scholarly journals Construction of a risk assessment model of cardiovascular disease in a rural Chinese hypertensive population based on lasso‐Cox analysis

2021 ◽  
Author(s):  
Nanxiang Ouyang ◽  
Guangxiao Li ◽  
Chang Wang ◽  
Yingxian Sun
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Population Based ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Hypertensive Population ◽  
Cox Analysis

scholarly journals A Risk Assessment Model for the Identification of Sickle Cell Disease Patients at Risk for Venous Thromboembolism

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3568-3568
Author(s):  
Jifang Zhou ◽  
Gregory Sampang Calip ◽  
Edith A. Nutescu
Keyword(s):  
Risk Assessment ◽  
Venous Thromboembolism ◽  
Risk Score ◽  
Validation Cohort ◽  
Population Based ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Cell Disease ◽  
Cohort Entry ◽  
Derivation Cohort

Abstract Background: Venous thromboembolism (VTE) is associated with significant morbidity, functional disability and mortality which leads to annual direct medical costs of 6 to 8 billion U.S. dollars. The incidence of VTE among patients with sickle cell disease (SCD) is significantly higher than in those without SCD, with lifetime risk of up to 25%. The highly variable clinical phenotypes of SCD, in addition to complex pathogenesis of thrombosis in SCD, are challenges to the early identification of high-risk patients and timely initiation of anticoagulant prophylaxis. Objective: To develop a population-based risk assessment model (Predictive AlgoRithm of VTE in SCD, PARViS) for the identification of SCD patients at high-risk of VTE using least absolute shrinkage and selection operator (LASSO) methodology and compare its validity to the Caprini VTE risk assessment model. Method: We conducted a retrospective cohort study using the 2009-2014 Truven Health MarketScan® databases to identify commercially-insured health plan enrollees with VTE and SCD based on International Classification of Diseases (ICD) codes for inpatient and outpatient encounters. Baseline characteristics were assessed over the 6 months period following cohort entry and a risk window for any VTE events starting from day 181 after cohort entry and onwards. The clinical outcomes were defined as occurrence of VTE over the 30-, 90- and 180-day period. The population-based cohort was divided into derivation and validation sets in a 2:1 ratio. The risk score was calculated using LASSO generalized linear regression models and divided into three risk categories for predicting 180-day VTE risk. Kaplan-Meier survivor functions were estimated for VTE rates by estimated risk score and censored for end of continuous enrollment, and end of observation period. The C-statistic was used to assess the prediction performance of the 7-factor risk score, which was compared with the Caprini VTE risk prediction model. Results: Among 11,774 subjects with SCD in the derivation cohort, the mean (SD) age at enrollment was 32.1 (19.8) years and 62.2% were female. From the validation cohort, 5949 SCD subjects were analyzed, participants' mean (SD) age at enrollment was 32.2 (19.7) years, and 62.6% were female. The 30-, 90- and 180-day VTE rates of the overall cohort were 0.6%, 1.3% and 2.0%, respectively. The risk model included age, recent central vein catheter use (<30 day), active cancer, history of VTE, iron overload, osteomyelitis and pulmonary hypertension. Patients with SCD in the validation cohort were stratified into high-, intermediate- and low-risk in 2:3:5 ratio by VTE risk scores. Demographics and distribution of VTE risk factors are listed in Table 1. The rates of VTE at 180-days were 0.47% (95%CI 0.35%-0.64%), 1.38% (95%CI 1.10%-1.73%),6.71% (95%CI 5.94%-7.57%). [Figure 1] In the derivation cohort, C statistics were 0.845 (95%CI 0.818-0.872) for 7-factor RAM in predicting 180-day VTE, 0.883 (95%CI 0.853-0.914) for 90-day VTE, and 0.917 (95%CI 0.875-0.959) for 30-day VTE. In the validation cohort, C statistics were 0.833 (95%CI 0.791-0.875) for 7-factor VTE risk assessment model in predicting 180-day VTE, 0.877 (95%CI 0.831-0.923) for 90-day VTE, and 0.942 (95%CI 0.911-0.972) for 30-day VTE. Using the Caprini VTE risk prediction model, we found statistically significant differences (p<0.0001) with C-statistics for 180-, 90- and 30-day VTE prediction of 0.721 (95%CI 0.672-0.770), 0.775 (95%CI 0.719-0.830), and 0.826 (95%CI 0.759-0.892). [Figure 2] Conclusion: We developed and validated a 7-factor VTE risk assessment model specific to patients with SCD (PARViS). With its straightforward calculation and demonstrated accurate prediction of 6-month VTE rates in patients with SCD, the PARViS model can prove to be a useful prediction tool for clinical practitioners. Disclosures No relevant conflicts of interest to declare.

