Digitization of Follow-Up Care in Orthopedic and Trauma Surgery With Video Consultations: Health Economic Evaluation Study From a Health Provider's Perspective.

BACKGROUND: Recommendations for health care digitization as issued with the Riyadh Declaration led to an uptake in telemedicine to cope with the COVID-19 pandemic. Evaluations based on clinical data are needed to support stakeholders' decision-making on the long-term implementation of digital health. OBJECTIVE: This health economic evaluation aims to provide the first German analysis of the suitability of video consultations in the follow-up care of patients in orthopedic and trauma surgery, investigate the financial impact on hospital operations and personnel costs, and provide a basis for decisions on digitizing outpatient care. METHODS: We conducted a randomized controlled trial that evaluated video consultations versus face-to-face consultations in the follow-up care of patients in orthopedic and trauma surgery at a German university hospital. We recruited 60 patients who had previously been treated conservatively or surgically for various knee or shoulder injuries. A digital health app and a browser-based software were used to conduct video consultations. The suitability of telemedicine was assessed using the Telemedicine Satisfaction Questionnaire and the EQ-5D-5L questionnaire. Economic analyses included average time spent by physician per consultation, associated personnel costs and capacities for additional treatable patients, and the break-even point for video consultation software fees. RESULTS: After 4 withdrawals in each arm, data from a total of 52 patients (telemedicine group: n=26; control group: n=26) were used for our analyses. In the telemedicine group, 77% (20/26) of all patients agreed that telemedicine provided for their health care needs, and 69% (18/26) found telemedicine an acceptable way to receive health care services. In addition, no significant difference was found in the change of patient utility between groups after 3 months (mean 0.02, SD 0.06 vs mean 0.07, SD 0.17; P=.35). Treatment duration was significantly shorter in the intervention group (mean 8.23, SD 4.45 minutes vs mean 10.92, SD 5.58 minutes; P=.02). The use of telemedicine saved 25% (€2.14 [US $2.35]/€8.67 [US $9.53]) in personnel costs and increased the number of treatable patients by 172 annually, assuming 2 hours of video consultations per week. Sensitivity analysis for scaling up video consultations to 10% of the hospital's outpatient cases resulted in personnel cost savings of €73,056 (US $ 80,275.39) for a senior physician. A total of 23 video consultations per month were required to recoup the software fees of telemedicine through reduced personnel costs (break-even point ranging from 12-38 in the sensitivity analysis). CONCLUSIONS: Our study supports stakeholders' decision-making on the long-term implementation of digital health by demonstrating that video consultations in the follow-up care of patients in orthopedic and trauma surgery result in cost savings and productivity gains for clinics with no negative impact on patient utility. TRIAL REGISTRATION: German Clinical Trials Register DRKS00023445; https://drks.de/search/en/trial/DRKS00023445.

Economic and Environmental Impact of Digital Health App Video Consultations in Follow-up Care for Patients in Orthopedic and Trauma Surgery in Germany: Randomized Controlled Trial.

BACKGROUND: Following the Riyadh Declaration, digital health technologies were prioritized in many countries to address the challenges of the COVID-19 pandemic. Digital health apps for telemedicine and video consultations help reduce potential disease spread in routine health care, including follow-up care in orthopedic and trauma surgery. In addition to the satisfaction, efficiency, and safety of telemedicine, its economic and environmental effects are highly relevant to decision makers, particularly for the goal of reaching carbon neutrality of health care systems. OBJECTIVE: This study aims to provide the first comprehensive health economic and environmental analysis of video consultations in follow-up care after knee and shoulder interventions in an orthopedic and trauma surgery department of a German university hospital. The analysis is conducted from a societal perspective. We analyze both economic and environmental impacts of video consultations, taking into account the goal of carbon neutrality for the German health care system by 2030. METHODS: We conducted a prospective randomized controlled trial comparing follow-up care with digital health app video consultations (intervention group) to conventional face-to-face consultations in the clinic (control group). Economic impact included the analysis of travel and time costs and production losses. Examination of the environmental impact comprised the emissions of greenhouse gases, carbon monoxide, volatile hydrocarbons, nitrogen oxides, and particulates, and the calculation of environmental costs. Sensitivity analysis included calculations with a higher cost per ton of carbon dioxide equivalent, which gives equal weight to the welfare of present and future generations. RESULTS: Data from 52 patients indicated that, from the patients' point of view, telemedicine helped reduce travel costs, time costs, and production losses, resulting in mean cost savings of €76.52 per video consultation. In addition, emissions of 11.248 kg of greenhouse gases, 0.070 kg of carbon monoxide, 0.011 kg of volatile hydrocarbons, 0.028 kg of nitrogen oxides, and 0.0004 kg of particulates could be saved per patient through avoided travel. This resulted in savings of environmental costs between €3.73 and €9.53 per patient. CONCLUSIONS: We presented the first comprehensive analysis of economic and environmental effects of telemedicine in the follow-up care of patients in orthopedic and trauma surgery in Germany. Video consultations were found to reduce the environmental footprint of follow-up care; saved travel costs, travel time, and time costs for patients; and helped to lower production losses. Our findings can support the decision-making on the use of digital health during and beyond the COVID-19 pandemic, providing decision makers with data for both economic and environmental effects. Thanks to the pragmatic design of our study, our findings can be applied to a wide range of clinical contexts and potential digital health applications that substitute outpatient hospital visits with video consultations. TRIAL REGISTRATION: German Clinical Trials Register DRKS00023445; https://tinyurl.com/4pcvhz4n.

