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BACKGROUND: Patients with obesity are at increased risk of postoperative pulmonary complications. CPAP has been used successfully to prevent and treat acute respiratory failure, but in many clinical scenarios, high-flow nasal cannula (HFNC) therapy is emerging as a possible alternative. We aimed to compare HFNC and CPAP in a sequential study measuring their effects on gas exchange, lung volumes, and gas distribution within the lungs measured through electrical impedance tomography (EIT). METHODS: We enrolled 15 subjects undergoing laparoscopic bariatric surgery. Postoperatively they underwent the following oxygen therapy protocol (10 min/step): baseline air-entrainment mask, HFNC at increasing (40, 60, 80, and 100 L/min) and decreasing flows (80, 60, and 40 L/min), washout air-entrainment mask and CPAP (10 cm H2O). Primary outcome was the change in end-expiratory lung impedance (ΔEELI) measured by EIT data processing. Secondary outcomes were changes of global inhomogeneity (GI) index and tidal impedance variation (TIV) measured by EIT, arterial oxygenation, carbon dioxide content, pH, respiratory frequency, and subject's comfort. RESULTS: Thirteen subjects completed the study. Compared to baseline, ΔEELI was higher during 10 cm H2O CPAP (P = .001) and HFNC 100 L/min (P = .02), as well as during decreasing flows HFNC 80, 60, and 40 L/min (P = .008, .004, and .02, respectively). GI index was lower during HFNC 100 compared to HFNC 60increasing (P = .044), HFNC 60decreasing (P = .02) HFNC 40decreasing (P = .01), and during 10 cm H2O CPAP compared to washout period (P = .01) and HFNC 40decreasing (P = .03). TIV was higher during 10 cm H2O CPAP compared to baseline (P = .008). Compared to baseline, breathing frequency was lower at HFNC 60increasing, HFNC 100, and HFNC 80decreasing (P = .01, .02, and .03, respectively). No differences were detected regarding arterial oxygenation, carbon dioxide content, pH, and subject's comfort. CONCLUSIONS: HFNC at a flow of 100 L/min induced postoperative pulmonary recruitment in bariatric subjects, with no significant differences compared to 10 cm H2O CPAP in terms of lung recruitment and ventilation distribution.
Subject(s)
Bariatric Surgery , Cannula , Continuous Positive Airway Pressure , Electric Impedance , Oxygen Inhalation Therapy , Humans , Female , Continuous Positive Airway Pressure/methods , Male , Adult , Middle Aged , Oxygen Inhalation Therapy/methods , Lung Volume Measurements , Postoperative Complications/etiology , Postoperative Complications/prevention & control , Pulmonary Gas Exchange , Lung/physiopathology , Respiratory Insufficiency/therapy , Respiratory Insufficiency/etiology , Tidal VolumeABSTRACT
Large language models (LLMs) can potentially transform healthcare, particularly in providing the right information to the right provider at the right time in the hospital workflow. This study investigates the integration of LLMs into healthcare, specifically focusing on improving clinical decision support systems (CDSSs) through accurate interpretation of medical guidelines for chronic Hepatitis C Virus infection management. Utilizing OpenAI's GPT-4 Turbo model, we developed a customized LLM framework that incorporates retrieval augmented generation (RAG) and prompt engineering. Our framework involved guideline conversion into the best-structured format that can be efficiently processed by LLMs to provide the most accurate output. An ablation study was conducted to evaluate the impact of different formatting and learning strategies on the LLM's answer generation accuracy. The baseline GPT-4 Turbo model's performance was compared against five experimental setups with increasing levels of complexity: inclusion of in-context guidelines, guideline reformatting, and implementation of few-shot learning. Our primary outcome was the qualitative assessment of accuracy based on expert review, while secondary outcomes included the quantitative measurement of similarity of LLM-generated responses to expert-provided answers using text-similarity scores. The results showed a significant improvement in accuracy from 43 to 99% (p < 0.001), when guidelines were provided as context in a coherent corpus of text and non-text sources were converted into text. In addition, few-shot learning did not seem to improve overall accuracy. The study highlights that structured guideline reformatting and advanced prompt engineering (data quality vs. data quantity) can enhance the efficacy of LLM integrations to CDSSs for guideline delivery.
