Publications

We report the fabrication and characterization of a highly sensitive pressure sensor that has been successfully tested using 3D-bioprinted skeletal muscle tissue. The proposed pressure sensor consists of two assembled 3D printed specimens, which were obtained using 60/40 v/v poly(3,4-ethylenedioxythiophene):polystyrene sulfonic acid (PEDOT:PSS) / poly(ethylene glycol) diacrylate (PEGDA) mixture, placed between two indium tin oxidecoated polyethylene terephthalate (PET-ITO) films. The printed specimens were shaped with a serrated structure, improving the sensitivity of the contact when pressed against PET-ITO film. Initially, the performance of the fabricated pressure sensor was tested using light cylindrical weights, which corresponded to pressures ranging from 0.99 to 14.71 kPa, and as prove of concept, carefully pressing with the finger (from 2.91 to 6.81 kPa). As the sensitivity and fast response of sensor were compatible with detection of soft muscle contractions, 3D-bioprinted skeletal muscle bioactuators were manufactured using myoblast cells. The contractions of the bioactuators, which were induced using electrical stimulation, exerted a pressure of 1.5 kPa only that was clearly and precisely detected by the sensor. Overall, the potential application of proposed pressure sensor for wearable and biomedical devices is evidenced by demonstrating its fast response time (< 50 ms) and sensitivity.

JTD Keywords: 4-ethylenedioxythiophene), Bioactuator, Healt, Hydrogels, Poly(3, Poly(ethylene glycol) diacrylate, Raman-spectroscopy, Soft electronics, Wearable electronic

[No abstract available]

JTD Keywords: Breathing, Cost, Developed country, Developing countries, Developing country, Health care facility, Home monitoring, Human, Humans, Internet, Internet of things, Letter, Lowest income group, Lung function, Lung mechanics, Lung resistance, Mathematical model, Middle income country, Mobile applications, Non invasive procedure, Open source technology, Oscillometry, Pneumotachygraphy, Telemedicine

Microbial biofilms are complex three-dimensional structures where sessile microbes are embedded in a polymeric extracellular matrix. Their resistance toward the host immune system as well as to a diverse range of antimicrobial treatments poses a serious health and development threat, being in the top 10 global public health threats declared by the World Health Organization. In an effort to combat biofilm-related microbial infections, several strategies have been developed to independently eliminate biofilms or to complement conventional antibiotic therapies. However, their limitations leave room for other treatment alternatives, where the application of nanotechnology to biofilm eradication has gained significant relevance in recent years. Their small size, penetration efficiency, and the design flexibility that they present makes them a promising alternative for biofilm infection treatment, although they also present set-backs. This review aims to describe the main possibilities and limitations of nanomedicine against biofilms, while covering the main aspects of biofilm formation and study, and the current therapies for biofilm treatment. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

JTD Keywords: Anti-bacterial agents, Anti-infective agents, Antiinfective agent, Antimicrobial, Antimicrobials, Antimicrobials,bacteria,biofilm,infectious diseases,microorganism, Bacteria, Biofilm, Biofilm infections, Biofilms, Complex three dimensional structures, Diseases, Diverse range, Drug-delivery systems,in-vitro,cellular toxicity,nanoparticles,penetration,model,biocompatibility,perspectives,hyperthermia,diagnosi, Extracellular matrices, Global public health, Health risks, Infectious disease, Infectious diseases, Medical nanotechnology, Microbial biofilm, Microorganisms, Nanomedicine, Polymer, Polymers, Regulatory issues, Roadmap

