A novel tool for the assessment of pain: validation in low back pain.

BACKGROUND: Adequate pain assessment is critical for evaluating the efficacy of analgesic treatment in clinical practice and during the development of new therapies. Yet the currently used scores of global pain intensity fail to reflect the diversity of pain manifestations and the complexity of underlying biological mechanisms. We have developed a tool for a standardized assessment of pain-related symptoms and signs that differentiates pain phenotypes independent of etiology. METHODS AND FINDINGS: Using a structured interview (16 questions) and a standardized bedside examination (23 tests), we prospectively assessed symptoms and signs in 130 patients with peripheral neuropathic pain caused by diabetic polyneuropathy, postherpetic neuralgia, or radicular low back pain (LBP), and in 57 patients with non-neuropathic (axial) LBP. A hierarchical cluster analysis revealed distinct association patterns of symptoms and signs (pain subtypes) that characterized six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain. Using a classification tree analysis, we identified the most discriminatory assessment items for the identification of pain subtypes. We combined these six interview questions and ten physical tests in a pain assessment tool that we named Standardized Evaluation of Pain (StEP). We validated StEP for the distinction between radicular and axial LBP in an independent group of 137 patients. StEP identified patients with radicular pain with high sensitivity (92%; 95% confidence interval [CI] 83%-97%) and specificity (97%; 95% CI 89%-100%). The diagnostic accuracy of StEP exceeded that of a dedicated screening tool for neuropathic pain and spinal magnetic resonance imaging. In addition, we were able to reproduce subtypes of radicular and axial LBP, underscoring the utility of StEP for discerning distinct constellations of symptoms and signs. CONCLUSIONS: We present a novel method of identifying pain subtypes that we believe reflect underlying pain mechanisms. We demonstrate that this new approach to pain assessment helps separate radicular from axial back pain. Beyond diagnostic utility, a standardized differentiation of pain subtypes that is independent of disease etiology may offer a unique opportunity to improve targeted analgesic treatment.

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.

Age above 60 years is not a negative predictive factor for combined antiviral therapy with pegylated interferon alpha and ribavirin in hepatitis C patients

Background: Age is frequently discussed as negative host factor to achieve a sustained virological response (SVR) to antiviral hepatitis C therapy. However, elderly patients often show relevant fibrosis or cirrhosis which is a known negative predictive factor, making it difficult to interpret age as an independent predictive factor. Methods: From the framework of the Swiss hepatitis C cohort (SCCS), we collected data from 545 antiviral hepatitis C therapies, including data from 67 hepatitis C patients ≥ 60 y who had been treated with PEG-interferon and ribavirin. We analyzed host factors (age, gender, fibrosis, haemoglobin, depression, earlier hepatitis C treatment), viral factors (genotype, viral load) and treatment course (early virological response, end of treatment response, SVR). Generalised estimating equations (GEE) regression modelling was used for the primary end point (SVR), with age ≥ 60 y and < 60 y as independent variable and gender, presence of cirrhosis, genotype, earlier treatment and viral load as confounders. SVR was analysed in young and elderly patients after matching for these confounders. Additionally, classification tree analysis was done in elderly patients using these confounders. Results: SVR analyzed in 545 patients was 55%. In genotype 1/4, SVR was 42.9% in 259 patients < 60 y and 26.1% in 46 patients ≥ 60 y. In genotype 2/3, SVR was 74.4% in 215 patients < 60 y and 84% in 25 patients ≥ 60 y. However, GEE model showed that age had no influence on achieving SVR (Odds ratio 0.91). Confounders influenced SVR as known from previous studies (cirrhosis, genotype 1/4, previous treatment and viral load >600'000 IE/ml as negative predictive factors). When young and elderly patients were matched (analysis in 59 elderly patients), SVR was not different in these patient groups (54.2% and 55.9%, resp.; p=0.795 in binomial test). The classification tree-derived best criterion for SVR in elderly patients was genotype, with no further criteria relevant for predicting SVR in genotype 2/3. In patients with genotype 1/4, further criteria were presence of cirrhosis and low viral load <600'000 IE/ml in non-cirrhotic patients. Conclusions: Age is not a relevant predictive factor for achieving SVR, when confounders were taken into account. In terms of effectiveness of antiviral therapy, age does not play a major role and should not be regarded as relevant negative predictive factor. Since life expectancy in Switzerland at age 60 is more than 22 y, hepatitis C therapy is reasonable in elderly patients with known relevant fibrosis or cirrhosis, because interferon-based hepatitis C therapy improves survival and reduces carcinogenesis.

The relation of body mass index and abdominal adiposity with dyslipidemia in 27 general populations of the WHO MONICA Project.

