Anemia and fatigue in cancer patients

1998 ◽  
Vol 4 (4_suppl) ◽  
pp. S5-S11
Author(s):  
Terri G Davidson
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Underlying Disease ◽  
Disease Treatment ◽  
Anemia Of Chronic Disease ◽  
Cancer Related Fatigue ◽  
Lack Of Exercise ◽  
Cancer Related Anemia ◽  
The Relationship ◽  
Adequate Tissue

Although strong evidence indicates that fatigue can be caused by anemia, little is known about the relationship between the extent and rate of hemoglobin loss and the development of fa tigue. Anemia, an insufficiency of red blood cells to maintain adequate tissue oxygenation, is the most common hematologic abnormality associ ated with cancer. It usually results from a de crease in red blood cell production, resulting from either direct tumor invasion of bone mar row or the anemia of chronic disease. Fatigue is a subjective sensation, often described as tired ness, exhaustion, lethargy, or malaise. The mechanism that precipitates or sustains fatigue is probably multifactorial and includes the re lease of inflammatory cytokines and the onset of the acute-phase inflammatory response. Other factors that contribute to cancer-related fatigue include the underlying disease, treatment of the disease, intercurrent systemic illnesses, sleep disorders, immobility and lack of exercise, chronic pain, and psychosocial factors. A review of cancer-related anemia and fatigue is pre sented, which focuses on the clinical decision- making process regarding the management of these syndromes when they exist concurrently.

4971Blood viscosity and its relevance to the diagnosis and management of pulmonary hypertension: a new elephant in the cathlab

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Kempny ◽  
K Dimopoulos ◽  
A E Fraisse ◽  
G P Diller ◽  
L C Price ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Cardiac Catheterization ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Pulmonary Vasculature ◽  
Pulmonary Vascular Disease ◽  
Significant Difference ◽  
The Difference ◽  
Clinically Significant ◽  
The Relationship

Abstract Background Pulmonary vascular resistance (PVR) is an essential parameter assessed during cardiac catheterization. It is used to confirm pulmonary vascular disease, to assess response to targeted pulmonary hypertension (PH) therapy and to determine the possibility of surgery, such as closure of intra-cardiac shunt or transplantation. While PVR is believed to mainly reflect the properties of the pulmonary vasculature, it is also related to blood viscosity (BV). Objectives We aimed to assess the relationship between measured (mPVR) and viscosity-corrected PVR (cPVR) and its impact on clinical decision-making. Methods We assessed consecutive PH patients undergoing cardiac catheterization. BV was assessed using the Hutton method. Results We included 465 patients (56.6% female, median age 63y). The difference between mPVR and cPVR was highest in patients with abnormal Hb levels (anemic patients: 5.6 [3.4–8.0] vs 7.8Wood Units (WU) [5.1–11.9], P<0.001; patients with raised Hb: 10.8 [6.9–15.4] vs. 7.6WU [4.6–10.8], P<0.001, respectively). Overall, 33.3% patients had a clinically significant (>2.0WU) difference between mPVR and cPVR, and this was more pronounced in those with anemia (52.9%) or raised Hb (77.6%). In patients in the upper quartile for this difference, mPVR and cPVR differed by 4.0WU [3.4–5.2]. Adjustment of PVR required Conclusions We report, herewith, a clinically significant difference between mPVR and cPVR in a third of contemporary patients assessed for PH. This difference is most pronounced in patients with anemia, in whom mPVR significantly underestimates PVR, whereas in most patients with raised Hb, mPVR overestimates it. Our data suggest that routine adjustment for BV is necessary.

scholarly journals Over one third of patients with symptomatic femoroacetabular impingement display femoral or acetabular version abnormalities

2021 ◽  
Author(s):  
Zaki Arshad ◽  
Henry David Maughan ◽  
Karadi Hari Sunil Kumar ◽  
Matthew Pettit ◽  
Arvind Arora ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Original Research ◽  
Distribution Analysis ◽  
Inclusion Criteria ◽  
Acetabular Version ◽  
Level Of Evidence ◽  
Femoral Version ◽  
Normal Mean ◽  
The Relationship

Abstract Purpose The aim of this study was investigate the relationship between version and torsional abnormalities of the acetabulum, femur and tibia in patients with symptomatic FAI. Methods A systematic review was performed according to PRISMA guidelines using the EMBASE, MEDLINE, PubMed and Cochrane databases. Original research articles evaluating the described version and torsional parameters in FAI were included. The MINORS criteria were used to appraise study quality and risk of bias. Mean version and torsion values were displayed using forest plots and the estimated proportion of hips displaying abnormalities in version/torsion were calculated. Results A total of 1206 articles were identified from the initial search, with 43 articles, involving 8861 hips, meeting the inclusion criteria. All studies evaluating femoral or acetabular version in FAI reported ‘normal’ mean version values (10–25 °). However, distribution analysis revealed that an estimated 31% and 51% of patients with FAI displayed abnormal central acetabular and femoral version, respectively. Conclusion Up to 51% of patients presenting with symptomatic FAI show an abnormal femoral version, whilst up to 31% demonstrate abnormal acetabular version. This high percentage of version abnormalities highlights the importance of evaluating these parameters routinely during assessment of patients with FAI, to guide clinical decision-making. Level of evidence IV.

