Ultra-short term HRV features as surrogates of short term HRV: a case study on mental stress detection in real life.

BACKGROUND: This paper suggests a method to assess the extent to which ultra-short Heart Rate Variability (HRV) features (less than 5 min) can be considered as valid surrogates of short HRV features (nominally 5 min). Short term HRV analysis has been widely investigated for mental stress assessment, whereas the validity of ultra-short HRV features remains unclear. Therefore, this study proposes a method to explore the extent to which HRV excerpts can be shortened without losing their ability to automatically detect mental stress. METHODS: ECGs were acquired from 42 healthy subjects during a university examination and resting condition. 23 features were extracted from HRV excerpts of different lengths (i.e., 30 s, 1 min, 2 min, 3 min, and 5 min). Significant differences between rest and stress phases were investigated using non-parametric statistical tests at different time-scales. Features extracted from each ultra-short length were compared with the standard short HRV features, assumed as the benchmark, via Spearman's rank correlation analysis and Bland-Altman plots during rest and stress phases. Using data-driven machine learning approaches, a model aiming to detect mental stress was trained, validated and tested using short HRV features, and assessed on the ultra-short HRV features. RESULTS: Six out of 23 ultra-short HRV features (MeanNN, StdNN, MeanHR, StdHR, HF, and SD2) displayed consistency across all of the excerpt lengths (i.e., from 5 to 1 min) and 3 out of those 6 ultra-short HRV features (MeanNN, StdHR, and HF) achieved good performance (accuracy above 88%) when employed in a well-dimensioned automatic classifier. CONCLUSION: This study concluded that 6 ultra-short HRV features are valid surrogates of short HRV features for mental stress investigation.

Detection of mental stress due to oral academic examination via ultra-short-term HRV analysis.

Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. Mental stress detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minutes) HRV has been not. This study aims to detect mental stress using linear and non-linear HRV features extracted from 3 minutes ECG excerpts recorded from 42 university students, during oral examination (stress) and at rest after a vacation. HRV features were then extracted and analyzed according to the literature using validated software tools. Statistical and data mining analysis were then performed on the extracted HRV features. The best performing machine learning method was the C4.5 tree algorithm, which discriminated between stress and rest with sensitivity, specificity and accuracy rate of 78%, 80% and 79% respectively.

A pilot study for development of a novel tool for clinical decision making to identify fallers among ophthalmic patients.

BACKGROUND: Falls in the elderly is a major problem. Although falls have a multifactorial etiology, a commonly cited cause of falls in older people is poor vision. This study proposes a method to discriminate fallers and non-fallers among ophthalmic patients, based on data-mining algorithms applied to health and socio-demographic information. METHODS: A group of 150 subjects aged 55 years and older, recruited at the Eye Clinic of the Second University of Naples, underwent a baseline ophthalmic examination and a standardized questionnaire, including lifestyles, general health, social engagement and eyesight problems. A subject who reported at least one fall within one year was considered as faller, otherwise as non-faller. Different tree-based data-mining algorithms (i.e., C4.5, Adaboost and Random Forest) were used to develop automatic classifiers and their performances were evaluated by assessing the receiver-operator characteristics curve estimated with the 10-fold-crossvalidation approach. RESULTS: The best predictive model, based on Random Forest, enabled to identify fallers with a sensitivity and specificity rate of 72.6% and 77.9%, respectively. The most informative variables were: intraocular pressure, best corrected visual acuity and the answers to the total difficulty score of the Activities of Daily Vision Scale (a questionnaire for the measurement of visual disability). CONCLUSIONS: The current study confirmed that some ophthalmic features (i.e. cataract surgery, lower intraocular pressure values) could be associated with a lower fall risk among visually impaired subjects. Finally, automatic analysis of a combination of visual function parameters (either self-evaluated either by ophthalmological tests) and other health information, by data-mining algorithms, could be a feasible tool for identifying fallers among ophthalmic patients.

Short term Heart Rate Variability to predict blood pressure drops due to standing: a pilot study.

BACKGROUND: Standing from a bed or chair may cause a significant lowering of blood pressure (ΔBP), which may have severe consequences such as, for example, falls in older subjects. The goal of this study was to develop a mathematical model to predict the ΔBP due to standing in healthy subjects, based on their Heart Rate Variability, recorded in the 5 minutes before standing. METHODS: Heart Rate Variability was extracted from an electrocardiogram, recorded from 10 healthy subjects during the 5 minutes before standing. The blood pressure value was measured before and after rising. A mathematical model aiming to predict ΔBP based on Heart Rate Variability measurements was developed using a robust multi-linear regression and was validated with the leave-one-subject-out cross-validation technique. RESULTS: The model predicted correctly the ΔBP in 80% of experiments, with an error below the measurement error of sphygmomanometer digital devices (± 4.5 mmHg), a false negative rate of 7.5% and a false positive rate of 10%. The magnitude of the ΔBP was associated with a depressed and less chaotic Heart Rate Variability pattern. CONCLUSIONS: The present study showes that blood pressure lowering due to standing can be predicted by monitoring the Heart Rate Variability in the 5 minutes before standing.

