Accuracy of sentinel lymph node dissection for melanoma staging in the presence of a collision tumour with a lymphoproliferative disease.

Sentinel lymph node dissection (SLND) identifies melanoma patients with metastatic disease who would benefit from radical lymph node dissection (RLND). Rarely, patients with melanoma have an underlying lymphoproliferative disease, and melanoma metastases might develop as collision tumours in the sentinel lymph node (SLN). The aim of this study was to measure the incidence and examine the effect of collision tumours on the accuracy of SLND and on the validity of staging in this setting. Between 1998 and 2012, 750 consecutive SLNDs were performed in melanoma patients using the triple technique (lymphoscintigraphy, gamma probe and blue dye). The validity of SLND in collision tumours was analysed. False negativity was reflected by the disease-free survival. The literature was reviewed on collision tumours in melanoma. Collision tumours of melanoma and chronic lymphocytic leukaemia (CLL) were found in two SLN and in one RLND (0.4%). Subsequent RLNDs of SLND-positive cases were negative for melanoma. The patient with negative SLND developed relapse after 28 months with an inguinal lymph node metastasis of melanoma; RLND showed collision tumours. The literature review identified 12 cases of collision tumours. CLL was associated with increased melanoma incidence and reduced overall survival. This is, to our knowledge, the first assessment of the clinical value of SLND when collision tumours of melanoma and CLL are found. In this small series of three patients with both malignancies present in the same lymph node basin, lymphocytic infiltration of the CLL did not alter radioisotope uptake into the SLN. No false-negative result was observed. Our data suggest the validity of SLND in collision tumours, but given the rarity of the problem, further studies are necessary to confirm this reliability.

Extent of Hypoattenuation On CT Angiography Source Images In Basilar Artery Occlusion: Prognostic Accuracy Of Posterior Circulation ASPECTS And The Pons-midbrain Score In The Basilar Artery International Cooperation Study

Background: The posterior circulation Acute Stroke Prognosis Early CT Score (pc-ASPECTS) and the combined Pons-midbrain score quantify the extent of early ischemic changes in the posterior circulation. We compared the prognostic accuracy of both scores if applied to CT angiography (CTA) source images (CTA-SI) of patients in the Basilar Artery International Cooperation Study (BASICS).Methods: BASICS was a prospective, observational, multi-centre, registry of consecutive patients who presented with acute symptomatic basilar artery occlusion (BAO). Functional outcome was assessed at 1 month. We applied pc-ASPECTS and the combined Pons-midbrain score to CTA-SI by 3-reader-consensus. Readers were blinded to clinical data. We performed multivariable logistic regression analysis, adjusting for thrombolysis, baseline NIHSS score and age, and used the output to derive ROC curves to compare the ability of both scores to discriminate patients with favourable (modified Rankin Scale [mRS] scores 0-3) from patients with unfavourable (mRS scores 4-6) functional outcome.Results: We reviewed CTAs of 158 patients (64% men, mean age 65 _ 15 years, median NIHSS score 25 [0-38], median GCS score 7 [3-15], median onset-to-CTA time 234 minutes [11-7380]). At 1 month, 40 (25%) patients had a favourable outcome, 49 (31%) had an unfavourable outcome (mRS score 4-5) and 69 (44%) were deceased. Both techniques of assessing CTA-SI hypoattenuation in the posterior circulation showed equally good discriminative value in predicting final outcome (C-statistics; area under ROC curve 0.74 versus 0.75, respectively; p_0.37). Pc-ASPECTS dichotomized at _6 versus _6 was an independent predictor of favourable functional outcome (RR _ 2.2; CI95 1.1-4.7; p _ 0.034).Conclusion: Compared to the combined Pons-midbrain score, the pc-ASPECTS score has similar prognostic accuracy to identify patients with a favourable functional outcome in BASICS. Dichotomized pc-ASPECTS (_6 versus _6) is an independent predictor of favourable functional outcome in this population. Author Disclosures: V. Puetz: None. A. Khomenko: None. M.D. Hill: None. I. Dzialowski: None. P. Michel: None. C. Weimar: None. C.A.C. Wijman: None. H. Mattle: None. K. Muir: None. T. Pfefferkorn: None. D. Tanne: None. S. Engelter: None. K. Szabo: None. A. Algra: None. A.M. Demchuk: None. W.J. Schonewille: None.

