scholarly journals Of Screening, Stratification, and Scores

2021 ◽  
Vol 11 (8) ◽  
pp. 736
Author(s):  
Bartha M. Knoppers ◽  
Alexander Bernier ◽  
Palmira Granados Moreno ◽  
Nora Pashayan
Keyword(s):  
Risk Stratification ◽  
Health Risk ◽  
Health Data ◽  
Risk Scores ◽  
Ethical Challenges ◽  
Clinical Implementation ◽  
Stratified Care ◽  
Large Databases ◽  
Risk Scoring ◽  
The Rich

Technological innovations including risk-stratification algorithms and large databases of longitudinal population health data and genetic data are allowing us to develop a deeper understanding how individual behaviors, characteristics, and genetics are related to health risk. The clinical implementation of risk-stratified screening programmes that utilise risk scores to allocate patients into tiers of health risk is foreseeable in the future. Legal and ethical challenges associated with risk-stratified cancer care must, however, be addressed. Obtaining access to the rich health data that are required to perform risk-stratification, ensuring equitable access to risk-stratified care, ensuring that algorithms that perform risk-scoring are representative of human genetic diversity, and determining the appropriate follow-up to be provided to stratification participants to alert them to changes in their risk score are among the principal ethical and legal challenges. Accounting for the great burden that regulatory requirements could impose on access to risk-scoring technologies is another critical consideration.

Risk Stratification in Acute Pulmonary Embolism: The Latest Algorithms

2021 ◽  
Vol 42 (02) ◽  
pp. 183-198
Author(s):  
Georgios A. Triantafyllou ◽  
Oisin O'Corragain ◽  
Belinda Rivera-Lebron ◽  
Parth Rali
Keyword(s):  
Pulmonary Embolism ◽  
Risk Stratification ◽  
Prediction Models ◽  
Bleeding Risk ◽  
Hemodynamic Instability ◽  
Reperfusion Therapy ◽  
Mortality Prediction ◽  
Risk Scores ◽  
Short Term Mortality ◽  
Urgent Patient

AbstractPulmonary embolism (PE) is a common clinical entity, which most clinicians will encounter. Appropriate risk stratification of patients is key to identify those who may benefit from reperfusion therapy. The first step in risk assessment should be the identification of hemodynamic instability and, if present, urgent patient consideration for systemic thrombolytics. In the absence of shock, there is a plethora of imaging studies, biochemical markers, and clinical scores that can be used to further assess the patients' short-term mortality risk. Integrated prediction models incorporate more information toward an individualized and precise mortality prediction. Additionally, bleeding risk scores should be utilized prior to initiation of anticoagulation and/or reperfusion therapy administration. Here, we review the latest algorithms for a comprehensive risk stratification of the patient with acute PE.

scholarly journals Quantitative disease risk scores from EHR with applications to clinical risk stratification and genetic studies

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Danqing Xu ◽  
Chen Wang ◽  
Atlas Khan ◽  
Ning Shang ◽  
Zihuai He ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Disease Risk ◽  
Association Studies ◽  
Large Datasets ◽  
Risk Scores ◽  
Sequencing Data ◽  
Case Definitions ◽  
Phenotypic Data ◽  
Clinical Risk ◽  
Phenotypic Features

AbstractLabeling clinical data from electronic health records (EHR) in health systems requires extensive knowledge of human expert, and painstaking review by clinicians. Furthermore, existing phenotyping algorithms are not uniformly applied across large datasets and can suffer from inconsistencies in case definitions across different algorithms. We describe here quantitative disease risk scores based on almost unsupervised methods that require minimal input from clinicians, can be applied to large datasets, and alleviate some of the main weaknesses of existing phenotyping algorithms. We show applications to phenotypic data on approximately 100,000 individuals in eMERGE, and focus on several complex diseases, including Chronic Kidney Disease, Coronary Artery Disease, Type 2 Diabetes, Heart Failure, and a few others. We demonstrate that relative to existing approaches, the proposed methods have higher prediction accuracy, can better identify phenotypic features relevant to the disease under consideration, can perform better at clinical risk stratification, and can identify undiagnosed cases based on phenotypic features available in the EHR. Using genetic data from the eMERGE-seq panel that includes sequencing data for 109 genes on 21,363 individuals from multiple ethnicities, we also show how the new quantitative disease risk scores help improve the power of genetic association studies relative to the standard use of disease phenotypes. The results demonstrate the effectiveness of quantitative disease risk scores derived from rich phenotypic EHR databases to provide a more meaningful characterization of clinical risk for diseases of interest beyond the prevalent binary (case-control) classification.

