scholarly journals An innovative risk-scoring system of dental procedures and safety protocols in the COVID-19 era

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
M. E. Bizzoca ◽  
G. Campisi ◽  
Lorenzo Lo Muzio
Keyword(s):  
Scoring System ◽  
Direct Contact ◽  
Infection Risk ◽  
Risk Scores ◽  
Risk Level ◽  
Clinical Tool ◽  
Dental Procedures ◽  
Risk Scoring ◽  
General Dentists ◽  
Risk Scoring System

Abstract Background The aim of this paper is to assess an innovative risk score for common dental procedures, based on the most recent contaminant SARS-CoV-2. After scoring the level of infection risk, safety procedures, advice and personal protective equipment (PPE) are recommended for the dental team in each dental practice. Methods The authors of this research analysed 42 common dental procedures on the basis of known transmission risks. In increasing order, many consider the parameters leading to different risk scores for the dental team and patients for each procedure to be: direct contact with saliva (score 1), direct contact with blood (score 2), production of low levels of spray/aerosol via air–water syringes (score 3), the production of high levels of spray/aerosol from rotating, ultrasound and piezoelectric tools (score 4); and the duration of the procedure, which may increase the risk of procedures producing droplets and aerosols. Results Using this innovative risk-scoring system, the authors classified the different dental procedures according to low, medium or high risk: low (1–3), medium (4–5), high (≥ 6). A safety protocol for each procedure was thereafter matched with the calculated risk level. Conclusions The innovative risk-scoring system presented in this research permits the reclassification of dental procedures according to the infection risk level. Consequently, specific procedures, previously considered as entry level, will now merit revision. This paper also highlighted an effective and routine clinical tool for general dentists and oral medicine practitioners.

scholarly journals An Inflammatory Polymorphisms Risk Scoring System for the Differentiation of Ischemic Stroke Subtypes

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Elena Muiño ◽  
Jurek Krupinski ◽  
Caty Carrera ◽  
Cristina Gallego-Fabrega ◽  
Joan Montaner ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Genetic Risk ◽  
Scoring System ◽  
Cardioembolic Stroke ◽  
Risk Scores ◽  
Stroke Subtype ◽  
Stroke Subtypes ◽  
Risk Scoring ◽  
Risk Scoring System ◽  
Independent Cohort

Inflammation has been associated with atherothrombotic stroke and recently with cardioembolic stroke. Different genetic risk factors have been specifically associated with the subtypes of ischemic stroke (cardioembolic, atherothrombotic, and lacunar). However, there are no studies that have generated genetic risk scores for the different subtypes of ischemic stroke using polymorphisms associated with inflammation.Methods.We have analyzed 68 polymorphisms of 30 inflammatory mediator genes in 2,685 subjects: 1,987 stroke cases and 698 controls. We generated a genetic scoring system with the most significant polymorphisms weighted by the odds ratio of every polymorphism and taken into consideration the stroke subtype.Results.Three polymorphisms, rs1205 (CRPgene), rs1800779, and rs2257073 (NOS3gene), were associated with cardioembolic stroke (pvalue<0.05). The score generated was only associated with the cardioembolic stroke subtype (pvalue: 0.001) and was replicated in an independent cohort (pvalue: 0.017). The subjects with the highest score presented a cardioembolic stroke in 92.2% of the cases (pvalue: 0.002).Conclusion.The genetics of inflammatory markers is more closely associated with cardioembolic strokes than with atherothrombotic or lacunar strokes. The genetic risk scoring system could be useful in the prediction and differentiation of ischemic stroke; however, it might be specific to particular ischemic stroke subtypes.

scholarly journals A Comparative Study of JASO TP15002-Based Security Risk Assessment Methods for Connected Vehicle System Design

2019 ◽  
Vol 2019 ◽  
pp. 1-35 ◽  
Author(s):  
Yasuyuki Kawanishi ◽  
Hideaki Nishihara ◽  
Daisuke Souma ◽  
Hirotaka Yoshida ◽  
Yoichi Hata
Keyword(s):  
Risk Assessment ◽  
Comparative Study ◽  
Scoring System ◽  
Risk Scores ◽  
Connected Vehicle ◽  
Security Risk ◽  
Multiple Use ◽  
Vehicle Systems ◽  
Risk Scoring ◽  
Risk Scoring System

In recent years, much attention has been paid to autonomous vehicles and security threats on such vehicles have become an important issue. One of these examples is a command injection issue on a gateway ECU, which was reported in 2016. In order to mitigate these threats, the secure design of connected vehicle systems, which is done at the concept phase during development, has become increasingly important in industry. From this perspective, a security guideline such as JASO TP15002 which specifies two concrete methods, CRSS (CVSS Based Risk Scoring System) and RSMA (Risk Scoring Methodology for Automotive System), was made public in 2015. The latest work on the application of TP15002 to the ITU-T X.1373 standard was published in 2017. However, the risk assessment in this publication seems limited. It is not clear from this publication how systematically the risk assessment task in TP15002 can be performed at the implementation level. Another interesting question is how different methods affect the risk scores of connected vehicle systems. In this paper, we focus on the risk assessment phase in JASO TP15002. For a systematic risk assessment, we introduce an idea of asset container and propose to extend CRSS to a novel RSS (Risk Scoring System), RSS-CVSSv3, by appropriately replacing CVSSv2 vulnerability scoring system on which CRSS is based with CVSSv3. To address the above questions, we perform a comparative study on CRSS, RSMA, and RSS-CVSSv3 for multiple use cases such as a CGW (Central Gateway) and a drone, to examine the efficiency and usefulness of our methods. For this comparative purpose, we devise an interesting approach for the refinement of RSMA to the obstacles in comparing CRSS with RSMA.

