No abstract

Within the National Innovation System, universities play a key role as the main source of knowledge that supports national productivity and as a system that seeks to improve the competitiveness of firms competitiveness and to find answers concerning market needs in today's fast-changing and globalized economy. Innovation, as a source of competitiveness, is normally supported by a firm's technological capabilities: internal R&D, external collaborative agreements, and relationships with universities. This study uses a cluster analysis to identify three clusters that represent respectively those firms that interact closely with universities for technology development (which include R&D projects) and technological learning activities, those firms that interact with universities for technological learning only, and those that do not have any kind of relationship with universities. We also analyze the innovation performance of each cluster. Data here come from the Second Colombian Innovation Survey, which was applied in 2005 to a sample of 6,222 firms. Among the main results, this study shows a higher innovation performance for those firms with relevant linkages for technology learning activities.

Objective: To determine the feasibility of the community pharmacist identifying new patients with hypercholesterolaemia (HC) through a screening program (PHI-CAPTCHA). Methods: The study begins with patients who attended any of four pharmacies in the town of Jovita (Argentina) to obtain their lipid-lowering medication between March 1 and April 30, 2017. The genealogical trees of the patients who agreed to participate were determined. Authorisation was requested to review the cholesterolaemia records of their relatives stored in the databases of the Jovita Clinical Analysis Laboratory (1997-2015). The hypothetical efficacy of PHI-CAPTCHA was determined as (i) the proportion of children confirmed to have HC, and (ii) the proportion of patients with at least one child with HC. Results: One hundred and thirty-nine patients of the 274 patients who obtained their lipid-lowering drugs from any of the four pharmacies, met the inclusion and exclusion criteria. Of the total number of patients' relatives, 532 had historical records of cholesterol readings and agreed to participate in the study. Thirty-five per cent of children (95/270) and 26% of grandchildren (69/262) presented with HC. Forty-eight per cent of patients had at least one child with HC. Of the 2nd generation patients of the service (original patient´s hypercholesterolaemic children), 35% of their children had HC and 50% had at least one child with this condition. A child's probability of having high cholesterol was found to double when their father also had HC (OR = 2.08, 95%CI [1.19, 3.63]). Conclusion: The results of this study indicate screening services should be offered to all HC patients, regardless of the age of their children and grandchildren.

Introduction. Parental hypercholesterolemia w o u l d b e a b e t t e r p r e d i c t o r o f hypercholesterolemia than family medical history in children. Objectives. To compare the strength of association and predictive values of parental hypercholesterolemia versus a positive family history in pediatric hypercholesterolemia. Material and methods. Cross-sectional, analytical study. Cholesterol levels were measured in children aged ≥ 6 and < 12 years and in their biological parents. A survey was administered to parents. The association was estimated using the odds ratio (OR), and its predictive value was determined. The relationship between hypercholesterolemia in parents and their children was studied with multilevel regression. Results. A total of 332 children, 304 mothers, and 206 fathers were assessed. A cholesterol level ≥ 240 mg/dL in one or both parents and ≥ 200 mg/dL in children showed: OR= 6.40; 95 % confidence interval (CI)= 2.85-14.48; p < 0.0001; sensitivity= 69 %; specificity= 74 %; positive predictive value (PPV)= 34 %; negative predictive value (NPV)= 93 %; positive likelihood ratio (LR+)= 2.69; negative likelihood ratio (LR-)= 0.42. Family medical history versus children with cholesterol level ≥ 200 showed: OR= 1.86; 95 % CI= 0.84-4.11; p= 0.1272; sensitivity= 69 %; specificity= 46 %; PPV= 19 %; NPV= 89 %; LR+= 1.27; LR-= 0.68. Cholesterol was 2.9 and 2.5 mg/dL higher per every 10 mg/dL of increased cholesterol in mothers and fathers, respectively. Conclusions: Parental hypercholesterolemia w a s s i g n i f i c a n t l y a s s o c i a t e d w i t h hypercholesterolemia in children and showed a higher predictive power than a positive family medical history.