Issues in the provision of nursing care to people undergoing cardiac surgery who also have type 2 diabetes
- Wellard, Sally, Cox, Helen, Bhujoharry, Claire
- Authors: Wellard, Sally , Cox, Helen , Bhujoharry, Claire
- Date: 2007
- Type: Text , Journal article
- Relation: International journal of nursing practice Vol. 13, no. 4 (2007), p. 222-228
- Full Text:
- Reviewed:
- Description: There has been little investigation of the issues associated with caring for patients presenting for cardiac surgery with a comorbid diagnosis of diabetes although there is some evidence that the diabetes management is suboptimal. This study aimed to identify issues that patients and cardiac specialist nurses experience with the provision of inpatient services for people undergoing cardiac surgery who also have type 2 diabetes. A qualitative interpretive design, using individual interviews with patients and nurses, provided data about some of these issues. The study found that nurses had high levels of confidence in their cardiac care but little confidence in diabetes management. Patients described concerns about their diabetes care and treatment regimens. A 'typical journey' for a person with diabetes undergoing cardiac surgery was identified. The findings support the need to build increased capacity in specialist nurses to support diabetes care as a secondary diagnosis.
- Description: C1
- Description: 2003005865
- Authors: Wellard, Sally , Cox, Helen , Bhujoharry, Claire
- Date: 2007
- Type: Text , Journal article
- Relation: International journal of nursing practice Vol. 13, no. 4 (2007), p. 222-228
- Full Text:
- Reviewed:
- Description: There has been little investigation of the issues associated with caring for patients presenting for cardiac surgery with a comorbid diagnosis of diabetes although there is some evidence that the diabetes management is suboptimal. This study aimed to identify issues that patients and cardiac specialist nurses experience with the provision of inpatient services for people undergoing cardiac surgery who also have type 2 diabetes. A qualitative interpretive design, using individual interviews with patients and nurses, provided data about some of these issues. The study found that nurses had high levels of confidence in their cardiac care but little confidence in diabetes management. Patients described concerns about their diabetes care and treatment regimens. A 'typical journey' for a person with diabetes undergoing cardiac surgery was identified. The findings support the need to build increased capacity in specialist nurses to support diabetes care as a secondary diagnosis.
- Description: C1
- Description: 2003005865
Psychometric evaluation of the revised Michigan Diabetes Knowledge Test (V.2016) in Arabic : Translation and validation
- Alhaiti, Ali, Alotaibi, Alanod, Jones, Linda, Dacosta, Cliff, Lenon, George
- Authors: Alhaiti, Ali , Alotaibi, Alanod , Jones, Linda , Dacosta, Cliff , Lenon, George
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Diabetes Research Vol. 2016, no. (2016), p. 1-7
- Full Text:
- Reviewed:
- Description: Objective. To translate the revised Michigan Diabetes Knowledge Test into the Arabic language and examine its psychometric properties. Setting. Of the 139 participants recruited through King Fahad Medical City in Riyadh, Saudi Arabia, 34 agreed to the second-round sample for retesting purposes. Methods. The translation process followed the World Health Organization's guidelines for the translation and adaptation of instruments. All translations were examined for their validity and reliability. Results. The translation process revealed excellent results throughout all stages. The Arabic version received 0.75 for internal consistency via Cronbach's alpha test and excellent outcomes in terms of the test-retest reliability of the instrument with a mean of 0.90 infraclass correlation coefficient. It also received positive content validity index scores. The item-level content validity index for all instrument scales fell between 0.83 and 1 with a mean scale-level index of 0.96. Conclusion. The Arabic version is proven to be a reliable and valid measure of patient's knowledge that is ready to be used in clinical practices. © 2016 Ali Hassan Alhaiti et al.