scholarly journals EPID-09. QUANTIFYING SOCIAL DETERMINANTS OF HEALTH AMONG GLIOMA PATIENTS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii80-ii80
Author(s):  
Angelica Hutchinson ◽  
Alexandria Marshall ◽  
Fang-Chi Hsu ◽  
Kathryn Weaver ◽  
Alisha DeTroye ◽  
...  
Keyword(s):  
Health Risk ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Active Treatment ◽  
Economic Education ◽  
Neighborhood Environment ◽  
Determinants Of Health ◽  
Risk Scores ◽  
Diffuse Astrocytoma ◽  
Modifiable Factors

Abstract BACKGROUND Social determinants of health (SDH) are modifiable factors that contribute to health outcomes. Despite studies linking SDHs with cervical, ovarian, and prostate cancer outcomes, few studies have explored SDHs in glioma patients. We conducted a cross-sectional survey to characterize and contextualize SDHs in glioma patients by community income, rural/urban residence, and treatment status. METHODS Two validated instruments: PRAPARE (Protocol for responding to and assessing patents’ assets risks and experiences) and AHC (accountable health communities instrument) quantified SDHs; along with study-specific supplemental questions. Risk scores were calculated and combined into an overall and domain-specific (economic, education, neighborhood environment, social context, and healthcare) SDH risk, with a higher score being indicative of higher SDH risk. Scores were compared between low-income (LIC) vs high-income (HIC) communities (defined by median household income), urban vs rural (defined by zip code), and active treatment vs surveillance (determined by patient medical record) using Wilcoxon rank-sum test. RESULTS 100 glioma patients were enrolled: mean age 53 years (range: 22–78); 49% male; 18% oligodendroglioma, 34% diffuse astrocytoma, 38% glioblastoma, 10% other glioma; 68% resided in LICs, 27% in rural zip codes, and 51% were on active treatment. Overall, SDH risk scores were low (mean= 4.43-out-of-38). Scores in the healthcare domain were the highest. Compared to patients from LICs, patients from HICs had higher healthcare risk scores (p< 0.05). Surveillance patients had higher overall SDH risk on the AHC than patients in active treatment (p< 0.05), with age being a confounder. In multivariable analysis, younger age, and astrocytoma histology were associated with higher social health risk. CONCLUSION Glioma patients report relatively few SDH risk factors on standardized instruments designed for general clinic populations. The higher health risk observed in patients in HICs and higher AHC risk for those in surveillance will be further explored in planned qualitative analysis.

scholarly journals Current challenges and opportunities for pharmacogenomics: perspective of the Industry Pharmacogenomics Working Group (I-PWG)

2021 ◽  
Author(s):  
Karina Bienfait ◽  
Aparna Chhibber ◽  
Jean-Claude Marshall ◽  
Martin Armstrong ◽  
Charles Cox ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Working Group ◽  
Direct Sequencing ◽  
Risk Scores ◽  
Pharmaceutical Companies ◽  
Patient Privacy ◽  
Clinical Implementation ◽  
Genomic Databases ◽  
Group I ◽  
Trial Participants

AbstractPharmaceutical companies have increasingly utilized genomic data for the selection of drug targets and the development of precision medicine approaches. Most major pharmaceutical companies routinely collect DNA from clinical trial participants and conduct pharmacogenomic (PGx) studies. However, the implementation of PGx studies during clinical development presents a number of challenges. These challenges include adapting to a constantly changing global regulatory environment, challenges in study design and clinical implementation, and the increasing concerns over patient privacy. Advances in the field of genomics are also providing new opportunities for pharmaceutical companies, including the availability of large genomic databases linked to patient health information, the growing use of polygenic risk scores, and the direct sequencing of clinical trial participants. The Industry Pharmacogenomics Working Group (I-PWG) is an association of pharmaceutical companies actively working in the field of pharmacogenomics. This I-PWG perspective will provide an overview of the steps pharmaceutical companies are taking to address each of these challenges, and the approaches being taken to capitalize on emerging scientific opportunities.

