrane Collaboration's Review Manager 5.3 software was used for meta-analysis.

RESULTS

A total of 7 valid studies involving 681 patients were included. The meta-analysis exhibited in comparison to conventional treatment, CM combined with conventional treatment significantly improved clinical efficacy (RR = 1.21, 95% CI [1.08,1.36]), and significantly increased viral nucleic acid negative conversion rate (RR = 1.49, 95% CI [1.13,1.97]). CM also prominently reduced pulmonary inflammation (RR = 1.27, 95% CI [1.12,1.44]), and improved host immune function (WBC, MD = 0.92, 95% CI [0.07,1.76]; LYM, MD = 0.33, 95% CI [0.08,0.57]; LYM%, MD = 2.90, 95% CI [2.09,3.71]; CRP, MD = -12.66, 95% CI [-24.40, -0.92]). Meanwhile, CM did not increase the incidence of adverse reactions (RR = 1.17, 95% CI [0.39,3.52]).

CONCLUSION

According to the allocated data, CM has demonstrated clinical efficacy and safety on COVID-19 pneumonia, which need to be confirmed by high quality, multiple-center, large sample randomized controlled trials.

Clinical characteristics and laboratory results of pregnant women with COVID-19 in Wuhan, China

Objective

To evaluate the clinical characteristics and laboratory test results in pregnant women with coronavirus disease 2019 (COVID‐19).

Methods

A retrospective study to review and compare clinical data including electronic medical records and laboratory tests from pregnant and nonpregnant patients admitted the Central Hospital of Wuhan, China from December 8, 2019 to April 1, 2020.

Results

A total of 72 women (30 pregnant and 42 nonpregnant) with COVID‐19 were included. No patients developed severe pneumonia during the study. Compared with the nonpregnant group, pregnant patients were admitted to hospital earlier (0.25 vs 11.00 days; P<0.001), presented milder symptoms, had a higher rate of asymptomatic infection (26.7% vs 0%), and shorter length of hospital stay (14.5 vs 17.0 days; P<0.01). Laboratory test results showed that levels of inflammation markers such as white blood cell count, neutrophil count and percentage, C‐reactive protein, procalcitonin, and D‐dimer were significantly higher in pregnant women, whereas mean lymphocyte percentage was significantly lower compared with nonpregnant women.

Conclusion

In some respects, the clinical characteristics and laboratory test results of COVID‐19 in pregnant patients seems to be distinctive from their nonpregnant counterparts. Appropriate advice and positive treatment might be critical to the prognosis when dealing with these pregnant patients. Pregnant patients with COVID‐19 had their own positive clinical characteristics and special laboratory test results. Responsive medical advice and active treatment for those patients are critical to recovery.

The clinical characteristics and laboratory test results of COVID‐19 in pregnancy seemed to be distinctive from those in non‐pregnancy in some respects. Immediate medical advice and active treatment for pregnant patients with COVID‐19 are critical to recovery.

C-reactive protein correlates with computed tomographic findings and predicts severe COVID-19 early

COVID-19 has developed into a worldwide pandemic; early identification of severe illness is critical for controlling it and improving the prognosis of patients with limited medical resources. The present study aimed to analyze the characteristics of severe COVID-19 and identify biomarkers for differential diagnosis and prognosis prediction. In total, 27 consecutive patients with COVID-19 and 75 patients with flu were retrospectively enrolled. Clinical parameters were collected from electronic medical records. The disease course was divided into four stages: initial, progression, peak, and recovery stages, according to computed tomography (CT) progress. to mild COVID-19, the lymphocytes in the severe COVID-19 progressively decreased at the progression and the peak stages, but rebound in the recovery stage. The levels of C-reactive protein (CRP) in the severe group at the initial and progression stages were higher than those in the mild group. Correlation analysis showed that CRP (R = .62; P < .01), erythrocyte sedimentation rate (R = .55; P < .01) and granulocyte/lymphocyte ratio (R = .49; P < .01) were positively associated with the CT severity scores. In contrast, the number of lymphocytes (R = -.37; P < .01) was negatively correlated with the CT severity scores. The receiver-operating characteristic analysis demonstrated that area under the curve of CRP on the first visit for predicting severe COVID-19 was 0.87 (95% CI 0.10-1.00) at 20.42 mg/L cut-off, with sensitivity and specificity 83% and 91%, respectively. CRP in severe COVID-19 patients increased significantly at the initial stage, before CT findings. Importantly, CRP, which was associated with disease development, predicted early severe COVID-19.

