Totally laparoscopic gastrectomy for gastric cancer: meta-analysis of short-term outcomes.

INTRODUCTION: We present a review of the literature, together with a meta-analysis of short-term outcomes of totally laparoscopic gastrectomy (TLG) compared with open gastrectomy (OG). MATERIAL & METHODS: We carried out a search in the Pubmed and Cochrane databases from September 2003 to May 2009. Controlled studies on early outcomes were included, both prospective and retrospective, randomized and non-randomized. RESULTS: We found nine eligible studies, one of which was a randomized controlled trial (RCT), while eight were series of patients (three consecutive). The study group consisted of 1,492 patients, 828 of whom had been treated with TLG and 664 treated with OG. TLG for gastric cancer shows a 32.5% (p < 0.001) longer operative time than OG, whereas TLG demonstrated a 44% (p < 0.001) reduction in blood loss, a 34% (p < 0.001) reduction time to first flatus and a 33.7% reduced (p < 0.001) hospital stay. No notable differences were registered regarding morbidity and mortality rates, and no significant difference was observed between the two groups regarding the extent of the lymphadenectomy. CONCLUSIONS: Despite a longer operative time for TLG, with a gastrointestinal recovery rate faster than the OG one for gastric cancer results, no notable differences were recorded between the two techniques for the morbidity and mortality rates and in the spread of the lymphadenectomy.

Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination.

BACKGROUND: This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes a classifier based on nonlinear features of HRV for automatic stress detection. METHODS: 42 students volunteered to participate to the study about HRV and stress. For each student, two recordings were performed: one during an on-going university examination, assumed as a real-life stressor, and one after holidays. Nonlinear analysis of HRV was performed by using Poincaré Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation Analysis, Recurrence Plot. For statistical comparison, we adopted the Wilcoxon Signed Rank test and for development of a classifier we adopted the Linear Discriminant Analysis (LDA). RESULTS: Almost all HRV features measuring heart rate complexity were significantly decreased in the stress session. LDA generated a simple classifier based on the two Poincaré Plot parameters and Approximate Entropy, which enables stress detection with a total classification accuracy, a sensitivity and a specificity rate of 90%, 86%, and 95% respectively. CONCLUSIONS: The results of the current study suggest that nonlinear HRV analysis using short term ECG recording could be effective in automatically detecting real-life stress condition, such as a university examination.

Antepartum cardiotocography: a study of fetal reactivity in frequency domain.

Cardiotocography (CTG) is the most widely used diagnostic technique in clinical practice to monitor fetal health. Cardiotocographic recording also permits to assess maturation of the fetal autonomous nervous system (ANS): fetal heart rate (FHR) modifications may reveal ANS' reactions to stimuli. To assess fetal reactivity, physicians evaluate specific clinical CTG parameters, generally, by means of visual inspection, thus depending on observer's expertise, with lack of reproducibility. Still nowadays, there is a very high intra- and inter-observer variation in the assessment of FHR patterns. More objective methods for CTG interpretation are of crucial importance. For adults, frequency analysis of heart rate variability (HRV) is a non-invasive and powerful method to investigate ANS activity. This frequency analysis can also be a valid support for a better knowledge of fetal ANS functional state and reactions. Indeed, fetal HRV is a good indicator of fetal well-being in non-stress conditions. Fetal reactivity is a very important CTG characteristic used to diagnose fetal distress, but its interpretation is still uncertain. The aim of this study is to characterise fetal reactivity proposing new fetal HRV frequency parameters to support a more exhaustive CTG analysis.

Estimation of out-of-plane vertebra rotations on radiographic projections using CT data: a simulation study.