Introduction

2018 ◽  
Author(s):  
John R. Peteet ◽  
Mary Lynn Dell ◽  
Wai Lun Alan Fung
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Ethics Committees ◽  
Clinical Decision ◽  
Cultural Formulation ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Religious Professionals ◽  
The Relationship

Historical tensions between psychiatry and religion continue to hinder dialogue and restrict consensus on how to approach areas of overlap in clinical decision making. In Part One, contributors to this volume discuss concerns arising in the general areas of values, religious and psychiatric ethics, diagnosis and treatment, and the work of religious professionals and ethics committees. In Part Two, chapter authors consider these issues as they arise within various subspecialties of psychiatric practice, often using the Jonsen Four Topics (or Four Quadrants) Model. The theme of the relationship between religion and culture runs throughout and is addressed more directly than in the Outline for Cultural Formulation in Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).

scholarly journals Precision medicine in inflammatory bowel disease: concept, progress and challenges

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 54 ◽  
Author(s):  
Simon P. Borg-Bartolo ◽  
Ray Kiran Boyapati ◽  
Jack Satsangi ◽  
Rahul Kalla
Keyword(s):  
Precision Medicine ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Underlying Disease ◽  
Response To Therapy ◽  
Current Evidence ◽  
Disease Biology ◽  
Bowel Diseases ◽  
Inflammatory Bowel ◽  
The Individual

Crohn’s disease and ulcerative colitis are increasingly prevalent, relapsing and remitting inflammatory bowel diseases (IBDs) with variable disease courses and complications. Their aetiology remains unclear but current evidence shows an increasingly complex pathophysiology broadly centring on the genome, exposome, microbiome and immunome. Our increased understanding of disease pathogenesis is providing an ever-expanding arsenal of therapeutic options, but these can be expensive and patients can lose response or never respond to certain therapies. Therefore, there is now a growing need to personalise therapies on the basis of the underlying disease biology and a desire to shift our approach from “reactive” management driven by disease complications to “proactive” care with an aim to prevent disease sequelae. Precision medicine is the tailoring of medical treatment to the individual patient, encompassing a multitude of data-driven (and multi-omic) approaches to foster accurate clinical decision-making. In IBD, precision medicine would have significant benefits, enabling timely therapy that is both effective and appropriate for the individual. In this review, we summarise some of the key areas of progress towards precision medicine, including predicting disease susceptibility and its course, personalising therapies in IBD and monitoring response to therapy. We also highlight some of the challenges to be overcome in order to deliver this approach.

Likelihood Ratio, Skull Roentgenograms, and Clinical Decision-Making

PEDIATRICS ◽  
1983 ◽  
Vol 71 (4) ◽  
pp. 672-673
Author(s):  
JOHN M. LEVENTHAL ◽  
ROBERT M. LEMBO
Keyword(s):  
Decision Making ◽  
Likelihood Ratio ◽  
Clinical Finding ◽  
Clinical Decision Making ◽  
Skull Fracture ◽  
Clinical Decision ◽  
Clinical Findings ◽  
Skull Fractures ◽  
Fractures In Children ◽  
The Relationship

To the Editor.— In the February 1982 issue of Pediatrics, Leonidas et al1 examined the relationship between clinical findings and skull fractures in children evaluated with skull roentgenograms to develop reliable criteria for the ordering of roentgenograms in patients with head trauma. In their analysis, the authors used the liklihood ratio (LR) to characterize quantitatively the relationship between a clinical finding and the presence of a skull fracture. As defined by the authors, the LR is that ratio between the probability of a certain clinical finding occurring in the presence of a fracture and the probability of the same clinical finding occurring in the absence of a fracture.

Data Mining and Analysis of Lung Cancer

2010 ◽  
pp. 118-144
Author(s):  
Guoxin Tang
Keyword(s):  
Lung Cancer ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
The United States ◽  
Claim Data ◽  
National Database ◽  
Appropriate Treatment ◽  
The World ◽  
The Cost ◽  
The Relationship

Lung cancer is the leading cause of cancer death in the United States and the world, with more than 1.3 million deaths worldwide per year. However, because of a lack of effective tools to diagnose lung cancer, more than half of all cases are diagnosed at an advanced stage, when surgical resection is unlikely to be feasible. The purpose of this study is to examine the relationship between patient outcomes and conditions of the patients undergoing different treatments for lung cancer and to develop models to estimate the population burden, the cost of cancer, and to help physicians and patients determine appropriate treatment in clinical decision-making. We use a national database, and also claim data to investigate treatments for lung cancer.

