scholarly journals Response to: ‘Correspondence on ‘Lung involvement in macrophage activation syndrome and severe COVID-19: results from a cross-sectional study to assess clinical, laboratory and artificial intelligence–radiological differences’ by Ruscitti et al’ by Chen et al

2020 ◽  
pp. annrheumdis-2020-218909
Author(s):  
Piero Ruscitti ◽  
Federico Bruno ◽  
Onorina Berardicurti ◽  
Chiara Acanfora ◽  
Viktoriya Pavlych ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Macrophage Activation Syndrome ◽  
Macrophage Activation ◽  
Clinical Laboratory ◽  
Cross Sectional Study ◽  
Lung Involvement ◽  
Sectional Study ◽  
Cross Sectional ◽  
Activation Syndrome

scholarly journals Lung involvement in macrophage activation syndrome and severe COVID-19: results from a cross-sectional study to assess clinical, laboratory and artificial intelligence–radiological differences

2020 ◽  
Vol 79 (9) ◽  
pp. 1152-1155 ◽  
Author(s):  
Piero Ruscitti ◽  
Federico Bruno ◽  
Onorina Berardicurti ◽  
Chiara Acanfora ◽  
Viktoriya Pavlych ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Macrophage Activation Syndrome ◽  
Macrophage Activation ◽  
Clinical Laboratory ◽  
Cross Sectional Study ◽  
Chest Ct ◽  
Lung Involvement ◽  
Cross Sectional ◽  
Single Centre Study ◽  
Activation Syndrome

ObjectivesTo evaluate the clinical pictures, laboratory tests and imaging of patients with lung involvement, either from severe COVID-19 or macrophage activation syndrome (MAS), in order to assess how similar these two diseases are.MethodsThe present work has been designed as a cross-sectional single-centre study to compare characteristics of patients with lung involvement either from MAS or severe COVID-19. Chest CT scans were assessed by using an artificial intelligence (AI)-based software.ResultsTen patients with MAS and 47 patients with severe COVID-19 with lung involvement were assessed. Although all patients showed fever and dyspnoea, patients with MAS were characterised by thrombocytopaenia, whereas patients with severe COVID-19 were characterised by lymphopaenia and neutrophilia. Higher values of H-score characterised patients with MAS when compared with severe COVID-19. AI-reconstructed images of chest CT scan showed that apical, basal, peripheral and bilateral distributions of ground-glass opacities (GGOs), as well as apical consolidations, were more represented in severe COVID-19 than in MAS. C reactive protein directly correlated with GGOs extension in both diseases. Furthermore, lymphopaenia inversely correlated with GGOs extension in severe COVID-19.ConclusionsOur data could suggest laboratory and radiological differences between MAS and severe COVID-19, paving the way for further hypotheses to be investigated in future confirmatory studies.

scholarly journals Comparison of predicted psychological distress among workers between artificial intelligence and psychiatrists: a cross-sectional study in Tsukuba Science City, Japan

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e046265
Author(s):  
Shotaro Doki ◽  
Shinichiro Sasahara ◽  
Daisuke Hori ◽  
Yuichi Oi ◽  
Tsukasa Takahashi ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Psychological Distress ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Explanatory Variables ◽  
The Neural Network ◽  
Significant Difference ◽  
Total Data

ObjectivesPsychological distress is a worldwide problem and a serious problem that needs to be addressed in the field of occupational health. This study aimed to use artificial intelligence (AI) to predict psychological distress among workers using sociodemographic, lifestyle and sleep factors, not subjective information such as mood and emotion, and to examine the performance of the AI models through a comparison with psychiatrists.DesignCross-sectional study.SettingWe conducted a survey on psychological distress and living conditions among workers. An AI model for predicting psychological distress was created and then the results were compared in terms of accuracy with predictions made by psychiatrists.ParticipantsAn AI model of the neural network and six psychiatrists.Primary outcomeThe accuracies of the AI model and psychiatrists for predicting psychological distress.MethodsIn total, data from 7251 workers were analysed to predict moderate and severe psychological distress. An AI model of the neural network was created and accuracy, sensitivity and specificity were calculated. Six psychiatrists used the same data as the AI model to predict psychological distress and conduct a comparison with the AI model.ResultsThe accuracies of the AI model and psychiatrists for predicting moderate psychological distress were 65.2% and 64.4%, respectively, showing no significant difference. The accuracies of the AI model and psychiatrists for predicting severe psychological distress were 89.9% and 85.5%, respectively, indicating that the AI model had significantly higher accuracy.ConclusionsA machine learning model was successfully developed to screen workers with depressed mood. The explanatory variables used for the predictions did not directly ask about mood. Therefore, this newly developed model appears to be able to predict psychological distress among workers easily, regardless of their subjective views.

scholarly journals Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xingrui Wang ◽  
Qinglin Che ◽  
Xiaoxiao Ji ◽  
Xinyi Meng ◽  
Lang Zhang ◽  
...  
Keyword(s):  
Peripheral Blood Lymphocyte ◽  
Peripheral Blood ◽  
Blood Lymphocyte ◽  
Clinical Laboratory ◽  
Lung Infection ◽  
Cross Sectional Study ◽  
Ct Images ◽  
Sectional Study ◽  
Laboratory Examination ◽  
Cross Sectional

