Готові списки джерел за темами / Heart risk

Добірка наукової літератури з теми "Heart risk"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 19 лютого 2023

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Статті в журналах з теми "Heart risk"

1

Davies, M. K. "Cardiac risk factors." Heart 87, no. 1 (January 1, 2002): 5. http://dx.doi.org/10.1136/heart.87.1.5.

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2

ROBSON, J. "Predicting and reducing cardiovascular risk." Heart 85, no. 5 (May 1, 2001): 487–88. http://dx.doi.org/10.1136/heart.85.5.487.

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3

Illien, S. "Atrial fibrillation: relation between clinical risk factors and transoesophageal echocardiographic risk factors for thromboembolism." Heart 89, no. 2 (February 1, 2003): 165–68. http://dx.doi.org/10.1136/heart.89.2.165.

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4

Weiss, Edward P. "Heart Failure Risk." Circulation: Heart Failure 7, no. 4 (July 2014): 549–51. http://dx.doi.org/10.1161/circheartfailure.114.001459.

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5

McGowan, J. H. "Hibernating myocardium: high or low risk?" Heart 90, no. 3 (February 13, 2004): 237–38. http://dx.doi.org/10.1136/heart.2003.021006.

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6

Pepper, J. R. "Risk assessment in coronary artery surgery." Heart 89, no. 1 (January 1, 2003): 1–2. http://dx.doi.org/10.1136/heart.89.1.1.

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7

lakshmi, V. S. Bhagya, M. V. Sailaja, and Vijitha. "The Risk Factor Atherosclerosis in Ageing for Heart Attacks." International Journal of Integrative Medical Sciences 2, no. 7 (July 31, 2015): 140–43. http://dx.doi.org/10.16965/ijims.2015.120.

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8

Timmis, A. "Coronary disease: Acute coronary syndromes: risk stratification." Heart 83, no. 2 (February 1, 2000): 241–46. http://dx.doi.org/10.1136/heart.83.2.241.

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9

Wong, S. H. "Assessing the risk of sudden cardiac death." Heart 86, no. 6 (December 1, 2001): 624–25. http://dx.doi.org/10.1136/heart.86.6.624.

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10

Liverpool, Layal. "Predicting heart disease risk." New Scientist 244, no. 3259 (December 2019): 8. http://dx.doi.org/10.1016/s0262-4079(19)32284-5.

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Дисертації з теми "Heart risk"

1

Bagés, Nuri. "Psychosocial risk factors and coronary heart disease." [Maastricht : Maastricht : Universiteit Maastricht] ; University Library, Maastricht University [Host], 2000. http://arno.unimaas.nl/show.cgi?fid=6899.

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2

Freitag, Daniel Franz. "Inflammatory pathways and coronary heart disease risk." Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648461.

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3

Goncalves, Alexandra. "Alcohol Consumption and Risk of Heart Failure." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:17613726.

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Aim: Alcohol is a known cardiac toxin and heavy consumption can lead to heart failure (HF). However, the relationship between moderate alcohol consumption and risk for HF, in either men or women, remains unclear. Methods and results: We examined 14,629 participants of the Atherosclerosis Risk in Communities (ARIC) study (54±6 years, 55% women) without prevalent HF at baseline (1987-89) who were followed for 24±1 years. Self-reported alcohol consumption was assessed as the number of drinks/week (1 drink=14g of alcohol) at baseline, and updated cumulative average alcohol intake was calculated over 8.9±0.3 years. Using multivariable Cox proportional hazards models, we examined the relation of alcohol intake with incident HF and assessed whether associations were modified by sex. Overall, most participants were abstainers (42%) or former drinkers (19%), with 25% reporting up to 7 drinks per week, 8% reporting ≥7 to 14 drinks per week, and 3% reporting ≥14 to 21 and ≥ 21 drinks per week, respectively. Incident HF occurred in 1,271 men and 1,237 women. Men consuming up to 7 drinks/week had reduced risk of HF relative to abstainers (HR 0.80, 95% CI 0.68-0.94, p=0.006); this effect was less robust in women (HR 0.84, 95% CI 0.71-1.00, p=0.05). In the higher drinking categories the risk of HF was not significantly different from abstainers, either in men or in women. Conclusion: In the community, alcohol consumption of up to 7 drinks/week at early-middle age is associated with lower risk for future HF, with a similar but less definite association in women than in men. These findings suggest that despite the dangers of heavy drinking, modest alcohol consumption in early-middle age may be associated with a lower risk of HF.
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4

Ó, Hartaigh Bríain William-John. "Resting heart rate in cardiovascular ageing : from risk marker to risk factor." Thesis, University of Birmingham, 2013. http://etheses.bham.ac.uk//id/eprint/4005/.

