Common Inflammation-Related Candidate Gene Variants and Acute Kidney Injury in 2647 Critically Ill Finnish Patients

Acute kidney injury (AKI) is a syndrome with high incidence among the critically ill. Because the clinical variables and currently used biomarkers have failed to predict the individual susceptibility to AKI, candidate gene variants for the trait have been studied. Studies about genetic predisposition to AKI have been mainly underpowered and of moderate quality. We report the association study of 27 genetic variants in a cohort of Finnish critically ill patients, focusing on the replication of associations detected with variants in genes related to inflammation, cell survival, or circulation. In this prospective, observational Finnish Acute Kidney Injury (FINNAKI) study, 2647 patients without chronic kidney disease were genotyped. We defined AKI according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria. We compared severe AKI (Stages 2 and 3, n = 625) to controls (Stage 0, n = 1582). For genotyping we used iPLEX(TM) Assay (Agena Bioscience). We performed the association analyses with PLINK software, using an additive genetic model in logistic regression. Despite the numerous, although contradictory, studies about association between polymorphisms rs1800629 in TNFA and rs1800896 in IL10 and AKI, we found no association (odds ratios 1.06 (95% CI 0.89-1.28, p = 0.51) and 0.92 (95% CI 0.80-1.05, p = 0.20), respectively). Adjusting for confounders did not change the results. To conclude, we could not confirm the associations reported in previous studies in a cohort of critically ill patients.Peer reviewe

Heme oxygenase-1 repeat polymorphism in septic acute kidney injury

Acute kidney injury (AKI) is a syndrome that frequently affects the critically ill. Recently, an increased number of dinucleotide repeats in the HMOX1 gene were reported to associate with development of AKI in cardiac surgery. We aimed to test the replicability of this finding in a Finnish cohort of critically ill septic patients. This multicenter study was part of the national FINNAKI study. We genotyped 300 patients with severe AKI (KDIGO 2 or 3) and 353 controls without AKI (KDIGO 0) for the guanine-thymine (GTn) repeat in the promoter region of the HMOX1 gene. The allele calling was based on the number of repeats, the cut off being 27 repeats in the S-L (short to long) classification, and 27 and 34 repeats for the S-M-L2 (short to medium to very long) classification. The plasma concentrations of heme oxygenase-1 (HO-1) enzyme were measured on admission. The allele distribution in our patients was similar to that published previously, with peaks at 23 and 30 repeats. The S-allele increases AKI risk. An adjusted OR was 1.30 for each S-allele in an additive genetic model (95% CI 1.01-1.66; p = 0.041). Alleles with a repeat number greater than 34 were significantly associated with lower HO-1 concentration (p<0.001). In septic patients, we report an association between a short repeat in HMOX1 and AKI risk

Narratives on value experience through activities of an individual’s well-being

Abstract The purpose of this paper is to explore individuals’ activities related to their own well-being and how these activities are linked to individuals’ value ex periences while improving their well-being. To address a need to move away from a service firm’s viewpoint, the authors adopt the customer-dominant (C-D) logic perspective of services. The analysis of individuals’ narratives reveals core, related and other activities following the idea of C-D logic, and a framework for value experience of three different types of individuals namely ‘Want to do’, ‘Need for motivation’ and ‘Have to do’. Theoretical and practical implications to service marketing suggest to shift the focus from a service firm’s view to individuals’ lives and processes, and to provide a fresh view to the role of individuals to control their value experiences through activities

Feasibility of digital footprint data for health analytics and services:an explorative case study

Abstract Background: As a result of digitalization, data is available about almost every aspect of our lives. Personal data collected by individuals themselves or stored by organizations interacting with people is known as a digital footprint. The purpose of this study was to identify prerequisites for collecting and using digital data that could be valuable for health data analytics and new health services. Methods: Researchers and their contacts involved in a nationwide research project focusing on digital health in Finland were asked to participate in a pilot study on collecting their own personal data from various organizations of their own choice, such as retail chains, banks, insurance companies, and healthcare providers. After the pilot, a qualitative inquiry was adopted to collect semi-structured interview data from twelve active participants in the pilot. Interviews comprised themes such as the experiences of collecting personal data, as well as the usefulness of the data in general and for the participants themselves. Interview data was then analyzed thematically. Results: Even if the participants had an academic background and were highly motivated to collect and use their data, they faced many challenges, such as quite long delays in the provision of the data, and the unresponsiveness of some organizations. Regarding the usefulness of the acquired personal data, our results show that participants had high expectations, but they were disappointed with the small amount of data and its irrelevant content. For the most part, the data was not in a format that would be useful for health data analytics and new health services. Participants also found that there were actual mistakes in their health data reports. Conclusions: The study revealed that collecting and using digital footprint data, even by knowledgeable individuals, is not an easy task. As the usefulness of the acquired personal health data mainly depended on its form and usability for services or solutions relevant to an individual, rather than on the data being valuable as such, more emphasis should be placed on providing the data in a reusable form

