scholarly journals Practical Clinical and Radiological Models to Diagnose COVID-19 on Chest CT in a French Multicentric Emergency Population

2020 ◽  
Author(s):  
Paul Schuster ◽  
Amandine Crombé ◽  
Hubert Nivet ◽  
Alice Berger ◽  
Laurent Pourriol ◽  
...  
Keyword(s):  
Clinical Data ◽  
Classification Tree ◽  
Stepwise Logistic Regression ◽  
Rt Pcr ◽  
Point Scale ◽  
Radiological Features ◽  
Cart Model ◽  
Multivariate Stepwise Logistic Regression ◽  
Independent Cohort ◽  
Do So

Abstract Our aim was to develop practical models built with simple clinical-radiological features to facilitate COVID-19 diagnosis. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 03/13/2020 to 04/14/2020 were included (244 [47.6%] with a positive RT-PCR). Chest CTs were immediately and prospectively analysed by on-call teleradiologists (OCTR) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. Multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC=0.92 versus 0.88 for OCTR) while step-LR provided the highest AUC with clinical-radiological variables (0.93 versus 0.86 for OCTR). Hence, these two simple models, depending on the availability of clinical data, could be used by any radiologist to support their conclusion in case of COVID-19 suspicion.

scholarly journals Practical clinical and radiological models to diagnose COVID-19 based on a multicentric teleradiological emergency chest CT cohort

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paul Schuster ◽  
Amandine Crombé ◽  
Hubert Nivet ◽  
Alice Berger ◽  
Laurent Pourriol ◽  
...  
Keyword(s):  
Clinical Data ◽  
Classification Tree ◽  
Real Life ◽  
Chest Ct ◽  
Stepwise Logistic Regression ◽  
Operating Characteristics ◽  
Rt Pcr ◽  
Radiological Features ◽  
Polymerase Chain ◽  
Cart Model

AbstractOur aim was to develop practical models built with simple clinical and radiological features to help diagnosing Coronavirus disease 2019 [COVID-19] in a real-life emergency cohort. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 2020-03-13 to 2020-04-14 were included as long as chest CT-scans and real-time polymerase chain reaction (RT-PCR) results were available (244 [47.6%] with a positive RT-PCR). Immediately after their acquisition, the chest CTs were prospectively interpreted by on-call teleradiologists (OCTRs) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. After pre-filtering clinical and radiological features through univariate Chi-2, Fisher or Student t-tests (as appropriate), multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively) through area under the receiver operating characteristics curves (AUC). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC = 0.92 [versus 0.88 for OCTR], sensitivity = 0.77, specificity = 0.94) while step-LR provided the highest AUC with clinical-radiological variables (AUC = 0.93 [versus 0.86 for OCTR], sensitivity = 0.82, specificity = 0.91). Hence, these two simple models, depending on the availability of clinical data, provided high performances to diagnose positive RT-PCR and could be used by any radiologist to support, modulate and communicate their conclusion in case of COVID-19 suspicion. Practically, using clinical and radiological variables (GGO, fever, presence of fibrotic bands, presence of diffuse lesions, predominant peripheral distribution) can accurately predict RT-PCR status.

scholarly journals Allogeneic Red Blood Cell Transfusion Rate and Risk Factors After Hemiarthroplasty in Elderly Patients With Femoral Neck Fracture

2021 ◽  
Vol 12 ◽  
Author(s):  
Rui Yue ◽  
Minghui Yang ◽  
Xiaohui Deng ◽  
Ping Zhang
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Femoral Neck ◽  
Elderly Patients ◽  
Blood Cell ◽  
Advanced Age ◽  
Stepwise Logistic Regression ◽  
Neck Fracture ◽  
Low Bmi ◽  
Multivariate Stepwise Logistic Regression

