Bayesian predictors of very poor health related quality of life and mortality in patients with COPD

Background: Chronic obstructive pulmonary disease (COPD) is associated with increased mortality and poor health-related quality of life (HRQoL) compared with the general population. The objective of this study was to identify clinical characteristics which predict mortality and very poor HRQoL among the COPD population and to develop a Bayesian prediction model. Methods: The data consisted of 738 patients with COPD who had visited the Pulmonary Clinic of the Helsinki and Turku University Hospitals during 1995-2006. The data set contained 49 potential predictor variables and two outcome variables: survival (dead/alive) and HRQoL measured with a 15D instrument (very poor HRQoL = 0.70). In the first phase of model validation we randomly divided the material into a training set (n = 538), and a test set (n = 200). This procedure was repeated ten times in random fashion to obtain independently created training sets and corresponding test sets. Modeling was performed by using the training set, and each model was tested by using the corresponding test set, repeated in each training set. In the second phase the final model was created by using the total material and eighteen most predictive variables. The performance of six logistic regressions approaches were shown for comparison purposes. Results: In the final model, the following variables were associated with mortality or very poor HRQoL: age at onset, cerebrovascular disease, diabetes, alcohol abuse, cancer, psychiatric disease, body mass index, Forced Expiratory Volume (FEV1) % of predicted, atrial fibrillation, and prolonged QT time in ECG. The prediction accuracy of the model was 77%, sensitivity 0.30, specificity 0.95, positive predictive value 0.68, negative predictive value 0.78, and area under the ROC curve 0.69. While the sensitivity of the model reminded limited, good specificity, moderate accuracy, comparable or better performance in classification and better performance in variable selection and data usage in comparison to the logistic regression approaches, and positive and negative predictive values indicate that the model has potential in predicting mortality and very poor HRQoL in COPD patients. Conclusion: We developed a Bayesian prediction model which is potentially useful in predicting mortality and very poor HRQoL in patients with COPD.Peer reviewe

The Impact of Pursed-lips Breathing Maneuver on Cardiac, Respiratory, and Oxygenation Parameters in COPD Patients

BACKGROUND: Respiratory system, together with the cardiovascular and central nervous system, is responsible for all processes related to oxygenation and hemodynamics and the defect in the functioning of each of these systems, along with ageing, can have mutual effects on their performance and physiological symptoms. The use of Pursed-lips Breathing (PLB) training is an essential part of the treatment of patients with the obstructive pulmonary disease, PLB stimulates the autonomic nervous system and causes relaxation and improvement of physiological parameters. AIM: This study was conducted to evaluate the effect of PLB on cardiac, pulmonary and oxygenation level in patients with Chronic Obstructive Pulmonary Disease (COPD). METHODS: A three-group clinical trial study with experimental and control which was purposefully conducted with the participation of patients with COPD and healthy individuals referring to Madani hospital Khoy, in 2017. The sample size was selected to be 60 subjects. The patients were randomly allocated to two groups of intervention and control with 20 patients, and 20 healthy subjects were assigned to the healthy intervention group. The demographic, anthropometric information form and checklist recording changes in levels of oxygenation, respiration, temperature, heart rate and blood pressure with cardiopulmonary follow up in three stages before, during and after PLB were used for data collection. Data were analysed using descriptive statistics, repeated measure test, ANOVA, and Chi-square. RESULTS: On evaluation within the COPD patient intervention group in Saturation of Peripheral Oxygen (SPO2) index with the mean difference of 2.05 percent, Respiratory Rate(RR)-0.65 minute and Pulse Rate(PR)-1.6 bpm was significant (p ≤ 0.05), and systolic blood pressure index in healthy subjects was increased (3.35 mmHg). CONCLUSION: The results of this study indicated that using effective PLB as an easy, inexpensive, non- invasive and non-pharmacological method is considered as an important factor in improving the status of oxygenation and physiological indicators in patients with COPD and should be considered as an important part of rehabilitation programs for these patients

Impact of Alcohol Consumption on Quality of Life, Depressive Mood and Metabolic Syndrome in Obstructive Lung Disease Patients: Analysis of Data from Korean National Health and Nutrition Examination Survey from 2014 and 2016