BackgroundA repeated number of passes during mechanical thrombectomy leads to worse clinical outcomes in acute ischemic stroke. Initial experiences with the simultaneous double stent-retriever (double-SR) technique as the first-line treatment showed promising safety and efficacy results.ObjectiveTo characterize the potential benefits of using the double-SR as first-line technique as compared with the traditional single-SR approach.MethodsThree types of clot analogs (soft, moderately stiff, and stiff) were used to create terminal internal carotid artery (T-ICA=44) and middle cerebral artery (MCA=88) occlusions in an in vitro neurovascular model. Sixty-six cases were randomized into each treatment arm: single-SR or double-SR, in combination with a 0.071" distal aspiration catheter. A total of 132 in vitro thrombectomies were performed. Primary endpoints were the rate of first-pass recanalization (%FPR) and procedural-related distal emboli.ResultsFPR was achieved in 42% of the cases. Overall, double-SR achieved a significantly higher %FPR than single-SR (52% vs 33%, P=0.035). Both techniques showed similar %FPR in T-ICA occlusions (single vs double: 23% vs 27%, P=0.728). Double-SR significantly outperformed single-SR in MCA occlusions (63% vs 38%, P=0.019), most notably in saddle occlusions (64% vs 14%, P=0.011), although no significant differences were found in single-branch occlusions (64% vs 50%, P=0.275). Double-SR reduced the maximal size of the clot fragments migrating distally (Feret diameter=1.08±0.65 mm vs 2.05±1.14 mm, P=0.038).ConclusionsThis randomized in vitro evaluation demonstrates that the front-line double-SR technique is more effective than single-SR in achieving FPR when treating MCA bifurcation occlusions that present saddle thrombus.

JTD Keywords: endovascular treatment, guidelines, health, stroke, technique, thrombectomy, Acute ischemic-stroke, Stroke, Thrombectomy

This study explored the use of parasternal second intercostal space and lower intercostal space surface electromyogram (sEMG) and surface mechanomyogram (sMMG) recordings (sEMGpara and sMMGpara, and sEMGlic and sMMGlic, respectively) to assess neural respiratory drive (NRD), neuromechanical (NMC) and neuroventilatory (NVC) coupling, and mechanical efficiency (MEff) noninvasively in healthy subjects and chronic obstructive pulmonary disease (COPD) patients. sEMGpara, sMMGpara, sEMGlic, sMMGlic, mouth pressure (Pmo), and volume (Vi) were measured at rest, and during an inspiratory loading protocol, in 16 COPD patients (8 moderate and 8 severe) and 9 healthy subjects. Myographic signals were analyzed using fixed sample entropy and normalized to their largest values (fSEsEMGpara%max, fSEsMMGpara%max, fSEsEMGlic%max, and fSEsMMGlic%max). fSEsMMGpara%max, fSEsEMGpara%max, and fSEsEMGlic%max were significantly higher in COPD than in healthy participants at rest. Parasternal intercostal muscle NMC was significantly higher in healthy than in COPD participants at rest, but not during threshold loading. Pmo-derived NMC and MEff ratios were lower in severe patients than in mild patients or healthy subjects during threshold loading, but differences were not consistently significant. During resting breathing and threshold loading, Vi-derived NVC and MEff ratios were significantly lower in severe patients than in mild patients or healthy subjects. sMMG is a potential noninvasive alternative to sEMG for assessing NRD in COPD. The ratios of Pmo and Vi to sMMG and sEMG measurements provide wholly noninvasive NMC, NVC, and MEff indices that are sensitive to impaired respiratory mechanics in COPD and are therefore of potential value to assess disease severity in clinical practice. Author

JTD Keywords: biomedical measurement, chronic obstructive pulmonary disease, couplings, diaphragm, disease severity, efficiency, electromyography, exacerbations, healthy volunteers, inspiratory muscles, loading, mechanomyography, obstructive pulmonary-disease, pressure measurement, protocols, respiratory mechanics, respiratory muscles, responsiveness, spirometry, stimulation, volume measurement, At rests, Biomedical measurement, Biomedical measurements, Chronic obstructive pulmonary disease, Couplings, Disease severity, Efficiency ratio, Electromyography, Healthy subjects, Healthy volunteers, Loading, Mechanical efficiency, Mechanomyogram, Muscle, Muscles, Neural respiratory drive, Noninvasive medical procedures, Pressure measurement, Protocols, Pulmonary diseases, Surface electromyogram, Volume measurement

