Identifying fallers among ophthalmic patients using classification tree methodology

Purpose To develop and validate a tool aiming to support ophthalmologists in identifying, during routine ophthalmologic visits, patients at higher risk of falling in the following year. Methods A group of 141 subjects (age: 73.2 ± 11.4 years), recruited at our Eye Clinic, underwent a baseline ophthalmic examination and a standardized questionnaire, including lifestyles, general health, social engagement and eyesight problems. Moreover, visual disability was assessed by the Activity of Daily Vision Scale (ADVS). The subjects were followed up for 12 months in order to record prospective falls. A subject who reported at least one fall within one year from the baseline assessment was considered as faller, otherwise as non-faller. Different tree-based algorithms (i.e., C4.5, AdaBoost and Random Forests) were used to develop automatic classifiers and their performances were evaluated by the cross-validation approach. Results Over the follow-up, 25 falls were referred by 13 patients. The logistic regression analysis showed the following variables as significant predictors of prospective falls: pseudophakia and use of prescribed eyeglasses as protective factors, recent worsening of visual acuity as risk factor. Random Forest ranked best corrected visual acuity, number of sleeping hours and job type as the most important features. Finally, AdaBoost enabled the identification of subjects at higher risk of falling in the following 12 months with a sensitivity rate of 69.2% and a specificity rate of 76.6%. Conclusions The current study proposes a novel method, based on classification trees applied to self-reported factors and health information assessed by a standardized questionnaire during ophthalmological visits, to identify ophthalmic patients at higher risk of falling in the following 12 months. The findings of the current study pave the way to the validation of the proposed novel tool for fall risk screening on a larger cohort of patients with visual impairment referred to eye clinics

Thermoregulation of feet in cold environments: A study on alpinism

Thermal comfort plays a crucial role in the performance and well-being of mountaineers, especially in extreme environments. The aim of this study was to develop a reliable protocol to assess the thermal comfort of mountaineering boots, with a specific focus on temperature variations in different regions of the foot and their correlation with physiological factors. Two different models of mountaineering boots were tested at two different environmental temperature (-15◦C and -30◦C). The mean skin temperature, measured according to International Standards BS EN ISO 9886:2004, was used as an indicator of overall thermal comfort. Physiological factors such as heart rate (HR), body mass index (BMI) and body surface area (BSA) were also measured to understand their relationship to thermoregulation. Kruskal-Wallis and Pearson’s ProductMoment correlation tests were performed to investigate whether there was a statistically significant relationship. The results showed significant differences in foot temperature among the Testers, indicating variations in the perception of thermal comfort. The correlation analysis showed a strong positive relationship between mean skin temperature and HR, highlighting the influence of physiological factors on thermal comfort. In addition, the analysis showed that the dorsum and hallux areas had the largest temperature variations, suggesting the occurrence of vasoconstriction and potential discomfort. This study represents a preliminary approach to establishing a reliable protocol for assessing the thermal performance of cold protective footwea

Heart rate variability for automatic assessment of congestive heart failure severity

The aim of this paper is to describe an automatic classifier to assess the severity of congestive heart failure (CHF) patients. Disease severity is defined according to the New York Heart Association classification (NYHA). The proposed classified aims to distinguish very mild CHF (NYHA I) from mild (NYHA II) and severe CHF patients (NYHA III), using long-term nonlinear Heart Rate Variability (HRV) measures. 24h Holter ECG recording from 2 public databases was performed, including 44 patients suffering from CHF. One non-linear HRV feature was effective in distinguishing very-mild CHF from mild CHF, by achieving a sensibility and specificity rate of 7% and 100% respectively. Moreover, we combine the results obtained by LDA in a classification tree (previously described) in order to obtain an automatic classifier for CHF severity assessment

Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis

Background There is consensus that Heart Rate Variability is associated with the risk of vascular events. However, Heart Rate Variability predictive value for vascular events is not completely clear. The aim of this study is to develop novel predictive models based on data-mining algorithms to provide an automatic risk stratification tool for hypertensive patients. Methods A database of 139 Holter recordings with clinical data of hypertensive patients followed up for at least 12 months were collected ad hoc. Subjects who experienced a vascular event (i.e., myocardial infarction, stroke, syncopal event) were considered as high-risk subjects. Several data-mining algorithms (such as support vector machine, tree-based classifier, artificial neural network) were used to develop automatic classifiers and their accuracy was tested by assessing the receiver-operator characteristics curve. Moreover, we tested the echographic parameters, which have been showed as powerful predictors of future vascular events. Results The best predictive model was based on random forest and enabled to identify high-risk hypertensive patients with sensitivity and specificity rates of 71.4% and 87.8%, respectively. The Heart Rate Variability based classifier showed higher predictive values than the conventional echographic parameters, which are considered as significant cardiovascular risk factors. Conclusions Combination of Heart Rate Variability measures, analyzed with data-mining algorithm, could be a reliable tool for identifying hypertensive patients at high risk to develop future vascular events

