by Keyword: Mechanical Ventilation
Pinto J, González H, Arizmendi C, Muñoz Y, Giraldo BF, (2023). Analysis of the Cardiorespiratory Pattern of Patients Undergoing Weaning Using Artificial Intelligence International Journal Of Environmental Research And Public Health 20, 4430
The optimal extubating moment is still a challenge in clinical practice. Respiratory pattern variability analysis in patients assisted through mechanical ventilation to identify this optimal moment could contribute to this process. This work proposes the analysis of this variability using several time series obtained from the respiratory flow and electrocardiogram signals, applying techniques based on artificial intelligence. 154 patients undergoing the extubating process were classified in three groups: successful group, patients who failed during weaning process, and patients who after extubating failed before 48 hours and need to reintubated. Power Spectral Density and time-frequency domain analysis were applied, computing Discrete Wavelet Transform. A new Q index was proposed to determine the most relevant parameters and the best decomposition level to discriminate between groups. Forward selection and bidirectional techniques were implemented to reduce dimensionality. Linear Discriminant Analysis and Neural Networks methods were implemented to classify these patients. The best results in terms of accuracy were, 84.61 ± 3.1% for successful versus failure groups, 86.90 ± 1.0% for successful versus reintubated groups, and 91.62 ± 4.9% comparing the failure and reintubated groups. Parameters related to Q index and Neural Networks classification presented the best performance in the classification of these patients.
JTD Keywords: Mechanical ventilation, Neural networks, Wavelet transform, Weaning
Farre, R, Rodriguez-Lazaro, MA, Gozal, D, Trias, G, Solana, G, Navajas, D, Otero, J, (2022). Simple low-cost construction and calibration of accurate pneumotachographs for monitoring mechanical ventilation in low-resource settings Frontiers Of Medicine 9, 938949
Assessing tidal volume during mechanical ventilation is critical to improving gas exchange while avoiding ventilator-induced lung injury. Conventional flow and volume measurements are usually carried out by built-in pneumotachographs in the ventilator or by stand-alone flowmeters. Such flow/volume measurement devices are expensive and thus usually unaffordable in low-resource settings. Here, we aimed to design and test low-cost and technically-simple calibration and assembly pneumotachographs. The proposed pneumotachographs are made by manual perforation of a plate with a domestic drill. Their pressure-volume relationship is characterized by a quadratic equation with parameters that can be tailored by the number and diameter of the perforations. We show that the calibration parameters of the pneumotachographs can be measured through two maneuvers with a conventional resuscitation bag and by assessing the maneuver volumes with a cheap and straightforward water displacement setting. We assessed the performance of the simplified low-cost pneumotachographs to measure flow/volume during mechanical ventilation as carried out under typical conditions in low-resource settings, i.e., lacking gold standard expensive devices. Under realistic mechanical ventilation settings (pressure- and volume-control; 200-600 mL), inspiratory tidal volume was accurately measured (errors of 2.1% on average and <4% in the worst case). In conclusion, a simple, low-cost procedure facilitates the construction of affordable and accurate pneumotachographs for monitoring mechanical ventilation in low- and middle-income countries.
JTD Keywords: Calibration, Flow, Flow measurement, Low- and middle-income countries, Lung injury, Mechanical ventilation, Pneumotachograph, Pressure-drop, Resistance, Tidal volume
Arboleda A, Amado L, Rodriguez J, Naranjo F, Giraldo BF, (2021). A new protocol to compare successful versus failed patients using the electromyographic diaphragm signal in extubation process Conference Proceedings : ... Annual International Conference Of The Ieee Engineering In Medicine And Biology Society. Ieee Engineering In Medicine And Biology Society. Conference , 5646-5649
In clinical practice, when a patient is undergoing mechanical ventilation, it is important to identify the optimal moment for extubation, minimizing the risk of failure. However, this prediction remains a challenge in the clinical process. In this work, we propose a new protocol to study the extubation process, including the electromyographic diaphragm signal (diaEMG) recorded through 5-channels with surface electrodes around the diaphragm muscle. First channel corresponds to the electrode on the right. A total of 40 patients in process of withdrawal of mechanical ventilation, undergoing spontaneous breathing tests (SBT), were studied. According to the outcome of the SBT, the patients were classified into two groups: successful (SG: 19 patients) and failure (FG: 21 patients) groups. Parameters extracted from the envelope of each channel of diaEMG in time and frequency domain were studied. After analyzing all channels, the second presented maximum differences when comparing the two groups of patients, with parameters related to root mean square (p = 0.005), moving average (p = 0.001), and upward slope (p = 0.017). The third channel also presented maximum differences in parameters as the time between maximum peak (p = 0.004), and the skewness (p = 0.027). These results suggest that diaphragm EMG signal could contribute to increase the knowledge of the behaviour of respiratory system in these patients and improve the extubation process.Clinical Relevance - This establishes the characterization of success and failure patients in the extubation process. © 2021 IEEE.
