Electrocardiograms of Children and Adolescents Practicing Non-competitive Sports: Normal Limits and Abnormal Findings in a Large European Cohort Evaluated by Telecardiology.

OBJECTIVE: The objective of this study was to derive normal electrocardiographic values and to report the abnormal findings in a large contemporary European cohort of physically active children and young adolescents. METHODS: In a 3-month period, data derived from subjects aged between 3 and 14 years and referred to the Telecardiology Centre (Genoa, Italy) for electrocardiogram (ECG) evaluation as pre-participation screening for non-competitive sports were analyzed. RESULTS: A total of 2060 ECGs were recorded. Of those, 1962 did not show any morphological abnormality and were used to derive normality ranges for heart rate, PR interval, QRS duration, corrected QT interval, and voltage of R wave as measured in V1 according to age and sex. Findings and clinical implications of the 98 ECGs with abnormal findings were also reported. Abnormal ECG findings were not as uncommon as expected in this population, being manifest in about 5 % of subjects. However, major ECG anomalies (diffuse negative T-waves, pre-excitation) were present in just ten subjects (0.5 %). Lower mean heart rate values (from 90-100 bpm at 3 years of age to 80-85 bpm at 14 years of age) and lower rates of the prevalence of negative T-waves in the V3 lead (from 55-60 % at 3 years of age to 8-10 % at 14 years of age) were observed with increasing age. CONCLUSIONS: This is the first work reporting derived normal limits and abnormal ECG findings in a large contemporary European cohort of children and adolescents aged 3-14 years practicing non-competitive sports. Clear pathological alterations are extremely uncommon, deserving, when encountered, additional examinations. Even in a physically active population, the common features of an adult athlete's ECG are absent.

Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease.

BACKGROUND: Structural MRI measures for monitoring Alzheimer's Disease (AD) progression are becoming instrumental in the clinical practice, and more so in the context of longitudinal studies. This investigation addresses the impact of four image analysis approaches on the longitudinal performance of the hippocampal volume. METHODS: We present a hippocampal segmentation algorithm and validate it on a gold-standard manual tracing database. We segmented 460 subjects from ADNI, each subject having been scanned twice at baseline, 12-month and 24month follow-up scan (1.5T, T1 MRI). We used the bilateral hippocampal volume v and its variation, measured as the annualized volume change Λ=δv/year(mm(3)/y). Four processing approaches with different complexity are compared to maximize the longitudinal information, and they are tested for cohort discrimination ability. Reference cohorts are Controls vs. Alzheimer's Disease (CTRL/AD) and CTRL vs. Mild Cognitive Impairment who subsequently progressed to AD dementia (CTRL/MCI-co). We discuss the conditions on v and the added value of Λ in discriminating subjects. RESULTS: The age-corrected bilateral annualized atrophy rate (%/year) were: -1.6 (0.6) for CTRL, -2.2 (1.0) for MCI-nc, -3.2 (1.2) for MCI-co and -4.0 (1.5) for AD. Combined (v, Λ) discrimination ability gave an Area under the ROC curve (auc)=0.93 for CTRL vs AD and auc=0.88 for CTRL vs MCI-co. CONCLUSIONS: Longitudinal volume measurements can provide meaningful clinical insight and added value with respect to the baseline provided the analysis procedure embeds the longitudinal information.

Automatic temporal lobe atrophy assessment in prodromal AD: Data from the DESCRIPA study.

BACKGROUND: In the framework of the clinical validation of research tools, this investigation presents a validation study of an automatic medial temporal lobe atrophy measure that is applied to a naturalistic population sampled from memory clinic patients across Europe. METHODS: The procedure was developed on 1.5-T magnetic resonance images from the Alzheimer's Disease Neuroimaging Initiative database, and it was validated on an independent data set coming from the DESCRIPA study. All images underwent an automatic processing procedure to assess tissue atrophy that was targeted at the hippocampal region. For each subject, the procedure returns a classification index. Once provided with the clinical assessment at baseline and follow-up, subjects were grouped into cohorts to assess classification performance. Each cohort was divided into converters (co) and nonconverters (nc) depending on the clinical outcome at follow-up visit. RESULTS: We found the area under the receiver operating characteristic curve (AUC) was 0.81 for all co versus nc subjects, and AUC was 0.90 for subjective memory complaint (SMCnc) versus all co subjects. Furthermore, when training on mild cognitive impairment (MCI-nc/MCI-co), the classification performance generally exceeds that found when training on controls versus Alzheimer's disease (CTRL/AD). CONCLUSIONS: Automatic magnetic resonance imaging analysis may assist clinical classification of subjects in a memory clinic setting even when images are not specifically acquired for automatic analysis.

Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer's disease.

BACKGROUND: Medial temporal lobe (MTL) atrophy is one of the key biomarkers to detect early neurodegenerative changes in the course of Alzheimer's disease (AD). There is active research aimed at identifying automated methodologies able to extract accurate classification indexes from T1-weighted magnetic resonance images (MRI). Such indexes should be fit for identifying AD patients as early as possible. SUBJECTS: A reference group composed of 144AD patients and 189 age-matched controls was used to train and test the procedure. It was then applied on a study group composed of 302 MCI subjects, 136 having progressed to clinically probable AD (MCI-converters) and 166 having remained stable or recovered to normal condition after a 24month follow-up (MCI-non converters). All subjects came from the ADNI database. METHODS: We sampled the brain with 7 relatively small volumes, mainly centered on the MTL, and 2 control regions. These volumes were filtered to give intensity and textural MRI-based features. Each filtered region was analyzed with a Random Forest (RF) classifier to extract relevant features, which were subsequently processed with a Support Vector Machine (SVM) classifier. Once a prediction model was trained and tested on the reference group, it was used to compute a classification index (CI) on the MCI cohort and to assess its accuracy in predicting AD conversion in MCI patients. The performance of the classification based on the features extracted by the whole 9 volumes is compared with that derived from each single volume. All experiments were performed using a bootstrap sampling estimation, and classifier performance was cross-validated with a 20-fold paradigm. RESULTS: We identified a restricted set of image features correlated with the conversion to AD. It is shown that most information originate from a small subset of the total available features, and that it is enough to give a reliable assessment. We found multiple, highly localized image-based features which alone are responsible for the overall clinical diagnosis and prognosis. The classification index is able to discriminate Controls from AD with an Area Under Curve (AUC)=0.97 (sensitivity ≃89% at specificity ≃94%) and Controls from MCI-converters with an AUC=0.92 (sensitivity ≃89% at specificity ≃80%). MCI-converters are separated from MCI-non converters with AUC=0.74(sensitivity ≃72% at specificity ≃65%). FINDINGS: The present automated MRI-based technique revealed a strong relationship between highly localized baseline-MRI features and the baseline clinical assessment. In addition, the classification index was also used to predict the probability of AD conversion within a time frame of two years. The definition of a single index combining local analysis of several regions can be useful to detect AD neurodegeneration in a typical MCI population.

Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease.