- Authors: Alhaiti, Ali , Alotaibi, Alanod , Jones, Linda , Dacosta, Cliff , Lenon, George
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Diabetes Research Vol. 2016, no. (2016), p. 1-7
- Full Text:
- Reviewed:
- Description: Objective. To translate the revised Michigan Diabetes Knowledge Test into the Arabic language and examine its psychometric properties. Setting. Of the 139 participants recruited through King Fahad Medical City in Riyadh, Saudi Arabia, 34 agreed to the second-round sample for retesting purposes. Methods. The translation process followed the World Health Organization's guidelines for the translation and adaptation of instruments. All translations were examined for their validity and reliability. Results. The translation process revealed excellent results throughout all stages. The Arabic version received 0.75 for internal consistency via Cronbach's alpha test and excellent outcomes in terms of the test-retest reliability of the instrument with a mean of 0.90 infraclass correlation coefficient. It also received positive content validity index scores. The item-level content validity index for all instrument scales fell between 0.83 and 1 with a mean scale-level index of 0.96. Conclusion. The Arabic version is proven to be a reliable and valid measure of patient's knowledge that is ready to be used in clinical practices. © 2016 Ali Hassan Alhaiti et al.
Data-analytically derived flexible HbA1c thresholds for type 2 diabetes mellitus diagnostic
- Stranieri, Andrew, Yatsko, Andrew, Jelinek, Herbert, Venkatraman, Sitalakshmi
- Authors: Stranieri, Andrew , Yatsko, Andrew , Jelinek, Herbert , Venkatraman, Sitalakshmi
- Date: 2015
- Type: Text , Journal article
- Relation: Artificial Intelligence Research Vol. 5, no. 1 (2015), p. 111-134
- Full Text:
- Reviewed:
- Description: Glycated haemoglobin (HbA1c) is now more commonly used as an alternative test to the fasting plasma glucose and oral glucose tolerance tests for the identification of Type 2 Diabetes Mellitus (T2DM) because it is easily obtained using the point-of-care technology and represents long-term blood sugar levels. According to WHO guidelines, HbA1c values of 6.5% or above are required for a diagnosis of T2DM. However outcomes of a large number of trials with HbA1c have been inconsistent across the clinical spectrum and further research is required to determine the efficacy of HbA1c testing in identification of T2DM. Medical records from a diabetes screening program in Australia illustrate that many patients could be classified as diabetics if other clinical indicators are included, even though the HbA1c result does not exceed 6.5%. This suggests that a cutoff for the general population of 6.5% may be too simple and miss individuals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied to identify markers that can be used with HbA1c. The results indicate that T2DM is best classified by HbA1c at 6.2% - a cutoff level lower than the currently recommended one, which can be even less, having assumed the threshold flexibility, if additionally to HbA1c being high the rule is conditioned on oxidative stress or inflammation being present, atherogenicity or adiposity being high, or hypertension being diagnosed, etc.
- Authors: Stranieri, Andrew , Yatsko, Andrew , Jelinek, Herbert , Venkatraman, Sitalakshmi
- Date: 2015
- Type: Text , Journal article
- Relation: Artificial Intelligence Research Vol. 5, no. 1 (2015), p. 111-134
- Full Text:
- Reviewed:
- Description: Glycated haemoglobin (HbA1c) is now more commonly used as an alternative test to the fasting plasma glucose and oral glucose tolerance tests for the identification of Type 2 Diabetes Mellitus (T2DM) because it is easily obtained using the point-of-care technology and represents long-term blood sugar levels. According to WHO guidelines, HbA1c values of 6.5% or above are required for a diagnosis of T2DM. However outcomes of a large number of trials with HbA1c have been inconsistent across the clinical spectrum and further research is required to determine the efficacy of HbA1c testing in identification of T2DM. Medical records from a diabetes screening program in Australia illustrate that many patients could be classified as diabetics if other clinical indicators are included, even though the HbA1c result does not exceed 6.5%. This suggests that a cutoff for the general population of 6.5% may be too simple and miss individuals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied to identify markers that can be used with HbA1c. The results indicate that T2DM is best classified by HbA1c at 6.2% - a cutoff level lower than the currently recommended one, which can be even less, having assumed the threshold flexibility, if additionally to HbA1c being high the rule is conditioned on oxidative stress or inflammation being present, atherogenicity or adiposity being high, or hypertension being diagnosed, etc.