Background: There is a pressing need for scalable healthcare solutions and a shift in the rehabilitation paradigm from hospitals to homes to tackle the increase in stroke incidence while reducing the practical and economic burden for patients, hospitals, and society. Digital health technologies can contribute to addressing this challenge; however, little is known about their effectiveness in at-home settings. In response, we have designed the RGS@home study to investigate the effectiveness, acceptance, and cost of a deep tech solution called the Rehabilitation Gaming System (RGS). RGS is a cloud-based system for delivering Al-enhanced rehabilitation using virtual reality, motion capture, and wearables that can be used in the hospital and at home. The core principles of the brain theory-based RGS intervention are to deliver rehabilitation exercises in the form of embodied, goal-oriented, and task-specific action.; Methods: The RGS@home study is a randomized longitudinal clinical trial designed to assess whether the combination of the RGS intervention with standard care is superior to standard care alone for the functional recovery of stroke patients at the hospital and at home. The study is conducted in collaboration with hospitals in Spain, Sweden, and France and includes inpatients and outpatients at subacute and chronic stages post-stroke. The intervention duration is 3 months with assessment at baseline and after 3, 6, and 12 months. The impact of RGS is evaluated in terms of quality of life measurements, usability, and acceptance using standardized clinical scales, together with health economic analysis. So far, one-third of the patients expected to participate in the study have been recruited (N = 90, mean age 60, days after stroke >= 30 days). The trial will end in July 2023.; Discussion: We predict an improvement in the patients' recovery, high acceptance, and reduced costs due to a soft landing from the clinic to home rehabilitation. In addition, the data provided will allow us to assess whether the prescription of therapy at home can counteract deterioration and improve quality of life while also identifying new standards for online and remote assessment, diagnostics, and intervention across European hospitals.

JTD Keywords: deep tech, e-health, home treatment, motor recovery, randomized clinical trial, stroke, upper extremities, virtual reality, Deep tech, E-health, Functional recovery, Home treatment, Motor recovery, Randomized clinical trial, Stroke, Upper extremities, Virtual reality, Wearables

Aims: The aim of this rapid review and opinion paper is to present the state of the current evidence and present future directions for telehealth research and clinical service delivery for stroke rehabilitation. Methods: We conducted a rapid review of published trials in the field. We searched Medline using key terms related to stroke rehabilitation and telehealth or virtual care. We also searched clinical trial registers to identify key ongoing trials. Results: The evidence for telehealth to deliver stroke rehabilitation interventions is not strong and is predominantly based on small trials prone to Type 2 error. To move the field forward, we need to progress to trials of implementation that include measures of adoption and reach, as well as effectiveness. We also need to understand which outcome measures can be reliably measured remotely, and/or develop new ones. We present tools to assist with the deployment of telehealth for rehabilitation after stroke. Conclusion: The current, and likely long-term, pandemic means that we cannot wait for stronger evidence before implementing telehealth. As a research and clinical community, we owe it to people living with stroke internationally to investigate the best possible telehealth solutions for providing the highest quality rehabilitation.

JTD Keywords: rehabilitation, telehealth, Care, Feasibility, Rehabilitation, Telehealth, Trial, Virtual care

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

Patients with spinal cord injury (SCI) have an increased risk of sleep-disordered breathing (SDB), which can lead to serious comorbidities and impact patients’ recovery and quality of life. However, sleep tests are rarely performed on SCI patients, given their multiple health needs and the cost and complexity of diagnostic equipment. The objective of this study was to use a novel smartphone system as a simple non-invasive tool to monitor SDB in SCI patients. We recorded pulse oximetry, acoustic, and accelerometer data using a smartphone during overnight tests in 19 SCI patients and 19 able-bodied controls. Then, we analyzed these signals with automatic algorithms to detect desaturation, apnea, and hypopnea events and monitor sleep position. The apnea–hypopnea index (AHI) was significantly higher in SCI patients than controls (25 ± 15 vs. 9 ± 7, p < 0.001). We found that 63% of SCI patients had moderate-to-severe SDB (AHI ? 15) in contrast to 21% of control subjects. Most SCI patients slept predominantly in supine position, but an increased occurrence of events in supine position was only observed for eight patients. This study highlights the problem of SDB in SCI and provides simple cost-effective sleep monitoring tools to facilitate the detection, understanding, and management of SDB in SCI patients.