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Background: The ability to merge the two retinal images to perceive depth (stereopsis) plays an important role in human vision. Its proper development requires binocular alignment and good visual acuity in both eyes during childhood. Because treatments are more effective when applied early, early diagnosis is important. Unfortunately, assessing stereo deficiencies in infants and young children remains challenging. Recently, it has been shown that ocular-following responses (OFRs; reflexive, short-latency eye movements induced by the sudden motion of a large textured pattern) are sensitive to changes in interocular correlation, making them potentially useful for stereo deficiency assessments. To test this hypothesis, we measured OFRs elicited by dichoptic stimulation in children with normal and compromised stereopsis (due to amblyopia). Methods: Two groups of six children (age- and sex-matched: 3M/3F aged 7-12 yo), one with compromised stereopsis and one with normal stereopsis, were included. OFRs were recorded using a custom high-resolution video eye-tracking system. The relative differences between eye displacement induced by correlated stimuli (up-correlated-down-correlated) and anticorrelated (up-anticorrelated-down-anticorrelated) were compared. Results: We found significant differences between OFRs induced by two dichoptic conditions (correlated and anticorrelated stimuli) in most children with normal stereopsis, whereas no differences were observed in children with compromised stereopsis, indicating a lack of disparity detectors. Conclusions: OFRs might thus be exploited as a diagnostic tool for the objective identification of stereo deficiencies in children. This might lead to improved early diagnosis and treatment outcomes for conditions like amblyopia and strabismus.
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CONTEXT.: Shoulder muscles are active during front crawl swimming to provide propulsion and stabilize the glenohumeral and scapulothoracic joints. It has been proposed that fatigue might contribute to altered activation of these muscles and represent a risk factor for injuries. Tensiomyography (TMG) might represent a non-invasive tool to detect exercise-induced neuromuscular fatigue changes in contractile parameters of the skeletal muscles, and it has never been used in the shoulder muscles in swimmers. OBJECTIVE.: The aim of this study was to assess the effects of a fatiguing swimming protocol on shoulder muscles TMG parameters and isometric strength in competitive swimmers. DESIGN.: A cross-sectional study. SETTING.: A swimming pool facility. PATIENTS OR OTHER PARTICIPANTS.: Sixteen young front crawl competitive swimmers were invited to participate in the study, and 14 of them (21 y, range 17-26, 11 males 3 females) completed all the assessments before and after a 30-min high-intensity swimming training. MAIN OUTCOME MEASURE(S).: The main outcome included the TMG assessment which was performed on seven muscles of the shoulder according to front crawl biomechanics and applicability of the technique, in order to obtain data such as time to contraction and muscle belly radial displacement (Dm), whereas isometric strength was assessed with a digital dynamometer during shoulder flexion, extension, external rotation and internal rotation. RESULTS.: Fatigue induced a smaller Dm (-0.5 mm, 95% CI: -0.7 - -0.3, p< 0.001, pη2= 0.692), mostly observable in latissimus dorsi and pectoralis major muscles. Only shoulder extension showed a significant isometric strength reduction after the fatiguing protocol (-0.03 N/kg, 95% CI: -0.05 - -0.01, p= 0.045, pη2= 0.275). CONCLUSIONS.: This study provides preliminary evidence for the usefulness of TMG to detect fatigue-induced changes in contractile properties of the shoulder muscles in swimmers, in particular the latissimus dorsi, pectoralis major and lower trapezius.
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Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson's Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. Clinical Trial Registration: ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).
