I lost my daughter after her 2 yr fight with colon cancer. She was 18 when they found it already in stage 4. I lost my beautiful 20 yr old daughter to this cancer on my mothers birthday whom had past away 2 months before Kayla.
Young people need to be checked to for this cancer and I hope some one elses mother doesnt have to go thru this because I have a hole in my heart now because i lost my daughter. Please find a cure and fast. FightCRC Logo fcc-logo-light. Search for:. Learn More.
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That is why knowing and detecting the early signs of colon cancer is important for your health. Fatigue is the most common and least definitive of symptoms associated with colon cancer. Fatigue can happen if polyps or tumors bleed into the digestive tract, leading to a loss of iron over time and possibly iron-deficiency anemia. A direct side effect of iron-deficiency anemia is that individuals to feel tired and short of breath. If you find yourself tired more often and especially if this symptom recently surfaced , ask your doctor for a blood test.
If your result reveals a low red blood cell count, it may be an early warning sign. This may prompt your doctor to order a full screening for colon cancer. You can identify this if your stool has a dark red or black appearance.
But Regardless of the cause, bloody stool is a sign that should warrant examination. The appearance of blood in the toilet, after wiping, or in the stool itself can potentially indicate polyps or tumors somewhere in the colon. Please keep in mind that vegetables like beets and some iron supplements can also darken stool color, so a quick recap of your diet will help you to determine whether or not you should schedule a checkup or an additional scan.
A Escala de Fadiga de Piper - Revisada foi utilizada para avaliar fadiga. La Escala de Fatiga de Piper - Revisada fue utilizada para evaluar fatiga. For a long time, fatigue in cancer has been studied as an isolated symptom. There were studies that aimed to identify its prevalence, the evolution according to the course of the disease, different treatments for cancer and treatments for fatigue.
As these pieces of knowledge seemed relevant, new studies tried to identify the factors that could predict the presence and intensity of fatigue. Studies that investigate the tumor site as a risk factor for fatigue or focus on patients with a single disease site are important for the development of diagnostic strategies and targeted fatigue interventions.
Few studies have investigated fatigue in colorectal cancer patients, and none has identified predictors of fatigue in these patients. Thus, aiming to fill this gap, this study was undertaken to identify predictive factors of fatigue in patients with colorectal cancer.
The prevalence of fatigue is undoubtedly high. The intensity of the symptom is also considerable, with mean scores ranging from 2. Fatigue is a deleterious symptom that causes suffering, distress, functional limitation and predicts overall survival and quality of life Many factors may be related to the occurrence or aggravation of the symptom and recent studies have investigated predictors of cancer-related fatigue in non-specific site groups, such as advanced cancer, outpatients and cancer survivors.
It shows that, according to the disease stage, the associated factors may vary. It seems that, in outpatients, the predictors include a reasonable amount of socio-demographic variables female gender, high education, having a regular job and living without a partner , besides depression and performance status On the other hand, fatigue-associated factors in patients with advanced cancer are basically related to other signs and symptoms present in terminally ill patients e.
Interestingly, among cancer survivors, fatigue predictors include not only performance and symptoms, but also cognitive impairment stress, coping, self-efficacy 5. From the description, a vast variety of physiological, physical, emotional, affective, socio-demographic and treatment-related predictive factors are noted.
Yet, it was observed that many studies involved patients with cancer in various sites and that, in those that included patients with different tumors, the tumor site was not a predictive factor. Therefore, this paper specifically focused on colorectal cancer patients' fatigue experience, aiming to investigate its prevalence and independent associated factors. Cross-sectional study, involving Brazilian adults with primary colon or rectal cancer. Inclusion criteria were: age 18 or more, being treated or followed in outpatient oncology services inpatients were not included.
To have or not fatigue was not an inclusion criteria. The sample representation from each service ranged between The number of patients that refused to participate was considered low 8 patients. Oncologists identified the subjects at the participating oncology services. After a medical appointment, the researcher recruited the patients, checked the inclusion criteria and invited them to participate in the study.
All participants signed the informed consent term and the ethics committees of each of the institutions involved approved the study. Pain and sleep disturbance were assessed on a numerical scale scale. It is a self-report instrument that consists of 21 items to evaluate depressive symptoms.
Each item is scored from 0 to 3 and the total BDI score varies between 0 and Scores between 16 and 20 account for dysphoria and above 21 for depression In the current study, Cronbach's alpha equaled 0. Each item is scored on a numerical scale The dimension scores and total score vary between 0 and 10 and are obtained by adding up the score of each item and dividing this by the number of items on each dimension, or by 22 when calculating the total score.
When the subjects finished answering the self-report instruments, the researcher checked for missing data and, in case data were missing, the researcher handed the items back to the subjects so they could complete the instrument.
Nevertheless, missing data occurred. On the BDI, a total of two items were blank and the mean score of that item all other subjects had answered was used to replace the missing data. On the PFS, three items were blank and the patient's mean subscale score of all items in the same dimension was used to replace the missing data. Missing socio-demographic, clinical, treatment data were left blank. The variables that were associated to fatigue were inserted in the logistic regression model.
The variables were inserted in the logistic regression model, using forward stepwise. The Statistical Package for the Social Sciences-version Most subjects were middle-aged adults years , and the mean age was The clinical characterization of the participants is presented in Table 1. In Table 1 , a significant portion of subjects with altered BMI Of subjects, Scores compatible with dysphoria and depression were present in Mild, moderate and severe fatigue was reported by 37 Among those who reported fatigue, the mean score was 5.
In univariate analysis, fatigue showed association with five out of twenty investigated variables: to be assisted at a public hospital, pain, sleep disturbance, depression and performance status. These five variables were included in the multiple regression model Table 2 and three independent predictors for fatigue were identified: sleep disturbance, depression and performance status. Utilizing the estimated error for each of the independent predictive variables, the Fatigue Prediction Table Table 3 could be constructed.
It is observed that not only the number of factors, but also their nature influences the likelihood of having fatigue. Depression increases the likelihood of having fatigue more than the other factors Table 3. The sensitivity of the model identified in this study was The specificity level equaled
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