JTD Keywords: apnea syndrome, biomedical signal processing, individuals, mhealth, monitoring, nasal resistance, people, position, prevalence, questionnaire, sample, sleep apnea, sleep position, sleep-disordered breathing, smartphone, time, Apnea-hypopnea indices, Biomedical signal processing, Biomedical signals processing, Cost effectiveness, Diagnosis, Mhealth, Monitoring, Noninvasive medical procedures, Oximeters, Oxygen-saturation, Patient rehabilitation, Simple++, Sleep apnea, Sleep position, Sleep research, Sleep-disordered breathing, Smart phones, Smartphone, Smartphones, Spinal cord injury, Spinal cord injury patients

Poor sleep quality or disturbed sleep is associated with multiple health conditions. Sleep position affects the severity and occurrence of these complications, and positional therapy is one of the less invasive treatments to deal with them. Sleep positions can be self-reported, which is unreliable, or determined by using specific devices, such as polysomnography, polygraphy or cameras, that can be expensive and difficult to employ at home. The aim of this study is to determine how smartphones could be used to monitor and treat sleep position at home. We divided our research into three tasks: (1) develop an Android smartphone application (‘SleepPos’ app) which monitors angle-based high-resolution sleep position and allows to simultaneously apply positional treatment; (2) test the smartphone application at home coupled with a pulse oximeter; and (3) explore the potential of this tool to detect the positional occurrence of desaturation events. The results show how the ‘SleepPos’ app successfully determined the sleep position and revealed positional patterns of occurrence of desaturation events. The ‘SleepPos’ app also succeeded in applying positional therapy and preventing the subjects from sleeping in the supine sleep position. This study demonstrates how smartphones are capable of reliably monitoring high-resolution sleep position and provide useful clinical information about the positional occurrence of desaturation events.

JTD Keywords: accelerometry, android, apnea patients, app, association, biomedical signal processing, management, mhealth, monitoring, pathophysiology, pilot mhealth, questionnaire, sleep position, smartphone, supine position, time, Accelerometry, Android, App, Biomedical signal processing, Mhealth, Monitoring, Sleep position, Smart-phone, Smartphone, Tennis ball technique

Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG.

JTD Keywords: accelerometry, actigraphy, association, biomedical signal processing, index, latency, mhealth, monitoring, pathophysiology, quality, questionnaire, score, sleep apnea, sleep position, smartphone, time, Accelerometry, Biomedical signal processing, Mhealth, Monitoring, Sleep apnea, Sleep position, Smartphone, Supine position

Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. OSA is also known to be position-dependent in some patients, which is referred to as positional OSA (pOSA). Screening for pOSA is necessary in order to design more personalized and effective treatment strategies. In this article, we propose analyzing accelerometry signals, recorded with a smartphone, to detect and monitor OSA at home. Our objectives were to: (1) develop an algorithm for detecting thoracic movement associated with disordered breathing events; (2) compare the performance of smartphones as OSA monitoring tools with a type 3 portable sleep monitor; and (3) explore the feasibility of using smartphone accelerometry to retrieve reliable patient sleep position data and assess pOSA. Accelerometry signals were collected through simultaneous overnight acquisition using both devices with 13 subjects. The smartphone tool showed a high degree of concordance compared to the portable device and succeeded in estimating the apnea-hypopnea index (AHI) and classifying the severity level in most subjects. To assess the agreement between the two systems, an event-by-event comparison was performed, which found a sensitivity of 90% and a positive predictive value of 80%. It was also possible to identify pOSA by determining the ratio of events occurring in a specific position versus the time spent in that position during the night. These novel results suggest that smartphones are promising mHealth tools for OSA and pOSA monitoring at home.

