An emerging epidemic: cancer and heart failure

2016 ◽  
Vol 131 (2) ◽  
pp. 113-121 ◽  
Author(s):  
Paaladinesh Thavendiranathan ◽  
Mark T. Nolan
Keyword(s):  
Heart Failure ◽  
Cancer Therapy ◽  
Clinical Decision Making ◽  
Prediction Models ◽  
Clinical Decision ◽  
Prevention Strategies ◽  
Patients With Cancer ◽  
Increased Risk ◽  
Adult Cancer Survivors ◽  
Shared Risk

Heart disease and cancer are the two leading causes of mortality globally. Cardiovascular complications of cancer therapy significantly contribute to the global burden of cardiovascular disease. Heart failure (HF) in particular is a relatively common and life-threatening complication. The increased risk is driven by the shared risk factors for cancer and HF, the direct impact of cancer therapy on the heart, an existing care gap in the cardiac care of patients with cancer and the increasing population of adult cancer survivors. The clear relationship between cancer treatment initiation and the potential for myocardial injury makes this population attractive for prevention strategies, targeted cardiovascular monitoring and treatment. However, there is currently no consensus on the optimal strategy for managing this at-risk population. Uniform treatment using cardioprotective medications may reduce the incidence of HF, but would impose frequently unnecessary and burdensome side effects. Ideally we could use validated risk-prediction models to target HF-preventive strategies, but currently no such models exist. In the present review, we focus on evidence and rationales for contemporary clinical decision-making in this novel field and discuss issues, including the burden of HF in patients with cancer, the reasons for the elevated risk and potential prevention strategies.

scholarly journals Hemoglobin A1c and preoperative glycemia as a decision tool to help minimise sternal wound complications: a retrospective study in OPCAB patients

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jef Van den Eynde ◽  
Abel Van Vlasselaer ◽  
Annoushka Laenen ◽  
Delphine Szecel ◽  
Bart Meuris ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Hemoglobin A1c ◽  
Clinical Decision Making ◽  
Artery Bypass ◽  
Clinical Decision ◽  
Wound Complications ◽  
Minimal Risk ◽  
Off Pump ◽  
Increased Risk ◽  
Diabetes Patients

Abstract Background Poor glycemic control has been associated with an increased risk of wound complications after various types of operations. However, it remains unclear how hemoglobin A1c (HbA1c) and preoperative glycemia can be used in clinical decision-making to prevent sternal wound complications (SWC) following off-pump coronary artery bypass grafting (OPCAB). Methods We conducted a retrospective study of 1774 consecutive patients who underwent OPCAB surgery between January 2010 and November 2016. A new four-grade classification for SWC was used. The associations of HbA1c and preoperative glycemia with incidence and grade of SWC were analysed using logistic regression analysis and proportional odds models, respectively. Results During a median follow-up of 326 days (interquartile range (IQR) 21–1261 days), SWC occurred in 133/1316 (10%) of non-diabetes and 82/458 (18%) of diabetes patients (p < 0.001). Higher HbA1c was significantly associated with a higher incidence of SWC (odds ratio, OR 1.24 per 1% increase, 95% confidence interval, CI 1.04;1.48, p = 0.016) as well as a higher grade of SWC (OR 1.25, 95% CI 1.06;1.48, p = 0.010). There was no association between glycemia and incidence (p = 0.539) nor grade (p = 0.607) of SWC. Significant modifiers of these effects were found: HbA1c was associated with SWC in diabetes patients younger than 70 years (OR 1.41, 95% CI 1.17;1.71, p < 0.001), whereas it was not in those older than 70 years. Glycemia was associated with SWC in patients who underwent non-urgent surgery (OR 2.48, 95% CI 1.26;4.88, p = 0.009), in diabetes patients who received skeletonised grafts (OR 4.83, 95% CI 1.28;18.17, p = 0.020), and in diabetes patients with a BMI < 30 (OR 2.19, 95% CI 1.01;4.76, p = 0.047), whereas it was not in the counterparts of these groups. Conclusions Under certain conditions, HbA1c and glycemia are associated SWC following OPCAB. These findings are helpful in planning the procedure with minimal risk of SWC.

scholarly journals Choice of faecal immunochemical test matters: comparison of OC-Sensor and HM-JACKarc, in the assessment of patients at high risk of colorectal cancer