Consumer adoption of future MyData-based preventive eHealth services:an acceptance model and survey study

Abstract Background: Constantly increasing health care costs have led countries and health care providers to the point where health care systems must be reinvented. Consequently, electronic health (eHealth) has recently received a great deal of attention in social sciences in the domain of Internet studies. However, only a fraction of these studies focuses on the acceptability of eHealth, making consumers’ subjective evaluation an understudied field. This study will address this gap by focusing on the acceptance of MyData-based preventive eHealth services from the consumer point of view. We are adopting the term "MyData", which according to a White Paper of the Finnish Ministry of Transport and Communication refers to "1) a new approach, a paradigm shift in personal data management and processing that seeks to transform the current organization centric system to a human centric system, 2) to personal data as a resource that the individual can access and control." Objective: The aim of this study was to investigate what factors influence consumers’ intentions to use a MyData-based preventive eHealth service before use. Methods: We applied a new adoption model combining Venkatesh’s unified theory of acceptance and use of technology 2 (UTAUT2) in a consumer context and three constructs from health behavior theories, namely threat appraisals, self-efficacy, and perceived barriers. To test the research model, we applied structural equation modeling (SEM) with Mplus software, version 7.4. A Web-based survey was administered. We collected 855 responses. Results: We first applied traditional SEM for the research model, which was not statistically significant. We then tested for possible heterogeneity in the data by running a mixture analysis. We found that heterogeneity was not the cause for the poor performance of the research model. Thus, we moved on to model-generating SEM and ended up with a statistically significant empirical model (root mean square error of approximation [RMSEA] 0.051, Tucker-Lewis index [TLI] 0.906, comparative fit index [CFI] 0.915, and standardized root mean square residual 0.062). According to our empirical model, the statistically significant drivers for behavioral intention were effort expectancy (beta=.191, P&lt;.001), self-efficacy (beta=.449, P&lt;.001), threat appraisals (beta=.416, P&lt;.001), and perceived barriers (beta=−.212, P=.009). Conclusions: Our research highlighted the importance of health-related factors when it comes to eHealth technology adoption in the consumer context. Emphasis should especially be placed on efforts to increase consumers’ self-efficacy in eHealth technology use and in supporting healthy behavior

Heme oxygenase-1 repeat polymorphism in septic acute kidney injury

Abstract Acute kidney injury (AKI) is a syndrome that frequently affects the critically ill. Recently, an increased number of dinucleotide repeats in the HMOX1 gene were reported to associate with development of AKI in cardiac surgery. We aimed to test the replicability of this finding in a Finnish cohort of critically ill septic patients. This multicenter study was part of the national FINNAKI study. We genotyped 300 patients with severe AKI (KDIGO 2 or 3) and 353 controls without AKI (KDIGO 0) for the guanine–thymine (GTn) repeat in the promoter region of the HMOX1 gene. The allele calling was based on the number of repeats, the cut off being 27 repeats in the S–L (short to long) classification, and 27 and 34 repeats for the S–M–L₂ (short to medium to very long) classification. The plasma concentrations of heme oxygenase-1 (HO-1) enzyme were measured on admission. The allele distribution in our patients was similar to that published previously, with peaks at 23 and 30 repeats. The S-allele increases AKI risk. An adjusted OR was 1.30 for each S-allele in an additive genetic model (95% CI 1.01–1.66; p = 0.041). Alleles with a repeat number greater than 34 were significantly associated with lower HO-1 concentration (p&lt;0.001). In septic patients, we report an association between a short repeat in HMOX1 and AKI risk