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2.
J Infect Dis ; 2022 May 05.
Article in English | MEDLINE | ID: covidwho-1831182

ABSTRACT

The SARS-CoV-2 variant Omicron is now under investigation. We evaluated cross-neutralizing activity against Omicron in COVID-19 convalescent patients (n = 23) who had received two doses of an mRNA vaccination (BNT162b2 or mRNA-1273). Intriguingly, after the second vaccination, the neutralizing antibody titers of subjects against SARS-CoV-2 variants, including Omicron, all became seropositive, and significant fold-increases (21.1-52.0) were seen regardless of the disease severity of subjects. Our findings thus demonstrate that two doses of mRNA vaccination to SARS-CoV-2 convalescent patients can induce cross-neutralizing activity against Omicron.

3.
Front Immunol ; 13: 773652, 2022.
Article in English | MEDLINE | ID: covidwho-1742214

ABSTRACT

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the virus responsible for the Coronavirus Disease 2019 (COVID-19) pandemic. The emergence of variants of concern (VOCs) has become one of the most pressing issues in public health. To control VOCs, it is important to know which COVID-19 convalescent sera have cross-neutralizing activity against VOCs and how long the sera maintain this protective activity. Methods: Sera of patients infected with SARS-CoV-2 from March 2020 to January 2021 and admitted to Hyogo Prefectural Kakogawa Medical Center were selected. Blood was drawn from patients at 1-3, 3-6, and 6-8 months post onset. Then, a virus neutralization assay against SARS-CoV-2 variants (D614G mutation as conventional strain; B.1.1.7, P.1, and B.1.351 as VOCs) was performed using authentic viruses. Results: We assessed 97 sera from 42 patients. Sera from 28 patients showed neutralizing activity that was sustained for 3-8 months post onset. The neutralizing antibody titer against D614G significantly decreased in sera of 6-8 months post onset compared to those of 1-3 months post onset. However, the neutralizing antibody titers against the three VOCs were not significantly different among 1-3, 3-6, and 6-8 months post onset. Discussion: Our results indicate that neutralizing antibodies that recognize the common epitope for several variants may be maintained for a long time, while neutralizing antibodies having specific epitopes for a variant, produced in large quantities immediately after infection, may decrease quite rapidly.


Subject(s)
COVID-19/immunology , SARS-CoV-2/physiology , Aged , Antibodies, Viral/blood , Broadly Neutralizing Antibodies , Cross Reactions , Female , Humans , Immunity, Humoral , Immunodominant Epitopes/immunology , Male , Middle Aged , Time Factors
4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329141

ABSTRACT

The SARS-CoV-2 variant Omicron is now under investigation. We evaluated cross-neutralizing activity against Omicron in COVID-19 convalescent patients (n=23) who had received two doses of an mRNA vaccination (BNT162b2 or mRNA-1273). Surprisingly and interestingly, after the second vaccination, the subjects’ neutralizing antibody titers including that against Omicron all became seropositive, and significant fold-increases (21.1–52.0) were seen regardless of the subjects’ disease severity. Our findings thus demonstrate that at least two doses of mRNA vaccination to SARS-CoV-2 convalescent patients can induce cross-neutralizing activity against Omicron.

5.
Ann Transl Med ; 10(3): 130, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1687683

ABSTRACT

Background: We developed and validated a machine learning diagnostic model for the novel coronavirus (COVID-19) disease, integrating artificial-intelligence-based computed tomography (CT) imaging and clinical features. Methods: We conducted a retrospective cohort study in 11 Japanese tertiary care facilities that treated COVID-19 patients. Participants were tested using both real-time reverse transcription polymerase chain reaction (RT-PCR) and chest CTs between January 1 and May 30, 2020. We chronologically split the dataset in each hospital into training and test sets, containing patients in a 7:3 ratio. A Light Gradient Boosting Machine model was used for the analysis. Results: A total of 703 patients were included, and two models-the full model and the A-blood model-were developed for their diagnosis. The A-blood model included eight variables (the Ali-M3 confidence, along with seven clinical features of blood counts and biochemistry markers). The areas under the receiver-operator curve of both models [0.91, 95% confidence interval (CI): 0.86 to 0.95 for the full model and 0.90, 95% CI: 0.86 to 0.94 for the A-blood model] were better than that of the Ali-M3 confidence (0.78, 95% CI: 0.71 to 0.83) in the test set. Conclusions: The A-blood model, a COVID-19 diagnostic model developed in this study, combines machine-learning and CT evaluation with blood test data and performs better than the Ali-M3 framework existing for this purpose. This would significantly aid physicians in making a quicker diagnosis of COVID-19.

