Proposal of a new classification for optimising outcome assessment following partial cricotracheal resections in severe pediatric subglottic stenosis.

OBJECTIVE: Creation of a patent subglottic airway after partial cricotracheal resection (PCTR) may not always result in successful decannulation due to associated parameters such as co-morbidity and/or glottic involvement. We classified patients after incorporating these additional parameters into the original Myer-Cotton classification to assess whether this could better predict the outcome measures after PCTR. METHODS: One hundred children with Myer-Cotton grade III or IV subglottic stenosis who underwent PCTR between 1978 and 2008 were identified from a prospectively collected database. The patients were classified into four groups based on the association of co-morbidity and/or glottic involvement. Delay in decannulation, revision open surgery and rates of decannulation were the outcome measures compared between the groups. RESULTS: There were 68 children with Myer-Cotton grade III and 32 children with grade IV stenosis. Based on the new classification, there were 36 children with isolated SGS, 31 with associated co-morbidity, 19 with associated glottic involvement and 14 children with both co-morbidity and glottic involvement. A trend towards less optimal results was noticed with the association of co-morbidity and/or glottic involvement. Statistical significance was reached for maximum decannulation failure in the group with both co-morbidity and glottic involvement. Delayed decannulation significantly correlated in the group with associated glottic involvement. CONCLUSION: This new classification is relatively simple and aimed at providing more accurate and uniform prognostic information to both patients and surgeons when dealing with the whole spectrum of severe SGS.

Briefing 29: NCMP data 2008/9, East of England: ONS SOA classification

One in a series of six data briefings based on regional-level analysis of data from the National Child Measurement Programme (NCMP) undertaken by the National Obesity Observatory (NOO). The briefings are intended to complement the headline results for the region published in January 2010, at Quick Link 20510.

Appropriateness of respiratory care: development of evidence-based guidelines in an acute care hospital

Background: Respiratory care is universally recognised as useful, but its indications and practice vary markedly. In order to improve appropriateness of respiratory care in our hospital, we developed evidence-based local guidelines in a collaborative effort involving physiotherapists, physicians, and health services researchers. Methods: Recommendations were developed using the standardised RAND appropriateness method. A literature search was performed for the period between 1995 and 2008 based on terms associated with guidelines and with respiratory care. Publications were assessed according to the Oxford classification of quality of evidence. A working group prepared proposals for recommendations which were then independently rated by a multidisciplinary expert panel. All recommendations were then discussed in common and indications for procedures were rated confidentially a second time by the experts. Each indication for respiratory care was classified as appropriate, uncertain, or inappropriate, based on the panel median rating and the degree of intra-panel agreement. Results: Recommendations were formulated for the following procedures: non-invasive ventilation, continuous positive airway pressure, intermittent positive pressure breathing, intrapulmonary percussive ventilation, mechanical insufflation-exsufflation, incentive spirometry, positive expiratory pressure, nasotracheal suctioning, noninstrumental airway clearance techniques. Each recommendation referred to a particular medical condition, and was assigned to a hierarchical category based on the quality of evidence from literature supporting the recommendation and on the consensus of experts. Conclusion: Despite a marked heterogeneity of scientific evidence, the method used allowed us to develop commonly agreed local guidelines for respiratory care. In addition, this work fostered a closer relationship between physiotherapists and physicians in our institution.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

A prediction rule to identify low-risk patients with pulmonary embolism.

BACKGROUND: A simple prognostic model could help identify patients with pulmonary embolism who are at low risk of death and are candidates for outpatient treatment. METHODS: We randomly allocated 15,531 retrospectively identified inpatients who had a discharge diagnosis of pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our rule to predict 30-day mortality using classification tree analysis and patient data routinely available at initial examination as potential predictor variables. We used data from a European prospective study to externally validate the rule among 221 inpatients with pulmonary embolism. We determined mortality and nonfatal adverse medical outcomes across derivation and validation samples. RESULTS: Our final model consisted of 10 patient factors (age > or = 70 years; history of cancer, heart failure, chronic lung disease, chronic renal disease, and cerebrovascular disease; and clinical variables of pulse rate > or = 110 beats/min, systolic blood pressure < 100 mm Hg, altered mental status, and arterial oxygen saturation < 90%). Patients with none of these factors were defined as low risk. The 30-day mortality rates for low-risk patients were 0.6%, 1.5%, and 0% in the derivation, internal validation, and external validation samples, respectively. The rates of nonfatal adverse medical outcomes were less than 1% among low-risk patients across all study samples. CONCLUSIONS: This simple prediction rule accurately identifies patients with pulmonary embolism who are at low risk of short-term mortality and other adverse medical outcomes. Prospective validation of this rule is important before its implementation as a decision aid for outpatient treatment.

Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

Determinants and burden of chronic kidney disease in the population-based CoLaus study: a cross-sectional analysis.