An integrated mathematical model of the cardiovascular and respiratory response to exercise: model-building and comparison with reported models.

The use of physiological models in medicine allows the evaluation of new hypotheses, development of diagnosis and clinical treatment applications, and development of training and medical education tools, as well as medical device design. Although several mathematical models of physiological systems have been presented in the literature, few of them are able to predict the human cardiorespiratory response under physical exercise stimulus adequately. This paper aims to present the building and comparison of an integrated cardiorespiratory model focused on the prediction of the healthy human response under rest and aerobic exercise. The model comprises cardiovascular circulation, respiratory mechanics, and gas exchange system, as well as cardiovascular and respiratory controllers. Every system is based on previously reported physiological models and incorporates reported mechanisms related to the aerobic exercise dynamics. Experimental data of 30 healthy male volunteers undergoing a cardiopulmonary exercise test and simulated data from two of the most current and complete cardiorespiratory models were used to evaluate the performance of the presented model. Experimental design, processing, and exploratory analysis are described in detail. The simulation results were compared against the experimental data in steady state and in transient regime. The predictions of the proposed model closely mimic the experimental data, showing in overall the lowest prediction error (10.35%), the lowest settling times for cardiovascular and respiratory variables, and in general the fastest and similar responses in transient regime. These results suggest that the proposed model is suitable to predict the cardiorespiratory response of healthy adult humans under rest and aerobic exercise conditions.NEW & NOTEWORTHY This paper presents a new cardiorespiratory model focused on the prediction of the healthy human response under rest and aerobic dynamic exercise conditions. Simulation results of cardiorespiratory variables are compared against experimental data and two of the most current and complete cardiorespiratory models.

Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes' Location and Motion Artifacts Reduction for Wearable Monitoring Applications.

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by World Health Organization. Some wearables devices have been developed to monitor the Electrocardiographic in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an Electrocardiographic signal waveform comparison when the location of electrodes is changed, to find a electrodes' location that reduces distortion of interest signals. In addition, effects of motion artifacts and electrodes' location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain Electrocardiographic signals, the result was compared with a computational model of the heart behavior through the Ensemble Average Electrocardiographic, Dynamic Time Warping and Signal-to-Noise Ratio methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the Electrocardiographic signal from the patient's torso or back without a significant difference, and the electrodes position can be moved 6 cm at most from the suggested location by the Einthoven triangle in Mason-Likar's method.

An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education.

The traditional neurosurgical apprenticeship scheme includes the assessment of trainee's manual skills carried out by experienced surgeons. However, the introduction of surgical simulation technology presents a new paradigm where residents can refine surgical techniques on a simulator before putting them into practice in real patients. Unfortunately, in this new scheme, an experienced surgeon will not always be available to evaluate trainee's performance. For this reason, it is necessary to develop automatic mechanisms to estimate metrics for assessing manual dexterity in a quantitative way. Authors have proposed some hardware-software approaches to evaluate manual dexterity on surgical simulators. This paper presents IGlove, a wearable device that uses inertial sensors embedded on an elastic glove to capture hand movements. Metrics to assess manual dexterity are estimated from sensors signals using data processing and information analysis algorithms. It has been designed to be used with a neurosurgical simulator called Daubara NS Trainer, but can be easily adapted to another benchtop- and manikin-based medical simulators. The system was tested with a sample of 14 volunteers who performed a test that was designed to simultaneously evaluate their fine motor skills and the IGlove's functionalities. Metrics obtained by each of the participants are presented as results in this work; it is also shown how these metrics are used to automatically evaluate the level of manual dexterity of each volunteer.

Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation.