Risk assessment model for venous thromboembolism in hospitalized surgical and non-surgical patients in the 4th Hungarian Antithrombotic Guidelines entitled “Diminution and Treatment of Venous Thromboembolism”

2010 ◽  
Vol 151 (34) ◽  
pp. 1365-1374 ◽  
Author(s):  
Marianna Dávid ◽  
Hajna Losonczy ◽  
Miklós Udvardy ◽  
Zoltán Boda ◽  
György Blaskó ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Venous Thromboembolism ◽  
Assessment Model ◽  
Surgical Patients ◽  
Risk Assessment Model

A kórházban kezelt sebészeti és belgyógyászati betegekben jelentős a vénásthromboembolia-rizikó. Profilaxis nélkül, a műtét típusától függően, a sebészeti beavatkozások kapcsán a betegek 15–60%-ában alakul ki mélyvénás trombózis vagy tüdőembólia, és az utóbbi ma is vezető kórházi halálok. Bár a vénás thromboemboliát leggyakrabban a közelmúltban végzett műtéttel vagy traumával hozzák kapcsolatba, a szimptómás thromboemboliás események 50–70%-a és a fatális tüdőembóliák 70–80%-a nem a sebészeti betegekben alakul ki. Nemzetközi és hazai felmérések alapján a nagy kockázattal rendelkező sebészeti betegek többsége megkapja a szükséges trombózisprofilaxist. Azonban profilaxis nélkül marad a rizikóval rendelkező belgyógyászati betegek jelentős része, a konszenzuson alapuló nemzetközi és hazai irányelvi ajánlások ellenére. A belgyógyászati betegek körében növelni kell a profilaxisban részesülők arányát és el kell érni, hogy trombózisrizikó esetén a betegek megkapják a hatásos megelőzést. A beteg trombóziskockázatának felmérése fontos eszköze a vénás thromboembolia által veszélyeztetett betegek felderítésének, megkönnyíti a döntést a profilaxis elrendeléséről és javítja az irányelvi ajánlások betartását. A trombózisveszély megállapításakor, ha nem ellenjavallt, profilaxist kell alkalmazni. „A thromboemboliák kockázatának csökkentése és kezelése” című, 4. magyar antithromboticus irányelv felhívja a figyelmet a vénástrombózis-rizikó felmérésének szükségességére, és elsőként tartalmazza a kórházban fekvő belgyógyászati és sebészeti betegek kockázati kérdőívét. Ismertetjük a kockázatbecslő kérdőíveket és áttekintjük a kérdőívekben szereplő rizikófaktorokra vonatkozó bizonyítékokon alapuló adatokat.

Signature Analysis: Statistical Models and Their Application to FA

1996 ◽  
Author(s):  
C.K. Lakshminarayan ◽  
S. Pabbisetty ◽  
O. Adams ◽  
F. Pires ◽  
M. Thomas ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Analysis ◽  
Statistical Models ◽  
Essential Elements ◽  
Assessment Model ◽  
Signature Analysis ◽  
Risk Assessment Model ◽  
Sample Sizes ◽  
Reliability Engineering ◽  
Semiconductor Chips

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.

A semi-quantitative risk assessment model for the outbreak of grass carp hemorrhage

2013 ◽  
Vol 19 (3) ◽  
pp. 521-527 ◽  
Author(s):  
Song YANG ◽  
Shuqin WU ◽  
Ningqiu LI ◽  
Cunbin SHI ◽  
Guocheng DENG ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Grass Carp ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Risk Assessment Model

INTEGRAL RISK ASSESSMENT MODEL OF GEODYNAMIC ORIGIN EMERGENCY SITUATIONS

2020 ◽  
Vol 71 ◽  
pp. 162-171
Author(s):  
A. O. Faddeev ◽  
◽  
S. A. Pavlova ◽  
Keyword(s):  
Risk Assessment ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Emergency Situations

scholarly journals An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

2021 ◽  
Vol 13 (2) ◽  
pp. 826
Author(s):  
Meiling Zhou ◽  
Xiuli Feng ◽  
Kaikai Liu ◽  
Chi Zhang ◽  
Lijian Xie ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Assessment Model ◽  
Risk Assessments ◽  
Risk Assessment Model ◽  
Risk Area ◽  
The North ◽  
Coastal Cities ◽  
Risk Areas ◽  
The City

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.

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