JTD Keywords: Accelerometry, Biomedical signal processing, mHealth, Monitoring, Sleep apnea, Sleep position, Smartphone

Background: Home hospitalization is widely accepted as a cost-effective alternative to conventional hospitalization for selected patients. A recent analysis of the home hospitalization and early discharge (HH/ED) program at Hospital Clínic de Barcelona over a 10-year period demonstrated high levels of acceptance by patients and professionals, as well as health value-based generation at the provider and health-system levels. However, health risk assessment was identified as an unmet need with the potential to enhance clinical decision making. Objective: The objective of this study is to generate and assess predictive models of mortality and in-hospital admission at entry and at HH/ED discharge. Methods: Predictive modeling of mortality and in-hospital admission was done in 2 different scenarios: at entry into the HH/ED program and at discharge, from January 2009 to December 2015. Multisource predictive variables, including standard clinical data, patients’ functional features, and population health risk assessment, were considered. Results: We studied 1925 HH/ED patients by applying a random forest classifier, as it showed the best performance. Average results of the area under the receiver operating characteristic curve (AUROC; sensitivity/specificity) for the prediction of mortality were 0.88 (0.81/0.76) and 0.89 (0.81/0.81) at entry and at home hospitalization discharge, respectively; the AUROC (sensitivity/specificity) values for in-hospital admission were 0.71 (0.67/0.64) and 0.70 (0.71/0.61) at entry and at home hospitalization discharge, respectively. Conclusions: The results showed potential for feeding clinical decision support systems aimed at supporting health professionals for inclusion of candidates into the HH/ED program, and have the capacity to guide transitions toward community-based care at HH discharge.

JTD Keywords: Home hospitalization, Health risk assessment, Predictive modeling, Chronic care, Integrated care, Modeling, Hospitalization, Health risk, Prediction, Mortality, Clinical decision support

Bioimpedance has been widely studied as alternative to respiratory monitoring methods because of its linear relationship with respiratory volume during normal breathing. However, other body tissues and fluids contribute to the bioimpedance measurement. The objective of this study is to investigate the relevance of chest movement in thoracic bioimpedance contributions to evaluate the applicability of bioimpedance for respiratory monitoring. We measured airflow, bioimpedance at four electrode configurations and thoracic accelerometer data in 10 healthy subjects during inspiratory loading. This protocol permitted us to study the contributions during different levels of inspiratory muscle activity. We used chest movement and volume signals to characterize the bioimpedance signal using linear mixed-effect models and neural networks for each subject and level of muscle activity. The performance was evaluated using the Mean Average Percentage Errors for each respiratory cycle. The lowest errors corresponded to the combination of chest movement and volume for both linear models and neural networks. Particularly, neural networks presented lower errors (median below 4.29%). At high levels of muscle activity, the differences in model performance indicated an increased contribution of chest movement to the bioimpedance signal. Accordingly, chest movement contributed substantially to bioimpedance measurement and more notably at high muscle activity levels.

JTD Keywords: Diagnosis, Health care

Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Here we propose analyzing smartphone audio signals for screening OSA patients at home. Our objectives were to: (1) develop an algorithm for detecting silence events and classifying them into apneas or hypopneas; (2) evaluate the performance of this system; and (3) compare the information provided with a type 3 portable sleep monitor, based mainly on nasal airflow. Overnight signals were acquired simultaneously by both systems in 13 subjects (3 healthy subjects and 10 OSA patients). The sample entropy of audio signals was used to identify apnea/hypopnea events. The apnea-hypopnea indices predicted by the two systems presented a very high degree of concordance and the smartphone correctly detected and stratified all the OSA patients. An event-by-event comparison demonstrated good agreement between silence events and apnea/hypopnea events in the reference system (Sensitivity = 76%, Positive Predictive Value = 82%). Most apneas were detected (89%), but not so many hypopneas (61%). We observed that many hypopneas were accompanied by snoring, so there was no sound reduction. The apnea/hypopnea classification accuracy was 70%, but most discrepancies resulted from the inability of the nasal cannula of the reference device to record oral breathing. We provided a spectral characterization of oral and nasal breathing to correct this effect, and the classification accuracy increased to 82%. This novel knowledge from acoustic signals may be of great interest for clinical practice to develop new non-invasive techniques for screening and monitoring OSA patients at home.