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Анотація:
An accumulation of epidemiological studies along with several lines of experimental research highlight sustained elevated resting heart rate as a significant predictor of cardiovascular morbidity and mortality. However, resting heart rate as a simple and inexpensive clinical parameter often remains overlooked by physicians. We therefore sought to raise awareness concerning the detrimental role of elevated resting heart rate in cardiovascular disease. Using three separate large prospective cohort studies, we examined the clinical importance of accelerated resting heart rate as a robust predictor of adverse cardiovascular prognosis. The current data supports the contention that a raised resting heart rate amplifies the risk of having several cardio-metabolic risk factors including type 2 diabetes mellitus, the metabolic syndrome, and increased pulse wave velocity. Resting tachycardia also appeared to increase the risk of cardiovascular mortality in otherwise healthy individuals, as well as negatively predicting outcome in patients already at-risk for the condition. Notably, we observed a strong synergistic effect between inflammatory activity and concurrent elevated resting heart rate among those who experienced a cardiovascular event. Overall, these findings underline the relevance of a high resting heart rate in the pathogenesis of atherosclerosis and in the clinical manifestations of cardiovascular mortality.
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5

Ramsey, Priscilla W., and L. Lee Glenn. "Risk Factors for Heart Disease in Rural Appalachia." Digital Commons @ East Tennessee State University, 1998. https://dc.etsu.edu/etsu-works/7539.

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Анотація:
The objectives of the study were to identify which risk factors for heart disease were most prevalent in a poor, underserved, rural Appalachian county. A random sample of medical records was selected (n = 292) of adult men and women who participated in a countywide health care project. Data were obtained from a health risk appraisal questionnaire and other physical and demographic information and were analyzed using univariate and bivariate statistical procedures. The findings indicated that these rural Appalachian subjects had a significant number of heart disease risk factors: excessive smoking, lack of exercise, high fat diets, and abnormal serum lipid levels.
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6

Woodside, Jayne Valerie. "Micronutrients in hyperhomocysteinaemia and cardiovascular risk." Thesis, Queen's University Belfast, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388099.

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7

Streng, Vicki K. "CORONARY HEART DISEASE RISK STRATIFICATION IN FULL-TIME MIAMI VALLEY HOSPITAL EMPLOYEES." Wright State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=wright1165604997.

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8

Wu, Kelvin Kwan Hoe. "Gene-nutrient interactions and risk of coronary heart disease." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614117.

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9

Lo, Owen. "Heart data analysis, modelling and application in risk assessment." Thesis, Edinburgh Napier University, 2015. http://researchrepository.napier.ac.uk/Output/8833.