6.
Infect Chemother ; 53(4): 767-775, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1603475

ABSTRACT

BACKGROUND: Neutralizing antibody cocktail therapy, REGN-COV2, is promising in preventing a severe form of coronavirus disease 2019 (COVID-19), but its effectiveness in Japan has not been fully investigated. MATERIALS AND METHODS: To evaluate the effectiveness of REGN-COV2, clinical data of 20 patients with COVID-19 who received REGN-COV2 was compared with the control by matching age and sex. The primary outcome was the time from the onset to defervescence, the duration of hospitalization, and oxygen requirement. A sensitivity analysis using Bayesian analysis was also conducted. RESULTS: The time to defervescence was significantly shorter in the treatment group (5.25 vs. 7.95 days, P = 0.02), and so was the duration of hospitalization (7.115 vs. 11.45, P = 0.0009). However, the oxygen therapy requirement did not differ between the two groups (15% vs. 35%, P = 0.27). For Bayesian analysis, the median posterior probability of the time to defervescence since the symptom onset on the REGN-COV2 group was 5.28 days [95% credible interval (CrI): 4.28 - 6.31 days], compared with the control of 7.99 days (95% CrI: 6.81 - 9.24 days). The posterior probability of the duration of the hospitalization on the REGN-COV2 group was 7.17 days (95% CrI: 5.99 - 8.24 days), compared with the control of 11.54 days (95% CrI: 10.28 - 13.14 days). The posterior probability of the oxygen requirement on the REGN-COV2 group was 18% (95% CrI: 3 - 33%), compared with the control of 36% (95% CrI: 16 - 54%). CONCLUSION: REGN-COV2 may be effective in early defervescence and shorter hospitalization. Its effectiveness for preventing a severe form of infection needs to be evaluated by further studies.

7.
PLoS One ; 16(11): e0258760, 2021.
Article in English | MEDLINE | ID: covidwho-1502068

ABSTRACT

Ali-M3, an artificial intelligence program, analyzes chest computed tomography (CT) and detects the likelihood of coronavirus disease (COVID-19) based on scores ranging from 0 to 1. However, Ali-M3 has not been externally validated. Our aim was to evaluate the accuracy of Ali-M3 for detecting COVID-19 and discuss its clinical value. We evaluated the external validity of Ali-M3 using sequential Japanese sampling data. In this retrospective cohort study, COVID-19 infection probabilities for 617 symptomatic patients were determined using Ali-M3. In 11 Japanese tertiary care facilities, these patients underwent reverse transcription-polymerase chain reaction (RT-PCR) testing. They also underwent chest CT to confirm a diagnosis of COVID-19. Of the 617 patients, 289 (46.8%) were RT-PCR-positive. The area under the curve (AUC) of Ali-M3 for predicting a COVID-19 diagnosis was 0.797 (95% confidence interval: 0.762‒0.833) and the goodness-of-fit was P = 0.156. With a cut-off probability of a diagnosis of COVID-19 by Ali-M3 set at 0.5, the sensitivity and specificity were 80.6% and 68.3%, respectively. A cut-off of 0.2 yielded a sensitivity and specificity of 89.2% and 43.2%, respectively. Among the 223 patients who required oxygen, the AUC was 0.825. Sensitivity at a cut-off of 0.5% and 0.2% was 88.7% and 97.9%, respectively. Although the sensitivity was lower when the days from symptom onset were fewer, the sensitivity increased for both cut-off values after 5 days. We evaluated Ali-M3 using external validation with symptomatic patient data from Japanese tertiary care facilities. As Ali-M3 showed sufficient sensitivity performance, despite a lower specificity performance, Ali-M3 could be useful in excluding a diagnosis of COVID-19.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , Deep Learning , Diagnosis, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Adult , Aged , Algorithms , Area Under Curve , Cohort Studies , Female , Humans , Image Processing, Computer-Assisted , Japan/epidemiology , Male , Middle Aged , Probability , ROC Curve , Reproducibility of Results , Retrospective Studies , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2 , Sensitivity and Specificity
8.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-291706

ABSTRACT

Background: We developed and validated a machine learning diagnostic model for novel coronavirus (COVID-19) disease, integrating artificial-intelligence-based computed tomography (CT) imaging and clinical features. Methods We conducted a retrospective cohort study in 11 Japanese tertiary care facilities that treated COVID-19 patients. Participants were tested using both real-time reverse transcription polymerase chain reaction (RT-PCR) and chest CT between January 1 and May 30, 2020. We chronologically split the dataset in each hospital into training and test sets, containing patients in a 7:3 ratio. Light Gradient Boosting Machine model was used for analysis. Results A total of 703 patients were included with two models — the full model and the A-blood model — developed for their diagnosis. The A-blood model included eight variables (the Ali-M3 confidence, along with seven clinical features of blood counts and biochemistry markers). The areas under the receiver-operator curve of both models (0.91, 95% confidence interval (CI), 0.86 to 0.95 for the full model and 0.90, 95% CI, 0.86 to 0.94 for the A-blood model) were better than that of the Ali-M3 confidence (0.78, 95% CI, 0.71 to 0.83) in the test set. Conclusions The A-blood model, a COVID-19 diagnostic model developed in this study, combines machine-learning and CT evaluation with blood test data and is better than the Ali-M3 framework existing for this purpose. This would significantly aid physicians in making a quicker diagnosis of COVID-19.

