Factors causing interrupted delivery of enteral nutrition in trauma intensive care unit patients.

BACKGROUND: The intent of this study was to ascertain the adequacy of delivery of enteral nutrition (EN) to critically ill adult multiple trauma patients and to identify potential detrimental factors that affect EN delivery. METHODS: Retrospective observational study. Trauma intensive care unit (TICU) in a university-affiliated hospital. Adult patients (>/=18 years of age) admitted to the TICU who received enteral feeding. RESULTS: Fifty-six adult patients were enrolled for study. Patients received, on average, 67% +/- 19% of what was prescribed for 5.7 +/- 2.0 days. A total of 222 occurrences for temporary discontinuation of tube feeding were identified. Gastrointestinal intolerance, as defined by a gastric residual volume of >150 mL, abdominal pain, or >3 liquid stools per day, accounted for only 11% of the occurrences for discontinuation of feeding. Surgery (27%) and diagnostic procedures (15%) represented the majority of reasons for inadequate nutrient delivery. Minor factors for EN interruptions were mechanical feeding tube problems (8%), pharmacy delivery delay (4%), and miscellaneous factors (3%). Multiple and unknown reasons contributed to 14% and 18% of the occurrences, respectively. CONCLUSIONS: Surgery and diagnostic procedures accounted for the largest factor in enteral feeding discontinuations in our critically ill trauma patients. Gastrointestinal intolerance contributed a minor role in the temporary discontinuation of enteral feeding.     

Independent component analysis and clustering improve signal-to-noise ratio for statistical analysis of event-related potentials

OBJECTIVE: To evaluate the effectiveness of a new method of using Independent Component Analysis (ICA) and k-means clustering to increase the signal-to-noise ratio of Event-Related Potential (ERP) measurements while permitting standard statistical comparisons to be made despite the inter-subject variations characteristic of ICA. METHODS: Per-subject ICA results were used to create a channel pool, with unequal weights, that could be applied consistently across subjects. Signals derived from this and other pooling schemes, and from unpooled electrodes, were subjected to identical statistical analysis of the N170 own-face effect in a Joe/No Joe face recognition paradigm wherein participants monitored for a target face (Joe) presented amongst other unfamiliar faces and their own face. Results between the Joe, unfamiliar face and own face conditions were compared using Cohen's d statistic (square root of signal-to-noise ratio) to measure effect size. RESULTS: When the own-face condition was compared to the Joe and unfamiliar-face conditions, the channel map method increased effect size by a factor ranging from 1.2 to 2.2. These results stand in contrast to previous findings, where conventional pooling schemes failed to reveal an N170 effect to the own-face stimulus (Tanaka JW, Curran T, Porterfield A, Collins D. The activation of pre-existing and acquired face representations: the N250 ERP as an index of face familiarity. J Cogn Neurosci 2006;18:1488-97). Consistent with conventional pooling schemes, the channel map approach showed no reliable differences between the Joe and Unfamiliar face conditions, yielding a decrease in effect size ranging from 0.13 to 0.75. CONCLUSIONS: By increasing the signal-to-noise ratio in the measured waveforms, the channel pool method demonstrated an enhanced sensitivity to the neurophysiological response to own-face relative to other faces. SIGNIFICANCE: By overcoming the characteristic inter-subject variations of ICA, this work allows classic ERP analysis methods to exploit the improved signal-to-noise ratio obtainable with ICA.     

Clinical importance,statistical significance and the assessment of economic and quality-of-life outcomes

The assessment of economic and quality-of-life outcomes of health care interventions is moving into a new era, with such assessments increasingly being made within the context of controlled clinical trials. Traditionally the measurement of many variables in economic evaluations, particularly costs, has been deterministic. In the context of clinical trials the measurement of variables is stochastic, with the standard principles of statistical inference being applied to analyse differences between treatments in terms of effectiveness. Economists participating in clinical research are therefore being called upon to specify the sample size for the economic component of the evaluation and to undertake statistical tests for differences in cost or cost-effectiveness. This paper discusses the current methodological issues surrounding stochastic measurement in clinical trials, discusses the additional issues raised by the assessment of economic and quality-of-life outcomes and specifies the challenges facing economists if they are to answer the questions now being posed about economic analysis by statisticians and clinical researchers. It is concluded that application of the standard principles of statistical inference to economic data is not straightforward and will require value judgements to be made about statistical significance and economic importance, which may differ from those already made in purely clinical studies.     

An Automated Self‐Similarity Analysis of the Pulmonary Tree of the Sprague–Dawley Rat

We present the results of an automated analysis of the morphometry of the pulmonary airway trees of the Sprague–Dawley rat. Our work is motivated by a need to inform lower‐dimensional mathematical models to prescribe realistic boundary conditions for multiscale hybrid models of rat lung mechanics. Silicone casts were made from three age‐matched, male Sprague–Dawley rats, immersed in a gel containing a contrast agent and subsequently imaged with magnetic resonance (MR). From a segmentation of this data, we extracted a connected graph, representing the airway centerline. Segment statistics (lengths and diameters) were derived from this graph. To validate this MR imaging/digital analysis method, airway segment measurements were compared with nearly 1,000 measurements collected by hand using an optical microscope from one of the rat lung casts. To evaluate the reproducibility of the MR imaging/digital analysis method, two lung casts were each imaged three times with randomized orientations in the MR bore. Diameters and lengths of randomly selected airways were compared among each of the repeated imaging datasets to estimate the variability. Finally, we analyzed the morphometry of the airway tree by assembling individual airway segments into structures that span multiple generations, which we call branches. We show that branches not segments are the fundamental repeating unit in the rat lung and develop simple mathematical relationships describing these structures for the entire lung. Our analysis shows that airway diameters and lengths have both a deterministic and stochastic character. Anat Rec, 2008. © 2008 Wiley‐Liss, Inc.     

Linkage analysis of anorexia and bulimia nervosa cohorts using selected behavioral phenotypes as quantitative traits or covariates.

To increase the likelihood of finding genetic variation conferring liability to eating disorders, we measured over 100 attributes thought to be related to liability to eating disorders on affected individuals from multiplex families and two cohorts: one recruited through a proband with anorexia nervosa (AN; AN cohort); the other recruited through a proband with bulimia nervosa (BN; BN cohort). By a multilayer decision process based on expert evaluation and statistical analysis, six traits were selected for linkage analysis (1): obsessionality (OBS), age at menarche (MENAR), and anxiety (ANX) for quantitative trait locus (QTL) linkage analysis; and lifetime minimum body mass index (BMI), concern over mistakes (CM), and food-related obsessions (OBF) for covariate-based linkage analysis. The BN cohort produced the largest linkage signals: for QTL linkage analysis, four suggestive signals: (for MENAR, at 10p13; for ANX, at 1q31.1, 4q35.2, and 8q13.1); for covariate-based linkage analyses, both significant and suggestive linkages (for BMI, one significant [4q21.1] and three suggestive [3p23, 10p13, 5p15.3]; for CM, two significant [16p13.3, 14q21.1] and three suggestive [4p15.33, 8q11.23, 10p11.21]; and for OBF, one significant [14q21.1] and five suggestive [4p16.1, 10p13.1, 8q11.23, 16p13.3, 18p11.31]). Results from the AN cohort were far less compelling: for QTL linkage analysis, two suggestive signals (for OBS at 6q21 and for ANX at 9p21.3); for covariate-based linkage analysis, five suggestive signals (for BMI at 4q13.1, for CM at 11p11.2 and 17q25.1, and for OBF at 17q25.1 and 15q26.2). Overlap between the two cohorts was minimal for substantial linkage signals.