BACKGROUND: Chronic kidney disease (CKD) represents an increasing health burden. We present the population-based prevalence of CKD and compare the CKD Epidemiology collaboration (CKD-EPI) and modification of diet in renal disease (MDRD) equations to estimate the glomerular filtration rate, using the revised CKD classification with three albuminuria classes. We also explore factors associated with CKD. METHODS: The Swiss population-based, cross-sectional CoLaus study conducted in Lausanne (2003-2006) included 2810 men and 3111 women aged 35-75. CKD prevalence was assessed using CKD-EPI and MDRD equations and albuminuria estimated by the albumin-to-creatinine ratio in spot morning urine. Multivariate logistic regression was used to analyse determinants of CKD. RESULTS: Prevalence [95% confidence interval (CI)] of all stages CKD was 10.0% (9.2-10.8%) with CKD-EPI and 13.8% (12.9-14.6%) with MDRD. Using the revised CKD classification, the prevalence of low-, medium-, high- and very high-risk groups was 90.0, 8.46, 1.18 and 0.35% with CKD-EPI, respectively. With MDRD, the corresponding values were 86.24, 11.86, 1.55 and 0.35%. Using the revised classification, CKD-EPI systematically reclassified people in a lower risk category than MDRD. Age and obesity were more strongly associated with CKD in men [odds ratio (95% CI): 2.23(1.95; 2.56) per 10 years and 3.05(2.08;4.47), respectively] than in women [1.46 (1.29; 1.65) and 1.78 (1.30;2.44), respectively]. Hypertension, type 2 diabetes, serum homocysteine and uric acid were positively independently associated with CKD in men and women. CONCLUSIONS: One in 10 adults suffers from CKD in the population of Lausanne. CKD-EPI systematically reclassifies people in a lower CKD risk category than MDRD. Serum homocysteine and uric acid levels are associated with CKD independently of classical risk factors such as age, hypertension and diabetes.

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Breast cancer prognostic classification in the molecular era: the role of histological grade.

Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.

Risk of dengue occurrence based on the capture of gravid Aedes aegypti females using MosquiTRAP

We assessed the risk classification of dengue fever based on the capture of Aedes aegypti adults using MosquiTRAP, a type of sticky trap, in comparison with traditional larval infestation indices. A total of 27 MosquiTRAPs were installed, with one trap per block, and were inspected weekly between November 2008-February 2009. Infestation baseline data were obtained from a survey conducted prior to trap installation. The index generated by MosquiTRAP and house index (HI) classified the area "in alert situation". The set for risk of dengue occurrence proposed by the use of MosquiTRAP classify areas in the same way of the traditional HI.

Classification of immature mosquito species according to characteristics of the larval habitat in the subtropical province of Chaco, Argentina

To classify mosquito species based on common features of their habitats, samples were obtained fortnightly between June 2001-October 2003 in the subtropical province of Chaco, Argentina. Data on the type of larval habitat, nature of the habitat (artificial or natural), size, depth, location related to sunlight, distance to the neighbouring houses, type of substrate, organic material, vegetation and algae type and their presence were collected. Data on the permanence, temperature, pH, turbidity, colour, odour and movement of the larval habitat's water were also collected. From the cluster analysis, three groups of species associated by their degree of habitat similarity were obtained and are listed below. Group 1 consisted of Aedes aegypti. Group 2 consisted of Culex imitator, Culex davisi, Wyeomyia muehlensi and Toxorhynchites haemorrhoidalis separatus. Within group 3, two subgroups are distinguished: A (Psorophora ferox, Psorophora cyanescens, Psorophora varinervis, Psorophora confinnis, Psorophora cingulata, Ochlerotatus hastatus-oligopistus, Ochlerotatus serratus, Ochlerotatus scapularis, Culex intrincatus, Culex quinquefasciatus, Culex pilosus, Ochlerotatus albifasciatus, Culex bidens) and B (Culex maxi, Culex eduardoi, Culex chidesteri, Uranotaenia lowii, Uranotaenia pulcherrima, Anopheles neomaculipalpus, Anopheles triannulatus, Anopheles albitarsis, Uranotaenia apicalis, Mansonia humeralis and Aedeomyia squamipennis). Principal component analysis indicates that the size of the larval habitats and the presence of aquatic vegetation are the main characteristics that explain the variation among different species. In contrast, water permanence is second in importance. Water temperature, pH and the type of larval habitat are less important in explaining the clustering of species.

Conceptual framework and pilot study to benchmark phylogenomic databases based on reference gene trees.

Phylogenomic databases provide orthology predictions for species with fully sequenced genomes. Although the goal seems well-defined, the content of these databases differs greatly. Seven ortholog databases (Ensembl Compara, eggNOG, HOGENOM, InParanoid, OMA, OrthoDB, Panther) were compared on the basis of reference trees. For three well-conserved protein families, we observed a generally high specificity of orthology assignments for these databases. We show that differences in the completeness of predicted gene relationships and in the phylogenetic information are, for the great majority, not due to the methods used, but to differences in the underlying database concepts. According to our metrics, none of the databases provides a fully correct and comprehensive protein classification. Our results provide a framework for meaningful and systematic comparisons of phylogenomic databases. In the future, a sustainable set of 'Gold standard' phylogenetic trees could provide a robust method for phylogenomic databases to assess their current quality status, measure changes following new database releases and diagnose improvements subsequent to an upgrade of the analysis procedure.

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.

Fair bounds based solidarity

How should scholarships be distributed among the (public) higher education students? We raise this situation as a redistribution problem. Following the approach developed in Fleurbaey (1994) and Bossert (1995), redistribution should be based on the notion of solidarity and it re-allocates resources taking into account only agents’ relevant characteristics. We also follow Luttens (2010a), who considers that compensation of relevant characteristics must be based on a lower bound on what every individual deserves. In doing so, we use the so-called fair bound (Moulin (2002)) to define an egalitarian redistribution mechanism and characterize it in terms of non-negativity, priority in lower bound and solidarity. Finally, we apply our approach to the scholarships redistribution problem. Keywords: Redistribution mechanism, Lower bounds, Scholarship, Solidarity. JEL classification: C71, D63, D71