This study extends previous research concerning in vivo intervertebral motion by means of single-plane fluoroscopy in an attempt to overcome 2D analysis limitations. Knowledge of out-of-plane vertebra rotations will extend the results provided by planar kinematic studies, which is particularly important for lateral bending investigation where axial rotation accompanies side bending, but is also valuable in sagittal analysis (e.g. indicating an absence of coupled axial rotation). Combining a fluoroscopic projection of a vertebra with volumetric information provided by CT data, vertebra 3D position can be estimated. Out-of-plane vertebral rotations are estimated by comparing Digitally Reconstructed Radiographs (DRRs) in different orientations with a reference fluoroscopic projection, maximising the image cross-correlation index. DRRs have been computed from CT-data using a ray-casting algorithm. In this work a feasibility study of the method was performed by means of a computer simulation. To this end the CT volume (vertebra L4, segmented) provided by the Visible Human Project was utilised and reference fluoroscopic projections were simulated in different orientations adding various levels of noise. Accuracy and precision of the proposed method was determined. Error analysis reveals that an accuracy of less than 1 degree can be achieved in computation of out-of-plane vertebral angles.

Telemedicine services for two islands in the Bay of Naples.

In July 1997, telemedicine services were established for two islands, Procida and Ischia, in the Bay of Naples. The telemedicine network allowed a 24 h consultation service to be provided between the islands' health centres and mainland hospitals in the towns of Pozzuoli and Giugliano. Realtime videoconferencing was used, over an ISDN link at 384 kbit/s; radiographs were digitized using a scanner. During 1999 and 2000, there was an average of 46 telemedicine consultations per year from Procida (60% radiology, 30% cardiology, 10% other), 35% of which were emergencies, and 16 training sessions per year; there was an average of 28 telemedicine consultations per year from Ischia (80% radiology, 10% cardiology, 10% other), 10% of which were emergencies, and 12 training sessions per year. The average duration of a telemedicine consultation was 15 min. The total fixed cost of the telemedicine system between the two islands and the two mainland hospitals was approximately Euro 48,000 per year. The total variable costs of the telemedicine service at the observed workload were about Euro 750 per year. The total savings due to telemedicine were approximately Euro 40,000 per year. There was therefore little difference in the overall costs of health-care delivery. The positive consequences of the introduction of the telemedicine service included more rapid diagnosis and treatment, improved quality of service, and the transfer of skills and education. A costs-consequences analysis suggested that the telemedicine service was worthwhile.

Classification tree for risk assessment in patients suffering from congestive heart failure via long-term heart rate variability.

This study aims to develop an automatic classifier for risk assessment in patients suffering from congestive heart failure (CHF). The proposed classifier separates lower risk patients from higher risk ones, using standard long-term heart rate variability (HRV) measures. Patients are labeled as lower or higher risk according to the New York Heart Association classification (NYHA). A retrospective analysis on two public Holter databases was performed, analyzing the data of 12 patients suffering from mild CHF (NYHA I and II), labeled as lower risk, and 32 suffering from severe CHF (NYHA III and IV), labeled as higher risk. Only patients with a fraction of total heartbeats intervals (RR) classified as normal-to-normal (NN) intervals (NN/RR) higher than 80% were selected as eligible in order to have a satisfactory signal quality. Classification and regression tree (CART) was employed to develop the classifiers. A total of 30 higher risk and 11 lower risk patients were included in the analysis. The proposed classification trees achieved a sensitivity and a specificity rate of 93.3% and 63.6%, respectively, in identifying higher risk patients. Finally, the rules obtained by CART are comprehensible and consistent with the consensus showed by previous studies that depressed HRV is a useful tool for risk assessment in patients suffering from CHF.

Remote health monitoring of heart failure with data mining via CART method on HRV features.

Disease management programs, which use no advanced information and computer technology, are as effective as telemedicine but more efficient because less costly. We proposed a platform to enhance effectiveness and efficiency of home monitoring using data mining for early detection of any worsening in patient's condition. These worsenings could require more complex and expensive care if not recognized. In this letter, we briefly describe the remote health monitoring platform we designed and realized, which supports heart failure (HF) severity assessment offering functions of data mining based on the classification and regression tree method. The system developed achieved accuracy and a precision of 96.39% and 100.00% in detecting HF and of 79.31% and 82.35% in distinguishing severe versus mild HF, respectively. These preliminary results were achieved on public databases of signals to improve their reproducibility. Clinical trials involving local patients are still running and will require longer experimentation.

