Anthropometric measures as a predictor of cephalopelvic disproportion

This study compared three body measurements, height, hip width (bitrochanteric) and foot length, in 120 Hispanic women who had their first birth by cesarean section (N = 60) or by spontaneous vaginal delivery (N = 60). The objective of the study was to see if there were differences in these measurements that could be useful in predicting cephalopelvic disproportion. Data were collected from two public hospitals in Houston Texas over a 10 month period from December 1994 to October 1995. The statistical technique used to evaluate the measures was discriminant analysis.^ Women who delivered by cesarean section were older, shorter, had shorter feet and delivered heavier infants. There were no differences in the bitrochanteric widths of the women or in the mean gestational age or Apgar scores of the infants.^ Significantly more of the mothers and infants were ill following cesarean section delivery. Maternal illness was usually infection; infant illness was primarily infection or respiratory difficulties.^ Discriminant analysis is a technique which allows for classification and prediction to which group a particular entity will belong given a certain set of variables. Using discriminant analysis, with a probability of cesarean section 50 percent, the best combination to classify who would have a cesarean section was height and hip width, correctly classifying 74.2 percent of those who needed surgery. When the probability of cesarean section was 10 percent and probability of vaginal delivery was 90 percent, the best predictor of who would need operative delivery was height, hip width and age, correctly classifying 56.2 percent. In the population from which the study participants were selected the incidence of cephalopelvic disproportion was low, approximately 1 percent.^ With the technologic assistance available in most of the developed world, it is likely that the further pursuit of different measures and their use would not be of much benefit in attempting to predict and diagnose disproportion. However, in areas of the world where much of obstetrics is "hands on", the availability of technology extremely limited, and the incidence of disproportion larger, the use of anthropometric measures might be useful and of some potential benefit. ^

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study

BACKGROUND Prediction studies in subjects at Clinical High Risk (CHR) for psychosis are hampered by a high proportion of uncertain outcomes. We therefore investigated whether quantitative EEG (QEEG) parameters can contribute to an improved identification of CHR subjects with a later conversion to psychosis. METHODS This investigation was a project within the European Prediction of Psychosis Study (EPOS), a prospective multicenter, naturalistic field study with an 18-month follow-up period. QEEG spectral power and alpha peak frequencies (APF) were determined in 113 CHR subjects. The primary outcome measure was conversion to psychosis. RESULTS Cox regression yielded a model including frontal theta (HR=1.82; [95% CI 1.00-3.32]) and delta (HR=2.60; [95% CI 1.30-5.20]) power, and occipital-parietal APF (HR=.52; [95% CI .35-.80]) as predictors of conversion to psychosis. The resulting equation enabled the development of a prognostic index with three risk classes (hazard rate 0.057 to 0.81). CONCLUSIONS Power in theta and delta ranges and APF contribute to the short-term prediction of psychosis and enable a further stratification of risk in CHR samples. Combined with (other) clinical ratings, EEG parameters may therefore be a useful tool for individualized risk estimation and, consequently, targeted prevention.

Clinical relevance of brain volume measures in multiple sclerosis.

Multiple sclerosis (MS) is a chronic disease with an inflammatory and neurodegenerative pathology. Axonal loss and neurodegeneration occurs early in the disease course and may lead to irreversible neurological impairment. Changes in brain volume, observed from the earliest stage of MS and proceeding throughout the disease course, may be an accurate measure of neurodegeneration and tissue damage. There are a number of magnetic resonance imaging-based methods for determining global or regional brain volume, including cross-sectional (e.g. brain parenchymal fraction) and longitudinal techniques (e.g. SIENA [Structural Image Evaluation using Normalization of Atrophy]). Although these methods are sensitive and reproducible, caution must be exercised when interpreting brain volume data, as numerous factors (e.g. pseudoatrophy) may have a confounding effect on measurements, especially in a disease with complex pathological substrates such as MS. Brain volume loss has been correlated with disability progression and cognitive impairment in MS, with the loss of grey matter volume more closely correlated with clinical measures than loss of white matter volume. Preventing brain volume loss may therefore have important clinical implications affecting treatment decisions, with several clinical trials now demonstrating an effect of disease-modifying treatments (DMTs) on reducing brain volume loss. In clinical practice, it may therefore be important to consider the potential impact of a therapy on reducing the rate of brain volume loss. This article reviews the measurement of brain volume in clinical trials and practice, the effect of DMTs on brain volume change across trials and the clinical relevance of brain volume loss in MS.

Optimal Workflow and Process-Based Performance Measures for Endovascular Therapy in Acute Ischemic Stroke: Analysis of the Solitaire FR Thrombectomy for Acute Revascularization Study.

