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1.
Med Image Anal ; 70: 101992, 2021 Feb 06.
Artigo em Inglês | MEDLINE | ID: mdl-33601166

RESUMO

The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using RT-PCR for testing. As a complimentary tool with diagnostic imaging, chest Computed Tomography (CT) has been shown to be able to reveal visual patterns characteristic for COVID-19, which has definite value at several stages during the disease course. To facilitate CT analysis, recent efforts have focused on computer-aided characterization and diagnosis with chest CT scan, which has shown promising results. However, domain shift of data across clinical data centers poses a serious challenge when deploying learning-based models. A common way to alleviate this issue is to fine-tune the model locally with the target domains local data and annotations. Unfortunately, the availability and quality of local annotations usually varies due to heterogeneity in equipment and distribution of medical resources across the globe. This impact may be pronounced in the detection of COVID-19, since the relevant patterns vary in size, shape, and texture. In this work, we attempt to find a solution for this challenge via federated and semi-supervised learning. A multi-national database consisting of 1704 scans from three countries is adopted to study the performance gap, when training a model with one dataset and applying it to another. Expert radiologists manually delineated 945 scans for COVID-19 findings. In handling the variability in both the data and annotations, a novel federated semi-supervised learning technique is proposed to fully utilize all available data (with or without annotations). Federated learning avoids the need for sensitive data-sharing, which makes it favorable for institutions and nations with strict regulatory policy on data privacy. Moreover, semi-supervision potentially reduces the annotation burden under a distributed setting. The proposed framework is shown to be effective compared to fully supervised scenarios with conventional data sharing instead of model weight sharing.

2.
J Infect Chemother ; 27(2): 336-341, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-33402303

RESUMO

INTRODUCTION: In patients with severe coronavirus disease 2019 (COVID-19), respiratory failure is a major complication and its symptoms occur around one week after onset. The CURB-65, A-DROP and expanded CURB-65 tools are known to predict the risk of mortality in patients with community-acquired pneumonia. In this retrospective single-center retrospective study, we aimed to assess the correlations of the A-DROP, CURB-65, and expanded CURB-65 scores on admission with an increase in oxygen requirement in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia. METHODS: We retrospectively analyzed 207 patients who were hospitalized with SARS-CoV-2 pneumonia at the Self-Defense Forces Central Hospital in Tokyo, Japan. Performance of A-DROP, CURB-65, and the expanded CURB-65 scores were validated. In addition, we assessed whether there were any associations between an increase in oxygen requirement and known risk factors for critical illness in COVID-19, including elevation of liver enzymes and C-reactive protein (CRP), lymphocytopenia, high D-dimer levels and the chest computed tomography (CT) score. RESULTS: The areas under the curve for the ability of CURB-65, A-DROP, and the expanded CURB-65 scores to predict an increase in oxygen requirement were 0.6961, 0.6980 and 0.8327, respectively, and the differences between the three groups were statistically significant (p < 0.001). Comorbid cardiovascular disease, lymphocytopenia, elevated CRP, liver enzyme and D-dimer levels, and higher chest CT score were significantly associated with an increase in oxygen requirement CONCLUSIONS: The expanded CURB-65 score can be a better predictor of an increase in oxygen requirement in patients with SARS-CoV-2 pneumonia.


Assuntos
/terapia , Oxigenoterapia/métodos , Índice de Gravidade de Doença , Adulto , Idoso , Proteína C-Reativa/análise , /mortalidade , Feminino , Produtos de Degradação da Fibrina e do Fibrinogênio/análise , Humanos , Linfopenia/epidemiologia , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/mortalidade , Pneumonia Viral/terapia , Prognóstico , Insuficiência Respiratória/epidemiologia , Estudos Retrospectivos , Fatores de Risco , Tóquio , Tomografia Computadorizada por Raios X
3.
J Infect Chemother ; 27(1): 70-75, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-32950393