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Caroline J. Chapman ◽  
Ayan Banerjea ◽  
David J Humes ◽  
Jaren Allen ◽  
Simon Oliver ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Clinical Decision Making ◽  
Full Range ◽  
Clinical Decision ◽  
Detection Rates ◽  
Faecal Immunochemical Test ◽  
Specimen Collection ◽  
Increased Risk ◽  
Immunochemical Test

AbstractObjectivesCurrently, NICE recommends the use of faecal immunochemical test (FIT) at faecal haemoglobin concentrations (f-Hb) of 10 μg Hb/g faeces to stratify for colorectal cancer (CRC) risk in symptomatic populations. This f-Hb cut-off is advised across all analysers, despite the fact that a direct comparison of analyser performance, in a clinical setting, has not been performed.MethodsTwo specimen collection devices (OC-Sensor, OC-S; HM-JACKarc, HM-J) were sent to 914 consecutive individuals referred for follow up due to their increased risk of CRC. Agreement of f-Hb around cut-offs of 4, 10 and 150 µg Hb/g faeces and CRC detection rates were assessed. Two OC-S devices were sent to a further 114 individuals, for within test comparisons.ResultsA total of 732 (80.1%) individuals correctly completed and returned two different FIT devices, with 38 (5.2%) CRCs detected. Median f-Hb for individuals diagnosed with and without CRC were 258.5 and 1.8 µg Hb/g faeces for OC-S and 318.1 and 1.0 µg Hb/g faeces for HM-J respectively. Correlation of f-Hb results between OC-S/HM-J over the full range was rho=0.74, p<0.001. Using a f-Hb of 4 µg Hb/g faeces for both tests found an agreement of 88.1%, at 10 µg Hb/g faeces 91.7% and at 150 µg Hb/g faeces 96.3%. A total of 114 individuals completed and returned two OC-S devices; correlation across the full range was rho=0.98, p<0.001.ConclusionsWe found large variations in f-Hb when different FIT devices were used, but a smaller variation when the same FIT device was used. Our data suggest that analyser-specific f-Hb cut-offs are applied with regard to clinical decision making, especially at lower f-Hb.

Contemporary Heart Failure Treatment Based on Improved Knowledge and Personalized Care of Comorbidities

2019 ◽  
pp. 1565-1579
Author(s):  
Kostas Giokas ◽  
Charalampos Tsirmpas ◽  
Athanasios Anastasiou ◽  
Dimitra Iliopoulou ◽  
Vassilia Costarides ◽  
...  
Keyword(s):  
Heart Failure ◽  
Decision Making ◽  
Chronic Diseases ◽  
Clinical Decision Making ◽  
Medical Condition ◽  
Collective Intelligence ◽  
Clinical Decision ◽  
Mortality And Morbidity ◽  
Personalized Care ◽  
Care Approach

Chronic diseases are the leading cause of mortality and morbidity. A significant contribution to the burden of chronic diseases is the concurrence of co-morbidities. Heart failure (HF) is a complex, chronic medical condition frequently associated with co-morbidities. The current care approach for HF patients with co-morbidities is neither capable to deliver personalised care nor to halt the on-going increase of its socio-economic burden. Our approach aims to improve the complete care process for HF patients and related co-morbidities to improve outcome and quality of life. This will be achieved by the proposed standardised yet personalised patient-oriented ICT system that supports evidence-based clinical decision making as well as interaction and communication between all stakeholders with focus on the patients and their relatives to improve self-management. We propose that such a system should be build upon a novel European-wide data standard for clinical input and outcome and that it should facilitate decision making and outcome tracking by new collective intelligence algorithms.

scholarly journals A prospective evaluation of the Flacker-Kiely One Year Mortality Score and the added value of NT-proBNP

2020 ◽  
Vol 11 (2) ◽  
pp. 13
Author(s):  
Kjell Krüger ◽  
Bård R. Kittang ◽  
Sabine P. Solheim ◽  
Kristian Jansen
Keyword(s):  
Heart Failure ◽  
Failure Criterion ◽  
Clinical Decision Making ◽  
Cox Regression ◽  
Clinical Decision ◽  
Blood Chemistry ◽  
Discriminatory Power ◽  
Added Value ◽  
Youden Index ◽  
Mortality Data

