Association Of Lymphoma Family History (FH) With Other Risk Factors For Cancer Development: Analysis Of An Internet-Based Risk Assessment Tool

2020 ◽  
Vol 108 (3) ◽  
pp. e760-e761
Author(s):  
R. O'Keefe ◽  
M.J. LaRiviere ◽  
C. Vachani ◽  
M.K. Hampshire ◽  
C. Bach ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Family History ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Cancer Development ◽  
Development Analysis

scholarly journals Choice of a suitable diabetes risk assessment tool in Nepal – can we learn from Canada?

2016 ◽  
Vol 6 (2) ◽  
pp. 548-550
Author(s):  
Gina Agarwal ◽  
Brijesh Sathian ◽  
Sutapa Agrawal
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Health Outcomes ◽  
Assessment Tool ◽  
National Policy ◽  
Diabetes Risk ◽  
Risk Assessment Tool ◽  
Educational Tool ◽  
Diabetes Risk Factors ◽  
The Masses

If the population can be made more aware about diabetes by the use of a risk assessment tool as an educational tool as well, it could help to curb the diabetes epidemic in Nepal. Education of the masses about diabetes risk factors, prevention, and complications is urgently needed, using clear and simple messages. National policy efforts can be strengthened and health  outcomes improved when awareness is increased. Perhaps learning from Canada is a start, and Nepal will be able to make progress with something simple like ‘NEPAL-RISK’?

scholarly journals Comparison of Fall Risk Assessment Tools for Older Indonesian Adults in the Elderly Home and the Community

2019 ◽  
Vol 8 (3) ◽  
pp. 241
Author(s):  
Indri Hapsari Susilowati ◽  
Susiana Nugraha ◽  
Sabarinah Sabarinah ◽  
Bonardo Prayogo Hasiholan ◽  
Supa Pengpid ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Fall Risk ◽  
Assessment Tool ◽  
The Elderly ◽  
Risk Assessment Tool ◽  
Fall Risk Assessment ◽  
Elderly Home ◽  
Balance Confidence ◽  
Confidence Scale

Introduction: One of the causes of disability among elderly is falling. The ability to predict the risk of falls among this group is important so that the appropriate treatment can be provided to reduce the risk. The objective of this study was to compare the Stopping Elderly Accidents, Deaths, & Injuries (STEADI) Initiative from the Centers for Disease Control and Prevention (CDC) and The Johns Hopkins Fall Risk Assessment Tool (JHFRAT) from the Johns Hopkins University. Methods: This study used the STEADI tool, JHFRAT, Activities-Specific Balance Confidence Scale (ABC), and The Geriatric Depression Scale (GDS). The study areas were in community and elderly home in both public and private sectors and the samples were 427 after cleaning. Results: The results for the STEADI and JHFRAT tools were similar where the respondents at highest risk of falling among women (STEADI: 49%; JHFRAT: 3.4%), in Bandung area (63.5%; 5.4%), in private homes (63.3%; 4.4%), non-schools (54.6%; 6.2%), aged 80 or older (64.8%; 6.7%) and not working (48.9%;3.3%). The regression analysis indicated that there was a significant relationship between the risk factors for falls in the elderly determined by the JHFRAT and STEADI tools: namely, region, type of home, age, disease history, total GDS and ABC averages. Conclusion: Despite the similarity in the risk factors obtained through these assessments, there was a significant difference between the results for the STEADI tool and the JHFRAT. The test strength was 43%. However, STEADI is more sensitive to detect fall risk smong elderly than JHFRATKeywords: Activities-Specific Balance Confidence scale, elderly, fall risk,The Johns Hopkins Fall Risk Assessment Tool, the Stopping Elderly Accidents, Deaths, & Injuries

The genetic family history as a risk assessment tool in internal medicine

2003 ◽  
Vol 5 (2) ◽  
pp. 84-91 ◽  
Author(s):  
Theresa M. Frezzo ◽  
Wendy S. Rubinstein ◽  
Daniel Dunham ◽  
Kelly E. Ormond
Keyword(s):  
Internal Medicine ◽  
Risk Assessment ◽  
Family History ◽  
Assessment Tool ◽  
Risk Assessment Tool

Development of a risk assessment tool for women with a family history of breast cancer

2005 ◽  
Vol 29 (5) ◽  
pp. 433-439 ◽  
Author(s):  
Dejana Braithwaite ◽  
Stephen Sutton ◽  
James Mackay ◽  
Judith Stein ◽  
Jon Emery
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Family History ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
History Of

scholarly journals Impact of multiple factors on the incidence of developmental dysplasia of the hip: risk assessment tool

2022 ◽  
Author(s):  
Łukasz Pulik ◽  
Katarzyna Poszka ◽  
Krzysztof Romaniuk ◽  
Aleksandra Sibilska ◽  
Andrzej Jedynak ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Assessment Tool ◽  
Developmental Dysplasia ◽  
Risk Assessment Tool ◽  
Risk Calculator ◽  
Dysplasia Of The Hip

Abstract Introduction: Developmental dysplasia of the hip (DDH) is one of the most common musculoskeletal conditions in children. Not treated DDH leads to disability, gait abnormalities, limb shortening and chronic pain. Our study aims to determine the impact of multiple risk factors on the occurrence of DDH and develop an interactive risk assessment tool.Materials and Methods: We conducted a retrospective cohort study in the Outpatient Clinic for Children of University Hospital. The Graf classification system was used for ultrasonographic universal screening. In total, 3102 infants met the eligibility criteria (n =6204 hip joints). Results: The incidence of DDH was 4.45%. In multivariate analysis, risk factors for DDH were weight (OR = 2.17 (1.41-3.32)), week of delivery (OR = 1.18 (1.00-1.37)), gender (OR = 8.16 (4.86-13.71)), breech delivery presentation (OR = 5.92 (3.37-10.40)), symptoms of DDH (25.28 (8.77-72.83)) and positive family history in siblings (5.74 (2.68-12.31)). Multivariate logistic regression predictive model was used to construct the interactive risk calculator.Conclusion: We confirmed well-known DDH risk factors in the studied population. Our results support the recent hypothesis that preterm infants (37 < week) have lower rate of DDH. The DDH risk calculator was built but needs external validation in prospective study before being used in a clinical setting.Level of Evidence: Retrospective cohort study: Level III