BACKGROUND AND PURPOSE We report on workflow and process-based performance measures and their effect on clinical outcome in Solitaire FR Thrombectomy for Acute Revascularization (STAR), a multicenter, prospective, single-arm study of Solitaire FR thrombectomy in large vessel anterior circulation stroke patients. METHODS Two hundred two patients were enrolled across 14 centers in Europe, Canada, and Australia. The following time intervals were measured: stroke onset to hospital arrival, hospital arrival to baseline imaging, baseline imaging to groin puncture, groin puncture to first stent deployment, and first stent deployment to reperfusion. Effects of time of day, general anesthesia use, and multimodal imaging on workflow were evaluated. Patient characteristics and workflow processes associated with prolonged interval times and good clinical outcome (90-day modified Rankin score, 0-2) were analyzed. RESULTS Median times were onset of stroke to hospital arrival, 123 minutes (interquartile range, 163 minutes); hospital arrival to thrombolysis in cerebral infarction (TICI) 2b/3 or final digital subtraction angiography, 133 minutes (interquartile range, 99 minutes); and baseline imaging to groin puncture, 86 minutes (interquartile range, 24 minutes). Time from baseline imaging to puncture was prolonged in patients receiving intravenous tissue-type plasminogen activator (32-minute mean delay) and when magnetic resonance-based imaging at baseline was used (18-minute mean delay). Extracranial carotid disease delayed puncture to first stent deployment time on average by 25 minutes. For each 1-hour increase in stroke onset to final digital subtraction angiography (or TICI 2b/3) time, odds of good clinical outcome decreased by 38%. CONCLUSIONS Interval times in the STAR study reflect current intra-arterial therapy for patients with acute ischemic stroke. Improving workflow metrics can further improve clinical outcome. CLINICAL TRIAL REGISTRATION: URL http://www.clinicaltrials.gov. Unique identifier: NCT01327989.

Seasonal Variation in the Capacity for Plant Trait Measures to Predict Grassland Carbon and Water Fluxes

There is a need for accurate predictions of ecosystem carbon (C) and water fluxes in field conditions. Previous research has shown that ecosystem properties can be predicted from community abundance-weighted means (CWM) of plant functional traits and measures of trait variability within a community (FDvar). The capacity for traits to predict carbon (C) and water fluxes, and the seasonal dependency of these trait-function relationships has not been fully explored. Here we measured daytime C and water fluxes over four seasons in grasslands of a range of successional ages in southern England. In a model selection procedure, we related these fluxes to environmental covariates and plant biomass measures before adding CWM and FDvar plant trait measures that were scaled up from measures of individual plants grown in greenhouse conditions. Models describing fluxes in periods of low biological activity contained few predictors, which were usually abiotic factors. In more biologically active periods, models contained more predictors, including plant trait measures. Field-based plant biomass measures were generally better predictors of fluxes than CWM and FDvar traits. However, when these measures were used in combination traits accounted for additional variation. Where traits were significant predictors their identity often reflected seasonal vegetation dynamics. These results suggest that database derived trait measures can improve the prediction of ecosystem C and water fluxes. Controlled studies and those involving more detailed flux measurements are required to validate and explore these findings, a worthwhile effort given the potential for using simple vegetation measures to help predict landscape-scale fluxes.

Combined effect of soil bund with biological soil and water conservation measures in the northwestern Ethiopian highlands

Excessive runoff and soil erosion in the upper Blue Nile Basin poses a threat that has attracted the attention of the Ethiopian government because of the serious on-site effects in addition to downstream effects, such as the siltation of water harvesting structures and reservoirs. The objective of the study was to evaluate and recommend effective biophysical soil and water conservation measure(s) in the Debre Mewi watershed, about 30 km south of the Lake Tana. Six conservation measures were evaluated for their effects on runoff, soil loss, and forage yield using runoff plots. There was a significant difference between treatments for both runoff and soil loss. The four-year average annual soil loss in the different plots ranged from 26 to 71 t ha−1, and total runoff ranged from 180 to 302 mm, while annual rainfall varied between 854 mm in 2008 and 1247 mm in 2011. Soil bund combined with elephant grass had the lowest runoff and soil loss as compared to the other treatments, whereas the untreated control plot had the highest for both parameters. As an additional benefit, 2.8 and 0.7 t ha−1 year−1 of dried forage was obtained from elephant and local grasses, respectively. Furthermore, it was found that soil bund combined with Tephrosia increased soil organic matter by 13% compared to the control plot. Soil bund efficiency was significantly enhanced by combining them with biological measures and improved farmers’ perception of soil and water conservation measures.