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Inertial sensors (IMUs) have been recently widely used in exercise and rehabilitation science as they can provide reliable quantitative measures of range of motion (RoM). Moreover, the pressure pain threshold (PPT) evaluation provides an objective measure of pain sensation in different body areas. The aim of this study was to evaluate the efficacy of physiotherapy treatment in people with adhesive capsulitis in terms of RoM and pain improvement measured by IMUs and the PPT. A combined prospective cohort/cross-sectional study was conducted. Nineteen individuals with adhesive capsulitis (10/19 females, 54 ± 8 years) and nineteen healthy controls (10/19 females, 51 ± 6 years) were evaluated for active glenohumeral joint RoM and PPT on shoulder body areas. Then, individuals with adhesive capsulitis were invited to 20 sessions of a physiotherapy protocol, and the assessments were repeated within 1 week from the last session. The range of motion in the flexion (p = 0.001) and abduction (p < 0.001) of the shoulder increased significantly after the physiotherapy protocol. Similarly, the PPT was found to increase significantly in all the assessed shoulder body areas, leading to no significant differences compared to the healthy controls. IMU and PPT assessments could be used to evaluate the efficacy of physical therapy in people with adhesive capsulitis.
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Attention-deficit/hyperactivity disorder (ADHD) is a neurobehavioral disorder with known brain abnormalities but no biomarkers to support clinical diagnosis. Recently, EEG analysis methods such as functional connectivity have rekindled interest in using EEG for ADHD diagnosis. Most studies have focused on resting-state EEG, while connectivity during sleep and spindle activity has been underexplored. Here we present the results of a preliminary study exploring spindle-related connectivity as a possible biomarker for ADHD. We compared sensor-space connectivity parameters in eight children with ADHD and nine age/sex-matched healthy controls during sleep, before, during, and after spindle activity in various frequency bands. All connectivity parameters were significantly different between the two groups in the delta and gamma bands, and Principal Component Analysis (PCA) in the gamma band distinguished ADHD from healthy subjects. Cluster coefficient and path length values in the sigma band were also significantly different between epochs, indicating different spindle-related brain activity in ADHD.
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BACKGROUND: Chronic ankle instability can be common in sportsmen and can increase the risk of damaging the articular surfaces and result in negative consequences to joint health. Balance assessment is often used to evaluate ankle instability characteristics and guide rehabilitation protocols. This study aims to investigate balance-related parameters in people with chronic ankle instability and healthy-matched controls, using inertial sensors. METHODS: Ten young adults with a history of multiple ankle sprains (30 y, 25-34, 5 females) and ten matched healthy controls (30 y, 23-39, 5 females) were invited to participate in the study. Inertial sensors were placed on the head of the astragalus and on the chest to collect kinematic parameters during a 20-s single-leg stance performed on the leg with ankle instability (and corresponding for the healthy controls) and on the contralateral leg, randomly. Outcomes were calculated with MATLAB and subsequently analyzed. FINDINGS: A significant group effect was found only for the inversion angle (F1,15 = 12.514, p = 0.003, pη2 = 0.455), consisting of individuals with ankle instability being characterized by higher inversion angles (4.999 degrees, 95% CI: 1.987-8.011, p = 0.003) without significant side differences. No significant side x group effects were found for the assessed parameters. INTERPRETATION: Results from this study suggest that young adults with chronic ankle instability might be characterized by worse single-stance control in terms of inversion angle, and such worse performance could also be found in the contralateral leg. As such, inertial sensors could be used to assess kinematic parameters during balance tasks in people with chronic ankle instability.