ObjectiveThis study aimed to determine the rate and risk factors of allogeneic red blood cell transfusions (ABT) after hemiarthroplasty (HA) in elderly patients with femoral neck fracture (FNF).MethodsThe subjects of the study were elderly patients (≥65 years old) who were admitted to the geriatric trauma orthopedics ward of Beijing Jishuitan Hospital between March 2018 and June 2019 for HA treatment due to an FNF. The perioperative data were collected retrospectively, and univariate and multivariate stepwise logistic regression analyses were performed to determine the post-operative ABT rate and its risk factors.ResultsThere were 445 patients in the study, of whom 177 (39.8%) received ABT after surgery. Multivariate stepwise logistic regression analysis showed that preoperative low hemoglobin (Hb), high intraoperative blood loss (IBL), advanced age, and a low body mass index (BMI) are independent risk factors of ABT after HA in elderly FNF patients.ConclusionABT after HA is a common phenomenon in elderly patients with FNF. Their post-operative ABT needs are related to preoperative low Hb, high IBL, advanced age, and low BMI. Therefore, ABT can be reduced by taking these factors into account. When the same patient had three risk factors (preoperative low hemoglobin, advanced age, and low BMI), the risk of ABT was very high (78.3%). Also, when patients have two risk factors of preoperative low hemoglobin and low BMI, the risk of ABT was also high (80.0%).

scholarly journals Allogeneic Red Blood Cell Transfusion Rate and Risk Factors in Elderly Patients With Femoral Neck Fracture After Hemiarthroplasty

2020 ◽  
Author(s):  
Rui Yue ◽  
Minghui Yang ◽  
Xiaohui Deng ◽  
Ping Zhang
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Femoral Neck ◽  
Elderly Patients ◽  
Blood Cell ◽  
Stepwise Logistic Regression ◽  
Stepwise Logistic Regression Analysis ◽  
Neck Fracture ◽  
Multivariate Stepwise Logistic Regression

Abstract Objective: To determine the rate and risk factors of allogeneic red blood cell transfusions (ABT) in elderly patients with femoral neck fracture (FNF) after hemiarthroplasty (HA). Methods: We conducted a study on elderly patients (≥65 years old) who were admitted to the geriatric trauma orthopedics ward of Beijing Jishuitan Hospital for HA treatment from March 2018 to February 2019 due to FNF. The perioperative data were collected retrospectively, and univariate and multivariate stepwise logistic regression analysis were performed to determine the postoperative ABT rate and its risk factors. Results: 343 patients were included in the study, of which 151 (44.0%) received ABT after surgery. Multivariate stepwise logistic regression analysis showed that preoperative low hemoglobin (Hb), high intraoperative blood loss (IBL), advanced age, and low body mass index (BMI) are independent risk factors of ABT after HA in elderly FNF patients. Conclusion: ABT after HA is a common phenomenon in elderly patients with FNF. Their postoperative ABT needs are related to preoperative low Hb, high IBL, advanced age, and low BMI. Therefore, ABT can be reduced from the above aspects.

scholarly journals DINAMIKA KENDARAAN JALAN LURUS 3 PADA GEROBAK LISTRIK PENGANGKUT SAMPAH KAPASITAS 2 m3

POROS ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Edward Suhartono ◽  
G Soeharsono ◽  
Danardono Agus Sumarsono
Keyword(s):  
Dynamic Analysis ◽  
Maximum Velocity ◽  
Vehicle Dynamic ◽  
Garbage Disposal ◽  
Tractive Effort ◽  
Analytical Result ◽  
Cart Model ◽  
Human Powered ◽  
Maximum Inclination ◽  
Do So

Abstract: A residential dump transport to a temporary garbage disposal medium using a human-powered dump cart is not humane. An electrical-powered propulsion system can be one of the eco-friendly system which can be implemented to the cart, thus substitutes the human’s role to do so. This propulsion is analyzed by using vehicle dynamic analysis. Vehicle dynamic analysis which is conducted, discuss tractive effort which overcomes resistances during vehicle’s movement and accelerates the vehicle, and specification of drive train, used to drive it. Based on analytical result, it is obtained an electric dump cart model which can move at a 25 km/h maximum velocity, 20° maximum inclination while it is empty loaded, and 10° maximum inclination while it is fully loaded. 

Abstract 13312: Risk Factors for the Development of Tachyarrhythmia Following the Norwood Procedure in the Single Ventricle Reconstruction Trial

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Matthew Oster ◽  
Shan Chen ◽  
David Pober ◽  
Yaniv Bar-Cohen ◽  
Matthew Brothers ◽  
...  
Keyword(s):  
Risk Factors ◽  
Single Ventricle ◽  
Norwood Procedure ◽  
Stepwise Logistic Regression ◽  
Chi Square ◽  
Junctional Ectopic Tachycardia ◽  
C Statistic ◽  
Model C ◽  
Multivariate Stepwise Logistic Regression ◽  
Associated Variables

