Functional Prognostic value of optical coherence tomography in optic chiasmal decompression: A preliminary study.

PURPOSE: To assess the predictive value for functional recovery of Ganglion Cell Complex Layer (GCC) and Retinal Nerve Fiber Layer (RNFL) measurements obtained by Optical Coherence Tomography (OCT) in patients undergoing chiasmal decompression and to define potential OCT thresholds for visual recovery. METHODS: We measured preoperative GCC and RNFL thickness in patients with a sellar and/or perisellar tumor compressing the optic chiasm. Visual recovery was defined as recovery of mean deviation (MD) and pattern standard deviation (PSD) using Humphrey visual field testing after 12 successful decompressions (24 eyes). Receiver operating characteristic curve (ROC) analysis was used to identify the best thresholds. RESULTS: Robust global and focal OCT thresholds were found. Superior GCC≥63µm had the best functional prognostic value (AUC=1) for visual improvement. Mean GCC ≥ 67µm and mean RNFL≥75µm also had excellent predictive values (AUC>0.9). CONCLUSION: In this preliminary study, significant preoperative OCT thresholds for early visual recovery after chiasmal decompression were identified, mainly regarding GCC measurements. Further studies on larger cohorts with closely scheduled follow-up could refine our results.

Melanoma Diagnostic Practices of French-Speaking Belgian General Practitioners and the Prospective Study of Their Pigmented Skin Lesion Diagnostic Accuracy and Management.

General practitioners (GPs) are among the main actors involved in early melanoma diagnosis. However, melanoma diagnostic accuracy and management are reported to be insufficient among GPs in Europe. The primary aim of this observational prospective study was to shed light on melanoma diagnostic practices among French-speaking Belgian GPs. The second aim was to specifically analyse these GPs' pigmented skin lesion diagnostic accuracy and management. GPs from the five French-speaking districts of Belgium were asked to complete a questionnaire, before taking part in a melanoma diagnostic training session. First, we assessed the GPs' current melanoma diagnostic practices. Then, their pigmented skin lesion diagnostic accuracy and management were evaluated, through basic theoretical questions and clinical images. These results were subsequently analysed, according to the GPs' sociodemographic characteristics and medical practice type. In total, 89 GPs completed the questionnaire. Almost half of the GPs (43%; CI = [33;54]) were confronted with a suspicious skin lesion as the main reason for consultation once every 3 months, while 33% (CI = [24;43]) were consulted for a suspicious lesion as a secondary reason once a month. Prior to training, one-third of the GPs exhibited suboptimal diagnostic accuracy in at least one of six "life-threatening" clinical cases among two sets of 10 clinical images of pigmented skin lesions, which can lead to inadequate patient management (i.e. incorrect treatment and/or inappropriate reinsurance). This study underlines the need to train GPs in melanoma diagnosis. GPs' pigmented skin lesion diagnostic accuracy and management should be improved to increase early melanoma detection.

Comparison between principal component analysis and independent component analysis in electroencephalograms modelling.

Principal Component Analysis (PCA) is a classical technique in statistical data analysis, feature extraction and data reduction, aiming at explaining observed signals as a linear combination of orthogonal principal components. Independent Component Analysis (ICA) is a technique of array processing and data analysis, aiming at recovering unobserved signals or 'sources' from observed mixtures, exploiting only the assumption of mutual independence between the signals. The separation of the sources by ICA has great potential in applications such as the separation of sound signals (like voices mixed in simultaneous multiple records, for example), in telecommunication or in the treatment of medical signals. However, ICA is not yet often used by statisticians. In this paper, we shall present ICA in a statistical framework and compare this method with PCA for electroencephalograms (EEG) analysis. We shall see that ICA provides a more useful data representation than PCA, for instance, for the representation of a particular characteristic of the EEG named event-related potential (ERP).

[The epidemiology of occupational asthma in Belgium]. / Epidémiologie de l'asthme professionnel en Belgique.

INTRODUCTION: A national surveillance programme of occupational asthma was set up to estimate the incidence and identify the causes of this disorder in Belgium. MATERIALS AND METHODS: The programme was based on the voluntary notification of new cases of occupational asthma by chest specialists and occupational physicians during the period 2000-2002. RESULTS: 92% of the reported cases included occupational asthma of an immunological type and 8% bronchial irritability. According to the opinion of the reporting physicians the diagnosis was considered certain in 39%, probable in 29% and possible in 32% of cases. On the basis of these notifications the mean annual incidence of occupational asthma is estimated as 23.5 cases per million workers (95% confidence interval 19.2-28.8). The most frequently incriminated substances were isocyanates (16%), cereals (12%) and latex (10%). At the time of diagnosis 38% of patients had not applied for compensation. CONCLUSION: The results of this programme of notification of occupational asthma agree with the data available from other countries and provide information complementary to the medico-legal statistics.