Subject(s)
Ankle Injuries , Joint Instability , Young Adult , Female , Humans , Ankle , Ankle Joint , Leg , Chronic Disease , Postural BalanceABSTRACT
Cognitive impairment is one of the most prevalent symptoms of post Severe Acute Respiratory Syndrome COronaVirus 2 (SARS-CoV-2) state, which is known as Long COVID. Advanced neuroimaging techniques may contribute to a better understanding of the pathophysiological brain changes and the underlying mechanisms in post-COVID-19 subjects. We aimed at investigating regional cerebral perfusion alterations in post-COVID-19 subjects who reported a subjective cognitive impairment after a mild SARS-CoV-2 infection, using a non-invasive Arterial Spin Labeling (ASL) MRI technique and analysis. Using MRI-ASL image processing, we investigated the brain perfusion alterations in 24 patients (53.0 ± 14.5 years, 15F/9M) with persistent cognitive complaints in the post COVID-19 period. Voxelwise and region-of-interest analyses were performed to identify statistically significant differences in cerebral blood flow (CBF) maps between post-COVID-19 patients, and age and sex matched healthy controls (54.8 ± 9.1 years, 13F/9M). The results showed a significant hypoperfusion in a widespread cerebral network in the post-COVID-19 group, predominantly affecting the frontal cortex, as well as the parietal and temporal cortex, as identified by a non-parametric permutation testing (p < 0.05, FWE-corrected with TFCE). The hypoperfusion areas identified in the right hemisphere regions were more extensive. These findings support the hypothesis of a large network dysfunction in post-COVID subjects with cognitive complaints. The non-invasive nature of the ASL-MRI method may play an important role in the monitoring and prognosis of post-COVID-19 subjects.
Subject(s)
COVID-19 , Post-Acute COVID-19 Syndrome , Humans , COVID-19/diagnostic imaging , SARS-CoV-2 , Magnetic Resonance Imaging/methods , Neuroimaging/methods , Brain/diagnostic imaging , Brain/blood supply , Cerebrovascular Circulation/physiology , Spin LabelsABSTRACT
Hematocrit (HCT) is a crucial parameter for both adult and pediatric patients, indicating potentially severe pathological conditions. Most common methods for HCT assessment are microhematocrit and automated analyzers; however, developing countries present specific needs often not addressed by these technologies. Paper-based devices can be suitable for those environments being inexpensive, rapid, easy to use, and portable. The aim of this study is to describe and validate against a reference method, a novel HCT estimation method based on penetration velocity in lateral flow test strips complying with the requirements in low- or middle-income country (LMIC) scenarios. To calibrate and test the proposed method, 145 blood samples of 105 healthy neonates with gestational age greater than 37 weeks were collected (29 calibration set, 116 test set) in the range of HCT values (31.6-72.5%). The time difference (Δt) from the whole blood sample loading into the test strip instant till the nitrocellulose membrane saturation instant was measured by a reflectance meter. A nonlinear relation was observed between HCT and Δt and was estimated by a third-degree polynomial equation (R2 = 0.91) valid in 30% to 70% HCT interval. The proposed model was subsequently used to estimate HCT values on the test set showing a good agreement between the estimated HCT and the HCT measured by the reference method (r = 0.87, p < 0.001), with a low mean difference of 0.53 ± 5.04% and a slight trend of overestimation for higher hematocrit values. The mean absolute error was 4.29%, while the maximum absolute error was 10.69%. Although the proposed method did not present a sufficient accuracy to be used for diagnostic purposes, it could be suitable as a fast, low-cost, easy-to-use screening tool especially in LMIC scenarios.
Subject(s)
Algorithms , Infant, Newborn , Adult , Humans , Child , Infant , Hematocrit/methods , CalibrationABSTRACT
BACKGROUND AND PURPOSE: Among the most common post-COVID symptoms, many patients experienced subjective cognitive deficit, commonly named "brain fog," that might be present also in those individuals without severe acute COVID-19 respiratory involvement. Some studies have investigated some of the mechanisms that might be associated with the brain fog with objective techniques including transcranial magnetic stimulation and neuroimaging. METHODS: The aim of this study was to investigate the presence of electroencephalographic (EEG) alterations in people with post-COVID self-reported cognitive deficit. RESULTS: Out of the 90 patients attending the post-COVID neurology ambulatory service, twenty patients presenting brain fog at least 4 weeks after acute non-severe COVID-19 infection, and without previous history of epilepsy, were investigated with 19-channel EEG, Montreal Cognitive Assessment (MoCA), and magnetic resonance imaging (MRI). EEG was found altered in 65% of the sample, among which 69% presented a slowing activity and 31% were characterized by epileptic discharges principally in the frontal areas. None of the patients showed DWI MRI lesions. CONCLUSIONS: These findings highlight the usefulness of EEG analysis to objectively describe possible neurophysiological abnormalities in post-COVID patients presenting subjective cognitive deficit.