The purpose of this study is to develop a software for the extraction of the hippocampus and surrounding medial temporal lobe (MTL) regions from T1-weighted magnetic resonance (MR) images with no interactive input from the user, to introduce a novel statistical indicator, computed on the intensities in the automatically extracted MTL regions, which measures atrophy, and to evaluate the accuracy of the newly developed intensity-based measure of MTL atrophy to (a) distinguish between patients with Alzheimer disease (AD), patients with amnestic mild cognitive impairment (aMCI), and elderly controls by using established criteria for patients with AD and aMCI as the reference standard and (b) infer about the clinical outcome of aMCI patients. For the development of the software, the study included 61 patients with mild AD (17 men, 44 women; mean age +/- standard deviation (SD), 75.8 years +/- 7.8; Mini Mental State Examination (MMSE) score, 24.1 +/- 3.1), 42 patients with aMCI (11 men, 31 women; mean age +/- SD, 75.2 years +/- 4.9; MMSE score, 27.9 +/- 1.9), and 30 elderly healthy controls (10 men, 20 women; mean age +/- SD, 74.7 years +/- 5.2; MMSE score, 29.1 +/- 0.8). For the evaluation of the statistical indicator, 150 patients with mild AD (62 men, 88 women; mean age +/- SD, 76.3 years +/- 5.8; MMSE score, 23.2 +/- 4.1), 247 patients with aMCI (143 men, 104 women; mean age +/- SD, 75.3 years +/- 6.7; MMSE score, 27.0 +/- 1.8), and 135 elderly healthy controls (61 men, 74 women; mean age +/- SD, 76.4 years +/- 6.1). Fifty aMCI patients were evaluated every 6 months over a 3 year period to assess conversion to AD. For each participant, two subimages of the MTL regions were automatically extracted from T1-weighted MR images with high spatial resolution. An intensity-based MTL atrophy measure was found to separate control, MCI, and AD cohorts. Group differences were assessed by using two-sample t test. Individual classification was analyzed by using receiver operating characteristic (ROC) curves. Compared to controls, significant differences in the intensity-based MTL atrophy measure were detected in both groups of patients (AD vs controls, 0.28 +/- 0.03 vs 0.34 +/- 0.03, P < 0.001; aMCI vs controls, 0.31 +/- 0.03 vs 0.34 +/- 0.03, P < 0.001). Moreover, the subgroup of aMCI converters was significantly different from controls (0.27 +/- 0.034 vs 0.34 +/- 0.03, P < 0.001). Regarding the ROC curve for intergroup discrimination, the area under the curve was 0.863 for AD patients vs controls, 0.746 for all aMCI patients vs controls, and 0.880 for aMCI converters vs controls. With specificity set at 85%, the sensitivity was 74% for AD vs controls, 45% for aMCI vs controls, and 83% for aMCI converters vs controls. The automated analysis of MTL atrophy in the segmented volume is applied to the early assessment of AD, leading to the discrimination of aMCI converters with an average 3 year follow-up. This procedure can provide additional useful information in the early diagnosis of AD.

Proton beam radiotherapy of uveal melanoma: Italian patients treated in Nice, France.

PURPOSE: To evaluate the results of 15 years of experience with proton beam radiotherapy in the treatment of intraocular melanoma, and to determine univariate and multivariate risk factors for local failure, eye retention, and survival. METHODS: A total of 368 cases of intraocular melanoma were treated with proton beam radiotherapy at Centre Lacassagne Cyclotron Biomedical of Nice, France, between 1991 and 2006. Actuarial methods were used to evaluate rate of local tumor control, eye retention, and survival after proton beam radiotherapy. Cox regression models were extracted to evaluate univariate risk factors, while regularized least squares algorithm was used to have a multivariate classification model to better discriminate risk factors. RESULTS: Tumor relapse occurred in 8.4% of the eyes, with a median recurrence time of 46 months. Enucleation was performed on 11.7% of the eyes after a median time of 49 months following proton beam; out of these, 29 eyes were enucleated due to relapse and 16 due to other causes. The univariate regression analysis identified tumor height and diameter as primary risk factors for enucleation. Regularized least squares analysis demonstrated the higher effectiveness of a multivariate model of five risk factors (macula distance, optic disc distance, tumor height, maximum diameter, and age) in discriminating relapsed vs nonrelapsed patients. CONCLUSIONS: This data set, which is the largest in Italy with relatively long-term follow-up, demonstrates that a high rate of tumor control, survival, and eye retention were achieved after proton beam irradiation, as in other series.

The Italian Registry of Laparoscopic Surgery of the Spleen (IRLSS) A retrospective review of 379 patients undergoing laparoscopic splenectomy.