Augmentation of cancer outcomes through safe transitions.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 250-250
Author(s):  
Adarsh Hiremath ◽  
Joanna-Grace Manzano ◽  
Josiah Halm ◽  
Jeff Farroni
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Cancer Patients ◽  
Readmission Rate ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Cancer Outcomes ◽  
Readmission Rates ◽  
Cancer Centers ◽  
Benchmark Data

250 Background: Policymakers have identified 30-day readmissions as an important quality indicator of poor care or coordination of care. Among cancer centers, there is no benchmark data in terms of readmission rates or recommendations in terms of risk adjustment models. Methods: Retrospective data analysis to estimate baseline readmission rate and identify risk factors. Interventions: (1)admitting to single floor, (2) twice weekly interdisciplinary meetings with using risk assessment tool–Cancer Outcomes Augmented through Safe Transitions (COAST) tool, and (3) re-evaluate readmission rate post intervention at 6 months and 1 year. Results: Unplanned readmission rate on the Hospitalist Service at MD Anderson was 21.5% at baseline. After 6 months of interventions, our readmission rate over 6 months was 23.3%. Age 45-65, having Medicare insurance, and being discharged to hospice were protective of a readmission. Distant metastases and having more comorbidities were associated with increased risk for readmission. Readmitted patients have a greater length of stay (7 days) and a higher average cost of inpatient stay ($20.3K vs. 17.9K). The median days to readmission was 11 days. Top comorbidities: hypertension, fluid and electrolyte disorders, anemia, diabetes mellitus, and abnormal weight loss. Top reasons: metastatic disease, biliary tract disease, GI hemorrhage, intestinal obstruction, septicemia, renal failure. Conclusions: Our project has provided insight into the rates and risk factors for readmission in oncology hospitalist service in a tertiary cancer center. The development of web-based COAST risk assessment tool is expected to give an improved understanding of our patient population. Although our readmission rates have not shown decrease over the 6 months after our interventions, this means that more interventions and more time may be necessary to impact readmission rates of services dealing with complex cancer patients. Additionally, a proportion of these unplanned readmissions in cancer patients may not be preventable. Benchmark data we have presented and that we continue to collect will help inform recommendations for effective transitions of care, patient safety practices as well as strategies for reducing readmission rates in cancer centers.

scholarly journals A114 DEVELOPING AND VALIDATING A PATIENT RISK ASSESSMENT TOOL TO PREDICT POST-ERCP PANCREATITIS

2021 ◽  
Vol 4 (Supplement_1) ◽  
pp. 93-94
Author(s):  
R A MacMillan ◽  
T Ponich
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
High Risk ◽  
Screening Tool ◽  
Assessment Tool ◽  
Health Science ◽  
Risk Assessment Tool ◽  
Risk Screening ◽  
Preventative Measures ◽  
Prophylactic Measures

Abstract Background Post-ERCP pancreatitis (PEP), the most common complication of ERCP, can lead to significant patient morbidity and even mortality. Both American (ASGE) and European (ESGE) guidelines emphasize the importance of assessing PEP risk among patients about to undergo ERCP so appropriate preventative measures can be initiated. Though multiple PEP risk factors have been identified, an ideal risk assessment tool has not yet been developed that accurately predicts PEP risk among ERCP patients. An ideal PEP risk factor screening tool would be one that most sensitively identifies patients likely to benefit from PEP preventative measures. We have developed a patient PEP risk screening tool based on both ASGE and ESGE guidelines (Table 1) and analyzed its accuracy predicting PEP rates in our clinical practice. Aims We investigated whether the ERCP patient and procedural risk factors listed in the ASGE and ESGE guidelines were linked to PEP rates using a novel PEP risk screening tool in patients undergoing ERCP. Methods Retrospective chart reviews of patients undergoing ERCP were performed within a single clinician’s practice at the London Health Science Centre, Victoria Hospital, between January 2016 and October 2019 to: 1) assess the proportion of patients identified as high PEP risk using our novel PEP risk screening tool; 2) determine whether a high PEP risk score using this tool was linked to higher PEP rates following ERCP; and 3) identify the absolute score threshold that best delineates patients at higher risk. A chi-square test of independence was performed to examine the relationship between high PEP risk identified via screening and the actual PEP rate following ERCP. Results Five hundred sixty-one patients who underwent ERCP were assessed using the new PEP risk screening tool. Among those patients, 6.6% (37/561) developed post-ERCP pancreatitis. Using the screening tool, 79.5% (446/561) were identified as high risk, using a cut-off score of 1; the score with the highest sensitivity (95%) and specificity (22%) combination. Identifying high PEP risk patients at this cut-off was significantly linked to increased PEP rates in patients who underwent ERCP (X2 = 5.5; df = 1, p &lt; .05). Conclusions Using a cut-off score of 1, the PEP risk screening tool was very sensitive, but relatively non-specific at identifying patients who went on to develop post-ERCP pancreatitis. We hope that, based on these findings, high-risk patient identification can be improved, so more aggressive and appropriately-targeted prophylactic measures against PEP can be provided. Funding Agencies None

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