Low-grade fever during COVID-19 convalescence: A report of 3 cases

BACKGROUND

Low-grade fever during convalescence is an atypical symptom of coronavirus disease 2019 (COVID-19). Reports of such cases are rare, and the mechanism and outcome of low-grade fever during COVID-19 convalescence are not completely clear. We report 3 cases with low-grade fever during COVID-19 convalescence and highlight the main clinical, radiographic, and laboratory characteristics, thereby increasing the level of expertise in the clinical management of COVID-19 during convalescence and facilitating individualized decision-making.

CASE SUMMARY

We describe 3 patients with COVID-19, two females aged 62 and 66 years and a male 55 years, who had low-grade fever during COVID-19 convalescence. All 3 patients had no other discomfort or comorbidities during low-grade process. Lesions on computed tomography in all 3 patients had resolved during this period. Two patients tested negative on two consecutive severe acute respiratory syndrome coronavirus 2 tests with an interval of at least 24 h between tests. Body temperature in all 3 patients returned to normal after several days without treatment, and fever recurrence was not observed.

CONCLUSION

Enhancing the knowledge of low-grade fever during COVID-19 convalescence may increase the expertise in the delivery of optimal healthcare services.

Clinical characteristics of coronavirus disease (COVID-19) early findings from a teaching hospital in Pavia, North Italy, 21 to 28 February 2020

We describe clinical characteristics, treatments and outcomes of 44 Caucasian patients with coronavirus disease (COVID-19) at a single hospital in Pavia, Italy, from 21-28 February 2020, at the beginning of the outbreak in Europe. Seventeen patients developed severe disease, two died. After a median of 6 days, 14 patients were discharged from hospital. Predictors of lower odds of discharge were age > 65 years, antiviral treatment and for severe disease, lactate dehydrogenase > 300 mg/dL.

Comparative analysis of clinical characteristics, imaging and laboratory findings of different age groups with COVID-19

Objective

This study aims to provide scientific basis for rapid screening and early diagnosis of the coronavirus disease 2019 (COVID-19) through analysing the clinical characteristics and early imaging/laboratory findings of the inpatients.

Methods

Three hundred and three patients with laboratory-confirmed COVID-19 from the East Hospital of People's Hospital of Wuhan University (Wuhan, China) were selected and divided into four groups: youth (20-40 years, n = 64), middle-aged (41-60 years, n = 89), older (61-80 years, n = 118) and elderly (81-100 years, n = 32). The clinical characteristics and imaging/laboratory findings including chest computed tomography (CT), initial blood count, C-reactive protein [CRP]), procalcitonin (PCT) and serum total IgE were captured and analysed.

Results

(1) The first symptoms of all age groups were primarily fever (76%), followed by cough (12%) and dyspnoea (5%). Beside fever, the most common initial symptom of elderly patients was fatigue (13%). (2) Fever was the most common clinical manifestation (80%), with moderate fever being the most common (40%), followed by low fever in patients above 40 years old and high fever in those under 40 years (35%). Cough was the second most common clinical manifestation and was most common (80%) in the middle-aged. Diarrhoea was more common in the middle-aged (21%) and the older (19%). Muscle ache was more common in the middle-aged (15%). Chest pain was more common in the youth (13%), and 13% of the youth had no symptoms. (3) The proportion of patients with comorbidities increased with age. (4) Seventy-one per cent of the patients had positive reverse transcription-polymerase chain reaction results and 29% had positive chest CT scans before admission to the hospital. (5) Lesions in all lobes of the lung were observed as the main chest CT findings (76%). (6) Decrease in lymphocytes and increase in monocytes were common in the patients over 40 years old but rare in the youth. Eosinophils (50%), red blood cells (39%) and haemoglobin (40%) decreased in all age groups. (7) The proportion of patients with CRP and PCT elevation increased with age. (8) Thirty-nine per cent of the patients had elevated IgE, with the highest proportion in the old (49%).

Conclusion

The clinical characteristics and imaging/laboratory findings of COVID-19 patients vary in different age groups. Personalised criteria should be formulated according to different age groups in the early screening and diagnosis stage.