Intracranial pressure monitoring associated with increased mortality in pediatric brain injuries.

BackgroundUtilization of ICP monitors for pediatric patients is low and varies between centers. We hypothesized that in more severely injured patients (GCS 3-4), there would be a decreased mortality associated with invasive monitoring devices.MethodsThe pediatric Trauma Quality Improvement Program (TQIP) was queried for patients aged ≤ 16 years meeting criteria for invasive monitors. Our primary outcome was mortality. Patients with ICP monitoring were compared to those without. A logistic regression was used to examine the risk of mortality.ResultsOf 3,808 patients, 685 (18.0%) underwent ICP monitoring. ICP monitors were associated with increased risk of mortality (OR 1.82, CI 1.36-2.44, p < 0.001). A secondary analysis including type of invasive ICP monitor and dividing GCS into 3 categories revealed both intraventricular drain (OR 1.89, CI 1.3-2.7, p = 0.001) and intraparenchymal pressure monitor (OR 1.86, CI 1.32-2.6, p < 0.001) to be independently associated with an increased likelihood of mortality regardless of GCS, while intraparenchymal oxygen monitoring was not (OR 0.47, CI 0.11-2.05, p = 0.316). The strongest effect was seen in those patients with a GCS of 5-6.ConclusionICP monitors are an independent risk factor for mortality, particularly with intraventricular drains and intraparenchymal monitors in patients with a GCS 5-6

Summary statistics (mean ±SD) for diagnostic measures by score-defined clusters.

<p>Summary statistics (mean ±SD) for diagnostic measures by score-defined clusters.</p

Intracranial pressure monitoring associated with increased mortality in pediatric brain injuries.

BackgroundUtilization of ICP monitors for pediatric patients is low and varies between centers. We hypothesized that in more severely injured patients (GCS 3-4), there would be a decreased mortality associated with invasive monitoring devices.MethodsThe pediatric Trauma Quality Improvement Program (TQIP) was queried for patients aged ≤ 16&nbsp;years meeting criteria for invasive monitors. Our primary outcome was mortality. Patients with ICP monitoring were compared to those without. A logistic regression was used to examine the risk of mortality.ResultsOf 3,808 patients, 685 (18.0%) underwent ICP monitoring. ICP monitors were associated with increased risk of mortality (OR 1.82, CI 1.36-2.44, p &lt; 0.001). A secondary analysis including type of invasive ICP monitor and dividing GCS into 3 categories revealed both intraventricular drain (OR 1.89, CI 1.3-2.7, p = 0.001) and intraparenchymal pressure monitor (OR 1.86, CI 1.32-2.6, p &lt; 0.001) to be independently associated with an increased likelihood of mortality regardless of GCS, while intraparenchymal oxygen monitoring was not (OR 0.47, CI 0.11-2.05, p = 0.316). The strongest effect was seen in those patients with a GCS of 5-6.ConclusionICP monitors are an independent risk factor for mortality, particularly with intraventricular drains and intraparenchymal monitors in patients with a GCS 5-6

Use of principle component analysis to quantitatively score the equine metabolic syndrome phenotype in an Arabian horse population

<div><p>Equine metabolic syndrome (EMS), like human metabolic syndrome, comprises a collection of clinical signs related to obesity, insulin dysregulation and susceptibility to secondary inflammatory disease. Although the secondary conditions resulting from EMS can be life-threatening, diagnosis is not straightforward and often complicated by the presence of other concurrent conditions like pituitary pars intermedia dysfunction (PPID). In order to better characterize EMS, we sought to describe the variation within, and correlations between, typical physical and endocrine parameters for EMS. Utilizing an unsupervised statistical approach, we evaluated a population of Arabian horses using a physical examination including body measurements, as well as blood plasma insulin, leptin, ACTH, glucose, and lipid values. We investigated the relationships among these variables using principle component analysis (PCA), hierarchical clustering, and linear regression. Owner-assigned assessments of body condition were one full score (on a nine-point scale) lower than scores assigned by researchers, indicating differing perception of healthy equine body weight. Rotated PCA defined two factor scores explaining a total of 46.3% of variation within the dataset. Hierarchical clustering using these two factors revealed three groups corresponding well to traditional diagnostic categories of “Healthy”, “PPID-suspect”, and “EMS-suspect” based on the characteristics of each group. Proxies estimating up to 93.4% of the composite “EMS-suspect” and “PPID-suspect” scores were created using a reduced set of commonly used diagnostic variables, to facilitate application of these quantitative scores to horses of the Arabian breed in the field. Use of breed-specific, comprehensive physical and endocrinological variables combined in a single quantitative score may improve detection of horses at-risk for developing EMS, particularly in those lacking severe clinical signs. Quantification of EMS without the use of predetermined reference ranges provides an advantageous approach for future studies utilizing genomic or metabolomics approaches to improve understanding of the etiology behind this troubling condition.</p></div

Principle component analysis for EMS phenotype.

<p>(A) Vector loading plot of Factor 1 vs Factor 2, Factor 1 characterizes the EMS-suspect phenotype and Factor 2 the PPID-suspect phenotype. (B) Eigenvectors for each factor plotted against the original nine diagnostic variables. Factor 1 positively correlates with Triglycerides, leptin, MIRG, BCS, NC/H, and HG/H while Factor 2 correlates with age, ACTH, cholesterol and NC/H. (C) Factor 1 and Factor 2 scores plotted for each horse and colored according to hierarchical cluster: healthy (red), PPID-suspect (blue), and EMS-suspect (green).</p

Owner versus researcher reported BCS compared to the heart girth/height ratio.

<p>Owner reported body condition scores (BCS, triangles) underestimated obesity in their horse when compared to the researcher observed values (circles), potentially contributing to overfeeding. Both BCS observations correlated well with a ratio of heart girth circumference to height, suggesting the objective measurement method was an adequate proxy for adiposity/BCS.</p

Clusters based on PCA factors.

<p>Hierarchical clustering of horses into three diagnostic categories, Healthy (red), EMS-suspect (green), and PPID-suspect (blue), using Factor 1 and Factor 2. Below clusters, four of the nine variables from the PCA across disease clusters displaying quartiles (top and bottom of red box) and median (middle line across box) using whisker-bow plots. All p-values calculated by ANOVA tests. The PPID-suspect cluster had the highest Age (p < 0.0001) and ACTH (p = 0.0003). The EMS-suspect cluster had the highest AVG BCS (p < 0.0001) and MIRG values (p = 0.0002).</p

Correlations of obesity measures to various insulin and glucose ratios (R², P-values by ANOVA).

<p>Correlations of obesity measures to various insulin and glucose ratios (R², P-values by ANOVA).</p