BACKGROUND: The quest for improved diagnosis and treatment in home health care models has led to the development of wearable medical devices for remote vital signs monitoring. An accurate signal and a high diagnostic yield are critical for the cost-effectiveness of wearable health care monitoring systems and their widespread application in resource-constrained environments. Despite technological advances, the information acquired by these devices can be contaminated by motion artifacts (MA) leading to misdiagnosis or repeated procedures with increases in associated costs. This makes it necessary to develop methods to improve the quality of the signal acquired by these devices. OBJECTIVE: We aimed to present a novel method for electrocardiogram (ECG) signal denoising to reduce MA. We aimed to analyze the method's performance and to compare its performance to that of existing approaches. METHODS: We present the novel Redundant denoising Independent Component Analysis method for ECG signal denoising based on the redundant and simultaneous acquisition of ECG signals and movement information, multichannel processing, and performance assessment considering the information contained in the signal waveform. The method is based on data including ECG signals from the patient's chest and back, the acquisition of triaxial movement signals from inertial measurement units, a reference signal synthesized from an autoregressive model, and the separation of interest and noise sources through multichannel independent component analysis. RESULTS: The proposed method significantly reduced MA, showing better performance and introducing a smaller distortion in the interest signal compared with other methods. Finally, the performance of the proposed method was compared to that of wavelet shrinkage and wavelet independent component analysis through the assessment of signal-to-noise ratio, dynamic time warping, and a proposed index based on the signal waveform evaluation with an ensemble average ECG. CONCLUSIONS: Our novel ECG denoising method is a contribution to converting wearable devices into medical monitoring tools that can be used to support the remote diagnosis and monitoring of cardiovascular diseases. A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices' cost-effectiveness and contributes to their widespread application.

Changes in brain activity of trainees during laparoscopic surgical virtual training assessed with electroencephalography.

OBJECTIVE: Evaluate changes in brain activity of trainees during laparoscopic surgical training from electroencephalographic (EEG) signals in an ecological scenario with few restrictions for the user. DESIGN: Longitudinal study with two follow-up measurements in the first and last session of a 4-week training with LapSim laparoscopic surgery simulator. Variables analyzed include EEG neuronal activations in theta and alpha bands, tasks performance measures, and subjective measures such as perception of mental workload. SETTING: Medical School, Universidad de Antioquia, Medellin, Colombia. PARTICIPANTS: First-year surgical residents (n = 16, age = 28.0 ± 2.6 years old, right-handed, 9 females) RESULTS: Significant improvements in tasks performance were found together with changes in neuronal activity over frontal and parietal cortex. These changes were also correlated with task performance through training sessions. CONCLUSIONS: The use of neurophysiological measures such as electroencephalography combined with source separation techniques allows evaluating neural changes associated with motor training. The experiment proposed in this work establishes less controlled recording conditions leading to a more realistic analysis scenario to cognitive assessment in residents training.

Multifunctional magnetite nanoparticles to enable delivery of siRNA for the potential treatment of Alzheimer's.

Therapeutic drugs for Alzheimer's disease have been extensively studied due to its recurrence and abundance among neurodegenerative diseases. It is thought that the accumulation of amyloid precursor protein (APP) products, a consequence of an up-regulation of the ß-site APP-cleaving enzyme 1 (BACE1), is the main triggering mechanism during the early stages of the disease. This study aims to explore the ability of a multifunctional conjugate based on magnetite nanoparticles for the cellular delivery of siRNA against the expression of the BACE1 gene. We immobilized the siRNA strand on PEGylated magnetite nanoparticles and investigated the effects on biocompatibility and efficacy of the conjugation. Similarly, we co-immobilized the translocating protein OmpA on PEGylated nanoparticles to enhance cellular uptake and endosomal escape. BACE1 suppression was statistically significant in HFF-1 cells, without any presence of a cytotoxic effect. The delivery of the nanoconjugate was achieved through endocytosis pathways, where endosome formation was likely escaped due to the proton-sponge effect characteristic of PEGylated nanoparticles or mainly by direct translocation in the case of OmpA/PEGylated nanoparticles.

Respiratory muscular response to obstructive maneuvers in non-invasively ventilated healthy subjects.

The hypothesis of this study is that muscular activity measured through surface electromyography (sEMG) is useful to estimate the work of breathing (WOB) and respiratory mechanics. Thirty-two healthy volunteers were non-invasively ventilated, and an airflow resistor was attached to the airway circuit. sEMG signals from diaphragm, intercostal and sternocleidomastoid muscles were processed and compared with WOB changes. The airway resistance was increased from a median of 9.58 to 22.51 cmH2O/L/s adding a resistance of 20 cmH2O/L/s, achieving the lower compliance too. The respiratory mechanics changes implied linear increases in WOB, with Pearson correlation of 88.43% respect to changes in resistance. Muscles increased their activity in agreement with changes of WOB, being higher the increment in diaphragm followed by sternocleidomastoid. The non-invasively monitored respiratory muscles activity allowed evaluating the changes in WOB when it depends on addition of obstructive loads, confirming that it could be used to improve the available respiratory mechanics and WOB monitoring tools.