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Анотація:
The heart is a fundamental aspect of the human body. Significant work has been undertaken to better understand the characteristics and mechanisms of this organ in past research. Greater understanding of the heart not only provides advances in medicine but also enables practitioners to better assess the health risk of patients. This thesis approaches the study of the heart from a health informatics perspective. The questions posed in this thesis is whether research is capable of describing and modelling heart data from a statistical perspective, along with exploring techniques to improve the accuracy of clinical risk assessment algorithms that rely on this data. The contributions of this thesis may be grouped into two main areas: statistical analysis, modelling and simulation of heart data; and improved risk assessment accuracy of the Early Warning Score (EWS) algorithm using a quartile-based technique. Statistical analysis of heart data, namely RR intervals, contributes to more informed understanding of the underlying characteristics of the heart and is achieved using null-hypothesis testing through the Anderson-Darling (AD) test statistic. The modelling process of heart data demonstrates methodologies for simulation of this data type, namely individual distribution modelling and normal mixture modelling, and contributes to assessing techniques that are most capable of modelling this type of data. For improved accuracy on the EWS algorithms, a quartiles technique, inspired by anomaly-based intrusion detection systems, is presented which enables customisation of risk score thresholds for each patient defined during a training phase. Simulated heart data is used to evaluate the standard EWS algorithm against the quartile-based approach. The defined metric of accuracy ratio provides quantitative evidence on the accuracy of the standard EWS algorithm in comparison with the proposed quartile based technique. Statistical analysis in this thesis demonstrates that samples of heart data can be described using normal, Weibull, logistic and gamma distribution within the scope of two minute data samples. When there is strong evidence to suggest that RR intervals analysed fits a particular distribution, individual modelling technique is the ideal candidate whilst normal mixture modelling is better suited for long-term modelling, i.e. greater than two minutes of heart data. In comparative evaluation of the standard EWS algorithm and the quartile-based technique using modelled heart data, greater accuracy is demonstrated in the quartiles-based technique for patients whose heart rate is healthy, but outside the normal ranges of the general population.
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10

Spriggs, David Arthur. "Risk factors for stroke : a case-controlled study." Thesis, University of Newcastle Upon Tyne, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308766.

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Книги з теми "Heart risk"

1

Leigh, Ana. Heart at Risk. Toronto, Ontario: Silhouette, 2009.

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2

Leigh, Ana. Heart at risk. New York: Silhouette, 2009.

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3

Leigh, Ana. Heart at risk. New York: Silhouette Books, 2009.

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4

Risk of the heart. Richmond, Surrey: Mills & Boon, 1991.

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5

1959-, Osborn Kevin, and Philip Lief Group, eds. Heart disease: Reducing your risk. New York: Bantam Books, 1991.

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6

1961-, Gaziano J. Michael, ed. Atlas of cardiovascular risk factors. Philadelphia: Developed by Current Medicine, 2005.

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7

1940-, Roberts Robert, ed. Coronary heart disease and risk factors. Mount Kisco, NY: Futura Pub. Co., 1991.

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8

Association, Family Heart, ed. Cholesterol: Reducing your risk. London: Macdonald Optima, 1990.

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9

Symes, David. Cholesterol: Reducing your risk. London: Optima, 1994.

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10

White, Suzanne Cambre. Lady killer: Heart disease : women at risk. Atlanta, Ga: Pritchett & Hull Associates, 1995.

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Частини книг з теми "Heart risk"

1

Baggen, Vivan J. M., Laurie W. Geenen, and Jolien W. Roos-Hesselink. "Risk Stratification and Prognosis." In Heart Failure in Adult Congenital Heart Disease, 47–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77803-7_4.

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2

den Elzen, Wendy P. J., Simon P. Mooijaart, Bart E. P. B. Ballieux, Anne R. Cappola, and Jacobijn Gussekloo. "Thyroid and Cardiovascular Risk." In Thyroid and Heart, 205–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36871-5_16.

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3

Ashwell, Margaret. "Physiological Risk Factors." In Diet and Heart Disease, 15–21. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-009-0087-5_3.

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4

Mancini, M., A. Postiglione, and L. A. Ferrara. "Hyperlipidemia and Risk of Stroke." In Heart-Brain Interactions, 117–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-76652-7_14.

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5

Waring, Avantika C., and Anne R. Cappola. "Thyroid and Cardiovascular Risk." In Thyroid and Heart Failure, 151–65. Milano: Springer Milan, 2009. http://dx.doi.org/10.1007/978-88-470-1143-4_14.

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6

Brenta, Gabriela, and Laura Schreier. "Thyroid, Lipids, and Risk of Atherosclerosis." In Thyroid and Heart, 245–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36871-5_19.

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7

Kannel, William B. "Cardiovascular Risk Assessment in Hypertension." In Atlas of Heart Diseases, 100–117. London: Current Medicine Group, 2001. http://dx.doi.org/10.1007/978-1-4684-6909-7_5.