The association between adiposity measures and dyslipidemia has seldom been assessed in a multipopulational setting. 27 populations from Europe, Australia, New Zealand and Canada (WHO MONICA project) using health surveys conducted between 1990 and 1997 in adults aged 35-64 years (n = 40,480). Dyslipidemia was defined as the total/HDL cholesterol ratio >6 (men) and >5 (women). Overall prevalence of dyslipidemia was 25% in men and 23% in women. Logistic regression showed that dyslipidemia was strongly associated with body mass index (BMI) in men and with waist circumference (WC) in women, after adjusting for region, age and smoking. Among normal-weight men and women (BMI<25 kg/m(2)), an increase in the odds for being dyslipidemic was observed between lowest and highest WC quartiles (OR = 3.6, p < 0.001). Among obese men (BMI ≥ 30), the corresponding increase was smaller (OR = 1.2, p = 0.036). A similar weakening was observed among women. Classification tree analysis was performed to assign subjects into classes of risk for dyslipidemia. BMI thresholds (25.4 and 29.2 kg/m(2)) in men and WC thresholds (81.7 and 92.6 cm) in women came out at first stages. High WC (>84.8 cm) in normal-weight men, menopause in women and regular smoking further defined subgroups at increased risk. standard categories of BMI and WC, or their combinations, do not lead to optimal risk stratification for dyslipidemia in middle-age adults. Sex-specific adaptations are necessary, in particular by taking into account abdominal obesity in normal-weight men, post-menopausal age in women and regular smoking in both sexes.

Elderly age is not a negative predictive factor for virological response to therapy with pegylated interferon-α and ribavirin in chronic hepatitis C virus patients.

BACKGROUND & AIMS: Age is frequently discussed as negative host factor to achieve a sustained virological response (SVR) to antiviral therapy of chronic hepatitis C. However, elderly patients often show advanced fibrosis/cirrhosis as known negative predictive factor. The aim of this study was to assess age as an independent predictive factor during antiviral therapy. METHODS: Overall, 516 hepatitis C patients were treated with pegylated interferon-α and ribavirin, thereof 66 patients ≥60 years. We analysed the impact of host factors (age, gender, fibrosis, haemoglobin, previous hepatitis C treatment) and viral factors (genotype, viral load) on SVR per therapy course by performing a generalized estimating equations (GEE) regression modelling, a matched pair analysis and a classification tree analysis. RESULTS: Overall, SVR per therapy course was 42.9 and 26.1%, respectively, in young and elderly patients with hepatitis C virus (HCV) genotypes 1/4/6. The corresponding figures for HCV genotypes 2/3 were 74.4 and 84%. In the GEE model, age had no significant influence on achieving SVR. In matched pair analysis, SVR was not different in young and elderly patients (54.2 and 55.9% respectively; P = 0.795 in binominal test). In classification tree analysis, age was not a relevant splitting variable. CONCLUSIONS: Age is not a significant predictive factor for achieving SVR, when relevant confounders are taken into account. As life expectancy in Western Europe at age 60 is more than 20 years, it is reasonable to treat chronic hepatitis C in selected elderly patients with relevant fibrosis or cirrhosis but without major concomitant diseases, as SVR improves survival and reduces carcinogenesis.

Evaluating spine micro-architectural texture (via TBS) discriminates major osteoporotic fractures from controls both as well as and independent of site matched BMD: the Eastern European TBS study.

The aim of the study was to assess the clinical performance of the model combining areal bone mineral density (aBMD) at spine and microarchitecural texture (TBS) for the detection of the osteoporotic fracture. The Eastern European Study is a multicenter study (Serbia, Bulgaria, Romania and Ukraine) evaluating the role of TBS in routine clinical practice as a complement to aBMD. All scans were acquired on Hologic Discovery and GE Prodigy densitometers in a routine clinical manner. The additional clinical values of aBMD and TBS were analyzed using a two steps classification tree approach (aBMD followed by TBS tertiles) for all type of osteoporotic fracture (All-OP Fx). Sensitivity, specificity and accuracy of fracture detection as well as the Net Reclassification Index (NRI) were calculated. This study involves 1031 women subjects aged 45 and older recruited in east European countries. Clinical centers were cross-calibrated in terms of BMD and TBS. As expected, areal BMD (aBMD) at spine and TBS were only moderately correlated (r (2) = 0.19). Prevalence rate for All-OP Fx was 26 %. Subjects with fracture have significant lower TBS and aBMD than subjects without fracture (p < 0.01). TBS remains associated with the fracture even after adjustment for age and aBMD with an OR of 1.27 [1.07-1.51]. When using aBMD T-score of -2.5 and the lowest TBS tertile thresholds, both BMD and TBS were similar in terms of sensitivity (35 vs. 39 %), specificity (78 vs. 80 %) and accuracy (64 vs. 66 %). aBMD and TBS combination, induced a significant improvement in sensitivity (+28 %) and accuracy (+17 %) compared to aBMD alone whereas a moderate improvement was observed in terms of specificity (+9 %). The overall combination gain was 36 % as expressed using the NRI. aBMD and TBS combination decrease significantly the number of subjects needed to diagnose from 7 for aBMD alone to 2. In a multi-centre Eastern European cohort, we have shown that the use of TBS in addition to the aBMD permit to reclassified correctly more than one-third of the overall subjects. Furthermore, the number of subjects needed to diagnose fell to 2 subjects. Economical studies have to be performed to evaluate the gain induced by the use of TBS for the healthcare system.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

First insights into the transcriptome and development of new genomic tools of a widespread circum-Mediterranean tree species, Pinus halepensis Mill.

