Temporal changes in outcome following intensive care unit treatment after traumatic brain injury : a 17-year experience in a large academic neurosurgical centre

Traumatic brain injury (TBI) is a major cause of morbidity and mortality. However, it remains undetermined whether long-term outcomes after TBI have improved over the past two decades. We conducted a retrospective analysis of consecutive TBI patients admitted to an academic neurosurgical ICU during 1999-2015. Primary outcomes of interest were 6-month all-cause mortality (available for all patients) and 6-month Glasgow Outcome Scale (GOS, available from 2005 onwards). GOS was dichotomized to favourable and unfavourable functional outcome. Temporal changes in outcome were assessed using multivariate logistic regression analysis, adjusting for age, sex, GCS motor score, pupillary light responsiveness, Marshall CT classification and major extracranial injury. Altogether, 3193 patients were included. During the study period, patient age and admission Glasgow Coma Scale score increased, while the overall TBI severity did not change. Overall unadjusted 6-month mortality was 25% and overall unadjusted unfavourable outcome (2005-2015) was 44%. There was no reduction in the adjusted odds of 6-month mortality (OR 0.98; 95% CI 0.96-1.00), but the adjusted odds of favourable functional outcome significantly increased (OR 1.08; 95% CI 1.04-1.11). Subgroup analysis showed outcome improvements only in specific subgroups (conservatively treated patients, moderate-to-severe TBI patients, middle-aged patients). During the past two decades, mortality after significant TBI has remained largely unchanged, but the odds of favourable functional outcome have increased significantly in specific subgroups, implying an improvement in quality of care. These developments have been paralleled by notable changes in patient characteristics, emphasizing the importance of continuous epidemiological monitoring.Peer reviewe

Psychotropic medication use among patients with a traumatic brain injury treated in the intensive care unit : a multi-centre observational study

Background Psychiatric sequelae after traumatic brain injury (TBI) are common and may impede recovery. We aimed to assess the occurrence and risk factors of post-injury psychotropic medication use in intensive care unit (ICU)-treated patients with TBI and its association with late mortality. Methods We conducted a retrospective multi-centre observational study using the Finnish Intensive Care Consortium database. We included adult TBI patients admitted in four university hospital ICUs during 2003-2013 that were alive at 1 year after injury. Patients were followed-up until end of 2016. We obtained data regarding psychotropic medication use through the national drug reimbursement database. We used multivariable logistic regression models to assess the association between TBI severity, treatment-related variables and the odds of psychotropic medication use and its association with late all-cause mortality (more than 1 year after TBI). Results Of 3061 patients, 2305 (75%) were alive at 1 year. Of these, 400 (17%) became new psychotropic medication users. The most common medication types were antidepressants (61%), antipsychotics (35%) and anxiolytics (26%). A higher Glasgow Coma Scale (GCS) score was associated with lower odds (OR 0.93, 95% CI 0.90-0.96) and a diffuse injury with midline shift was associated with higher odds (OR 3.4, 95% CI 1.3-9.0) of new psychotropic medication use. After adjusting for injury severity, new psychotropic medication use was associated with increased odds of late mortality (OR 1.19, 95% CI 1.19-2.17, median follow-up time 6.4 years). Conclusions Psychotropic medication use is common in TBI survivors. Higher TBI severity is associated with increased odds of psychotropic medication use. New use of psychotropic medications after TBI was associated with increased odds of late mortality. Our results highlight the need for early identification of potential psychiatric sequelae and psychiatric evaluation in TBI survivors.Peer reviewe

Genotype-by-environment interaction for uniformity of growth in rainbow trout

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Psychotropic medication use among patients with a traumatic brain injury treated in the intensive care unit: a multi-centre observational study