JTD Keywords: classification, recognition, Airway extubation, Artificial ventilation, Clinical practices, Clinical process, Diaphragm, Diaphragm muscle, Diaphragms, Electrodes, Electromyographic, Extubation, Frequency domain analysis, Human, Humans, Maximum differences, Mechanical ventilation, New protocol, Respiration, artificial, Respiratory system, Risk of failure, Spontaneous breathing, Surface electrode, Surface emg signals, Thorax, Ventilation, Ventilator weaning
Sarlabous, L., Estrada, L., Cerezo-Hernández, A., Leest, Sietske V. D., Torres, A., Jané, R., Duiverman, M., Garde, Ainara, (2019). Electromyography-based respiratory onset detection in COPD patients on non-invasive mechanical ventilation Entropy 21, (3), 258
To optimize long-term nocturnal non-invasive ventilation in patients with chronic obstructive pulmonary disease, surface diaphragm electromyography (EMGdi) might be helpful to detect patient-ventilator asynchrony. However, visual analysis is labor-intensive and EMGdi is heavily corrupted by electrocardiographic (ECG) activity. Therefore, we developed an automatic method to detect inspiratory onset from EMGdi envelope using fixed sample entropy (fSE) and a dynamic threshold based on kernel density estimation (KDE). Moreover, we combined fSE with adaptive filtering techniques to reduce ECG interference and improve onset detection. The performance of EMGdi envelopes extracted by applying fSE and fSE with adaptive filtering was compared to the root mean square (RMS)-based envelope provided by the EMG acquisition device. Automatic onset detection accuracy, using these three envelopes, was evaluated through the root mean square error (RMSE) between the automatic and mean visual onsets (made by two observers). The fSE-based method provided lower RMSE, which was reduced from 298 ms to 264 ms when combined with adaptive filtering, compared to 301 ms provided by the RMS-based method. The RMSE was negatively correlated with the proposed EMGdi quality indices. Following further validation, fSE with KDE, combined with adaptive filtering when dealing with low quality EMGdi, indicates promise for detecting the neural onset of respiratory drive.
JTD Keywords: Fixed sample entropy, Adaptive filtering, Root mean square, Diaphragm electromyography, Non-invasive mechanical ventilation, Chronic obstructive pulmonary disease
Nonaka, P. N., Campillo, N., Uriarte, J. J., Garreta, E., Melo, E., de Oliveira, L. V. F., Navajas, D., Farré, R., (2014). Effects of freezing/thawing on the mechanical properties of decellularized lungs Journal of Biomedical Materials Research - Part A , 102, (2), 413-419
Lung bioengineering based on decellularized organ scaffolds is a potential alternative for transplantation. Freezing/thawing, a usual procedure in organ decellularization and storage could modify the mechanical properties of the lung scaffold and reduce the performance of the bioengineered lung when subjected to the physiological inflation-deflation breathing cycles. The aim of this study was to determine the effects of repeated freezing/thawing on the mechanical properties of decellularized lungs in the physiological pressure-volume regime associated with normal ventilation. Fifteen mice lungs (C57BL/6) were decellularized using a conventional protocol not involving organ freezing and based on sodium dodecyl sulfate detergent. Subsequently, the mechanical properties of the acellular lungs were measured before and after subjecting them to three consecutive cycles of freezing/thawing. The resistance (RL) and elastance (EL) of the decellularized lungs were computed by linear regression fitting of the recorded signals (tracheal pressure, flow, and volume) during mechanical ventilation. RL was not significantly modified by freezing-thawing: from 0.88 Â± 0.37 to 0.90 Â± 0.38 cmH2OÂ·sÂ·mL-1 (mean Â± SE). EL slightly increased from 64.4 Â± 11.1 to 73.0 Â± 16.3 cmH2OÂ·mL-1 after the three freeze-thaw cycles (p = 0.0013). In conclusion, the freezing/thawing process that is commonly used for both organ decellularization and storage induces only minor changes in the ventilation mechanical properties of the organ scaffold.