Background The objective of this study was to investigate whether alcohol consumption might affect the quality of life (QOL), depressive mood, and metabolic syndrome in patients with obstructive lung disease (OLD). Methods Data were obtained from the Korean National Health and Nutrition Examination Survey from 2014 and 2016. OLD was defined as spirometry of forced expiratory volume in 1 second/forced vital capacity <0.7 in those aged more than 40 years. QOL was evaluated using the European Quality of Life Questionnaire-5D (EQ-5D) index. Patient Health Questionnaire-9 (PHQ-9) was used to assess the severity of depressive mood. Alcohol consumption was based on a history of alcohol ingestion during the previous month. Results A total of 984 participants with OLD (695 males, 289 females, age 65.8±9.7 years) were enrolled. The EQ-5D index was significantly higher in alcohol drinkers (n=525) than in non-alcohol drinkers (n=459) (0.94±0.11 vs. 0.91±0.13, p=0.002). PHQ-9 scores were considerably lower in alcohol drinkers than in non-alcohol drinkers (2.15±3.57 vs. 2.78±4.13, p=0.013). However, multiple logistic regression analysis showed that alcohol consumption was not associated with EQ-5D index or PHQ-9 score. Body mass index ≥25 kg/m2, triglyceride ≥150 mg/dL, high-density lipoprotein <40 mg/dL in men and <50 mg/dL in women, and blood pressure ≥130/85 mm Hg were significantly more common in alcohol drinkers than in non-alcohol drinkers (all p<0.05). Conclusion Alcohol consumption did not change the QOL or depressive mood of OLD patients. However, metabolic syndrome-related factors were more common in alcohol drinkers than in non-alcohol drinkers

Context Relevant Prediction Model for COPD Domain Using Bayesian Belief Network

In the last three decades, researchers have examined extensively how context-aware systems can assist people, specifically those suffering from incurable diseases, to help them cope with their medical illness. Over the years, a huge number of studies on Chronic Obstructive Pulmonary Disease (COPD) have been published. However, how to derive relevant attributes and early detection of COPD exacerbations remains a challenge. In this research work, we will use an efficient algorithm to select relevant attributes where there is no proper approach in this domain. Such algorithm predicts exacerbations with high accuracy by adding discretization process, and organizes the pertinent attributes in priority order based on their impact to facilitate the emergency medical treatment. In this paper, we propose an extension of our existing Helper Context-Aware Engine System (HCES) for COPD. This project uses Bayesian network algorithm to depict the dependency between the COPD symptoms (attributes) in order to overcome the insufficiency and the independency hypothesis of naïve Bayesian. In addition, the dependency in Bayesian network is realized using TAN algorithm rather than consulting pneumologists. All these combined algorithms (discretization, selection, dependency, and the ordering of the relevant attributes) constitute an effective prediction model, comparing to effective ones. Moreover, an investigation and comparison of different scenarios of these algorithms are also done to verify which sequence of steps of prediction model gives more accurate results. Finally, we designed and validated a computer-aided support application to integrate different steps of this model. The findings of our system HCES has shown promising results using Area Under Receiver Operating Characteristic (AUC = 81.5%)

Multimorbidity, Management of COPD and Health Outcomes among Medicaid Beneficiaries

Chronic Obstructive Pulmonary Disease (COPD) is characterized by persistent and progressive airflow limitation caused due to chronic inflammation in the lungs. Approximately 15 million adults in the United States (U.S.) are estimated to be diagnosed with COPD and an equal number may have undiagnosed COPD. Challenges to COPD management include high prevalence of inflammation-related multimorbidity among individuals with COPD. The association between multimorbidity, existing COPD management and role of novel therapies with anti-inflammatory properties (e.g. statins) in improving COPD-specific outcomes is not well researched. Therefore, the purpose of this study was to use real-world observational data to provide a comprehensive understanding of the relationship between multimorbidity and COPD management as well as assess the effectiveness and safety of statins in terms of COPD management. The specific aims of three studies were to: (1) examine the association between inflammation-related multimorbidity and COPD management in terms of COPD medication receipt, long-acting bronchodilators persistence and COPD-specific outcomes; (2) assess the effectiveness of novel statin therapy in improving COPD-specific outcomes; (3) evaluate the safety of statins and other commonly used medications (antidepressants and inhaled corticosteroids) in terms of new-onset diabetes. This study used a retrospective longitudinal dynamic cohort design using data extracted from multiple years (2005-2008) of Medicaid Analytic eXtract (MAX) files to identify Medicaid beneficiaries with newly diagnosed COPD (n = 19,060). Findings from the first study documented very high prevalence of inflammation-related multimorbidity and indicated that it was significantly associated with reduced COPD-medication utilization and decreased persistence on long-bronchodilators. Our study findings suggest that COPD medication management may be poor due to competing demands arising from the presence of inflammation-related multimorbidity. The results from the study on effectiveness of statins revealed that any statin use improved COPD-specific outcomes compared to no statin use. A closer examination of the data revealed that only those with long-term statin use had better outcomes as compared to those with no statin use. We also found that beneficiaries with inflammation-related multimorbidity and statin use had better COPD-specific outcomes compared to those with multimorbidity and no statin use. From the third study, we found that association between statin use and risk of new-onset diabetes was no longer significant in analyses that controlled for selection bias in unobserved characteristics. Collectively, these findings indicate poor COPD management among those with multimorbidity and emphasize the need for novel therapies to effectively manage COPD. In this context, the current study underscores the advantage of statins in improving COPD-specific clinical and economic outcomes. This study indicate the need of randomized clinical trials and long-term observational studies to establish the efficacy, effectiveness, and safety of novel therapeutic agents in management of COPD