Discrimination power of short-term heart rate variability measures for CHF assessment.

In this study, we investigated the discrimination power of short-term heart rate variability (HRV) for discriminating normal subjects versus chronic heart failure (CHF) patients. We analyzed 1914.40 h of ECG of 83 patients of which 54 are normal and 29 are suffering from CHF with New York Heart Association (NYHA) classification I, II, and III, extracted by public databases. Following guidelines, we performed time and frequency analysis in order to measure HRV features. To assess the discrimination power of HRV features, we designed a classifier based on the classification and regression tree (CART) method, which is a nonparametric statistical technique, strongly effective on nonnormal medical data mining. The best subset of features for subject classification includes square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD), total power, high-frequencies power, and the ratio between low- and high-frequencies power (LF/HF). The classifier we developed achieved sensitivity and specificity values of 79.3 % and 100 %, respectively. Moreover, we demonstrated that it is possible to achieve sensitivity and specificity of 89.7 % and 100 %, respectively, by introducing two nonstandard features ΔAVNN and ΔLF/HF, which account, respectively, for variation over the 24 h of the average of consecutive normal intervals (AVNN) and LF/HF. Our results are comparable with other similar studies, but the method we used is particularly valuable because it allows a fully human-understandable description of classification procedures, in terms of intelligible "if … then …" rules.

Discrimination power of long-term heart rate variability measures for chronic heart failure detection.

The aim of this study was to investigate the discrimination power of standard long-term heart rate variability (HRV) measures for the diagnosis of chronic heart failure (CHF). The authors performed a retrospective analysis on four public Holter databases, analyzing the data of 72 normal subjects and 44 patients suffering from CHF. To assess the discrimination power of HRV measures, an exhaustive search of all possible combinations of HRV measures was adopted and classifiers based on Classification and Regression Tree (CART) method was developed, which is a non-parametric statistical technique. It was found that the best combination of features is: Total spectral power of all NN intervals up to 0.4 Hz (TOTPWR), square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) and standard deviation of the averages of NN intervals in all 5-min segments of a 24-h recording (SDANN). The classifiers based on this combination achieved a specificity rate and a sensitivity rate of 100.00 and 89.74%, respectively. The results are comparable with other similar studies, but the method used is particularly valuable because it provides an easy to understand description of classification procedures, in terms of intelligible "if … then …" rules. Finally, the rules obtained by CART are consistent with previous clinical studies.

An expectation-maximisation approach for simultaneous pixel classification and tracer kinetic modelling in dynamic contrast enhanced-magnetic resonance imaging.

Traditionally, tracer kinetic modelling and pixel classification of DCE-MRI studies are accomplished separately, although they could greatly benefit from each other. In this article, we propose an expectation-maximisation scheme for simultaneous pixel classification and compartmental modelling of DCE-MRI studies. The key point in the proposed scheme is the estimation of the kinetic parameters (K(trans) and K(ep)) of the two-compartmental model. Typically, they are estimated via nonlinear least-squares fitting. In our scheme, by exploiting the iterative nature of the EM algorithm, we use instead a Taylor expansion of the modelling equation. We developed the theoretical framework for the particular case of two classes and evaluated the performances of the algorithm by means of simulations. Results indicate that the accuracy of the proposed method supersedes the traditional pixel-by-pixel scheme and approaches the theoretical lower bound imposed by the Cramer-Rao theorem. Preliminary results on real data were also reported.

Adaptive removal of gradients-induced artefacts on ECG in MRI: a performance analysis of RLS filtering.