Subject(s)
COVID-19 , Cognition Disorders , Epilepsy , Humans , COVID-19/complications , Electroencephalography/methods , Cognition Disorders/diagnosis , Cognition Disorders/etiology , Cognition Disorders/psychology , Epilepsy/diagnosis , Cognition/physiologyABSTRACT
PURPOSE: We present two patients who developed neurogenic stuttering after long COVID-19 related to SARS-CoV-2 infection. METHODS AND RESULTS: Both patients experienced both physical (e.g., fatigue) and cognitive difficulties, which led to impaired function of attention, lexical retrieval, and memory consolidation. Both patients had new-onset stuttering-like speech dysfluencies: Blocks and repetitions were especially evident at the initial part of words and sentences, sometimes accompanied by effortful and associated movements (e.g., facial grimaces and oro-facial movements). Neuropsychological evaluations confirmed the presence of difficulties in cognitive tasks, while neurophysiological evaluations (i.e., electroencephalography) suggested the presence of "slowed" patterns of brain activity. Neurogenic stuttering and cognitive difficulties were evident for 4-5 months after negativization of SARS-CoV-2 nasopharyngeal swab, with gradual improvement and near-to-complete recovery. CONCLUSIONS: It is now evident that SARS-CoV-2 infection may significantly involve the central nervous system, also resulting in severe and long-term consequences, even if the precise mechanisms are still unknown. In the present report, long COVID-19 resulted in neurogenic stuttering, as the likely consequence of a "slowed" metabolism of (pre)frontal and sensorimotor brain regions (as suggested by the present and previous clinical evidence). As a consequence, the pathophysiological mechanisms related to the appearance of neurogenic stuttering have been hypothesized, which help to better understand the broader and possible neurological consequences of COVID-19.
Subject(s)
COVID-19 , Cerebrovascular Disorders , Stuttering , Humans , Stuttering/etiology , Post-Acute COVID-19 Syndrome , COVID-19/complications , SARS-CoV-2 , Speech/physiologyABSTRACT
Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs' motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5-9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units.
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Ocular following eye movements have provided insights into how the visual system of humans and monkeys processes motion. Recently, it has been shown that they also reliably reveal stereoanomalies, and, thus, might have clinical applications. Their translation from research to clinical setting has however been hindered by their small size, which makes them difficult to record, and by a lack of data about their properties in sizable populations. Notably, they have so far only been recorded in adults. We recorded ocular following responses (OFRs)-defined as the change in eye position in the 80-160 ms time window following the motion onset of a large textured stimulus-in 14 school-age children (6 to 13 years old, 9 males and 5 females), under recording conditions that closely mimic a clinical setting. The OFRs were acquired non-invasively by a custom developed high-resolution video-oculography system, described in this study. With the developed system we were able to non-invasively detect OFRs in all children in short recording sessions. Across subjects, we observed a large variability in the magnitude of the movements (by a factor of 4); OFR magnitude was however not correlated with age. A power analysis indicates that even considerably smaller movements could be detected. We conclude that the ocular following system is well developed by age six, and OFRs can be recorded non-invasively in young children in a clinical setting.