Ocriplasmin use in a selected case with preserved visual acuity

Background: Previous studies described cases of Ocriplasmin injections in patients with vitreo-macular traction and reduced central visual acuity. We describe the first case of a patient with 20/20 visual acuity and vitreo-macular traction treated with Ocriplasmin, and, for the first time in literature, we evaluated the functional changes of the macula in response to pharmacological treatment through multifocal-electroretinogram. Case presentation: We report the case of a female Caucasian patient aged 67 years with vitreo-macular traction in the right eye, treated with Ocriplasmin, at the Eye Clinic of the Second University of Naples. Visual acuity was 20/20 before treatment, associated with metamorphopsia. Two weeks after injection, optical coherence tomography showed the release of vitreo-macular traction and multifocal electroretinogram responses showed a significant increase of retinal density responses in all six rings (p < 0.03). Visual acuity remained constant with resolution of symptoms and the appearance of vitreous floaters. Conclusion: Intravitreal injection of Ocriplasmin resulted to be a safe and effective treatment in the case here reported. Our data show that the anatomical recovery with release of vitreo-macular traction was associated with a full functional recovery. In fact, the electrical retinal density response of the macular area improved two weeks after Ocriplasmin injection. Further studies with broader inclusion criteria for Ocriplasmin treatment (e.g. also with visual acuity higher than 20/25) on a larger study sample are needed to confirm our results

Ocriplasmin use in a selected case with preserved visual acuity

Background: Previous studies described cases of Ocriplasmin injections in patients with vitreo-macular traction and reduced central visual acuity. We describe the first case of a patient with 20/20 visual acuity and vitreo-macular traction treated with Ocriplasmin, and, for the first time in literature, we evaluated the functional changes of the macula in response to pharmacological treatment through multifocal-electroretinogram. Case presentation: We report the case of a female Caucasian patient aged 67 years with vitreo-macular traction in the right eye, treated with Ocriplasmin, at the Eye Clinic of the Second University of Naples. Visual acuity was 20/20 before treatment, associated with metamorphopsia. Two weeks after injection, optical coherence tomography showed the release of vitreo-macular traction and multifocal electroretinogram responses showed a significant increase of retinal density responses in all six rings (p < 0.03). Visual acuity remained constant with resolution of symptoms and the appearance of vitreous floaters. Conclusion: Intravitreal injection of Ocriplasmin resulted to be a safe and effective treatment in the case here reported. Our data show that the anatomical recovery with release of vitreo-macular traction was associated with a full functional recovery. In fact, the electrical retinal density response of the macular area improved two weeks after Ocriplasmin injection. Further studies with broader inclusion criteria for Ocriplasmin treatment (e.g. also with visual acuity higher than 20/25) on a larger study sample are needed to confirm our results

Wearable technology and ECG processing for fall risk assessment, prevention and detection

Falls represent one of the most common causes of injury-related morbidity and mortality in later life. Subjects with cardiovascular disorders (e.g., related to autonomic dysfunctions and postural hypotension) are at higher risk of falling. Autonomic dysfunctions increasing the risk of falling in the short and mid-term could be assessed by Heart Rate Variability (HRV) extracted by electrocardiograph (ECG). We developed three trials for assessing the usefulness of ECG monitoring using wearable devices for: risk assessment of falling in the next few weeks; prevention of imminent falls due to standing hypotension; and fall detection. Statistical and data-mining methods are adopted to develop classification and regression models, validated with the cross-validation approach. The first classifier based on HRV features enabled to identify future fallers among hypertensive patients with an accuracy of 72% (sensitivity: 51.1%, specificity: 80.2%). The regression model to predict falls due to orthostatic dropdown from HRV recorded before standing achieved an overall accuracy of 80% (sensitivity: 92%, specificity: 90%). Finally, the classifier to detect simulated falls using ECG achieved an accuracy of 77.3% (sensitivity: 81.8%, specificity: 72.7%). The evidence from these three studies showed that ECG monitoring and processing could achieve satisfactory performances compared to other system for risk assessment, fall prevention and detection. This is interesting as differently from other technologies actually employed to prevent falls, ECG is recommended for many other pathologies of later life and is more accepted by senior citizens