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8

Gomes, J. Anthony. "Noninvasive Risk Stratification for Sudden Cardiac Death." In Heart Rhythm Disorders, 377–91. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45066-3_26.

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9

Vijayakrishnan, Rajakrishnan, and Emma J. Birks. "Risk Factors for Mechanical Circulatory Support Use and Risk Assessment." In Mechanical Support for Heart Failure, 623–39. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47809-4_40.

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10

Champion, Howard R., Nova L. Panebianco, Jan J. De Waele, Lewis J. Kaplan, Manu L. N. G. Malbrain, Annie L. Slaughter, Walter L. Biffl, et al. "Acute Heart Failure: Risk Stratification." In Encyclopedia of Intensive Care Medicine, 63–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-00418-6_829.

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Тези доповідей конференцій з теми "Heart risk"

1

Bandara, K. R. C., D. D. T. D. Dureksha, S. C. Pinidiya, R. M. G. H. Amarasinghe, Samantha Thelijjagoda, and Jenny Kishara. "Healthy Heart – Heart Risk Prediction System on Personalized Guidance for Heart Patients." In 2022 IEEE 7th International conference for Convergence in Technology (I2CT). IEEE, 2022. http://dx.doi.org/10.1109/i2ct54291.2022.9824170.

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2

Mohawish, Ahmad, Ragini Rathi, Vibhanshu Abhishek, Thomas Lauritzen, and Rema Padman. "Predicting Coronary Heart Disease risk using health risk assessment data." In 2015 17th International Conference on E-health Networking, Application & Services (HealthCom). IEEE, 2015. http://dx.doi.org/10.1109/healthcom.2015.7454479.

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3

Bulut, Faruk. "Heart attack risk detection using Bagging classifier." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7496164.

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4

Voss, A., R. Schroeder, M. Vallverdu, I. Cygankiewicz, R. Vazquez, A. Bayes de Luna, and P. Caminal. "Linear and nonlinear heart rate variability risk stratification in heart failure patients." In 2008 35th Annual Computers in Cardiology Conference. IEEE, 2008. http://dx.doi.org/10.1109/cic.2008.4749102.

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5

Schramm, R., A. Zittermann, M. Morshuis, U. Fuchs, J. Fleischhauer, K. Hakim-Meibodi, and J. Gummert. "Risk Stratification in Heart Transplantation According to Donor and Recipient Risk Factors." In 48th Annual Meeting German Society for Thoracic, Cardiac, and Vascular Surgery. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1679017.

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6

Sharma, Neeraj, Manas Kumar Mishra, Jasroop Singh Chadha, and Praveen Lalwani. "Heart Stroke Risk Analysis: A Deep Learning Approach." In 2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT). IEEE, 2021. http://dx.doi.org/10.1109/csnt51715.2021.9509665.

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7

Bohacik, Jan, Karol Matiasko, Miroslav Benedikovic, and Iveta Nedeljakova. "Algorithmic model for risk assessment of heart failure patients." In 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2015. http://dx.doi.org/10.1109/idaacs.2015.7340724.

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8

Khatibi, Vahid, and Gholam Ali Montazer. "Coronary heart disease risk assessment using dempster-shafer theory." In 2009 14th International CSI Computer Conference (CSICC 2009) (Postponed from July 2009). IEEE, 2009. http://dx.doi.org/10.1109/csicc.2009.5349607.

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9

Kim, H. S., and P. LaCamera. "Risk of Non-Expandable Lung Following Open-Heart Surgery." In American Thoracic Society 2020 International Conference, May 15-20, 2020 - Philadelphia, PA. American Thoracic Society, 2020. http://dx.doi.org/10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a1569.

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10

"Diesel Oil Vapor Inhalation: Risk Factor for Heart Attack." In International Conference on Chemical, Environment & Biological Sciences. International Institute of Chemical, Biological & Environmental Engineering, 2014. http://dx.doi.org/10.15242/iicbe.c914145.

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Звіти організацій з теми "Heart risk"

1

Chen, Yujia, and Wen Li. Periodontitis Increase the Risk of Heart Failure. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0084.