RESUMO

OBJECTIVES: The symptoms of Coronavirus disease 2019 (COVID-19) vary among patients. The aim of this study was to investigate the clinical manifestation and disease duration in young versus elderly patients. METHODS: We retrospectively analyzed 187 patients (87 elderly and 100 young patients) with confirmed COVID-19. The clinical characteristics and chest computed tomography (CT) extent as defined by a score were compared between the two groups. RESULTS: The numbers of asymptomatic cases and severe cases were significantly higher in the elderly group (elderly group vs. young group; asymptomatic cases, 31 [35.6%] vs. 10 [10%], p < 0.0001; severe cases, 25 [28.7%] vs. 8 [8.0%], p = 0.0002). The proportion of asymptomatic patients and severe patients increased across the 10-year age groups. There was no significant difference in the total CT score and number of abnormal cases. A significant positive correlation between the disease duration and patient age was observed in asymptomatic patients (ρ = 0.4570, 95% CI 0.1198-0.6491, p = 0.0034). CONCLUSIONS: Although the extent of lung involvement did not have a significant difference between the young and elderly patients, elderly patients were more likely to have severe clinical manifestations. Elderly patients were also more likely to be asymptomatic and a source of COVID-19 viral shedding.


Assuntos
Infecções Assintomáticas/epidemiologia , Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Eliminação de Partículas Virais , Adulto , Fatores Etários , Idoso , Betacoronavirus , Infecções por Coronavirus/diagnóstico por imagem , Infecções por Coronavirus/patologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/diagnóstico por imagem , Pneumonia Viral/patologia , Estudos Retrospectivos , Índice de Gravidade de Doença , Tomografia Computadorizada por Raios X
5.
Eur Radiol ; 2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33146796

RESUMO

OBJECTIVES: The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. METHODS: Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. RESULTS: Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature (p < 0.01), CRP (p < 0.01), and KL-6 (p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume (p = 0.01), percent lung involvement (p = 0.01), and consolidation (p = 0.043) were associated with subsequent development of symptoms. CONCLUSIONS: COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. KEY POINTS: • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1-5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms.

6.
J Nippon Med Sch ; 2020 Aug 31.
Artigo em Inglês | MEDLINE | ID: mdl-32863339

RESUMO

BACKGROUND: Coronavirus disease 2019 (COVID-19) and heat related-illness are systemic febrile diseases. In the summer during the COVID-19 pandemic, a differential diagnosis between the two conditions is important. However, no studies have compared and distinguished heat-related illness from COVID-19. We aimed to compare the data between patients with early-stage heat-related illness and those with COVID-19. METHODS: This retrospective observational study included 90 patients with early-stage heat-related illness selected from Heatstroke STUDY 2017-2019 (nationwide registries of heat-related illness in Japan) and 86 patients with laboratory-confirmed COVID-19 with complaints of fever or fatigue and were admitted to one of two hospitals in Tokyo, Japan. RESULTS: Amongvital signs, systolic blood pressure (119 vs. 125 mmHg, p = 0.02), oxygen saturation (98% vs. 97%, p < 0.001), and body temperature (36.6 vs. 37.6 °C, p<0.001) showed significant between-group differences for the heatstroke and COVID-19 groups, respectively. Numerous intergroup differences in laboratory findings were present, including white blood cell counts (10.8 vs. 5.2 × 103/µL, p<0.001), creatinine (2.2 vs. 0.85 mg/dL, p<0.001), and C-reactive protein (0.2 vs. 2.8 mg/dL, p<0.001), although a logistic regression model achieved an area under the curve (AUC) of 0.966 using these three factors. A Random Forest machine learning model achieved accuracy, precision, recall, and AUC of 0.908, 0.976, 0.842, and 0.978, respectively. Creatinine was the most important feature of this model. CONCLUSIONS: Acute kidney injury was associated with heat-related illness, which could be key in distinguishing or evaluating patients with fever in the summer during the COVID-19 pandemic.

7.
Int J Mol Sci ; 21(18)2020 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-32937754

RESUMO

Stroke is the most prevalent cardiovascular disease worldwide, and is still one of the leading causes of death and disability. Stem cell-based therapy is actively being investigated as a new potential treatment for certain neurological disorders, including stroke. Various types of cells, including bone marrow mononuclear cells, bone marrow mesenchymal stem cells, dental pulp stem cells, neural stem cells, inducible pluripotent stem cells, and genetically modified stem cells have been found to improve neurological outcomes in animal models of stroke, and there are some ongoing clinical trials assessing their efficacy in humans. In this review, we aim to summarize the recent advances in cell-based therapies to treat stroke.