scholarly journals Prospect of positron emission tomography for abdominal aortic aneurysm risk stratification

2021 ◽  
Author(s):  
Richa Gandhi ◽  
Michael Bell ◽  
Marc Bailey ◽  
Charalampos Tsoumpas
Keyword(s):  
Positron Emission Tomography ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Risk Stratification ◽  
Patient Management ◽  
Emission Tomography ◽  
Clinical Implementation ◽  
Positron Emission ◽  
Abdominal Aortic

AbstractAbdominal aortic aneurysm (AAA) disease is characterized by an asymptomatic, permanent, focal dilatation of the abdominal aorta progressing towards rupture, which confers significant mortality. Patient management and surgical decisions rely on aortic diameter measurements via abdominal ultrasound surveillance. However, AAA rupture can occur at small diameters or may never occur at large diameters, implying that anatomical size is not necessarily a sufficient indicator. Molecular imaging may help identify high-risk patients through AAA evaluation independent of aneurysm size, and there is the question of the potential role of positron emission tomography (PET) and emerging role of novel radiotracers for AAA. Therefore, this review summarizes PET studies conducted in the last 10 years and discusses the usefulness of PET radiotracers for AAA risk stratification. The most frequently reported radiotracer was [18F]fluorodeoxyglucose, indicating inflammatory activity and reflecting the biomechanical properties of AAA. Emerging radiotracers include [18F]-labeled sodium fluoride, a calcification marker, [64Cu]DOTA-ECL1i, an indicator of chemokine receptor type 2 expression, and [18F]fluorothymidine, a marker of cell proliferation. For novel radiotracers, preliminary trials in patients are warranted before their widespread clinical implementation. AAA rupture risk is challenging to evaluate; therefore, clinicians may benefit from PET-based risk assessment to guide patient management and surgical decisions.

scholarly journals Prevalence and Correlates of Alcohol Use among a Sample of Nigerian Semirural Community Dwellers in Nigeria

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Victor Olufolahan Lasebikan ◽  
Bolanle Adeyemi Ola
Keyword(s):  
Rural Communities ◽  
Alcohol Use ◽  
Health Risk ◽  
Risk Scores ◽  
Low Socioeconomic ◽  
Care Services ◽  
Associated Risk Factors ◽  
Substance Involvement ◽  
Current Alcohol ◽  
Community Dwellers

Objective. To determine the prevalence and correlates of alcohol use among a sample of Nigerian semirural community dwellers in Nigeria.Methods. In a single arm nonrandomized intervention study, the assessment of baseline hazardous and harmful alcohol use and associated risk factors was conducted in two semirural local government areas of Oyo State, Nigeria, with the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Participants included 1203 subjects 15 years and older, recruited between October 2010 and April 2011. ASSIST score of 0–10 was classified as lower risk scores, 11–26 as moderate risk, and 27+ as high risk.Results. Prevalence of lifetime alcohol use was 57.9% and current alcohol use was 23.7%. Current alcohol use was more prevalent among the younger age groupp=0.02, male genderp=0.003, unmarriedp<0.01, low educational levelp=0.003, low socioeconomic classp=0.01, unemployedp<0.001, and the Christiansp<0.01. Of the current drinkers, the majority (69.1%) were at either moderate or high health risk from alcohol use.Conclusion. Alcohol consumption is prevalent in semirural communities in Nigeria and the majority of these drinkers are at moderate or high health risk. Screening, brief intervention, and referral for treatment for unhealthy alcohol use should be integrated into community care services in Nigerian rural communities.

scholarly journals Development of a risk stratification and prevention index for stratified care in chronic low back pain. Focus

PAIN Reports ◽  
2017 ◽  
Vol 2 (6) ◽  
pp. e623 ◽  
Author(s):  
Pia-Maria Wippert ◽  
Anne-Katrin Puschmann ◽  
David Drießlein ◽  
Adamantios Arampatzis ◽  
Winfried Banzer ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Risk Stratification ◽  
Chronic Low Back Pain ◽  
Low Back ◽  
Stratified Care