Aleppo pine (Pinus halepensis Mill.) is a relevant conifer species for studying adaptive responses to drought and fire regimes in the Mediterranean region. In this study, we performed Illumina next-generation sequencing of two phenotypically divergent Aleppo pine accessions with the aims of (i) characterizing the transcriptome through Illumina RNA-Seq on trees phenotypically divergent for adaptive traits linked to fire adaptation and drought, (ii) performing a functional annotation of the assembled transcriptome, (iii) identifying genes with accelerated evolutionary rates, (iv) studying the expression levels of the annotated genes and (v) developing gene-based markers for population genomic and association genetic studies. The assembled transcriptome consisted of 48,629 contigs and covered about 54.6 Mbp. The comparison of Aleppo pine transcripts to Picea sitchensis protein-coding sequences resulted in the detection of 34,014 SNPs across species, with a Ka /Ks average value of 0.216, suggesting that the majority of the assembled genes are under negative selection. Several genes were differentially expressed across the two pine accessions with contrasted phenotypes, including a glutathione-s-transferase, a cellulose synthase and a cobra-like protein. A large number of new markers (3334 amplifiable SSRs and 28,236 SNPs) have been identified which should facilitate future population genomics and association genetics in this species. A 384-SNP Oligo Pool Assay for genotyping with the Illumina VeraCode technology has been designed which showed an high overall SNP conversion rate (76.6%). Our results showed that Illumina next-generation sequencing is a valuable technology to obtain an extensive overview on whole transcriptomes of nonmodel species with large genomes.

Cryptic diversity among Western Palearctic tree frogs: postglacial range expansion, range limits, and secondary contacts of three European tree frog lineages (Hyla arborea group).

We characterize divergence times, intraspecific diversity and distributions for recently recognized lineages within the Hyla arborea species group, based on mitochondrial and nuclear sequences from 160 localities spanning its whole distribution. Lineages of H. arborea, H. orientalis, H. molleri have at least Pliocene age, supporting species level divergence. The genetically uniform Iberian H. molleri, although largely isolated by the Pyrenees, is parapatric to H. arborea, with evidence for successful hybridization in a small Aquitanian corridor (southwestern France), where the distribution also overlaps with H. meridionalis. The genetically uniform H. arborea, spread from Crete to Brittany, exhibits molecular signatures of a postglacial range expansion. It meets different mtDNA clades of H. orientalis in NE-Greece, along the Carpathians, and in Poland along the Vistula River (there including hybridization). The East-European H. orientalis is strongly structured genetically. Five geographic mitochondrial clades are recognized, with a molecular signature of postglacial range expansions for the clade that reached the most northern latitudes. Hybridization with H. savignyi is suggested in southwestern Turkey. Thus, cryptic diversity in these Pliocene Hyla lineages covers three extremes: a genetically poor, quasi-Iberian endemic (H. molleri), a more uniform species distributed from the Balkans to Western Europe (H. arborea), and a well-structured Asia Minor-Eastern European species (H. orientalis).

Evaluation cardiologique préopératoire avant chirurgie non cardiaque: du choix cornélien a l'arbre décisionnel [Pre-operative cardiac assessment in non-cardiac surgery: a frequent dilemma simplified by a decision tree].

In patients undergoing non-cardiac surgery, cardiac events are the most common cause of perioperative morbidity and mortality. It is often difficult to choose adequate cardiologic examinations before surgery. This paper, inspired by the guidelines of the European and American societies of cardiology (ESC, AHA, ACC), discusses the place of standard ECG, echocardiography, treadmill or bicycle ergometer and pharmacological stress testing in preoperative evaluations. The role of coronary angiography and prophylactic revascularization will also be discussed. Finally, we provide a decision tree which will be helpful to both general practitioners and specialists.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Sympatric speciation in palms on an oceanic island.

The origin of species diversity has challenged biologists for over two centuries. Allopatric speciation, the divergence of species resulting from geographical isolation, is well documented. However, sympatric speciation, divergence without geographical isolation, is highly controversial. Claims of sympatric speciation must demonstrate species sympatry, sister relationships, reproductive isolation, and that an earlier allopatric phase is highly unlikely. Here we provide clear support for sympatric speciation in a case study of two species of palm (Arecaceae) on an oceanic island. A large dated phylogenetic tree shows that the two species of Howea, endemic to the remote Lord Howe Island, are sister taxa and diverged from each other well after the island was formed 6.9 million years ago. During fieldwork, we found a substantial disjunction in flowering time that is correlated with soil preference. In addition, a genome scan indicates that few genetic loci are more divergent between the two species than expected under neutrality, a finding consistent with models of sympatric speciation involving disruptive/divergent selection. This case study of sympatric speciation in plants provides an opportunity for refining theoretical models on the origin of species, and new impetus for exploring putative plant and animal examples on oceanic islands.