a-machine-learning-approach-to-design-an-efficient-selective

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Common ...

Universidad CEU Cardenal Herrera

An inverse relationship has been reported between decreased postoperative Antithrombin (AT) plasmatic levels and the incidence of complications. We hypothesized that Nuclear Hormone Receptors could modulate the expression of SERPINC1, encoding AT, through a Hormone Regulatory Element present in its promoter, and thus hormone analogs could be a pharmacological complement in surgical procedures to activate endogenous AT synthesis.

Glucocorticoids as modulators of expression and activity of Antithrombin (At): potential clinical relevance.

 Decreased antithrombin (AT) activity in patients scheduled for cardiovascular surgery under cardiopulmonary bypass (CPB) is related to increased postoperative complications and hospitalization time. Indirect evidence suggests that glucocorticoids mitigate this decreased AT activity. To better understand the beneficial effects of AT we have analyzed: (i) the clinical relevance of acute dexamethasone (DX) administration before cardiac surgery on AT activity, (ii) the modulation by DX of AT expression in human endothelial cells (hECs), (iii) the activity of AT on migration and angiogenesis of hECs, or on angiogenesis of rat aorta.  A retrospective cohort study in patients undergoing aortic valve replacement surgery was designed to evaluate the effect of DX administration on AT activity at five separate time points: preoperatively, during CPB, at intensive care unit admission and at 12 and 24 h post-intervention. We have analyzed also clinical differences in postoperative outcomes as safety and the length of stay in hospitalization. Changes in mRNA levels of AT induced by DX were determined by qRT-PCR in human coronary (hCEC), aorta (hAEC) and cardiac microvasculature (hCMEC) endothelial cells. AT activity on migration and angiogenesis were also assayed. Angiogenic growth of rat aortic rings incubated in Matrigel was determined in presence and absence of AT.  The cohort comprised 51 patients in the control group and 29 patients in the group receiving dexamethasone. Preoperative DX supplementation reduced intraoperative decrease of AT activity (67.71 ± 10.49% DX treated  58.12 ± 9.11% untreated,  < 0.001) that could be related to a decrease in the hospitalization time (7.59 ± 4.08 days DX treated  13.59 ± 16.00 days untreated,  = 0.014). Treatment of hECs with 500 nM DX slightly increased AT expression. Incubation with 0.5 and 1 IU/mL of AT increased migration and angiogenesis in hCAECs and hAECs, but not in hCMECs. The same concentrations of AT potentiated angiogenic sprouting of new vessels from rat aorta.  Preoperative DX supplementation could be an interesting procedure to avoid excessive decrease in AT levels during cardiac surgery. Positive outcomes associated with maintaining adequate AT levels could be related to its potential beneficial effect on endothelial function (migration and angiogenesis).

Dexamethasone Preconditioning in Cardiac Procedures Reduces Decreased Antithrombin Activity and Is Associated to Beneficial Outcomes: Role of Endothelium.

 The early detection of Mild Cognitive Impairment (MCI) is essential in aging societies where dementia is becoming a common manifestation among the elderly. Thus our aim is to develop a decision tree to discriminate individuals at risk of MCI among non-institutionalized elderly users of community pharmacy. A more clinically and patient-oriented role of the community pharmacist in primary care makes the dispensation of medication an adequate situation for an effective, rapid, easy, and reproducible screening of MCI.  A cross-sectional study was conducted with 728 non-institutionalized participants older than 65. A total of 167 variables were collected such as age, gender, educational attainment, daily sleep duration, reading frequency, subjective memory complaint, and medication. Two screening tests were used to detect possible MCI: Short Portable Mental State Questionnaire (SPMSQ) and the Mini-Mental State Examination (MMSE). Participants classified as positive were referred to clinical diagnosis. A decision tree and predictive models are presented as a result of applying techniques of machine learning for a more efficient enrollment.  One hundred and twenty-eight participants (17.4%) scored positive on MCI tests. A recursive partitioning algorithm with the most significant variables determined that the most relevant for the decision tree are: female sex, sleeping more than 9 h daily, age higher than 79 years as risk factors, and reading frequency. Moreover, psychoanaleptics, nootropics, and antidepressants, and anti-inflammatory drugs achieve a high score of importance according to the predictive algorithms. Furthermore, results obtained from these algorithms agree with the current research on MCI.  Lifestyle-related factors such as sleep duration and the lack of reading habits are associated with the presence of positive in MCI test. Moreover, we have depicted how machine learning provides a sound methodology to produce tools for early detection of MCI in community pharmacy.  The community of pharmacists provided with adequate tools could develop a crucial task in the early detection of MCI to redirect them immediately to the specialists in neurology or psychiatry. Pharmacists are one of the most accessible and regularly visited health care professionals and they can play a vital role in early detection of MCI.

Decision Tree for Early Detection of Cognitive Impairment by Community Pharmacists.

Community pharmacists and general practitioners have daily contact with patients with Alzheimer's disease (AD) but the number of positive cases constantly increases every day. Thus, the aim of this research is to describe the level of AD knowledge among community pharmacists and general practitioners in Spain, in order to see where the biggest gaps in the knowledge are. Therefore, a cross-sectional study has been carried out, using the Alzheimer's disease knowledge survey (ADKS), among members of the Spanish Society of Primary Care Physicians and the Spanish Society of Family and Community Pharmacy to report the differences in AD knowledge in both professional collectives. The ADKS has been responded by 578 community pharmacists and 104 general practitioners and consists of a battery of 30 questions, whose possible answers are true or false. It assesses the AD knowledge in seven areas (impact on the disease, risk factors, course of the disease, diagnosis, care, treatment and symptoms). Results indicate that Spanish pharmacists and general practitioners have a high personal knowledge of AD, nevertheless, it is not associated with greater awareness. Both scored above 80% at the categories: diagnostic, treatment and symptoms. However, lower knowledge level (60% of correct answers) was found in those related to risk factors, such as the ignorance about hypercholesterolemia or hypertension as risk factors for the disease. Community pharmacists are already acting to control cardiovascular risk factors, but a wider knowledge of the relationship of these factors to AD is needed to act against these silent risk factors. Thus, pharmacists may also be involved in the management of AD that includes recognizing early symptoms for early detection of cognitive impairment. Hence, knowledge about risk factors is very important in developing this expanding role.

Lucrecia Moreno

Department of Pharmacy

Universidad CEU Cardenal Herrera

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Lucrecia Moreno

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Pharmacy

Universidad CEU Cardenal Herrera

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Department of Pharmacy