Analysis of Classifiers for Prediction of Type II Diabetes Mellitus
- Barhate, Rahul, Kulkarni, Pradnya
- Authors: Barhate, Rahul , Kulkarni, Pradnya
- Date: 2018
- Type: Text , Conference proceedings , Conference paper
- Relation: 4th International Conference on Computing, Communication Control and Automation, ICCUBEA 2018
- Full Text:
- Reviewed:
- Description: Diabetes mellitus is a chronic disease and a health challenge worldwide. According to the International Diabetes Federation, 451 million people across the globe have diabetes, with this number anticipated to rise up to 693 million people by 2045. It has been shown that 80% of the complications arising from type II diabetes can be prevented or delayed by early identification of the people who are at risk. Diabetes is difficult to diagnose in the early stages as its symptoms grow subtly and gradually. In a majority of the cases, the patients remain undiagnosed until they are admitted for a heart attack or begin to lose their sight. This paper analyzes the different classification algorithms based on a patient's health history to aid doctors identify the presence of as well as promote early diagnosis and treatment. The experiments were conducted on Pima Indian Diabetes data set. Various classifiers used include K Nearest Neighbors, Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, Support Vector Machine and Neural Network. Results demonstrate that Random Forests performed well on the data set giving an accuracy of 79.7%. © 2018 IEEE.
- Description: E1
- Authors: Barhate, Rahul , Kulkarni, Pradnya
- Date: 2018
- Type: Text , Conference proceedings , Conference paper
- Relation: 4th International Conference on Computing, Communication Control and Automation, ICCUBEA 2018
- Full Text:
- Reviewed:
- Description: Diabetes mellitus is a chronic disease and a health challenge worldwide. According to the International Diabetes Federation, 451 million people across the globe have diabetes, with this number anticipated to rise up to 693 million people by 2045. It has been shown that 80% of the complications arising from type II diabetes can be prevented or delayed by early identification of the people who are at risk. Diabetes is difficult to diagnose in the early stages as its symptoms grow subtly and gradually. In a majority of the cases, the patients remain undiagnosed until they are admitted for a heart attack or begin to lose their sight. This paper analyzes the different classification algorithms based on a patient's health history to aid doctors identify the presence of as well as promote early diagnosis and treatment. The experiments were conducted on Pima Indian Diabetes data set. Various classifiers used include K Nearest Neighbors, Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, Support Vector Machine and Neural Network. Results demonstrate that Random Forests performed well on the data set giving an accuracy of 79.7%. © 2018 IEEE.
- Description: E1
Perceptions of people with Type 2 diabetes about self-management and the efficacy of community based services
- Wellard, Sally, Rennie, Sheree, King, Rosemary
- Authors: Wellard, Sally , Rennie, Sheree , King, Rosemary
- Date: 2008
- Type: Text , Journal article
- Relation: Contemporary nurse : a journal for the Australian nursing profession Vol. 29, no. 2 (2008), p. 218-226
- Full Text:
- Description: Self-management has become a key strategy for managing the health care of people with diabetes. This study explored issues people with type 2 diabetes experienced in their self-management practices and access to regional community based services. Using a qualitative interpretative design data was collected from four participants who were interviews about their perceptions of facilitators, barriers and issues they encountered in their diabetes care in a regional setting. The findings indicate difficulties participants experienced in gaining access to quality services in regional areas, including long waiting times, difficulties making appointments, and their perception that healthcare professionals fail to acknowledge patients self-management knowledge and practices. Additionally, participants reported food choices affected their family relationships and experience of social stigma. These issues compromised their self-management decisions. The findings support other studies that show a need for health professionals to develop strategies to improve community based services for people with type 2 diabetes and to increase public awareness of the scope of diabetes management.
- Authors: Wellard, Sally , Rennie, Sheree , King, Rosemary
- Date: 2008
- Type: Text , Journal article
- Relation: Contemporary nurse : a journal for the Australian nursing profession Vol. 29, no. 2 (2008), p. 218-226
- Full Text:
- Description: Self-management has become a key strategy for managing the health care of people with diabetes. This study explored issues people with type 2 diabetes experienced in their self-management practices and access to regional community based services. Using a qualitative interpretative design data was collected from four participants who were interviews about their perceptions of facilitators, barriers and issues they encountered in their diabetes care in a regional setting. The findings indicate difficulties participants experienced in gaining access to quality services in regional areas, including long waiting times, difficulties making appointments, and their perception that healthcare professionals fail to acknowledge patients self-management knowledge and practices. Additionally, participants reported food choices affected their family relationships and experience of social stigma. These issues compromised their self-management decisions. The findings support other studies that show a need for health professionals to develop strategies to improve community based services for people with type 2 diabetes and to increase public awareness of the scope of diabetes management.
- «
- ‹
- 1
- ›
- »