ABSTRACT
BACKGROUND Relationships between serum prolactin concentrations and various CV risk factors in older adults have rarely been assessed. The aim of this study was to examine the relationships between serum prolactin concentrations and CV risk factors in older patients with multiple CV risk factors. MATERIAL AND METHODS This case-control study included 92 patients, 50-89 years old (median, 69 years), with multiple CV risk factors. We used data from general practice electronic health records and biochemical laboratory tests. Patients were divided according to categories of CV risk factors. RESULTS Serum prolactin concentrations were significantly higher in elderly people (£65 vs. >65) and in men (70.65±58.02 vs. 150.82±114.05 mIU/L), as well as in patients with lower renal function (156.70±127.23 vs. 72.53±37.25 mIU/L, the bottom vs. top quartile of creatinine clearance), higher serum homocysteine and TSH concentrations, and in those who used NSAID and statins. Parameters indicating chronic inflammation (CRP) and renal function decline (creatinine clearance) were significantly and independently correlated with increased serum prolactin concentrations in multiple regression analysis. CONCLUSIONS When assessing the relationships between prolactin and CV risk factors in older people with multiple CV risk factors, the effect of renal function decline and chronic inflammation should receive attention.
Subject(s)
Cardiovascular Diseases/blood , Prolactin/blood , Aged , Aged, 80 and over , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/etiology , Cardiovascular Diseases/physiopathology , Case-Control Studies , Chronic Disease , Croatia/epidemiology , Databases, Factual , Female , Humans , Inflammation/physiopathology , Kidney/physiopathology , Kidney Function Tests , Male , Middle Aged , Risk FactorsABSTRACT
BACKGROUND: There is potential for medical research on the basis of routine data used from general practice electronic health records (GP eHRs), even in areas where there is no common GP research platform. We present a case study on menopausal women with hypertension and metabolic syndrome (MS). The aims were to explore the appropriateness of the standard definition of MS to apply to this specific, narrowly defined population group and to improve recognition of women at high CV risk. METHODS: We investigated the possible uses offered by available data from GP eHRs, completed with patients interview, in goal of the study, using a combination of methods. For the sample of 202 hypertensive women, 47-59 years old, a data set was performed, consisted of a total number of 62 parameters, 50 parameters used from GP eHRs. It was analysed by using a mixture of methods: analysis of differences, cutoff values, graphical presentations, logistic regression and decision trees. RESULTS: The age range found to best match the emergency of MS was 51-55 years. Deviations from the definition of MS were identified: a larger cut-off value of the waist circumference measure (89 vs 80 cm) and parameters BMI and total serum cholesterol perform better as components of MS than the standard parameters waist circumference and HDL-cholesterol. The threshold value of BMI at which it is expected that most of hypertensive menopausal women have MS, was found to be 25.5. The other best means for recognision of women with MS include triglycerides above the threshold of 1.7 mmol/L and information on statins use. Prevention of CVD should focus on women with a new onset diabetes and comorbidities of a long-term hypertension with anxiety/depression. CONCLUSIONS: The added value of this study goes beyond the current paradigm on MS. Results indicate characteristics of MS in a narrowly defined, specific population group. A comprehensive view has been enabled by using heterogenoeus data and a smart combination of various methods for data analysis. The paper shows the feasibility of this research approach in routine practice, to make use of data which would otherwise not be used for research.
Subject(s)
Body Mass Index , Cholesterol/blood , Clinical Decision-Making , Electronic Health Records/statistics & numerical data , General Practice/statistics & numerical data , Hypertension/diagnosis , Menopause , Metabolic Syndrome/diagnosis , Waist Circumference , Aged , Croatia/epidemiology , Female , Humans , Hypertension/epidemiology , Menopause/blood , Metabolic Syndrome/blood , Metabolic Syndrome/epidemiology , Middle AgedABSTRACT
BACKGROUND: The impact of hypertension duration and the time of onset on the expression of metabolic syndrome (MS) and other CV risk factors, in perimenopausal women, have not been studied so far. Methods. A total of 202 women, old 47-59 years, and diagnosed with hypertension, were recruited from primary care practices in eastern Croatia. The categories of hypertension duration were defined as <5, 5-10, and >10 years. Data were analyzed by standard statistical procedures. RESULTS: The proportion of women with MS increases in parallel with hypertension duration (p = 0.025). Among the examined CV risk factors, significant increase in parallel with hypertension duration was found for body mass index (p = 0.007) and triglycerides (p = 0.07). The highest proportion of women with diabetes duration of less than 5 years, indicating recent diabetes onset, was found in the category of hypertension duration of less than 5 years, corresponding with the onset of hypertension in the time around menopause (p = 0.003). The strongest linear correlations with BMI and waist circumference were found for total serum cholesterol (r = 0.355 and 0.499, respectively). CONCLUSION: Hypertension onset at the time around menopause appears together with abdominal obesity and may be a driving force for CV risk factor accumulation in postmenopausal women.
ABSTRACT
INTRODUCTION: Primary lymphomas of the small intestine are rare. Burkitt's lymphoma (BL) occurs sporadically in adults. Nodular lymphoid hyperplasia (NLH) is a rare disorder characterized by diffuse nodular lesions, which represent hyperplastic lymphoid follicles, and it is often associated with immunodeficiency syndromes. PRESENTATION OF CASE: We present a 38-year-old male patient in a state of surgical emergency, suspected of Crohn's disease, who had an unusual combination of NLH and BL of the proximal ileum. Furthermore, retrospectively analyzed documentation revealed selective IgA deficiency. DISCUSSION: Association between NLH and intestinal lymphomas in patients with immunodeficiency syndromes was indicated before. This case report supports the notion on NLH as a transition state between immunodeficiency and intestinal lymphomas. CONCLUSION: This is one of the first case reports which presents the combination of NHL and BL. The awareness of the existence of this rare combination, especially in young adult males, can improve the diagnostic accuracy and the treatment management.
ABSTRACT
In this article, we demonstrate the impact of interactive machine learning: we develop biomedical entity recognition dataset using a human-into-the-loop approach. In contrary to classical machine learning, human-in-the-loop approaches do not operate on predefined training or test sets, but assume that human input regarding system improvement is supplied iteratively. Here, during annotation, a machine learning model is built on previous annotations and used to propose labels for subsequent annotation. To demonstrate that such interactive and iterative annotation speeds up the development of quality dataset annotation, we conduct three experiments. In the first experiment, we carry out an iterative annotation experimental simulation and show that only a handful of medical abstracts need to be annotated to produce suggestions that increase annotation speed. In the second experiment, clinical doctors have conducted a case study in annotating medical terms documents relevant for their research. The third experiment explores the annotation of semantic relations with relation instance learning across documents. The experiments validate our method qualitatively and quantitatively, and give rise to a more personalized, responsive information extraction technology.