Objective: Several mortality indices have been constructed to aid clinical decision making in older adults. We aimed to prospectively validate the Flacker-Kiely (FK) mortality index in a Norwegian nursing home cohort, which has not been done before, and explore whether NT-ProBNP could improve its discriminatory power.Methods: We performed a cohort/mortality study. From November 2017 to July 2018, physicians in all public long-term nursing homes in Bergen, Norway, scored residents according to the original Flacker Kiely index. Mortality data were derived from the Norwegian Cause of Death Registry and NT-ProBNP values were obtained from routinely collected blood chemistry. An alternative FK index using the NT-ProBNP-value as a marker for the presence of heart failure was constructed (FK NT-ProBNP index). The ProBNP cut-off value was selected based on a Cox regression model (“dead/alive 1 year”/” NT-ProBNP (Ng/l)”, where the value with the highest Youden index was identified. We judged index performance by using c-statistics.Results: Both the original FK index and the constructed FK NT-ProBNP index discriminated between risk strata. The FK NT-ProBNP index yielded a C-index of 0.66 compared to 0.62 for the original FK index. Optimal discriminatory power was shown with a NT-ProBNP cut-off value of 1,595 Ng/l as heart failure criterion, and FK NT-ProBNP score 6.6.Conclusions: The prospective mortality estimation ability of the FK-index was comparable to previous retrospective studies. The inclusion of NT-ProBNP as a heart failure criterion strengthen the discriminatory power and utility of the index, both in clinic and administration.

Goals of palliative cancer therapy.

1993 ◽  
Vol 11 (2) ◽  
pp. 378-381 ◽  
Author(s):  
F Porzsolt ◽  
I Tannock
Keyword(s):  
Quality Of Life ◽  
Decision Making ◽  
Cost Effectiveness ◽  
Cancer Therapy ◽  
Health Professionals ◽  
Palliative Treatment ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Oncology Practice

The major conclusions of the Workshop on Goals of Palliative Cancer Therapy are as follows: 1. The goals of any cancer therapy should be stated explicitly. 2. If the goal of treatment is palliation, this should be documented according to one of the established and validated methods for assessment of quality of life. Several validated methods are available, and although imperfect, have been shown to give reliable information. 3. The use of simple measures of quality of life (eg, symptom checklists, pain assessment cards) should become routine in oncology practice. The act of introducing such measures improves palliation. 4. Measures of cost-effectiveness should be used more widely in clinical decision making to ensure the appropriate deployment of resources. 5. There must be improved education of all health professionals with regard to the multiple methods for provision of palliative treatment to cancer patients and the assessment of palliation.

scholarly journals MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care

2020 ◽  
Vol 27 (12) ◽  
pp. 2011-2015 ◽  
Author(s):  
Tina Hernandez-Boussard ◽  
Selen Bozkurt ◽  
John P A Ioannidis ◽  
Nigam H Shah
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Clinical Decision Making ◽  
Prediction Models ◽  
Clinical Decision ◽  
Digital Data ◽  
Reporting Standards ◽  
Minimum Information ◽  
Support Tools ◽  
Hidden Biases

Abstract The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.

Predicting and Preventing Anthracycline-Related Cardiotoxicity

2018 ◽  
pp. 3-12 ◽  
Author(s):  
Saro Armenian ◽  
Smita Bhatia
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Cancer Survivors ◽  
Childhood Cancer ◽  
Prediction Models ◽  
Lymphoblastic Leukemia ◽  
Childhood Cancer Survivors ◽  
Chemotherapeutic Agents ◽  
Increased Risk ◽  
Risk Reducing

Anthracyclines (doxorubicin, daunorubicin, epirubicin, and idarubicin) are among the most potent chemotherapeutic agents and have truly revolutionized the management of childhood cancer. They form the backbone of chemotherapy regimens used to treat childhood acute lymphoblastic leukemia, acute myeloid leukemia, Hodgkin lymphoma, Ewing sarcoma, osteosarcoma, and neuroblastoma. More than 50% of children with cancer are treated with anthracyclines. The clinical utility of anthracyclines is compromised by dose-dependent cardiotoxicity, manifesting initially as asymptomatic cardiac dysfunction and evolving irreversibly to congestive heart failure. Childhood cancer survivors are at a five- to 15-fold increased risk for congestive heart failure compared with the general population. Once diagnosed with congestive heart failure, the 5-year survival rate is less than 50%. Prediction models have been developed for childhood cancer survivors (i.e., after exposure to anthracyclines) to identify those at increased risk for cardiotoxicity. Studies are currently under way to test risk-reducing strategies. There remains a critical need to identify patients with childhood cancer at diagnosis (i.e., prior to anthracycline exposure) such that noncardiotoxic therapies can be contemplated.

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