Subject(s)
Motion Perception , Adult , Child , Humans , Child, Preschool , Adolescent , Motion Perception/physiology , Photic Stimulation , Eye MovementsABSTRACT
"Long-COVID" is a clinical entity that consists of persisting post-infectious symptoms that last for more than three months after the onset of the first acute COVID-19 symptoms. Among these, a cluster of neurological persisting symptoms defines Neuro-Long-COVID. While the debate about the pathogenesis of Long-COVID is still ongoing, sex differences have been individuated for both the acute and the chronic stage of the infection. We conducted a retrospective study describing sex differences in a large sample of patients with Neuro-Long-COVID. Demographic and clinical data were collected in a specifically designed Neuro-Long-Covid outpatient service. Our sample included 213 patients: 151 were females and 62 were males; the mean age was similar between females (53 y, standard deviation 14) and males (55 y, standard deviation 15); no significant differences was present between the demographic features across the two groups. Despite the prevalence of the specific chronic symptoms between male and females showed no significant differences, the total number of females accessing our service was higher than that of males, confirming the higher prevalence of Neuro-Long-COVID in female individuals. Conversely, a worse acute phase response in males rather than females was confirmed by a significant difference in the rates of acute respiratory symptoms (p = 0.008), dyspnea (p = 0.018), respiratory failure (p = 0.010) and the consequent need for ventilation (p = 0.015), together with other acute symptoms such as palpitations (p = 0.049), headache (p = 0.001) and joint pain (p = 0.049). Taken together, these findings offer a subgroup analysis based on sex-dependent characteristics, which can support a tailored-medicine approach.
Subject(s)
COVID-19 , Neurology , COVID-19/complications , COVID-19/epidemiology , Female , Humans , Male , Retrospective Studies , SARS-CoV-2 , Sex Characteristics , Post-Acute COVID-19 SyndromeABSTRACT
There is a growing research interest in wireless non-invasive solutions for core temperature estimation and their application in clinical settings. This study aimed to investigate the use of a novel wireless non-invasive heat flux-based thermometer in acute stroke patients admitted to a stroke unit and compare the measurements with the currently used infrared (IR) tympanic temperature readings. The study encompassed 30 acute ischemic stroke patients who underwent continuous measurement (Tcore) with the novel wearable non-invasive CORE device. Paired measurements of Tcore and tympanic temperature (Ttym) by using a standard IR-device were performed 3−5 times/day, yielding a total of 305 measurements. The predicted core temperatures (Tcore) were significantly correlated with Ttym (r = 0.89, p < 0.001). The comparison of the Tcore and Ttym measurements by Bland−Altman analysis showed a good agreement between them, with a low mean difference of 0.11 ± 0.34 °C, and no proportional bias was observed (B = −0.003, p = 0.923). The Tcore measurements correctly predicted the presence or absence of Ttym hyperthermia or fever in 94.1% and 97.4% of cases, respectively. Temperature monitoring with a novel wireless non-invasive heat flux-based thermometer could be a reliable alternative to the Ttym method for assessing core temperature in acute ischemic stroke patients.
Subject(s)
Ischemic Stroke , Thermometers , Body Temperature , Fever/diagnosis , Humans , Temperature , Tympanic MembraneABSTRACT
Diagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of classification and regression tree (CART) modeling, the predictive power of heart rate variability (HRV) features together with clinical parameters to support the diagnosis in the early stage of IHD and DCM. The study included 263 IHD and 181 DCM patients, as well as 689 healthy subjects. A 24 h Holter monitoring was used and linear and non-linear HRV parameters were extracted considering both normal and ectopic beats (heart rate total variability signal). We used a CART algorithm to produce classification models based on HRV together with relevant clinical (age, sex, and left ventricular ejection fraction, LVEF) features. Among HRV parameters, MeanRR, SDNN, pNN50, LF, LF/HF, LFn, FD, Beta exp were selected by the CART algorithm and included in the produced models. The model based on pNN50, FD, sex, age, and LVEF features presented the highest accuracy (73.3%). The proposed approach based on HRV parameters, age, sex, and LVEF features highlighted the possibility to produce clinically interpretable models capable to differentiate IHD, DCM, and healthy subjects with accuracy which is clinically relevant in first steps of the IHD and DCM diagnostic process.