Abstract Background Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in COVID-19 and to analyse its underlying mechanism. Methods Chest high-resolution computer tomography (CT) images and laboratory examination data of 31 patients with COVID-19 were extracted, and the lesion areas in CT images were quantitatively segmented and calculated using a deep learning (DL) system. A cross-sectional study method was carried out to explore the differences among the proportions of lung lobe infection and to correlate the percentage of infection (POI) of the whole lung in all patients with clinical laboratory examination values. Results No significant difference in the proportion of infection was noted among various lung lobes (P > 0.05). The POI of total lung was negatively correlated with the peripheral blood lymphocyte percentage (L%) (r = − 0.633, P < 0.001) and lymphocyte (LY) count (r = − 0.555, P = 0.001) but positively correlated with the neutrophil percentage (N%) (r = 0.565, P = 0.001). Otherwise, the POI was not significantly correlated with the peripheral blood white blood cell (WBC) count, monocyte percentage (M%) or haemoglobin (HGB) content. In some patients, as the infection progressed, the L% and LY count decreased progressively accompanied by a continuous increase in the N%. Conclusions Lung lesions in COVID-19 patients are significantly correlated with the peripheral blood lymphocyte and neutrophil levels, both of which could serve as prognostic indicators that provide warning implications, and contribute to clinical interventions in patients.

scholarly journals High hepatic macrophage activation and low liver function in stable Wilson patients - a Danish cross-sectional study

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Jessica Björklund ◽  
Tea Lund Laursen ◽  
Thomas Damgaard Sandahl ◽  
Holger Jon Møller ◽  
Hendrik Vilstrup ◽  
...  
Keyword(s):  
Liver Function ◽  
Macrophage Activation ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Hepatic Macrophage

Correlates of Axial Gout: A Cross-sectional Study

2012 ◽  
Vol 39 (7) ◽  
pp. 1445-1449 ◽  
Author(s):  
RUKMINI M. KONATALAPALLI ◽  
ELENA LUMEZANU ◽  
JAMES S. JELINEK ◽  
MARK D. MURPHEY ◽  
HONG WANG ◽  
...  
Keyword(s):  
Back Pain ◽  
Clinical Laboratory ◽  
Gouty Arthritis ◽  
Cross Sectional Study ◽  
Strongly Correlated ◽  
Sectional Study ◽  
Cross Sectional ◽  
American College Of Rheumatology ◽  
History Of ◽  
Hands And Feet

Objective.A cross-sectional study was undertaken to determine the prevalence of axial gout in patients with established gouty arthritis and to analyze clinical, laboratory, and radiological correlations.Methods.Forty-eight subjects with a history of gouty arthritis (American College of Rheumatology criteria) for ≥ 3 years under poor control were included. Subjects underwent history, physical examination, laboratory testing, and imaging studies, including radiographs of the hands and feet and computerized tomography (CT) of the cervical and lumbar spines and sacroiliac joints (SIJ). Patients with characteristic erosions and/or tophi in the spine or SIJ were considered to have axial or spinal gout.Results.Seventeen patients (35%) had CT evidence of spinal erosions and/or tophi, with tophi identified in 7 of the 48 subjects (15%). The spinal location of axial gout was cervical in 7 patients (15%), lumbar in 16 (94%), SIJ in 1 (6%), and more than 1 location in 14 (82%). Duration of gout, presence of back pain, and serum uric acid levels did not correlate with axial gout. Extremity radiographs characteristic of gouty arthropathy found in 21 patients (45%) were strongly correlated with CT evidence of axial gout (p < 0.001). All patients with tophi in the spine had abnormal hand or feet radiographs (p = 0.005).Conclusion.Axial gout may be a common feature of chronic gouty arthritis. The lack of correlation with back pain, the infrequent use of CT imaging in patients with back pain, and the lack of recognition of the problem of spinal involvement in gouty arthritis suggest that this diagnosis is often missed.

scholarly journals A hospital based cross sectional study on clinical, laboratory and complications profile of patients with hypertension

2021 ◽  
Vol 8 (11) ◽  
pp. 1724
Author(s):  
Keerthana Medidhi ◽  
Abhishek Sabbani
Keyword(s):  
Blood Pressure ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Kidney Disease ◽  
Blood Sugar ◽  
Clinical Laboratory ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Co Morbidity

Background: Hypertension is a major risk factor for critical diseases like coronary heart disease, stroke, kidney disease etc. Hence adequate control of blood pressure is of utmost importance to prevent these complications. Objectives of the study was to study the clinical, laboratory and complication profile of patients with hypertensionMethods: A hospital based cross sectional study was carried out among 30 known cases of hypertension. Investigations/measurements like Blood pressure, body mass index, lipid profile, fasting blood sugar were done for all cases.Results: Majority belonged to age group of >60 years (56.7%). Males were more (70%) than females (30%). About 60% had hypertension for >5 years. Only 26.7% were normal weight and remaining were either overweight or obese. The 56.7% admitted that they consumed alcohol. The 76.7% were non-smokers and only 10% were tobacco chewers. The 63.3% had family history of hypertension. Diabetes was the most common co morbidity associated with hypertension in 16.7% of the cases. The 10% each had coronary heart disease, and kidney disease. Mean levels of total cholesterol was 163.93; mean level of triglyceride was 159.53; mean level of HDL was 44.4; mean level of LDL was 84.76; mean level of Fasting blood sugar was 110.66; mean Systolic blood pressure was 134.66 and mean diastolic blood pressure was 86. Majority i.e., 90% were taking treatment for hypertension regularly while only 10% were not taking it regularly Conclusions: Hypertensives were elderly and males were more affected with hypertension than females. Majority were hypertensives for more than five years. Diabetes was the most common co morbidity. Blood pressure was under control as majority were taking treatment regularly

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