In December 2000, the Italian Registry of Laparoscopic Surgery of the Spleen (IRLSS) was formally launched under the auspices of the Italian Society for Endoscopic Surgery and New Technologies (SICE). The aim of this multicentre study was to analyse various aspects of the treatment that are still under discussion, such as the extension of the laparoscopic indications in cases of malignancy, independently of the associated splenomegaly, patient selection and operative techniques. A retrospective review of 379 patients undergoing laparoscopic splenectomy for haematological diseases from February 1, 1993, to September 15, 2005, was conducted. Data were collected from the 18 italian centres participating in the IRLSS. The mean length of surgery was 140 minutes (range: 25-420). Conversion was necessary in 25 cases (6.6%), and at least one accessory spleen was found in 30 patients (8%). The mean spleen weight was 1200 g (range: 85-4500). Perioperative death occurred in two cases (0.5%). There were no complications in 312 patients (82.3%), with a mean hospital stay of 5.5 days (range: 2-30). Morbidity occurred in 67 patients (17.8%), mainly consisting in transient fever (n = 22), pleural effusions (n = 16), and actual or suspected haemorrhage (n = 14), requiring re-intervention in 7 patients. This first study carried out on the IRLSS data shows that laparoscopic splenectomy may constitute the gold standard for haematological diseases with a normal-sized spleen. The low morbidity and mortality rates suggest that laparoscopic splenectomy can be successfully proposed also for splenomegaly in haematological malignancies.

Professional shift-work drivers who adopt prophylactic naps can reduce the risk of car accidents during night work.

STUDY OBJECTIVES: Night work can be dangerous because both circadian sleep propensity (process C) and sleep pressure due to the prolonged wakefulness (process S) contribute to the reduction of vigilance levels. As naps are a countermeasure to sleepiness, this study evaluates the role they play in preventing sleep-related accidents in Italian shift-working police drivers. DESIGN/SETTING/PARTICIPANTS: The study concerns highway car accidents that occurred to Italian shift-working police drivers; it was performed in 2 steps: a retrospective analysis of the overall number of accidents that occurred during the years 1993--1997 (n, 1195), followed by a validation analysis of a smaller cohort of accidents prospectively collected during 2003 (n, 84). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: RETROSPECTIVE ANALYSIS: The influence of process S, process C, driver characteristics, and context conditions on accident risk, estimated by means of Cox hazard regression, revealed that nighttime accident risk was mainly influenced by process S levels. Consequently, an experimental mathematical model linking the hourly observed number of accidents to process S levels was designed. Its generalization to the theoretical case of drivers omitting naps showed an increase of about 38% of accidents. PROSPECTIVE ANALYSIS: In order to validate our results, we compared retrospective and prospective sleep patterns: no statistical difference was found. Again, the hourly number of accidents increased with homeostatic sleep pressure; the theoretical efficacy of napping was quantified in 48% accidents decrease. CONCLUSIONS: Our data seem to confirm that napping before working a night shift is an effective countermeasure to alertness and performance deterioration associated with night work. Moreover, this self-initiated behavior could have a prophylactic efficacy in reducing the number of car accidents.

Sleepiness and sleep disorders in shift workers: a study on a group of italian police officers.

STUDY OBJECTIVES: evaluation of shift-work effect on sleepiness, sleep disorders, and sleep-related accidents in a population of police officers. DESIGN: Aquestionnaire-based survey was used to gather information on age and physical characteristics, working conditions, sleep problems, and accidents. Sleepiness was measured by the Epworth Sleepiness Scale (ESS) while the presence of sleep disorders was evaluated by a score (SDS) drawn from indicators of insomnia, breathing disorders, periodic limb movements and restless legs syndrome, and hypersomnia. The effects of age, gender, body mass index, working conditions, and seniority on ESS, SD score, and accidents were analyzed by linear and logistic regression. SETTING: The self-administered questionnaires were filled in by police officers in the district of Genoa (Italy). PARTICIPANTS: 1,280 police officers: 611 shift workers (SW) and 669 non-shift workers (NSW). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: The ESS score was not higher in SW than in NSW, while the SDS was significantly influenced by shift-work conditions and seniority in shift work. The occurrence of sleep-ascribed accidents was significantly increased in the SW group and related to the presence of indicators of sleep disorders. There was evidence for sleep disorders in 35.7% of SW and in 26.3% of NSW. CONCLUSIONS: Shift-work conditions and seniority may enhance sleep disorders and may favor sleep-related accidents, but they do not influence ESS score. Stressful conditions could cause sleepiness to be underestimated, or else they might overcome sleepiness. However, our data should alert occupational health physicians for the diagnosis and prevention of possible undetected intrinsic sleep disorders, which could possibly worsen shift workers' health and increase the risk of accidents.