Assessment of inter-institutional post-operative hypoparathyroidism status using a common data model (Preprint)

2021 ◽  
Author(s):  
Joon-Hyop Lee ◽  
Suhyun Kim ◽  
Kwangsoo Kim ◽  
Young Jun Chai ◽  
Hyeong Won Yu ◽  
...  
Keyword(s):  
Data Model ◽  
Tumor Resection ◽  
Health Data ◽  
Common Data Model ◽  
Tertiary Institutions ◽  
Logistic Analysis ◽  
Large Databases ◽  
Tertiary Hospitals ◽  
Tingling Sensation ◽  
Transient Hypoparathyroidism

BACKGROUND Post-thyroidectomy hypoparathyroidism may result in various transient or permanent symptoms, ranging from tingling sensation to severe breathing difficulties. Its incidence varies among surgeons and institutions, making it difficult to determine its actual incidence and associated factors. OBJECTIVE This study attempted to estimate the incidence of post-operative hypoparathyroidism in patients at two tertiary institutions that share a common data model, the Observational Health Data Sciences and Informatics. METHODS This study used the Common Data Model to extract explicitly specified encoding and relationships among concepts using standardized vocabularies. The EDI-codes of various thyroid disorders and thyroid operations were extracted from two separate tertiary hospitals between January 2013 and December 2018. Patients were grouped into no evidence of/transient/permanent hypoparathyroidism groups to analyze the likelihood of hypoparathyroidism occurrence related to operation types and diagnosis RESULTS Of the 4848 eligible patients at the two institutions who underwent thyroidectomy, 1370 (28.26%) experienced transient hypoparathyroidism and 251 (5.18%) experienced persistent hypoparathyroidism. Univariate logistic regression analysis predicted that, relative to total bilateral thyroidectomy, radical tumor resection was associated with a 48% greater likelihood of transient hypoparathyroidism and a 102% greater likelihood of persistent hypoparathyroidism. Moreover, multivariate logistic analysis found that radical tumor resection was associated with a 50% greater likelihood of transient hypoparathyroidism and a 97% greater likelihood of persistent hypoparathyroidism than total bilateral thyroidectomy. CONCLUSIONS These findings, by integrating and analyzing two databases, suggest that this analysis could be expanded to include other large databases that share the same Observational Health Data Sciences and Informatics protocol.

scholarly journals Development of a Crash Risk-Scoring Tool for Pedestrian and Bicycle Projects in Oregon

2018 ◽  
Vol 2672 (32) ◽  
pp. 30-39 ◽  
Author(s):  
Yi Wang ◽  
Christopher M. Monsere ◽  
Chen Chen ◽  
Haizhong Wang
Keyword(s):  
Risk Model ◽  
Motor Vehicle ◽  
Research Effort ◽  
Google Earth ◽  
Risk Scores ◽  
Crash Risk ◽  
Scoring Method ◽  
Risk Scoring ◽  
Pedestrian Crashes ◽  
Scoring Tool

Methods for identifying and prioritizing high-crash locations for safety improvements are generally crash-based. There are fewer reported crashes involving non-motorized users and, in most states, reported crashes must involve a motor vehicle. This means that minor, non-injury events are not reported and those crashes that are reported tend to be more severe. Selecting projects based only on crash performance is sometimes limiting for these crash types and predicting where these crashes will occur next is also a challenging task. An alternative to crash-based selection is to develop risk-based criteria and methods. This paper presents the results of a research effort to develop a risk-scoring method with weights derived from data for use in project screening and selection in Oregon. To develop the risk model, data were collected from 188 segments and 184 intersections randomly selected on both state and non-state roadways. Geometric, land use, volume, and crash data were collected from Google Earth, EPA’s Smart Location Database, and the Oregon Department of Transportation crash database from 2009 to 2013. The sample included 213 bicycle and pedestrian crashes on the segments and 238 at intersections. Logistic regression models were developed and the outputs used to create pedestrian and bicycle risk-scoring tools for segments and intersections. The risk-scoring tool was applied to safety projects identified in the 2015 All Roads Transportation Safety (ARTS) project lists from Oregon. The risk scores for the case study applications aligned reasonably well with the project’s benefits-costs estimates.

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