Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications.

Herein, we show differences in blood serum of asymptomatic and symptomatic pregnant women infected with COVID-19 and correlate them with laboratory indexes, ATR FTIR and multivariate machine learning methods. We collected the sera of COVID-19 diagnosed pregnant women, in the second trimester (n = 12), third-trimester (n = 7), and second-trimester with severe symptoms (n = 7) compared to the healthy pregnant (n = 11) women, which makes a total of 37 participants. To assign the accuracy of FTIR spectra regions where peak shifts occurred, the Random Forest algorithm, traditional C5.0 single decision tree algorithm and deep neural network approach were used. We verified the correspondence between the FTIR results and the laboratory indexes such as: the count of peripheral blood cells, biochemical parameters, and coagulation indicators of pregnant women. CH2 scissoring, amide II, amide I vibrations could be used to differentiate the groups. The accuracy calculated by machine learning methods was higher than 90%. We also developed a method based on the dynamics of the absorbance spectra allowing to determine the differences between the spectra of healthy and COVID-19 patients. Laboratory indexes of biochemical parameters associated with COVID-19 validate changes in the total amount of proteins, albumin and lipase.

A disease progression prediction model and nervous system symptoms in coronavirus disease 2019 patients.

This study aimed to investigate factors affecting coronavirus disease 2019 (COVID-19) progression, also to explore the clinical features and prognosis of nervous system symptom (NSS) involved COVID-19 patients. 417 COVID-19 patients were analyzed in this retrospective study, and they were clinically classified as severe patients and non-severe patients. According to NSS involved status, COVID-19 patients were further divided into NSS patients and non-NSS patients. Elderly cases, males, common comorbidities, NSS, respiratory/cardiovascular/gastrointestinal symptoms, bilateral lesion, multifocal lesion, bacterial infection, bacterial&fungal infection were more common in severe patients compared to non-severe patients. Meanwhile, severe COVID-19 patients showed increased baseline APTT, TT, D-dimer, CRP, ESR, CK-MB, creatine kinase, AST, ALT, creatinine, but decreased baseline platelet level, lymphocyte, albumin, GFR compared to non-severe patients. Notably, the continuous differences of lymphocyte, D-dimer, CRP, AST, ALT, albumin, GFR between severe patients and non-severe patients during treatment were observed. Age, NSS, bacterial & fungal infection, CRP and creatinine were further identified as independent risk factors for severe COVID-19, which could predict severe COVID-19 with area under curve of 0.861. Furthermore, severe patients presented with worse prognosis. Regrading NSS patients, they were related to older age, surgery history, diabetes comorbidities, respiratory/cardiovascular/gastrointestinal symptoms, bilateral lesion, multifocal lesion, bacterial infection, bacterial&fungal infection and more dysregulated laboratory indexes compared to non-NSS patients. Besides, NSS patients were correlated with poor prognosis to some extent. More intensive attention should be paid to COVID-19 patients with severe-disease risk factors and those with NSS involvement, in case of rapid deterioration.

Immune reactivity during COVID-19: Implications for treatment.

Clinical symptoms of COVID-19 include fever, cough, and fatigue which may progress to acute respiratory distress syndrome (ARDS). The main hematological laboratory findings associated with the severe form of disease are represented by lymphopenia and eosinopenia which mostly occur in the elderly population characterized by cardiovascular comorbidities and immunosenescence. Besides, increased levels of D-dimer, procalcitonin, and C reactive protein (CRP) seem to be powerful prognostic biomarkers helping to predict the onset of coagulopathy. The host immune response to SARS-CoV-2 can lead to an aberrant inflammatory response or "cytokine storm" which contributes to the severity of illness. At immunological level, patients affected by a severe form of COVID-19 show poor clinical trajectories characterized by differential "immunotypes" for which T cell response seems to play a critical role in understanding pathogenic mechanisms of disease. Also, patients with mild to severe COVID-19 displayed macrophage activation syndrome (MAS), very low human leukocyte antigen D related (HLA-DR) expression with a parallel reduction of CD04+ lymphocytes, CD19 lymphocytes, and natural killer (NK) cells. Corticosteroids resulted the best therapy for the immune dysregulation whereas repurposing of tocilizumab (IL-6 receptor antagonist) appears to have mixed results in patients with COVID-19. Besides, anticoagulative therapy was associated with reduced in-hospital mortality and need of intubation among COVID-19 patients. Furthermore, the beneficial use of intravenous immunoglobulin (IVIG) and passive immunotherapy with convalescent plasma needs to be validated in large controlled clinical trials. In this review, we summarize the main hematological parameters with a prognostic value in COVID-19 and the basis of immunological reactivity during COVID-19, with a focus on ongoing clinical trials evaluating immune targets as possible therapeutic strategies.

Analysis of clinical features and outcomes of 161 patients with severe and critical COVID-19: A multicenter descriptive study.

BACKGROUND: This study aimed to investigate clinical characteristics, laboratory indexes, treatment regimens, and short-term outcomes of severe and critical coronavirus disease 2019 (COVID-19) patients. METHODS: One hundred and sixty one consecutive severe and critical COVID-19 patients admitted in intensive care unit (ICU) were retrospectively reviewed in this multicenter study. Demographic features, medical histories, clinical symptoms, lung computerized tomography (CT) findings, and laboratory indexes on admission were collected. Post-admission complications, treatment regimens, and clinical outcomes were also documented. RESULTS: The mean age was 59.38 ± 16.54 years, with 104 (64.60%) males and 57 (35.40%) females. Hypertension (44 [27.33%]) and diabetes were the most common medical histories. Fever (127 [78.88%]) and dry cough (111 [68.94%]) were the most common symptoms. Blood routine indexes, hepatic and renal function indexes, and inflammation indexes were commonly abnormal. Acute respiratory distress syndrome (ARDS) was the most common post-admission complication (69 [42.86%]), followed by electrolyte disorders (48 [29.81%]), multiple organ dysfunction (MODS) (37 [22.98%]), and hypoproteinemia (36 [22.36%]). The most commonly used antiviral drug was lopinavir/ritonavir tablet. 50 (31.06%) patients died, while 78 (48.45%) patients healed and discharged, and the last 33 (20.50%) patients remained in hospital. Besides, the mean hospital stay of deaths was 21.66 ± 11.18 days, while the mean hospital stay of discharged patients was 18.42 ± 12.77 days. Furthermore, ARDS (P < .001) and MODS (P = .008) correlated with increased mortality rate. CONCLUSION: Severe and critical COVID-19 presents with high mortality rate, and occurrence of ARDS or MODS greatly increases its mortality risk.