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Анотація:
Review question / Objective: Can periodontitis increase the risk of heart failure? Condition being studied: Previous studies reported that periodontal disease is associated with higher risk of HF. However, their conclusions conflicted a little bit with each other. In this case, a systematic review may help drawing a more comprehensive conclusion. Therefore, the purpose of the present analysis is to tell if periodontitis is associated with HF as well as the subtypes of HF.
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2

Krauss, Ronald. CRADA Final Report: Genetic Testing for Evaluation of Heart Disease Risk. Office of Scientific and Technical Information (OSTI), January 2002. http://dx.doi.org/10.2172/1157021.

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3

Nalla, Vineetha, and Nihal Ranjit. Afterwards: Graphic Narratives of Disaster Risk and Recovery from India. Indian Institute for Human Settlements, 2022. http://dx.doi.org/10.24943/9788195648559.

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Анотація:
Afterwards is an anthology of visual narratives of disaster impacts and the process of recovery that follows. These stories were drawn from the testimonies of disaster-affected individuals, households, and communities documented between 2018-19 from the Indian states of Odisha, Tamil Nadu, and Kerala. They communicate challenges related to housing resettlement, loss of livelihoods, gender-based exclusion among others. At the heart of this anthology lies the idea of ‘representation’: how are those affected portrayed by the media, state actors, official documents; how are their needs represented and how do these portrayals impact the lives of those at risk and shape their recovery? Graphically illustrating these themes provides a platform to relay personal experiences of disaster risk and recovery.
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4

Rich-Edwards, Janet, and Ellen Seely. Can an Online Program Help Women with a History of Preeclampsia Reduce Their Risk of Heart Disease? Patient-Centered Outcomes Research Institute® (PCORI), January 2020. http://dx.doi.org/10.25302/1.2020.cer.130601603.

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5

AlBakri, Aref, Auswaf Ahsan, Manoj Vengal, KR Ashir, Abdul Majeed, and Hanan Siddiq. Antibiotic Prophylaxis before Invasive Dental Procedures for Patients at High-Risk of Infective Endocarditis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, July 2022. http://dx.doi.org/10.37766/inplasy2022.7.0011.

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Анотація:
Review question / Objective: The aim of the present systematic review and meta-analysis is to determine whether there is a genuine clinical need for Antibiotic Prophylaxis(AP) for the prevention of Infective Endocarditis(IE) in high-risk individuals (particularly those with demonstrable structural heart diseases or valve surgery) undergoing invasive dental procedures. Information sources: PubMed, Science Direct, British Dental Journal and Cochrane Register of Controlled Trials. Search terms used included various combinations of the following subject headings and title or abstract keywords – prophylactic antibiotics, antibiotic prophylaxis, antimicrobial, dentist, extraction, implant, infective endocarditis, or bacterial endocarditis.
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6

Nalla, Vineetha, Nihal Ranjit, Yashodara Udupa, Mythili Madhavan, Jasmitha Arvind, Garima Jain, and Teja Malladi. Afterwards – Graphic Narratives of Disaster Risk and Recovery from India (Volume Set). Indian Institute for Human Settlements, 2022. http://dx.doi.org/10.24943/9788195648573.

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Анотація:
Afterwards is an anthology of graphic narratives of disaster impacts and the process of recovery that follows. These stories were drawn from the testimonies of disaster-affected individuals, households, and communities documented from the Indian states of Odisha, Tamil Nadu, and Kerala. The book has been translated into the regional languages of these states – Odia, Tamil, and Malayalam. They communicate challenges related to housing resettlement, loss of livelihoods, and gender-based exclusion among others. At the heart of this anthology lies the idea of ‘representation’: how are disaster-affected people portrayed by the media, state actors, and official documents; how are their needs represented and how do these portrayals impact the lives of those at risk and shape their recovery?
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7

Yu, Yipin, Duoting Tan, Dan Sheng, Liqin Zhong, Zhixi Hu, and Hao Liang. Neutrophil-to-lymphocyte ratio as a prognostic predictor for heart failure patients: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2022. http://dx.doi.org/10.37766/inplasy2022.3.0062.