scholarly journals Prospective Analysis of Risk for Hypothyroidism after Hemithyroidectomy

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Virgilijus Beisa ◽  
Darius Kazanavicius ◽  
Arminas Skrebunas ◽  
Gintaras Simutis ◽  
Justinas Ivaska ◽  
...  
Keyword(s):  
Risk Factors ◽  
Scoring System ◽  
Significant Risk ◽  
Thyroid Stimulating Hormone ◽  
Risk Scores ◽  
Weight Index ◽  
Risk Scoring ◽  
Lower Ratio ◽  
Risk Scoring System ◽  
Benign Thyroid

Objectives. To evaluate risk factors and to develop a simple scoring system to grade the risk of postoperative hypothyroidism (PH).Methods. In a controlled prospective study, 109 patients, who underwent hemithyroidectomy for a benign thyroid disease, were followed up for 12 months. The relation between clinical data and PH was analyzed for significance. A risk scoring system based on significant risk factors and clinical implications was developed.Results. The significant risk factors of PH were higher TSH (thyroid-stimulating hormone) level and lower ratio of the remaining thyroid weight to the patient’s weight (derived weight index). Based on the log of risk factor, preoperative TSH level greater than 1.4 mU/L was assigned 2 points; 1 point was for 0.8–1.4 mU/L. The derived weight index lower than 0.8 g/kg was assigned 1 point. A risk scoring system was calculated by summing the scores. The incidences of PH were 7.3%, 30.4%, and 69.2% according to the risk scores of 0-1, 2, and 3.Conclusion. Risk factors for PH are higher preoperative TSH level and lower derived weight index. Our developed risk scoring system is a valid and reliable tool to identify patients who are at risk for PH before surgery.

scholarly journals A Risk Scoring System to Predict Progression to Severe Pneumonia in Patients with Covid-19

2020 ◽  
Author(s):  
Ji Yeon Lee ◽  
Byung-Ho Nam ◽  
Mhinjine Kim ◽  
Jongmin Hwang ◽  
Jin Young Kim ◽  
...  
Keyword(s):  
High Risk ◽  
Sensitivity And Specificity ◽  
Scoring System ◽  
Resource Constraints ◽  
Validation Cohort ◽  
Severe Pneumonia ◽  
High Risk Group ◽  
Risk Scores ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Rapid outbreak of coronavirus disease 2019 (Covid-19) raised major concern regarding medical resource constraints. We constructed and validated a scoring system for early prediction of progression to severe pneumonia in patients with Covid-19. A total of 561 patients from a Covid-19 designated hospital in Daegu, South Korea were randomly divided into two cohorts: development cohort (N=421) and validation cohort (N=140). We used multivariate logistic regression to identify four independent risk predictors for progression to severe pneumonia and constructed a risk scoring system by giving each factor a number of scores corresponding to its regression coefficient. We calculated risk scores for each patient and defined two groups: low risk (0 to 8 points) and high risk (9 to 20 points). In the development cohort, the sensitivity and specificity were 83.8% and 78.9%. In the validation cohort, the sensitivity and specificity were 70.8% and 79.3%, respectively. The C-statistics was 0.884 (95% CI, 0.833-0.934) in the development cohort and 0.828 (95% CI, 0.733-0.923) in the validation cohort. This risk scoring system is useful to identify high-risk group for progression to severe pneumonia in Covid-19 patients and can prevent unnecessary overuse of medical care in limited-resource settings.

A Risk Scoring System for Predicting Overall Survival in Patients with Liver Cancer

2020 ◽  
Author(s):  
Haibei Xin ◽  
Guanxiong Zhang ◽  
Wei Zhou ◽  
Shanshan Li ◽  
Minfeng Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Liver Cancer ◽  
Scoring System ◽  
Risk Scoring ◽  
Risk Scoring System

A Novel Risk Scoring System for Predicting Primary Graft Dysfunction after Orthotopic Heart Transplantation

2020 ◽  
Vol 26 (10) ◽  
pp. S136-S137
Author(s):  
Syed Adeel Ahsan ◽  
Jasjit Bhinder ◽  
Syed Zaid ◽  
Parija Sharedalal ◽  
Chhaya Aggarwal-Gupta ◽  
...  
Keyword(s):  
Heart Transplantation ◽  
Scoring System ◽  
Orthotopic Heart Transplantation ◽  
Primary Graft Dysfunction ◽  
Graft Dysfunction ◽  
Risk Scoring ◽  
Risk Scoring System

scholarly journals Novel risk scoring system for metastatic renal cell carcinoma patients treated with cabozantinib

2021 ◽  
pp. 100393
Author(s):  
Dylan J. Martini ◽  
Meredith R. Kline ◽  
Yuan Liu ◽  
Julie M. Shabto ◽  
Bradley C. Carthon ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Scoring System ◽  
Risk Scoring ◽  
Risk Scoring System

scholarly journals Risk Scoring System of Mortality and Prediction Model of Hospital Stay for Critically Ill Patients Receiving Parenteral Nutrition

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 853
Author(s):  
Jee-Yun Kim ◽  
Jeong Yee ◽  
Tae-Im Park ◽  
So-Youn Shin ◽  
Man-Ho Ha ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Linear Regression ◽  
Parenteral Nutrition ◽  
Prediction Model ◽  
Scoring System ◽  
Prediction Equation ◽  
Icu Patients ◽  
Risk Scoring ◽  
Risk Scoring System

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.

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