9.
Open Forum Infect Dis ; 8(10): ofab430, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1462455

ABSTRACT

BACKGROUND: As of March 2021, Japan is facing a fourth wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To prevent further spread of infection, sera cross-neutralizing activity of patients previously infected with conventional SARS-CoV-2 against novel variants is important but has not been firmly established. METHODS: We investigated the neutralizing potency of 81 coronavirus disease 2019 (COVID-19) patients' sera from the first to fourth waves of the pandemic against SARS-CoV-2 D614G, B.1.1.7, P.1, and B.1.351 variants using their authentic viruses. RESULTS: Most sera had neutralizing activity against all variants, showing similar activity against B.1.1.7 and D614G, but lower activity especially against B.1.351. In the fourth wave, sera-neutralizing activity against B.1.1.7 was significantly higher than that against any other variants, including D614G. The sera-neutralizing activity in less severe patients was lower than that of more severe patients for all variants. CONCLUSIONS: The cross-neutralizing activity of convalescent sera was effective against all variants but was potentially weaker for B.1.351. The high neutralizing activity specific to B.1.1.7 in the fourth wave suggests that mutations in the virus might cause conformational change of its spike protein, which affects immune recognition of D614G. Our results indicate that individuals who recover from COVID-19 could be protected from the severity caused by infection with newly emerging variants.

10.
Circ Rep ; 3(7): 375-380, 2021 Jul 09.
Article in English | MEDLINE | ID: covidwho-1286857

ABSTRACT

Background: The COVID-19 pandemic has challenged healthcare systems, at times overwhelming intensive care units (ICUs). We aimed to describe the length and rate of ICU admission, and explore the clinical variables influencing ICU use, for COVID-19 patients with known cardiovascular diseases or their risk factors (CVDRF). Methods and Results: A post hoc analysis was performed of 693 Japanese COVID-19 patients with CVDRF enrolled in the nationwide CLAVIS-COVID registration system between January and May 2020 (mean [±SD] age 68.3±14.9 years; 35% female); 199 patients (28.7%) required ICU management. The mean (±SD) ICU length of stay (LOS) was 19.3±18.5 days, and the rate of in-hospital death and hospital LOS were significantly higher (P<0.001) and longer (P<0.001), respectively, in the ICU than non-ICU group. Logistic regression analysis revealed that clinical variables reflecting impaired general condition (e.g., high C-reactive protein, low Glasgow Coma Scale score, SpO2, albumin level), male sex, and previous use of ß-blockers) were associated with ICU admission (all P<0.001). Notably, age was inversely associated with ICU admission, and this was particularly prominent among elderly patients (OR 0.97, 95% confidence interval 0.95-0.99; P=0.0018). Conclusions: One-third of COVID patients with CVDRF required ICU care during the first phase of the pandemic in Japan. Other than anticipated clinical variables, such as hypoxia and altered mental status, age was inversely associated with the use of the ICU, warranting further investigation.

11.
J Infect Dis ; 223(7): 1145-1149, 2021 04 08.
Article in English | MEDLINE | ID: covidwho-1174909

ABSTRACT

Most patients with coronavirus disease 2019 (COVID-19) experience asymptomatic disease or mild symptoms, but some have critical symptoms requiring intensive care. It is important to determine how patients with asymptomatic or mild COVID-19 react to severe acute respiratory syndrome coronavirus 2 infection and suppress virus spread. Innate immunity is important for evasion from the first virus attack, and it may play an important role in the pathogenesis in these patients. We measured serum cytokine levels in 95 patients with COVID-19 during the infection's acute phase and report that significantly higher interleukin 12 and 2 levels were induced in patients with asymptomatic or mild disease than in those with moderate or severe disease, indicating the key roles of these cytokines in the pathogenesis of asymptomatic or mild COVID-19.


Subject(s)
COVID-19/immunology , Immunity, Innate , Interleukin-12/blood , Interleukin-2/blood , SARS-CoV-2/immunology , Adolescent , Adult , Aged , Aged, 80 and over , Asymptomatic Infections , COVID-19/blood , COVID-19/diagnosis , COVID-19/virology , COVID-19 Nucleic Acid Testing , Case-Control Studies , Female , Healthy Volunteers , Humans , Interleukin-12/immunology , Interleukin-2/immunology , Male , Middle Aged , RNA, Viral/isolation & purification , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Severity of Illness Index , Young Adult
12.
JMA J ; 4(1): 1-7, 2021 Jan 29.
Article in English | MEDLINE | ID: covidwho-1084276

ABSTRACT

Patients with coronavirus disease 2019 (COVID-19) exhibit a wide clinical spectrum ranging from mild respiratory symptoms to critical and fatal diseases, and older individuals are known to be more severely affected. The underlying mechanism of this phenomenon is unknown. A neutralizing antibody against viruses is known to be important to eliminate the virus. In addition, this antibody is induced at high levels in patients with severe COVID-19, followed by a termination of virus replication. Severe COVID-19 patients exhibit high levels of cytokines/chemokines, even after the disappearance of the virus. This indicates that cytokines/chemokines play significant roles in disease severity. These findings also suggest that antiviral therapy (monoclonal antibody and/or convalescent plasma therapy) should be administered early to eliminate the virus, followed by steroid treatment after viral genome disappearance, especially in patients with severe symptoms.

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