Background: Tachyarrhythmias are an important contributor to morbidity following the Norwood procedure for single ventricle congenital heart disease. The purpose of this study was to determine what demographic, preoperative, or operative factors may be associated with the development of postoperative tachyarrhythmias in this population. Methods: We performed a retrospective analysis of data collected prospectively through the multicenter Pediatric Heart Network Single Ventricle Reconstruction Trial for infants undergoing a Norwood procedure in 2005-2008. Our primary outcome of interest was any documented tachyarrhythmia requiring treatment or intervention during the inpatient postoperative stay. Subjects with a documented preoperative tachyarrhythmia (n=15) were excluded. After performing univariate chi-square analyses on a variety of candidate factors, we conducted multivariate stepwise logistic regression, including spline terms for nonlinearly associated variables, to calculate the adjusted odds ratios for the final variables. Results: Of 529 subjects, 108 (20%) had at least one documented tachyarrhythmia, with 11 having more than one. Tachyarrhythmias included: 77 supraventricular tachycardia, 23 junctional ectopic tachycardia, 10 atrial flutter, 7 ventricular tachycardia, and 2 atrial fibrillation. In the final multivariate model (c-statistic=0.65), significant factors associated with arrhythmia included receiving a modified Blalock-Taussig shunt, use of ultrafiltration, and age. (Table) Conclusions: Tachyarrhythmias are common following the Norwood procedure and are associated with the modifiable risk factors of shunt type and use of ultrafiltration. In addition, when surgery is performed between 8 and 20 days of age, older age is associated with a decreasing risk for tachyarrhythmia.

scholarly journals A Comparative Study on the Clinical Features of Coronavirus 2019 (COVID-19) Pneumonia With Other Pneumonias

2020 ◽  
Vol 71 (15) ◽  
pp. 756-761 ◽  
Author(s):  
Dahai Zhao ◽  
Feifei Yao ◽  
Lijie Wang ◽  
Ling Zheng ◽  
Yongjun Gao ◽  
...  
Keyword(s):  
Clinical Features ◽  
Clinical Symptoms ◽  
Severe Pneumonia ◽  
Ground Glass Opacity ◽  
Chest Ct ◽  
Rt Pcr ◽  
Bilateral Involvement ◽  
Radiological Features ◽  
History Of ◽  
Novel Coronavirus

Abstract Background A novel coronavirus (COVID-19) has raised world concern since it emerged in Wuhan, China in December 2019. The infection may result in severe pneumonia with clusters of illness onsets. Its impacts on public health make it paramount to clarify the clinical features with other pneumonias. Methods Nineteen COVID-19 and 15 other patients with pneumonia (non-COVID-19) in areas outside of Hubei were involved in this study. Both COVID-19 and non-COVID-19 patients were confirmed to be infected using throat swabs and/or sputa with/without COVID-2019 by real-time RT-PCR. We analyzed the demographic, epidemiological, clinical, and radiological features from those patients, and compared the differences between COVID-19 and non-COVID-19. Results All patients had a history of exposure to confirmed cases of COVID-19 or travel to Hubei before illness. The median (IQR) duration was 8 (6–11) and 5 (4–11) days from exposure to onset in COVID-19 and non-COVID-19 cases, respectively. The clinical symptoms were similar between COVID-19 and non-COVID-19. The most common symptoms were fever and cough. Fifteen (78.95%) COVID-19 but 4 (26.67%) non-COVID-19 patients had bilateral involvement while 17 COVID-19 patients (89.47%) but 1 non-COVID-19 patient (6.67%) had multiple mottling and ground-glass opacity on chest CT images. Compared with non-COVID-19, COVID-19 presents remarkably more abnormal laboratory tests, including AST, ALT, γ-GT, LDH, and α-HBDH. Conclusions The COVID-19 infection has onsets similar to other pneumonias. CT scan may be a reliable test for screening COVID-19 cases. Liver function damage is more frequent in COVID-19 than non-COVID-19 patients. LDH and α-HBDH may be considerable markers for evaluation of COVID-19.