One of the main vital signs used in patient monitoring during Magnetic Resonance Imaging (MRI) is Electro-Cardio-Gram (ECG). Unfortunately, magnetic fields gradients induce artefacts which severely affect ECG quality. Adaptive Noise Cancelling (ANC) is one of the preferred techniques for artefact removal. ANC involves the adaptive estimation of the impulse response of the system constituted by the MRI equipment, the patient and the ECG recording device. Least Mean Square (LMS) adaptive filtering has been traditionally employed because of its simplicity: anyway, it requires the choice of a step-size parameter, whose proper value for the specific application must be estimated case by case: an improper choice could yield slow convergence and unsatisfactory behaviour. Recursive Least Square (RLS) algorithm has, potentially, faster convergence while not requiring any parameter. As far as the authors' knowledge, there is no systematic analysis of performances of RLS in this scenario. In this study we evaluated the performance of RLS for adaptive removal of artefacts induced by magnetic field gradients on ECG in MRI, in terms of efficacy of suppression. Tests have been made on real signals, acquired via an expressly developed system. A comparison with LMS was made on the basis of opportune performance indices. Results indicate that RLS is superior to LMS in several respects.

Eye movement baseline oscillation and variability of eye position during foveation in congenital nystagmus.

Despite the inability to maintain steady fixation, congenital nystagmus does not necessarily reduce visual acuity, that can be achieved during the foveation periods. The duration of the foveation period, but also the cycle-to-cycle variability of eye position and velocity during foveations play an important role. A quantitative relationship that relates visual acuity with foveation time and cycle-to-cycle variability of eye position during foveation has been previously proposed. In many infrared-oculographic and electro-oculographic eye position recordings of our database, a sinusoidal-like oscillation of the baseline was observed, on which the nystagmus waveforms lay. This oscillation may contribute to increase cycle-to-cycle variability during foveations. The aim of this work is to extract the baseline oscillation from the recordings and to verify its relationship with eye position variability during foveation. On the basis of the observations, the baseline oscillation was assumed to be sinusoidal, and was estimated (using a least mean square technique) from eye movement signals recorded during fixation intervals, at different gaze positions, from 20 patients affected by congenital nystagmus with low visual acuity. The average baseline oscillation amplitude was 1.31 degrees, while the average frequency was 0.34 Hz. Baseline oscillation amplitude was well correlated (with a coefficient of 0.66) to the standard deviations of eye-position during foveation, which in turn is connected to visual acuity.

International concerted action on collaboration in telemedicine: recommendations of the G-8 Global Healthcare Applications Subproject-4.

The main objectives of the G-8 Global Healthcare Applications Subproject-4 (G-8 GHAP-SP-4) were to establish an international concerted action on collaboration in telemedicine, telehealth, and health telematics (hereafter referred in this paper as telemedicine). In order to promote and facilitate the implementation of telemedicine or health telematics networks around the world, it was considered necessary to address certain key issues. Five thematic solution-seeking forums were held between May 1998 and December 1999. Each addressed a key issue, including interoperability of telemedicine and telehealth systems, impact of telemedicine on health care management, evaluation and cost effectiveness of telemedicine, clinical and technical quality and standards, and medico-legal aspects of national and international applications. The main objectives of these forums were to establish best practices and a thorough review of the issues and discussions among experts to determine the best solutions for the facilitation of global international telemedicine networks. More than 650 invited participants from 16 countries attended the five forums, which were of 2-3 days in duration. These forums provided a foundation for the exchange of ideas resulting in the initiation of collaborative activities. Based on these deliberations, a series of 21 recommendations were prepared by the national representatives of the G-8 GHAP SP-4. These recommendations propose to political leaders and health care managers of the G-8 and other countries roadmaps to follow in order to accelerate the achievement of a Global Society of Healthcare via Telemedicine, Telehealth, and Health Telematics. The 21 recommendations are presented in this report.