Caries Risk Assessment and Referral Tool (CRA‐RT)—A novel risk scoring system for early childhood caries in community settings

ABSTRACTBackground: While venous thromboembolism (VTE) risk assessment and prophylaxis is well established for medical and surgical in-patients, there is a paucity of evidence, and therefore guidelines, in this area for psychogeriatric in-patients. We wished to determine VTE incidence, risk, and use of prophylaxis, in a psychogeriatric in-patient population.Methods: Retrospective audit of consecutive psychogeriatric patients aged 65 years and over admitted to Bankstown Hospital over a 3-year period, 2007–2009. Using an adapted VTE risk scoring system, patients were assigned as low, medium, or high VTE risk.Results: A total of 192 patients were included in the study. Mean age was 79.1 ± 7.0 years. Out of the total, 55.2% of patients had diagnosis of dementia, and 33.3% had depression. Overall, 81.8% (157/192) were assessed as low risk, and 18.2% (35/192) as medium risk. Also, 16.7% (32/192) received VTE prophylaxis.Four new VTE events occurred in medium-risk group, and one in low-risk group (p = 0.004). Overall VTE incidence was 10.5/10,000 patient-days, but 44.2 per 10,000 in medium-risk group. VTE risk score was predictive of VTE events – IRR 6.02 (95% Confidence Intervals (CI) = 1.76–20.7, p = 0.004) for every one-point increment in risk. Depression was associated with significantly higher VTE occurrence (6.3% in those with diagnosis vs. 0.8% without, p = 0.043).Conclusion: Using a VTE risk scoring system adapted for psychogeriatric in-patients, those assessed to be at medium risk had a significantly increased rate of VTE. On this basis, we would recommend VTE prophylaxis be prescribed for psychogeriatric in-patients assessed to be at medium and high level of risk.

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

Security and Communication Networks ◽

10.1155/2019/4614721 ◽

2019 ◽

Vol 2019 ◽

pp. 1-35 ◽

Cited By ~ 3

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.

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Oral Microbiota Composition Predicts Early Childhood Caries Onset

Journal of Dental Research ◽

10.1177/0022034520979926 ◽

2020 ◽

pp. 002203452097992

Author(s):

A. Grier ◽

J.A. Myers ◽

T.G. O’Connor ◽

R.G. Quivey ◽

S.R. Gill ◽

...

Keyword(s):

Risk Assessment ◽

Early Childhood ◽

Early Childhood Caries ◽

Gene Sequencing ◽

Rrna Gene ◽

Oral Microbiota ◽

Microbiota Composition ◽

Caries Risk ◽

Rrna Gene Sequencing ◽

Childhood Caries

As the most common chronic disease in preschool children in the United States, early childhood caries (ECC) has a profound impact on a child’s quality of life, represents a tremendous human and economic burden to society, and disproportionately affects those living in poverty. Caries risk assessment (CRA) is a critical component of ECC management, yet the accuracy, consistency, reproducibility, and longitudinal validation of the available risk assessment techniques are lacking. Molecular and microbial biomarkers represent a potential source for accurate and reliable dental caries risk and onset. Next-generation nucleotide-sequencing technology has made it feasible to profile the composition of the oral microbiota. In the present study, 16S ribosomal RNA (rRNA) gene sequencing was applied to saliva samples that were collected at 6-mo intervals for 24 mo from a subset of 56 initially caries-free children from an ongoing cohort of 189 children, aged 1 to 3 y, over the 2-y study period; 36 children developed ECC and 20 remained caries free. Analyses from machine learning models of microbiota composition, across the study period, distinguished between affected and nonaffected groups at the time of their initial study visits with an area under the receiver operating characteristic curve (AUC) of 0.71 and discriminated ECC-converted from healthy controls at the visit immediately preceding ECC diagnosis with an AUC of 0.89, as assessed by nested cross-validation. Rothia mucilaginosa, Streptococcus sp., and Veillonella parvula were selected as important discriminatory features in all models and represent biomarkers of risk for ECC onset. These findings indicate that oral microbiota as profiled by high-throughput 16S rRNA gene sequencing is predictive of ECC onset.

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