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Анотація:
Review question / Objective: This study aimed to evaluate the relationship between NLR and in-hospital or long-term prognosis of patients with heart failure by meta-analysis. Eligibility criteria: Inclusion criteria: (1) Patients with heart failure who underwent NLR measurement ;the study types were prospective cohort study or retrospective cohort study; and (3) risk estimates of association between NLR levels and heart failure related events occurring during hospital or follow-up were studied experimentally. Case reports, reviews, animal studies, conference proceedings, letters to editors, abstract only and duplicated studies were excluded.
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8

Kent, David M., Jason Nelson, Jenica N. Upshaw, Gaurav Gulati, Riley Brazil, Esmee Venema, Christine M. Lundquist, et al. Using Different Data Sets to Test How Well Clinical Prediction Models Work to Predict Patients' Risk of Heart Disease. Patient-Centered Outcomes Research Institute (PCORI), September 2021. http://dx.doi.org/10.25302/09.2021.me.160635555.

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9

Brown, Yolanda, Twonia Goyer, and Maragaret Harvey. Heart Failure 30-Day Readmission Frequency, Rates, and HF Classification. University of Tennessee Health Science Center, December 2020. http://dx.doi.org/10.21007/con.dnp.2020.0002.

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Анотація:
30 Day Hospital Readmission Rates, Frequencies, and Heart Failure Classification for Patients with Heart Failure Background Congestive heart failure (CHF) is the leading cause of mortality, morbidity, and disability worldwide among patients. Both the incidence and the prevalence of heart failure are age dependent and are relatively common in individuals 40 years of age and older. CHF is one of the leading causes of inpatient hospitalization readmission in the United States, with readmission rates remaining above the 20% goal within 30 days. The Center for Medicare and Medicaid Services imposes a 3% reimbursement penalty for excessive readmissions including those who are readmitted within 30 days from prior hospitalization for heart failure. Hospitals risk losing millions of dollars due to poor performance. A reduction in CHF readmission rates not only improves healthcare system expenditures, but also patients’ mortality, morbidity, and quality of life. Purpose The purpose of this DNP project is to determine the 30-day hospital readmission rates, frequencies, and heart failure classification for patients with heart failure. Specific aims include comparing computed annual re-admission rates with national average, determine the number of multiple 30-day re-admissions, provide descriptive data for demographic variables, and correlate age and heart failure classification with the number of multiple re-admissions. Methods A retrospective chart review was used to collect hospital admission and study data. The setting occurred in an urban hospital in Memphis, TN. The study was reviewed by the UTHSC Internal Review Board and deemed exempt. The electronic medical records were queried from July 1, 2019 through December 31, 2019 for heart failure ICD-10 codes beginning with the prefix 150 and a report was generated. Data was cleaned such that each patient admitted had only one heart failure ICD-10 code. The total number of heart failure admissions was computed and compared to national average. Using age ranges 40-80, the number of patients re-admitted withing 30 days was computed and descriptive and inferential statistics were computed using Microsoft Excel and R. Results A total of 3524 patients were admitted for heart failure within the six-month time frame. Of those, 297 were re-admitted within 30 days for heart failure exacerbation (8.39%). An annual estimate was computed (16.86%), well below the national average (21%). Of those re-admitted within 30 days, 50 were re-admitted on multiple occasions sequentially, ranging from 2-8 re-admissions. The median age was 60 and 60% male. Due to the skewed distribution (most re-admitted twice), nonparametric statistics were used for correlation. While graphic display of charts suggested a trend for most multiple re-admissions due to diastolic dysfunction and least number due to systolic heart failure, there was no statistically significant correlation between age and number or multiple re-admissions (Spearman rank, p = 0.6208) or number of multiple re-admissions and heart failure classification (Kruskal Wallis, p =0.2553).
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10

Moser, Debra, Frances Feltner, Martha Biddle, Misook Chung, Mary Kay Rayens, Gia Mudd‐Martin, Kristen Ashford, et al. Does a Program that Focuses on Lifestyle Changes Reduce Heart Disease Risk Factors in a Rural Community in Appalachian Kentucky? Patient‐Centered Outcomes Research Institute (PCORI)., May 2019. http://dx.doi.org/10.25302/4.2019.cer.850.

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