JTD Keywords: Sleep apnea, Acoustics, Monitoring, Entropy, Sensors, Microphones, Acoustics, Biomedical signal processing, mHealth, Monitoring, Sleep apnea, Smartphone

Home hospitalization (HH) is presented as a healthcare alternative capable of providing high standards of care when patients no longer need hospital facilities. Although HH seems to lower healthcare costs by shortening hospital stays and improving patient's quality of life, the lack of continuous observation at home may lead to complications in some patients. Since blood tests have been proven to provide relevant prognosis information in many diseases, this paper analyzes the impact of different sampling methods on the prediction of HH outcomes. After a first exploratory analysis, some variables extracted from routine blood tests performed at the moment of HH admission, such as hemoglobin, lymphocytes or creatinine, were found to unmask statistically significant differences between patients undergoing successful and unsucessful HH stays. Then, predictive models were built with these data, in order to identify unsuccessful cases eventually needing hospital facilities. However, since these hospital admissions during HH programs are rare, their identification through conventional machine-learning approaches is challenging. Thus, several sampling strategies designed to face class imbalance were herein overviewed and compared. Among the analyzed approaches, over-sampling strategies, such as ROSE (Random Over-Sampling Examples) and conventional random over-sampling, showed the best performances. Nevertheless, further improvements should be proposed in the future so as to better identify those patients not benefiting from HH.

JTD Keywords: Hospitals, Blood, Training, Standards, Diseases, Prognostics and health management

Introduction: Continuous positive airway pressure (CPAP) is the first-choice treatment for obstructive sleep apnoea (OSA), but adherence is frequently suboptimal. Innovative, patient-centred interventions are, therefore, needed to enhance compliance. Due to its low cost and ubiquity, mobile health (mHealth) technology seems particularly suited for this purpose. We endeavoured to develop an mHealth application called “APPnea,” aimed at promoting patient self-monitoring of CPAP treatment. We then assessed the feasibility and acceptability of APPnea in a group of OSA patients. Methods: Consecutive OSA patients used APPnea for six weeks. APPnea gave patients daily reminders to answer three questions about their OSA treatment (CPAP use, physical activity, and diet) and prompted them to upload their body weight weekly. Answers were saved to a secure server for further analysis. After completing the study, patients gave their anonymous opinions about APPnea. Results: We enrolled 60 patients with OSA receiving CPAP treatment. The mean age was 56 ± 10 years and the apnoea–hypopnea index was 47 ± 25 events/hour. In total, 63% of participants completed the daily questionnaire for more than 66% of the study period. Objective CPAP compliance was generally high (5.3 ± 1.6 hours/night). In a subset of 38 patients naïve to CPAP, those who used APPnea regularly had significantly higher CPAP compliance. Satisfaction levels were high for the majority of users. Conclusion: This mHealth intervention is not only feasible but also satisfactory to patients. Although larger randomized trials and cost-effectiveness studies should be performed, this study shows that APPnea could promote participation and improve compliance among patients with OSA, thereby improving outcomes.

JTD Keywords: CPAP, MHealth, Sleep apnoea, Smartphone application

Lung disease models are useful to study how cell engraftment, proliferation and differentiation are modulated in lung bioengineering. The aim of this work was to characterize the local stiffness of decellularized lungs in aged and fibrotic mice. Mice (2- and 24-month old; 14 of each) with lung fibrosis (N=20) and healthy controls (N=8) were euthanized after 11 days of intratracheal bleomycin (fibrosis) or saline (controls) infusion. The lungs were excised, decellularized by a conventional detergent-based (sodium-dodecyl sulfate) procedure and slices of the acellular lungs were prepared to measure the local stiffness by means of atomic force microscopy. The local stiffness of the different sites in acellular fibrotic lungs was very inhomogeneous within the lung and increased according to the degree of the structural fibrotic lesion. Local stiffness of the acellular lungs did not show statistically significant differences caused by age. The group of mice most affected by fibrosis exhibited local stiffness that were ~2-fold higher than in the control mice: from 27.2±1.64 to 64.8±7.1. kPa in the alveolar septa, from 56.6±4.6 to 99.9±11.7. kPa in the visceral pleura, from 41.1±8.0 to 105.2±13.6. kPa in the tunica adventitia, and from 79.3±7.2 to 146.6±28.8. kPa in the tunica intima. Since acellular lungs from mice with bleomycin-induced fibrosis present considerable micromechanical inhomogeneity, this model can be a useful tool to better investigate how different degrees of extracellular matrix lesion modulate cell fate in the process of organ bioengineering from decellularized lungs.