Countertransference and ethics: A perspective on clinical dilemmas in end-of-life decisions

2003 ◽  
Vol 1 (4) ◽  
pp. 367-375 ◽  
Author(s):  
BRIAN J. KELLY ◽  
FRANCIS T. VARGHESE ◽  
DAN PELUSI
Keyword(s):  
End Of Life ◽  
End Of Life Care ◽  
Assisted Suicide ◽  
Clinical Decision Making ◽  
Ethical Dilemmas ◽  
Clinical Decision ◽  
Life Care ◽  
End Of Life Decisions ◽  
The Relationship ◽  
Dying Patient

Ethical dilemmas in end-of-life care, such as the request for assisted suicide, must be understood in the context of the relationship that exists between patients and the clinicians treating them. This context includes the way health professionals respond to the tasks in caring for a dying patient. This article reviews the literature exploring the factors the influence clinical decision making at the end of life. The interplay of ethics, countertransference and transference are explained in detail.

The Obesity Paradox in Cancer: How Important Is Muscle?

2018 ◽  
Vol 38 (1) ◽  
pp. 357-379 ◽  
Author(s):  
Elizabeth M. Cespedes Feliciano ◽  
Candyce H. Kroenke ◽  
Bette J. Caan
Keyword(s):  
Cancer Patients ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Obesity Paradox ◽  
Future Research ◽  
Reverse Causality ◽  
Research Directions ◽  
Future Research Directions ◽  
Relationship Of ◽  
The Relationship

Although higher body mass index (BMI) increases the incidence of many cancers, BMI can also exhibit a null or U-shaped relationship with survival among patients with existing disease; this association of higher BMI with improved survival is termed the obesity paradox. This review discusses possible explanations for the obesity paradox, the prevalence and consequences of low muscle mass in cancer patients, and future research directions. It is unlikely that methodological biases, such as reverse causality or confounding, fully explain the obesity paradox. Rather, up to a point, higher BMI may truly be associated with longer survival in cancer patients. This is due, in part, to the limitations of BMI, which scales weight to height without delineating adipose tissue distribution or distinguishing between adipose and muscle tissue. Thus, cancer patients with higher BMIs often have higher levels of protective muscle. We assert that more precise measures of body composition are required to clarify the relationship of body size to cancer outcomes, inform clinical decision-making, and help tailor lifestyle interventions.

scholarly journals Balancing accuracy and interpretability of machine learning approaches for radiation treatment outcomes modeling

BJR|Open ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 20190021 ◽  
Author(s):  
Yi Luo ◽  
Huan-Hsin Tseng ◽  
Sunan Cui ◽  
Lise Wei ◽  
Randall K. Ten Haken ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Decision Making ◽  
Radiation Treatment ◽  
Clinical Decision ◽  
Black Box ◽  
Prediction Performance ◽  
Learning Approaches ◽  
Treatment Plans ◽  
The Relationship ◽  
Review Current

Radiation outcomes prediction (ROP) plays an important role in personalized prescription and adaptive radiotherapy. A clinical decision may not only depend on an accurate radiation outcomes’ prediction, but also needs to be made based on an informed understanding of the relationship among patients’ characteristics, radiation response and treatment plans. As more patients’ biophysical information become available, machine learning (ML) techniques will have a great potential for improving ROP. Creating explainable ML methods is an ultimate task for clinical practice but remains a challenging one. Towards complete explainability, the interpretability of ML approaches needs to be first explored. Hence, this review focuses on the application of ML techniques for clinical adoption in radiation oncology by balancing accuracy with interpretability of the predictive model of interest. An ML algorithm can be generally classified into an interpretable (IP) or non-interpretable (NIP) (“black box”) technique. While the former may provide a clearer explanation to aid clinical decision-making, its prediction performance is generally outperformed by the latter. Therefore, great efforts and resources have been dedicated towards balancing the accuracy and the interpretability of ML approaches in ROP, but more still needs to be done. In this review, current progress to increase the accuracy for IP ML approaches is introduced, and major trends to improve the interpretability and alleviate the “black box” stigma of ML in radiation outcomes modeling are summarized. Efforts to integrate IP and NIP ML approaches to produce predictive models with higher accuracy and interpretability for ROP are also discussed.

Sign in / Sign up

Export Citation Format

Share Document