Subject(s)
Cardiomyopathy, Dilated , Myocardial Ischemia , Cardiomyopathy, Dilated/diagnosis , Heart Rate/physiology , Humans , Myocardial Ischemia/diagnosis , Stroke Volume , Ventricular Function, LeftABSTRACT
Outcome prediction in wake-up ischemic stroke (WUS) is important for guiding treatment strategies, in order to improve recovery and minimize disability. We aimed at producing an interpretable model to predict a good outcome (NIHSS 7-day<5) in thrombolysis treated WUS patients by using Classification and Regression Tree (CART) method. The study encompassed 104 WUS patients and we used a dataset consisting of demographic, clinical and neuroimaging features. The model was produced by CART with Gini split criterion and evaluated by using 5-fold cross-validation. The produced decision tree model was based on NIHSS at admission, ischemic core volume and age features. The predictive accuracy of model was 86.5% and the AUC-ROC was 0.88. In conclusion, in this preliminary study we identified interpretable model based on clinical and neuroimaging features to predict clinical outcome in thrombolysis treated wake-up stroke patients.
Subject(s)
Ischemic Stroke , Stroke , Decision Trees , Humans , Prognosis , Stroke/drug therapy , Stroke/therapy , Treatment OutcomeABSTRACT
OBJECTIVE: Orthostatic hypotension (OH) represents a frequent but under-recognized phenomenon in Parkinson's disease (PD). During COVID-19 pandemic, Information and Communication Technologies (ICT) have become pivotal in the management of chronic diseases like PD, not only to assess motor impairment, but also for vital signs monitoring. This pilot study aimed to propose a real-time remote home-monitoring system and protocol for PD patients with OH. METHODS: Vital parameters were acquired by wireless devices and transmitted to an ICT platform, providing data and smart notifications to the healthcare provider through an interactive web portal. Eight patients with idiopathic PD and OH underwent 5-day monitoring. Data about OH episodes, therapeutic interventions, impact on daily activities, and patient satisfaction were collected and analyzed. RESULTS: The proposed solution allowed the identification of 65 OH episodes and subsequent medical interventions. Thirty-five episodes were asymptomatic, especially in the postprandial and in the afternoon recordings. Systolic-blood-pressure (SBP) and diastolic-blood-pressure (DBP) were significantly lower in symptomatic episodes, while the pressure drops resulted significantly higher in presence of symptoms. High usability and patient satisfaction scores were observed. CONCLUSION: The proposed home-monitoring system and protocol have proved to provide useful information and to allow prompt interventions in the management of PD patients with OH during COVID-19 pandemic.
Subject(s)
COVID-19 , Hypotension, Orthostatic , Parkinson Disease , Telemedicine , Blood Pressure/physiology , Humans , Hypotension, Orthostatic/diagnosis , Hypotension, Orthostatic/epidemiology , Hypotension, Orthostatic/etiology , Pandemics , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/drug therapy , Pilot ProjectsABSTRACT
OBJECTIVE: We investigated brain cortical activity alterations, using a resting-state 256-channel high-density EEG (hd-EEG), in Alzheimer's (AD) and Parkinson's (PD) disease subjects with mild cognitive impairment (MCI) and correlations between quantitative spectral EEG parameters and the global cognitive status assessed by Montreal Cognitive Assessment (MoCA) score. METHODS: Fifteen AD-MCI, eleven PD-MCI and ten age-matched healthy-controls (HC) underwent hd-EEG recordings and neuropsychological assessment. Cerebrospinal fluid biomarker analysis was performed to obtain well-characterized groups. EEG spectral features were extracted and the differences between the three groups, as well as correlations with MoCA, were investigated. RESULTS: The results showed significantly lower alpha2 power and alpha2/alpha1 ratio in both AD-MCI and PD-MCI compared to controls. The significantly higher theta and lower beta power and alpha/theta ratio were observed in PD-MCI compared to AD-MCI and HC. MoCA score correlated inversely with theta power and directly with alpha2 and beta powers, as well as with alpha2/alpha1 and alpha/theta ratios. CONCLUSIONS: This study highlighted significant differences in EEG patterns in AD-MCI and PD-MCI patients and remarked the role of EEG parameters as possible surrogate markers of cognitive status in both neurodegenerative diseases. SIGNIFICANCE: In addition to well-established biomarkers, our findings could support early detection of cognitive dysfunction in neurodegenerative disorders and could help to monitor disease progression and therapeutic responses.