instruction:
In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.
question:
Context: The aim of this exploratory study was to identify those factors associated with asthma control assessed according to GINA Guidelines.', '809 (56% female) subjects with asthma were recruited consecutively from both specialist and primary care centres. Asthma control was assessed over a 4-week follow-up period using a composite measure. A multivariate analysis was performed, in which asthma control was included as the dependent variable and several explanatory variables were included as independent variables.', 'Analysis performed on the whole population rendered gender (p=0.003), the type of physician (p<0.001), and age group (p<0.001), as significant factors associated with asthma control. In adults, gender (p=0.001), asthma severity (p<0.001), and type of physician (p<0.001) were significant, and only asthma severity was significant (p=0.043) in children.\Question: Are women , patients with severe asthma , and patients attended by primary care physicians , at higher risk of suffering from poorly controlled asthma?
answer:
After model adjustment, we suggest that being female, suffering from more severe asthma, or being attended by a primary care physician, could pose a significantly higher risk of having poorly controlled asthma in adults.


question:
Context: Studies in chronic noncancer pain settings have found that opioid use increases health care utilization. Despite the key role of analgesics, specifically opioids, in the setting of cancer pain, there is no literature to our knowledge about the relationship between adherence to prescribed around-the-clock (ATC) analgesics and acute health care utilization (hospitalization) among patients with cancer pain.', 'To identify adherence patterns over time for cancer patients taking ATC analgesics for pain, cluster these patterns into adherence types, combine the types into an adherence risk factor for hospitalization, identify other risk factors for hospitalization, and identify risk factors for inconsistent analgesic adherence.', 'Data from a 3-month prospective observational study of patients diagnosed with solid tumors or multiple myeloma, having cancer-related pain, and having at least one prescription of oral ATC analgesics were collected. Adherence data were collected electronically using the medication event-monitoring system. Analyses were conducted using adaptive modeling methods based on heuristic search through alternative models controlled by likelihood cross-validation scores.', 'Six adherence types were identified and combined into the risk factor for hospitalization of inconsistent versus consistent adherence over time. Twenty other individually significant risk factors for hospitalization were identified, but inconsistent analgesic adherence was the strongest of these predictors (ie, generating the largest likelihood cross-validation score). These risk factors were adaptively combined into a model for hospitalization based on six pairwise interaction risk factors with exceptional discrimination (ie, area under the receiver-operating-characteristic curve of 0.91). Patients had from zero to five of these risk factors, with an odds ratio of 5.44 (95% confidence interval 3.09-9.58) for hospitalization, with a unit increase in the number of such risk factors.\Question: Do patterns of analgesic adherence predict health care utilization among outpatients with cancer pain?
answer:
Inconsistent adherence to prescribed ATC analgesics, specifically the interaction of strong opioids and inconsistent adherence, is a strong risk factor for hospitalization among cancer outpatients with pain.


question:
Context: Recently, the role of osteoprotegerin (OPG) in the pathogenesis of heart failure through different mechanisms has received much attention. Subclinical changes in left ventricular (LV) function can be identified using quantification of myocardial strain, and global longitudinal strain (GLS) is a superior predictor of outcomes than ejection fraction. We hypothesized that increased OPG levels could predict subclinical LV systolic dysfunction in treated diabetic hypertensive patients with preserved LV ejection fraction.', 'The study was composed of 86 diabetic hypertensive and 30 nondiabetic hypertensive patients. All patients underwent echocardiography and venous blood samples were taken for determination of OPG. The relation between OPG levels and LV GLS was investigated using 2-dimensional speckle tracking echocardiography.', 'Diabetic hypertensive patients had higher diastolic peak early/early diastolic tissue velocity and lower systolic tissue velocity, GLS, GLS rate systolic, and GLS rate early diastolic than nondiabetic hypertensive patients (P = 0.009, P = 0.049, P < 0.001, P = 0.004, and P < 0.001, respectively). Diabetic hypertensive patients were divided into 2 groups according to median GLS value (> 18.5 and ≤ 18.5). The patients with GLS ≤ 18.5 had higher diastolic blood pressure (mm Hg; P = 0.048), OPG (pmol/L; P < 0.001), and hemoglobin A1c (%; P = 0.042) values than those with GLS > 18.5. In multivariate logistic regression analysis, OPG was found to be an independent predictor of impaired GLS (P = 0.001). Receiver operating characteristic curve analysis revealed that OPG values of > 6.45 (pmol/L) identified the patients with GLS ≤ 18.5.\Question: Is osteoprotegerin associated with subclinical left ventricular systolic dysfunction in diabetic hypertensive patients : a speckle tracking study?
answer:

Plasma OPG values could predict subclinical LV systolic dysfunction in diabetic hypertensive patients.