Background: Psychiatric sequelae after traumatic brain injury (TBI) are common and may impede recovery. We aimed to assess the occurrence and risk factors of post-injury psychotropic medication use in intensive care unit (ICU)-treated patients with TBI and its association with late mortality.Methods: We conducted a retrospective multi-centre observational study using the Finnish Intensive Care Consortium database. We included adult TBI patients admitted in four university hospital ICUs during 2003-2013 that were alive at 1 year after injury. Patients were followed-up until end of 2016. We obtained data regarding psychotropic medication use through the national drug reimbursement database. We used multivariable logistic regression models to assess the association between TBI severity, treatment-related variables and the odds of psychotropic medication use and its association with late all-cause mortality (more than 1 year after TBI).Results: Of 3061 patients, 2305 (75%) were alive at 1 year. Of these, 400 (17%) became new psychotropic medication users. The most common medication types were antidepressants (61%), antipsychotics (35%) and anxiolytics (26%). A higher Glasgow Coma Scale (GCS) score was associated with lower odds (OR 0.93, 95% CI 0.90-0.96) and a diffuse injury with midline shift was associated with higher odds (OR 3.4, 95% CI 1.3-9.0) of new psychotropic medication use. After adjusting for injury severity, new psychotropic medication use was associated with increased odds of late mortality (OR 1.19, 95% CI 1.19-2.17, median follow-up time 6.4 years).Conclusions: Psychotropic medication use is common in TBI survivors. Higher TBI severity is associated with increased odds of psychotropic medication use. New use of psychotropic medications after TBI was associated with increased odds of late mortality. Our results highlight the need for early identification of potential psychiatric sequelae and psychiatric evaluation in TBI survivors.</p

Reframing gender and feminist knowledge construction in marketing and consumer research: missing feminisms and the case of men and masculinities

Gender has been theorised and studied in many ways and across different disciplines. Although a number of these theorisations have been recognised and adopted in marketing and consumer research, the significance of feminism in knowledge construction has largely remained what we would call ‘unfinished’. Based on a critical reframing of gender research in marketing and consumer research, in dialogue with feminist theory, this article offers theoretical and practical suggestions for how to reinvigorate these research efforts. The analysis highlights dominant theorisations of gender, relating to gender as variable, difference and role; as fundamental difference and structuring; and as cultural and identity constructions. This reframing emphasises various neglected or ‘missing feminisms’, including queer theory; critical race, intersectional and transnational feminisms; material-discursive feminism; and critical studies on men and masculinities. A more detailed discussion of the latter, as a relatively new, growing and politically contentious area, is further developed to highlight more specifically which feminist and gender theories are mainly in use in marketing and consumer research and which are little or not used. In the light of this, it is argued that marketing and related disciplines have thus far largely neglected several key contemporary gender and feminist theorisations, particularly those that centre on gender power relations. The potential impact of these theoretical frames on transdisciplinary studies in marketing and consumer research and research agenda(s) is discussed

Top-Down Control of Herbivory by Birds and Bats in the Canopy of Temperate Broad-Leaved Oaks (Quercus robur)

The intensive foraging of insectivorous birds and bats is well known to reduce the density of arboreal herbivorous arthropods but quantification of collateral leaf damage remains limited for temperate forest canopies

From spatial ecology to spatial epidemiology: Modeling spatial distributions of different cancer types with principal coordinates of neighbor matrices

Epidemiology and ecology share many fundamental research questions. Here we describe how principal coordinates of neighbor matrices (PCNM), a method from spatial ecology, can be applied to spatial epidemiology. PCNM is based on geographical distances among sites and can be applied to any set of sites providing a good coverage of a study area. In the present study, PCNM eigenvectors corresponding to positive autocorrelation were used as explanatory variables in linear regressions to model incidences of eight most common cancer types in Finnish municipalities (n = 320). The dataset was provided by the Finnish Cancer Registry and it included altogether 615,839 cases between 1953 and 2010. Results: PCNM resulted in 165 vectors with a positive eigenvalue. The first PCNM vector corresponded to the wavelength of hundreds of kilometers as it contrasted two main subareas so that municipalities located in southwestern Finland had the highest positive site scores and those located in midwestern Finland had the highest negative scores in that vector. Correspondingly, the 165thPCNM vector indicated variation mainly between the two small municipalities located in South Finland. The vectors explained 13 - 58% of the spatial variation in cancer incidences. The number of outliers having standardized residual > |3| was very low, one to six per model, and even lower, zero to two per model, according to Chauvenet's criterion. The spatial variation of prostate cancer was best captured (adjusted r 2= 0.579). Conclusions: PCNM can act as a complementary method to causal modeling to achieve a better understanding of the spatial structure of both the response and explanatory variables, and to assess the spatial importance of unmeasured explanatory factors. PCNM vectors can be used as proxies for demographics and causative agents to deal with autocorrelation, multicollinearity, and confounding variables. PCNM may help to extend spatial epidemiology to areas with limited availability of registers, improve cost-effectiveness, and aid in identifying unknown causative agents, and predict future trends in disease distributions and incidences. A large advantage of using PCNM is that it can create statistically valid reflectors of real predictors for disease incidence models with only little resources and background information