Cloud-Based Smart Health Monitoring System for Automatic Cardiovascular and Fall Risk Assessment in Hypertensive Patients.

The aim of this paper is to describe the design and the preliminary validation of a platform developed to collect and automatically analyze biomedical signals for risk assessment of vascular events and falls in hypertensive patients. This m-health platform, based on cloud computing, was designed to be flexible, extensible, and transparent, and to provide proactive remote monitoring via data-mining functionalities. A retrospective study was conducted to train and test the platform. The developed system was able to predict a future vascular event within the next 12 months with an accuracy rate of 84 % and to identify fallers with an accuracy rate of 72 %. In an ongoing prospective trial, almost all the recruited patients accepted favorably the system with a limited rate of inadherences causing data losses (<20 %). The developed platform supported clinical decision by processing tele-monitored data and providing quick and accurate risk assessment of vascular events and falls.

Beneficial effects of fibrin glue (Quixil) versus Lichtenstein conventional technique in inguinal hernia repair: a randomized clinical trial.

INTRODUCTION: In inguinal hernia repair, many complications are due to mesh fixation technique. Therefore, new types of atraumatic methods of fixation have been proposed. In this article, we present the results of a prospective multicentric parallel randomized controlled trial aiming to compare two mesh fixation techniques: fibrin sealant (QUIXIL(®), Omrix Biopharmaceuticals S.A., Belgium) and Lichtenstein technique. METHOD: Adult patients with primary uncomplicated inguinal hernia were randomized in two groups: fibrin sealant group (FSG) and Lichtenstein group (LTG). The two groups underwent a follow-up of 15 months. Operative time is the primary outcome. Intraoperative and postoperative outcomes were analyzed. Moreover, a differential cost analysis was performed. Patients and evaluators (with exception of the surgeon who treated the patient) were blinded. RESULTS: A total of 102 patients, 50 in FSG and 52 in LTG, were enrolled from January 2009 to June 2010, and two patients were lost to follow-up at the twelfth month. No significant differences in baseline and clinical characteristics were observed in the two groups. Operative time was longer in LTG (median/ interquartile range: 35 min/30-42.5 min vs. 31 min/28-35 min; effect size: 0.65/95% CI 0.50-0.91; p < 0.05). No differences in intraoperative complications were observed. No significant differences were observed in early complication rate (RR = 0.62; p > 0.05). Numbness rate was lower in the FSG at 1 week (RR = 0.43; p < 0.01) and at 1 month (RR = 0.17; p < 0.05). No significant differences were observed after 6 months. Postoperative pain was lower in the FSG at 1 week (0/0-1 vs. 1/0-2; p < 0.05) and at 1 month (0/0-0 vs. 0/0-1; p < 0.05). Pain disappeared in all patients after 6 months. Analgesic assumption rate was lower in the FSG (RR = 0.42; p < 0.05). Twenty per cent of FSG and 9.62% of LTG patients were discharged within 12 h; 78% of FSG and 90.38% of LTG patients were discharged within 24 h. The only one recurrence we observed was in FSG group. About costs, although fibrin sealant needed for one mesh fixation is about 10 times more costly than the needed sutures, the total costs of the two procedures did not change significantly. This was mainly due to reduction in operative time. CONCLUSIONS: The use of fibrin sealant determined a significant reduction in short-term numbness rate and postoperative pain. There was no relevant difference in total costs per patient between the two procedures.

In vitro susceptibility of chromoblastomycosis and phaeohyphomycosis agents to antifungal drugs.

The in vitro susceptibility of chromoblastomycosis and phaeohyphomycosis agents to antifungal drugs was appraised using the reference macrodilution method proposed by the National Committee for Clinical Laboratory Standards (NCCLS) for yeasts modified for filamentous fungi. The antifungal drugs amphotericin B, 5-fluorocytosine, itraconazole and fluconazole were tested against one environmental and 18 clinical isolates. This work amended the macrodilution methods proposed by NCCLS and suggests that a conidial suspension free of hyphae leads to a more reliable assay and provides for better reproducibility. The macrodilution method was performed with 10(4) conidia ml-1. The MIC values ranged from 1.0 to 16.0 micrograms ml-1 for amphotericin B and 3.12 to 25.0 micrograms ml-1 for 5-fluorocytosine. A MIC range of 0.06 to 1.95 micrograms ml-1 was determined for itraconazole while 2.0 to 64.0 micrograms ml-1 was detected for fluconazole.

[Evaluation of the clinical efficacy of azithromycin in acute respiratory infections in children]. / Valutazione dell'efficacia clinica dell'azitromicina nelle infezioni acute delle vie respiratorie del bambino.

Azithromycin activity in vivo has been studied in a group of children with acute respiratory tract infections in order to test the efficacy and tolerability of this antibiotic. The study involved 135 children treated with a single daily 10 mg/kg dose of azithromycin for three consecutive days. Ten days after this treatment 100% of children with otitis media, tracheobronchitis, or rhinosinusitis and 95.9% of children with pharyngo-tonsillitis were cured. Recurrences were never observed. Azithromycin proved remarkably effective for treatment of acute respiratory infections and otitis media in children. Tolerability and therapeutic compliance were excellent.