8.
J Infect Chemother ; 26(11): 1220-1223, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32792249

RESUMO

Coronavirus disease 2019 (COVID-19) is spreading worldwide and poses an imminent threat to public health. We encountered 2 cases of COVID-19 with progression resulting in severe respiratory failure and improvement without any specific treatment. To examine the course of infection, we performed reverse-transcription (RT) polymerase chain reaction assay with serum specimens, and serum SARS-CoV-2 RNA was detected in both cases when body temperature increased and respiratory status deteriorated. We, then examined, retrospectively and prospectively, the clinical course during hospitalization by performing serial examinations of serum SARS-CoV-2 RNA status. The findings from our cases suggest that not only is detection of viremia useful as a predictive marker of severity, but also serial serum SARS-CoV-2 RNA results can be helpful for predicting the clinical course.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/complicações , Pneumonia Viral/complicações , RNA Viral/sangue , Insuficiência Respiratória/diagnóstico , Viremia/diagnóstico , Adulto , Idoso , Betacoronavirus/genética , Técnicas de Laboratório Clínico , Infecções por Coronavirus/sangue , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/virologia , Humanos , Masculino , Pandemias , Pneumonia Viral/sangue , Pneumonia Viral/diagnóstico , Pneumonia Viral/virologia , RNA Viral/isolamento & purificação , Insuficiência Respiratória/sangue , Insuficiência Respiratória/virologia , Estudos Retrospectivos , Reação em Cadeia da Polimerase Via Transcriptase Reversa , Índice de Gravidade de Doença , Fatores de Tempo , Viremia/complicações , Viremia/virologia
9.
Nat Commun ; 11(1): 4080, 2020 08 14.
Artigo em Inglês | MEDLINE | ID: mdl-32796848

RESUMO

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set (not included in training and validation) of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations.


Assuntos
Inteligência Artificial , Técnicas de Laboratório Clínico/métodos , Infecções por Coronavirus/diagnóstico por imagem , Pneumonia Viral/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Betacoronavirus/isolamento & purificação , Criança , Pré-Escolar , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/virologia , Aprendizado Profundo , Feminino , Humanos , Imageamento Tridimensional/métodos , Pulmão/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/virologia , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Adulto Jovem
10.
Resuscitation ; 154: 77-84, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32531404

RESUMO

AIM: Assessment of brainstem function plays a key role in predicting the neurological outcome after cardiac arrest. However, the relationship of the two quantitative brainstem assessment methods-automated infrared pupillometry (AIP) and auditory brainstem response (ABR)-with neurological prognoses remains unclear. This study compares the prognostic value of AIP and ABR after cardiopulmonary arrest. METHODS: This retrospective observational study included 124 comatose patients after cardiopulmonary arrest. ABR and AIP measurements were performed simultaneously within 72 h after return of spontaneous circulation. Neurological outcome was assessed at discharge by estimating the cerebral performance category (CPC) score; favourable neurological outcome (CPC score, 1-2) or poor neurological outcome (CPC score, 3-5). The correlation of each AIP parameter and ABR I-V wave latency was tested using Pearson's product moment correlation coefficient, and the prognostic value was compared using the area under the receiver operating characteristics curve (AUC). RESULTS: Pupillary light reflex (PLR) was not detected in 69 patients, and ABR wave V was not detected in 47 patients. All these patients had poor neurological outcome. Among those whose PLR and ABR could be measured, each AIP parameter had a tendency to be correlated with ABR I-V wave latency. Pupil constriction velocity provided the greatest AUC (0.819), with 81% sensitivity and 77% specificity. ABR I-V wave latency provided extremely low AUC (0.560). CONCLUSIONS: Although AIP and ABR were correlated, the AIP measures were superior in predicting the neurological outcome after cardiac arrest as compared with the ABR measures.