Assessing ignition probability and moisture of extinction in a Mediterranean grass fuel

2010 ◽  
Vol 19 (1) ◽  
pp. 29 ◽  
Author(s):  
A. P. Dimitrakopoulos ◽  
I. D. Mitsopoulos ◽  
K. Gatoulas
Keyword(s):  
Moisture Content ◽  
Classification Tree ◽  
Weather Conditions ◽  
Stepwise Logistic Regression ◽  
Fuel Moisture ◽  
Ignition Probability ◽  
Plant Moisture ◽  
Plant Moisture Content ◽  
Fuel Moisture Content

The objective of this study was the assessment of the probability of ignition and moisture of extinction of the annual herbaceous species Slender Oat (Avena barbata Pott. ex Link) in Greece. Multiple ignition tests were conducted in situ with a drip torch during two fire seasons, with simultaneous monitoring of the weather conditions. Stepwise logistic regression was applied to assess the probability of ignition based on plant moisture content and meteorological parameters. Fuel moisture content was determined to be the only statistically significant (P < 0.0001) parameter and, therefore, it was the only variable kept in the analysis. The logistic model correctly predicted fire ignition in 93.6% of the tests and 50% ignition probability was determined at 38.5% oven-dried weight (ODW) plant moisture content. Moisture of extinction (i.e. probability of ignition at 1%) was calculated at 55.5% ODW. Furthermore, classification tree analysis was applied to determine the independent variables that explain the variability in ignition probability. Wind speed was found to have an effect on ignition probability only at relatively high (>30% ODW) fuel moisture contents. Assessment of the ignition potential and moisture of extinction of grass fuels is a prerequisite for reliable fire danger prediction.

Noninvasive Predictors of Mortality for Patients with Chagas’ Heart Disease: A Multivariate Stepwise Logistic Regression Study

Cardiology ◽  
1994 ◽  
Vol 84 (4-5) ◽  
pp. 261-267 ◽  
Author(s):  
Reinaldo B Bestetti ◽  
Creusa M.R Dalbo ◽  
Olavo C. Freitas ◽  
Luis A.C. Teno ◽  
Oswaldo T Castilho ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Heart Disease ◽  
Stepwise Logistic Regression ◽  
Predictors Of Mortality ◽  
Multivariate Stepwise Logistic Regression

Differences in clinical predictors of influenza in adults and children with influenza-like illness

Open Medicine ◽  
2010 ◽  
Vol 5 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Maja Sočan ◽  
Katarina Prosenc ◽  
Mateja Nagode
Keyword(s):  
Clinical Data ◽  
Predictive Value ◽  
Influenza A ◽  
Influenza Infection ◽  
Care Hospital ◽  
Rt Pcr ◽  
Clinical Predictors ◽  
Influenza Like Illness ◽  
Breath Sounds ◽  
Sensitivity Specificity

AbstractInfluenza contributes significantly to morbidity and mortality in the winter season. The aim of the study was to identify clinical signs and symptoms most predictive of influenza infection in children and adults with influenza-like illness. A prospective systematic sampling analysis of clinical data collected through sentinel surveillance system for influenza in 32 primary care centers and one tertiary care hospital in Slovenia during two consecutive influenza seasons (2004/2005 and 2005/2006) was carried out. Children and adults who had influenza-like illness, defined as febrille illness with sudden onset, prostration and weakness, muscle and joint pain and at least (cough, sore throat, coryza) were included and tested for influenza A and B virus, adenovirus, respiratory syncytial virus and enterovirus by RT-PCR. Clinical data were evaluated in statistical models to identify the best predictors for the confirmation of influenza for children (under age of 15) and adults. Of 1,286 patients with influenza-like symptoms in both seasons 211 were confirmed to have influenza A or B alone and compared to 780 influenza-negative patients. A fever over 38°C, chills, headache, malaise and sore eyes revealed a significant association with positive RT-PCR test for influenza virus in children. In adults, only three symptoms were significantly related to PCR-confirmed influenza infection: fever, cough and abnormal breath sounds. The stepwise logistic regression analysis showed that four symptoms predicted influenza in children: fever (38°C or more) (p=0.010), headache (p=0.030), cough (p=0.044) and absence of abnormal breathing sounds (p=0.015) with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 5.1%, 98.1%, 57.1% and 80.1%, respectively. For adults, the strongest impact on influenza positivity was found for fever (p=0.008) and cough (p=0.085). The model for adults had less favorable characteristics, with sensitivity, specificity, PPV and NPV of 0%, 100%, 0% and 76.4%, respectively. Differences in clinical predictors of influenza in children compared to adults were found. The model for adults was acceptable but not a good one. The model for children was found to be more reliable than the prediction model for adults.

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