Paper 3: EUROCAT data quality indicators for population-based registries of congenital anomalies.

The European Surveillance of Congenital Anomalies (EUROCAT) network of population-based congenital anomaly registries is an important source of epidemiologic information on congenital anomalies in Europe covering live births, fetal deaths from 20 weeks gestation, and terminations of pregnancy for fetal anomaly. EUROCAT's policy is to strive for high-quality data, while ensuring consistency and transparency across all member registries. A set of 30 data quality indicators (DQIs) was developed to assess five key elements of data quality: completeness of case ascertainment, accuracy of diagnosis, completeness of information on EUROCAT variables, timeliness of data transmission, and availability of population denominator information. This article describes each of the individual DQIs and presents the output for each registry as well as the EUROCAT (unweighted) average, for 29 full member registries for 2004-2008. This information is also available on the EUROCAT website for previous years. The EUROCAT DQIs allow registries to evaluate their performance in relation to other registries and allows appropriate interpretations to be made of the data collected. The DQIs provide direction for improving data collection and ascertainment, and they allow annual assessment for monitoring continuous improvement. The DQI are constantly reviewed and refined to best document registry procedures and processes regarding data collection, to ensure appropriateness of DQI, and to ensure transparency so that the data collected can make a substantial and useful contribution to epidemiologic research on congenital anomalies.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

Utility of the mini-cog for detection of cognitive impairment in primary care: data from two spanish studies.

Objectives. To study the utility of the Mini-Cog test for detection of patients with cognitive impairment (CI) in primary care (PC). Methods. We pooled data from two phase III studies conducted in Spain. Patients with complaints or suspicion of CI were consecutively recruited by PC physicians. The cognitive diagnosis was performed by an expert neurologist, after formal neuropsychological evaluation. The Mini-Cog score was calculated post hoc, and its diagnostic utility was evaluated and compared with the utility of the Mini-Mental State (MMS), the Clock Drawing Test (CDT), and the sum of the MMS and the CDT (MMS + CDT) using the area under the receiver operating characteristic curve (AUC). The best cut points were obtained on the basis of diagnostic accuracy (DA) and kappa index. Results. A total sample of 307 subjects (176 CI) was analyzed. The Mini-Cog displayed an AUC (±SE) of 0.78 ± 0.02, which was significantly inferior to the AUC of the CDT (0.84 ± 0.02), the MMS (0.84 ± 0.02), and the MMS + CDT (0.86 ± 0.02). The best cut point of the Mini-Cog was 1/2 (sensitivity 0.60, specificity 0.90, DA 0.73, and kappa index 0.48 ± 0.05). Conclusions. The utility of the Mini-Cog for detection of CI in PC was very modest, clearly inferior to the MMS or the CDT. These results do not permit recommendation of the Mini-Cog in PC.

What spatial data do we need to develop global mammal conservation strategies?

Spatial data on species distributions are available in two main forms, point locations and distribution maps (polygon ranges and grids). The first are often temporally and spatially biased, and too discontinuous, to be useful (untransformed) in spatial analyses. A variety of modelling approaches are used to transform point locations into maps. We discuss the attributes that point location data and distribution maps must satisfy in order to be useful in conservation planning. We recommend that before point location data are used to produce and/or evaluate distribution models, the dataset should be assessed under a set of criteria, including sample size, age of data, environmental/geographical coverage, independence, accuracy, time relevance and (often forgotten) representation of areas of permanent and natural presence of the species. Distribution maps must satisfy additional attributes if used for conservation analyses and strategies, including minimizing commission and omission errors, credibility of the source/assessors and availability for public screening. We review currently available databases for mammals globally and show that they are highly variable in complying with these attributes. The heterogeneity and weakness of spatial data seriously constrain their utility to global and also sub-global scale conservation analyses.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Critical thinking and accuracy of nurses' diagnoses. Part I: risk of low accuracy diagnoses and new views of critical thinking

Interpretations of patient data are complex and diverse, contributing to a risk of low accuracy nursing diagnoses. This risk is confirmed in research findings that accuracy of nurses' diagnoses varied widely from high to low. Highly accurate diagnoses are essential, however, to guide nursing interventions for the achievement of positive health outcomes. Development of critical thinking abilities is likely to improve accuracy of nurses' diagnoses. Newer views of critical thinking serve as a basis for critical thinking in nursing. Seven cognitive skills and ten habits of mind are identified as dimensions of critical thinking for use in the diagnostic process.