JTD Keywords: Ageing, Atomic force microscopy, Decellularization, Lung fibrosis, Tissue engineering, Atomic force microscopy, Biological organs, Peptides, Sodium dodecyl sulfate, Sodium sulfate, Tissue engineering, Ageing, Decellularization, Extracellular matrices, Healthy controls, Inhomogeneities, Lung fibrosis, Micro-mechanical, Statistically significant difference, Mammals, bleomycin, adventitia, animal experiment, animal model, article, atomic force microscopy, bleomycin-induced pulmonary fibrosis, cell fate, controlled study, extracellular matrix, female, intima, lung alveolus, lung fibrosis, lung mechanics, mechanical probe, microenvironment, mouse, nonhuman, pleura, priority journal, rigidity, tissue engineering

Even if the performance of a given ventilator has been evaluated in the laboratory under very well controlled conditions, inappropriate maintenance and lack of long-term stability and accuracy of the ventilator sensors may lead to ventilation errors in actual clinical practice. The aim of this study was to evaluate the actual performances of ventilators during clinical routines. A resistance (7.69 cmH(2)O/L/s) - elastance (100 mL/cmH(2)O) test lung equipped with pressure, flow, and oxygen concentration sensors was connected to the Y-piece of all the mechanical ventilators available for patients in four intensive care units (ICUs; n = 66). Ventilators were set to volume-controlled ventilation with tidal volume = 600 mL, respiratory rate = 20 breaths/minute, positive end-expiratory pressure (PEEP) = 8 cmH(2)O, and oxygen fraction = 0.5. The signals from the sensors were recorded to compute the ventilation parameters. The average standard deviation and range (min-max) of the ventilatory parameters were the following: inspired tidal volume = 607 36 (530-723) mL, expired tidal volume = 608 36 (530-728) mL, peak pressure = 20.8 2.3 (17.2-25.9) cmH(2)O, respiratory rate = 20.09 0.35 (19.5-21.6) breaths/minute, PEEP = 8.43 0.57 (7.26-10.8) cmH(2)O, oxygen fraction = 0.49 0.014 (0.41-0.53). The more error-prone parameters were the ones related to the measure of flow. In several cases, the actual delivered mechanical ventilation was considerably different from the set one, suggesting the need for improving quality control procedures for these machines.

JTD Keywords: Equipment and supplies, Medical devices, Intravenous, Quality assurance, Health care quality assessment, Ventilator accuracy, Ventilation error

Background: Home continuous positive airway pressure (CPAP) titration with automatic devices is not possible in a non-negligible percentage of patients with sleep apnea-hypopnea syndrome (SAHS). Objectives: To test the feasibility of a novel telemetric system for home CPAP titration. Methods: One-night home CPAP titration was carried out on 20 SAHS patients (56 +/- 3 years; BMI = 35 +/- 2 kg/m(2)). A telemetric unit, based on the conventional GPRS mobile phone network and connected to a commercial CPAP device, allowed the hospital technician to monitor flow, pressure and air leaks by remote control and titrate CPAP (elimination of apneas, hypopneas, flow limitation and snoring) in real time. After 1 week, a full hospital polysomnography was performed while the patient was subjected to the value of CPAP that was previously titrated at home via telemetry. Results: The home-titrated CPAP systematically improved patients' breathing: the apnea-hypopnea index and percentage of sleep time with arterial oxygen saturation below 90% were reduced from 58.1 +/- 5.1 to 3.8 +/- 0.6 events/h and from 19.8 +/- 1.1% to 4.4 +/- 0.7%, respectively. This CPAP value (9.15 +/- 0.47 cmH(2)O) was virtually the same as the pressure that optimized breathing during hospital polysomnography (9.20 +/- 0.41 cmH(2)O; mean difference: 0.02 cmH(2)O, limits of agreement: +/- 1.00 cmH(2)O). Conclusions: This pilot study shows that a simple telemetric system, requiring neither a special telemedicine network nor any infrastructure in the patient's home, made it possible to perform effective remote CPAP titration on SAHS patients.

JTD Keywords: Home CPAP titration by telemetry, Telecare, Telemedicine, E-health, Obstructive sleep apnea, Point of care