Successful Object Encoding Induces Increased Directed Connectivity in Presymptomatic Early-Onset Alzheimer's Disease.

BACKGROUND: Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer's disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG. OBJECTIVE: To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach. METHODS: EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis. RESULTS: Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity. CONCLUSION: Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD.

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer's Disease Detected Using Quantitative Electroencephalography.

BACKGROUND: Presenilin-1 (PSEN1) mutations are the most common cause of familial early onset Alzheimer's disease (AD). The PSEN1 E280A (E280A) mutation has an autosomal dominant inheritance and is involved in the production of amyloid-ß. The largest family group of carriers with E280A mutation is found in Antioquia, Colombia. The study of mutation carriers provides a unique opportunity to identify brain changes in stages previous to AD. Electroencephalography (EEG) is a low cost and minimally invasiveness technique that enables the following of brain changes in AD. OBJECTIVE: To examine how previous reported differences in EEG for Theta and Alpha-2 rhythms in E280A subjects are related to specific regions in cortex and could be tracked across different ages. METHODS: EEG signals were acquired during resting state from non-carriers and carriers, asymptomatic and symptomatic subjects from E280A kindred from Antioquia, Colombia. Independent component analysis (ICA) and inverse solution methods were used to locate brain regions related to differences in Theta and Alpha-2 bands. RESULTS: ICA identified two components, mainly related to the Precuneus, where the differences in Theta and Alpha-2 exist simultaneously at asymptomatic and symptomatic stages. When the ratio between Theta and Alpha-2 is used, significant correlations exist with age and a composite cognitive scale. CONCLUSION: Theta and Alpha-2 rhythms are altered in E280A subjects. The alterations are possible to track at Precuneus regions using EEG, ICA, and inverse solution methods.

Cambios en la mecánica ventilatoria debidos a variaciones de la PEEP y la presión soporte: estudio en sujetos sanos bajo ventilación mecánica no invasiva / Changes in ventilatory mechanics caused by variations in PEEP and pressure support: study in healthy subjects under non-invasive mechanical ventilation

Resumen Introducción. Por lo general, la mecánica ventilatoria se ha estimado en modo controlado con el uso de aproximaciones no adecuadas para ventilación espontánea. Objetivo. Medir los cambios de la mecánica ventilatoria ante variaciones de la presión positiva al final de la expiración (PEEP, por su sigla en inglés) y la presión soporte (PS) en ventilación mecánica no invasiva. Materiales y métodos. A través de una estrategia no invasiva, se estimó la mecánica ventilatoria bajo diferentes niveles de PEEP y PS. Para tal fin, se utilizó un simulador mecánico y se registró una base de datos de 14 sujetos sanos conectados de manera no invasiva a un ventilador mecánico. Resultados. Se obtuvieron valores medianos de resistencia y compliancia de 91.2[77.8-135.9]mL/cmH2O y 8.3[6.1-10.4]cmH2O/L/s para los 14 sujetos sanos con PEEP y PS de 0 cmH2O, respectivamente. En los incrementos de PEEP, los sujetos presentaron aumento estadísticamente significativo en la compliancia. Por el contrario, en el incremento de presión soporte, no se observaron cambios de ningún parámetro. Conclusiones. Se encontraron valores de compliancia y resistencia, acordes con los configurados en el simulador mecánico y coherentes con los reportados en la literatura en el caso de sujetos sanos. Esto resulta de gran utilidad al tomar decisiones en unidades de cuidados intensivos.

Abstract Introduction: Traditionally, ventilatory mechanics has been delivered in controlled modes through the use of inappropriate approaches for spontaneous ventilation. Objective: To measure the changes of ventilatory mechanics caused by PEEP and pressure support (PS) variations in non-invasive mechanical ventilation. Materials and methods: The ventilatory mechanics was evaluated through a non-invasive strategy, under different PEEP and pressure support levels. For this purpose, a mechanical simulator was used, and a database of 14 healthy subjects non-invasively connected to a mechanical ventilator was recorded. Results: For the 14 healthy subjects under PEEP and pressure support conditions of 0 cmH2O, the median resistance and compliance values were 91.2 [77.8-135.9] mL/cmH2O and 8.3[6.1-10.4]cmH2O/L/s, respectively. PEEP compliance showed a statistically significant increase in all subjects. On the other hand, no changes in any of the parameters were observed regarding pressure support increase. Conclusions: The proposed technique allowed to find compliance and resistance values consistent with those set in the mechanical simulator, which, in turn, coincide with those reported in the literature for healthy subjects. This information is useful for decision-making in intensive care units.