Diagnostic Accuracy of (18)F-FDG-PET and PET/CT in the Differential Diagnosis between Malignant and Benign Pleural Lesions: A Systematic Review and Meta-Analysis.

RATIONALE AND OBJECTIVES: To systematically review and meta-analyze published data about the diagnostic accuracy of fluorine-18-fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) and PET/computed tomography (CT) in the differential diagnosis between malignant and benign pleural lesions. METHODS AND MATERIALS: A comprehensive literature search of studies published through June 2013 regarding the diagnostic performance of (18)F-FDG-PET and PET/CT in the differential diagnosis of pleural lesions was carried out. All retrieved studies were reviewed and qualitatively analyzed. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR+ and LR-) and diagnostic odds ratio (DOR) of (18)F-FDG-PET or PET/CT in the differential diagnosis of pleural lesions on a per-patient-based analysis were calculated. The area under the summary receiver operating characteristic curve (AUC) was calculated to measure the accuracy of these methods. Subanalyses considering device used (PET or PET/CT) were performed. RESULTS: Sixteen studies including 745 patients were included in the systematic review. The meta-analysis of 11 selected studies provided the following results: sensitivity 95% (95% confidence interval [95%CI]: 92-97%), specificity 82% (95%CI: 76-88%), LR+ 5.3 (95%CI: 2.4-11.8), LR- 0.09 (95%CI: 0.05-0.14), DOR 74 (95%CI: 34-161). The AUC was 0.95. No significant improvement of the diagnostic accuracy considering PET/CT studies only was found. CONCLUSIONS: (18)F-FDG-PET and PET/CT demonstrated to be accurate diagnostic imaging methods in the differential diagnosis between malignant and benign pleural lesions; nevertheless, possible sources of false-negative and false-positive results should be kept in mind.

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

On the accuracy of Latin American trade statistics: A nonparametric test for 1925

This paper proposes a nonparametric test in order to establish the level of accuracy of theforeign trade statistics of 17 Latin American countries when contrasted with the trade statistics of the main partners in 1925. The Wilcoxon Matched-Pairs Ranks test is used to determine whether the differences between the data registered by exporters and importers are meaningful, and if so, whether the differences are systematic in any direction. The paper tests for the reliability of the data registered for two homogeneous products, petroleum and coal, both in volume and value. The conclusion of the several exercises performed is that we cannot accept the existence of statistically significant differences between the data provided by the exporters and the registered by the importing countries in most cases. The qualitative historiography of Latin American describes its foreign trade statistics as mostly unusable. Our quantitative results contest this view.

Individual patient data systematic review and meta-analysis of optic nerve sheath diameter ultrasonography for detecting raised intracranial pressure: protocol of the ONSD research group.

BACKGROUND: The purpose of the optic nerve sheath diameter (ONSD) research group project is to establish an individual patient-level database from high quality studies of ONSD ultrasonography for the detection of raised intracranial pressure (ICP), and to perform a systematic review and an individual patient data meta-analysis (IPDMA), which will provide a cutoff value to help physicians making decisions and encourage further research. Previous meta-analyses were able to assess the diagnostic accuracy of ONSD ultrasonography in detecting raised ICP but failed to determine a precise cutoff value. Thus, the ONSD research group was founded to synthesize data from several recent studies on the subject and to provide evidence on the diagnostic accuracy of ONSD ultrasonography in detecting raised ICP. METHODS: This IPDMA will be conducted in different phases. First, we will systematically search for eligible studies. To be eligible, studies must have compared ONSD ultrasonography to invasive intracranial devices, the current reference standard for diagnosing raised ICP. Subsequently, we will assess the quality of studies included based on the QUADAS-2 tool, and then collect and validate individual patient data. The objectives of the primary analyses will be to assess the diagnostic accuracy of ONSD ultrasonography and to determine a precise cutoff value for detecting raised ICP. Secondly, we will construct a logistic regression model to assess whether patient and study characteristics influence diagnostic accuracy. DISCUSSION: We believe that this IPD MA will provide the most reliable basis for the assessment of diagnostic accuracy of ONSD ultrasonography for detecting raised ICP and to provide a cutoff value. We also hope that the creation of the ONSD research group will encourage further study. TRIAL REGISTRATION: PROSPERO registration number: CRD42012003072.

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.