Prediction of the survival and functional ability of severe stroke patients after ICU therapeutic intervention

<p>Abstract</p> <p>Background</p> <p>This study evaluated the benefits and impact of ICU therapeutic interventions on the survival and functional ability of severe cerebrovascular accident (CVA) patients.</p> <p>Methods</p> <p>Sixty-two ICU patients suffering from severe ischemic/haemorrhagic stroke were evaluated for CVA severity using APACHE II and the Glasgow coma scale (GCS). Survival was determined using Kaplan-Meier survival tables and survival prediction factors were determined by Cox multivariate analysis. Functional ability was assessed using the stroke impact scale (SIS-16) and Karnofsky score. Risk factors, life support techniques and neurosurgical interventions were recorded. One year post-CVA dependency was investigated using multivariate analysis based on linear regression.</p> <p>Results</p> <p>The study cohort constituted 6% of all CVA (37.8% haemorrhagic/62.2% ischemic) admissions. Patient mean(SD) age was 65.8(12.3) years with a 1:1 male: female ratio. During the study period 16 patients had died within the ICU and seven in the year following hospital release.</p> <p>The mean(SD) APACHE II score at hospital admission was 14.9(6.0) and ICU mean duration of stay was 11.2(15.4) days. Mechanical ventilation was required in 37.1% of cases. Risk ratios were; GCS at admission 0.8(0.14), (p = 0.024), APACHE II 1.11(0.11), (p = 0.05) and duration of mechanical ventilation 1.07(0.07), (p = 0.046). Linear coefficients were: type of CVA – haemorrhagic versus ischemic: -18.95(4.58) (p = 0.007), GCS at hospital admission: -6.83(1.08), (p = 0.001), and duration of hospital stay -0.38(0.14), (p = 0.40).</p> <p>Conclusion</p> <p>To ensure a better prognosis CVA patients require ICU therapeutic interventions. However, as we have shown, where tests can determine the worst affected patients with a poor vital and functional outcome should treatment be withheld?</p

Factors that could explain the increasing prevalence of type 2 diabetes among adults in a Canadian province: a critical review and analysis

Abstract: Background: The prevalence of diabetes has increased since the last decade in New Brunswick. Identifying factors contributing to the increase in diabetes prevalence will help inform an action plan to manage the condition. The objective was to describe factors that could explain the increasing prevalence of type 2 diabetes in New Brunswick since 2001. Methods: A critical literature review was conducted to identify factors potentially responsible for an increase in prevalence of diabetes. Data from various sources were obtained to draw a repeated cross-sectional (2001–2014) description of these factors concurrently with changes in the prevalence of type 2 diabetes in New Brunswick. Linear regressions, Poisson regressions and Cochran Armitage analysis were used to describe relationships between these factors and time. Results: Factors identified in the review were summarized in five categories: individual-level risk factors, environmental risk factors, evolution of the disease, detection effect and global changes. The prevalence of type 2 diabetes has increased by 120% between 2001 and 2014. The prevalence of obesity, hypertension, prediabetes, alcohol consumption, immigration and urbanization increased during the study period and the consumption of fruits and vegetables decreased which could represent potential factors of the increasing prevalence of type 2 diabetes. Physical activity, smoking, socioeconomic status and education did not present trends that could explain the increasing prevalence of type 2 diabetes. During the study period, the mortality rate and the conversion rate from prediabetes to diabetes decreased and the incidence rate increased. Suggestion of a detection effect was also present as the number of people tested increased while the HbA1c and the age at detection decreased. Period and birth cohort effect were also noted through a rise in the prevalence of type 2 diabetes across all age groups, but greater increases were observed among the younger cohorts. Conclusions: This study presents a comprehensive overview of factors potentially responsible for population level changes in prevalence of type 2 diabetes. Recent increases in type 2 diabetes in New Brunswick may be attributable to a combination of some individual-level and environmental risk factors, the detection effect, the evolution of the disease and global changes

A Guide to Estimating the Reference Range From a Meta-Analysis Using Aggregate or Individual Participant Data.

Clinicians frequently must decide whether a patient's measurement reflects that of a healthy "normal" individual. Thus, the reference range is defined as the interval in which some proportion (frequently 95%) of measurements from a healthy population is expected to fall. One can estimate it from a single study or preferably from a meta-analysis of multiple studies to increase generalizability. This range differs from the confidence interval for the pooled mean and the prediction interval for a new study mean in a meta-analysis, which do not capture natural variation across healthy individuals. Methods for estimating the reference range from a meta-analysis of aggregate data that incorporates both within- and between-study variations were recently proposed. In this guide, we present 3 approaches for estimating the reference range: one frequentist, one Bayesian, and one empirical. Each method can be applied to either aggregate or individual-participant data meta-analysis, with the latter being the gold standard when available. We illustrate the application of these approaches to data from a previously published individual-participant data meta-analysis of studies measuring liver stiffness by transient elastography in healthy individuals between 2006 and 2016