11.
Lancet Infect Dis ; 20(9): 1043-1050, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32539988

RESUMO

BACKGROUND: The ongoing COVID-19 pandemic is a global threat. Identification of markers for symptom onset and disease progression is a pressing issue. We described the clinical features of people infected on board the Diamond Princess cruise ship who were diagnosed with asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or mild or severe COVID-19, on admission to the Self-Defense Forces Central Hospital (Tokyo, Japan) and at the end of observation. METHODS: This retrospective, single-centre study included participants with laboratory-detected SARS-CoV-2 infection who were admitted to the Self-Defense Forces Central Hospital from Feb 11 to Feb 25, 2020. Clinical records, laboratory data, and radiological findings were analysed. Clinical outcomes were followed up until discharge or Feb 26, 2020, whichever came first. We defined asymptomatic infection as SARS-CoV-2 infection with no history of clinical signs and symptoms, severe COVID-19 as clinical symptoms of pneumonia (dyspnoea, tachypnoea, peripheral capillary oxygen saturation <93%, and need for oxygen therapy), and mild COVID-19 as all other symptoms. Clinical features on admission were compared among patients with different disease severity, including asymptomatic infection, at the end of observation. We used univariable analysis to identify factors associated with symptomatic illness among asymptomatic people infected with SARS-CoV-2 and disease progression in patients with COVID-19. FINDINGS: Among the 104 participants included in the final analysis, the median age was 68 years (IQR 47-75) and 54 (52%) were male. On admission, 43 (41%) participants were classified as asymptomatic, 41 (39%) as having mild COVID-10, and 20 (19%) as having severe COVID-19. At the end of observation, 33 (32%) participants were confirmed as being asymptomatic, 43 (41%) as having mild COVID-19, and 28 (27%) as having severe COVID-19. Serum lactate hydrogenase concentrations were significantly higher in the ten participants who were asymptomatic on admission but developed symptomatic COVID-19 compared with the 33 participants who remained asymptomatic throughout the observation period (five [50%] vs four [12%] participants; odds ratio 7·25, 95% CI 1·43-36·70; p=0·020). Compared with patients with mild disease at the end of observation, patients with severe COVID-19 were older (median age 73 years [IQR 55-77] vs 60 years [40-71]; p=0·028) and had more frequent consolidation on chest CT (13 [46%] of 28 vs nine [21%] of 43; p=0·035) and lymphopenia (16 [57%] vs ten [23%]; p=0·0055) on admission. INTERPRETATION: Older age, consolidation on chest CT images, and lymphopenia might be risk factors for disease progression of COVID-19 and contribute to improved clinical management. FUNDING: None.


Assuntos
Betacoronavirus/fisiologia , Infecções por Coronavirus/diagnóstico por imagem , Linfopenia/complicações , Pandemias , Pneumonia Viral/diagnóstico por imagem , Síndrome Respiratória Aguda Grave/diagnóstico por imagem , Adulto , Idoso , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/virologia , Progressão da Doença , Feminino , Hospitais , Humanos , Japão , Pulmão/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , Estudos Retrospectivos , Fatores de Risco , Síndrome Respiratória Aguda Grave/epidemiologia , Síndrome Respiratória Aguda Grave/virologia , Navios , Tomografia Computadorizada por Raios X
13.
JA Clin Rep ; 4(1): 16, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29479560

RESUMO

Background: Heterotaxy syndrome (HS) is characterized by a wide variety of cardiac and extra-cardiac malformations, including pulmonary valve stenosis, interruption of the inferior vena cava, total anomalous pulmonary venous connection (TAPVC), asplenia, polysplenia, intestinal malrotation, and preduodenal portal vein (PDPV). We report the case of a heterotaxic infant with an infracardiac TAPVC and preduodenal portal vein who experienced repetitive hemodynamic instability during urgent laparotomy for duodenal obstruction. Case presentation: A 3-day-old boy with HS was planned to undergo urgent laparotomy for duodenal atresia. Echocardiogram showed an interrupted inferior vena cava, single right ventricle, pulmonary valve stenosis, and infracardiac TAPVC. On exploratory laparotomy, intestinal malrotation characterized by Ladd's band was found. During further exploration, repetitive severe hypotension and hypoxia occurred. Thorough examination revealed a greatly dilated PDPV crossing over and compressing the proximal duodenum externally. Finally, we considered the possibility that surgical manipulation directly compressed the dilated PDPV into which the TAPVC had pulmonary venous drainage, leading to repetitive pulmonary venous obstruction (PVO). Computed tomography, which was examined after laparotomy, indicated that the vertical vein from pulmonary venous confluence drained into the portal vein. Conclusion: PDPV is a rare anomaly associated with HS. In case of intestinal malrotation and duodenal obstruction in HS with infracardiac TAPVC, both the presence of PDPV and the possibility of pulmonary venous drainage into the PDPV should be considered by pediatric surgeons and anesthesiologists performing laparotomy to avoid catastrophic PVO.

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