Subgingival microbiota of Sri Lankan tea labourers naïve to oral hygiene measures.

AIM To characterize the subgingival microbiota within a cohort of adult males (n = 32) naïve to oral hygiene practices, and to compare the composition of bacterial taxa present in periodontal sites with various probing depths. MATERIAL AND METHODS Subgingival plaque samples were collected from single shallow pocket [pocket probing depth (PPD)≤3 mm] and deep pocket (PPD≥6 mm) sites from each subject. A polymerase chain reaction based strategy was used to construct a clone library of 16S ribosomal RNA (rRNA) genes for each site. The sequences of ca. 30-60 plasmid clones were determined for each site to identify resident taxa. Microbial composition was compared using a variety of statistical and bioinformatics approaches. RESULTS A total of 1887 cloned 16S rRNA gene sequences were analysed, which were assigned to 318 operational taxonomic units (98% identity cut-off). The subgingival microbiota was dominated by Firmicutes (69.8%), Proteobacteria (16.3%), and Fusobacteria (8.0%). The overall composition of microbial communities in shallow sites was significantly different from those within deep sites (∫-Libshuff, p < 0.001). CONCLUSIONS A taxonomically diverse subgingival microbiota was present within this cohort; however, the structures of the microbial communities present in the respective subjects exhibited limited variation. Deep and shallow sites contained notably different microbial compositions, but this was not correlated with the rate of periodontal progression.

The effects of anti-infective preventive measures on the occurrence of biologic implant complications and implant loss: a systematic review.

PURPOSE To systematically appraise whether anti-infective protocols are effective in preventing biologic implant complications and implant loss after a mean observation period ≥ 10 years after loading. MATERIALS AND METHODS An electronic search of Medline via PubMed and Embase via Ovid databases complemented by manual search was conducted up to October 31, 2012. Studies were included provided that they were published in English, German, French, or Italian, and conducted on ≥ 20 partially and fully edentulous patients with dental implants and regular (≥ 1×/year) supportive periodontal therapy (SPT) over a mean observation period ≥ 10 years. Assessment of the identified studies and data extraction were performed independently by two reviewers. Authors were contacted if required. Collected data were reported by descriptive methods. RESULTS The initial electronic search resulted in the identification of 994 titles from Medline via PubMed and 531 titles from Embase via Ovid databases, respectively. After elimination of duplicate titles and exclusion of 60 full-text articles, 143 articles were analyzed, resulting in 15 studies eligible for qualitative analysis. The implant survival rate ranged from 85.7% to 99.2% after a mean observation period ≥ 10 years. One comparative study assessed the effects of regular SPT on the occurrence of biologic complications and implant loss. Overall, regular diagnosis and implementation of anti-infective therapeutic protocols were effective in the management of biological complications and prevention of implant loss. Residual probing depths at the end of active periodontal therapy and development of reinfection during supportive periodontal therapy (SPT) represented a significant risk for the onset of peri-implantitis and implant loss. Comparative studies indicated that implant survival and success rates were lower in periodontally compromised vs noncompromised patients. CONCLUSIONS In order to achieve high long-term survival and success rates of dental implants and their restorations, enrollment in regular SPT including anti-infective preventive measures should be implemented. Therapy of peri-implant mucositis should be considered as a preventive measure for the onset of peri-implantitis. Completion of active periodontal therapy should precede implant placement in periodontally compromised patients.

Risk assessment and causal preventive measures.

A prerequisite for preventive measures is to diagnose erosive tooth wear and to evaluate the different etiological factors in order to identify persons at risk. No diagnostic device is available for the assessment of erosive defects. Thus, they can only be detected clinically. Consequently, erosion not diagnosed at an early stage may render timely preventive measures difficult. In order to assess the risk factors, patients should record their dietary intake for a distinct period of time. Then a dentist can determine the erosive potential of the diet. A table with common beverages and foodstuffs is presented for judging the erosive potential. Particularly, patients with more than 4 dietary acid intakes have a higher risk for erosion when other risk factors are present. Regurgitation of gastric acids is a further important risk factor for the development of erosion which has to be taken into account. Based on these analyses, an individually tailored preventive program may be suggested to the patients. It may comprise dietary advice, use of calcium-enriched beverages, optimization of prophylactic regimes, stimulation of salivary flow rate, use of buffering medicaments and particular motivation for nondestructive toothbrushing habits with an erosive-protecting toothpaste as well as rinsing solutions. Since erosion and abrasion often occur simultaneously, all of the causative components must be taken into consideration when planning preventive strategies but only those important and feasible for an individual should be communicated to the patient.