JTD Keywords: Elastance, Freezing/thawing, Lung bioengineering, Lung decellularization, Mechanical ventilation, Organ scaffold
Correa, L.S., Giraldo, B., Correa, R., Arini, P.D., Laciar, E., (2014). Estudio de la pausa espiratoria en pacientes con enfermedades obstructivas en proceso de desconexión de la ventilación mecánica IFMBE Proceedings VI Latin American Congress on Biomedical Engineering (CLAIB 2014) , Springer (Paraná, Argentina) 49, 705-708
In this work, the flow signal Expiratory Pause (EP) temporal analysis is used in 18 patients with obstructive lung diseases going through spontaneous breathing trial at weaning process. The main objective was to identify the patients who were successfully disconnected (success group: 9 patients), and those who were not (failure and reintubated group: 9 patients). A variable selection stage was done by mean group comparison and step wise variable inclusion, leading to a 3 parameters set: EP time median; cycle time mean; and median absolute deviation of the EP maxima local number. Next, this set was used in a classifier based on linear discriminant analysis, which results in 17 patients (94.4%) correctly classified, with 88.9% of specificity (Sp) and 100% of sensitivity (Se). Finally, applying the leave-one-out cross validation method, results were 88.9% of correctly classified patients (Sp=77.8% and Se=100%). In conclusion, the proposed parameters showed a good performance and could be used to help therapists to wean patients with obstructive diseases.
JTD Keywords: Chronic Obstructive Pulmonary Disease (COPD), Weaning, Mechanical ventilation, Expiratory pause
Giraldo, B. F., Chaparro, J. A., Caminal, P., Benito, S., (2013). Characterization of the respiratory pattern variability of patients with different pressure support levels Engineering in Medicine and Biology Society (EMBC) 35th Annual International Conference of the IEEE , IEEE (Osaka, Japan) , 3849-3852
One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity.
JTD Keywords: autoregressive moving average processes, feature extraction, medical signal processing, patient care, pneumodynamics, signal classification, support vector machines, time series, ARX, autoregressive modeling techniques, autoregressive models with exogenous input, autoregressive moving average model, breath duration time series, classification method, classifier method, discontinuing mechanical ventilation, expiratory time, feature extraction, final prediction errors, fractional inspiratory time, intensive care, interquartile range, linear discriminant analysis, logistic regression analysis, mean inspiratory flow, patient respiratory volume signal, pressure support level, pressure support ventilation, rapid shallow breathing, respiratory pattern variability characterization, support vector machines, tidal volume, weaning trial, Analytical models, Autoregressive processes, Biological system modeling, Estimation, Support vector machines, Time series analysis, Ventilation
Gonzalez, H., Acevedo, H., Arizmendi, C., Giraldo, B. F., (2013). Methodology for determine the moment of disconnection of patients of the mechanical ventilation using discrete wavelet transform Complex Medical Engineering (CME) 2013 ICME International Conference , IEEE (Beijing, China) , 483-486
The process of weaning from mechanical ventilation is one of the challenges in intensive care units. 66 patients under extubation process (T-tube test) were studied: 33 patients with successful trials and 33 patients who failed to maintain spontaneous breathing and were reconnected. Each patient was characterized using 7 time series from respiratory signals, and for each serie was evaluated the discrete wavelet transform. It trains a neural network for discriminating between patients from the two groups.
JTD Keywords: discrete wavelet transforms, neural nets, patient treatment, pneumodynamics, time series, ventilation, T-tube test, discrete wavelet transform, extubation process, intensive care units, mechanical ventilation, moment of disconnection, neural network, patients, respiratory signals, spontaneous breathing, time series, weaning, Mechanical Ventilation, Neural Networks, Time series from respiratory signals, Wavelet Transform
Chimenti, L., Luque, T., Bonsignore, M. R., Ramirez, J., Navajas, D., Farre, R., (2012). Pre-treatment with mesenchymal stem cells reduces ventilator-induced lung injury European Respiratory Journal 40, (4), 939-948
Bone marrow-derived mesenchymal stem cells (MSCs) reduce acute lung injury in animals challenged by bleomycin or bacterial lipopolysaccaride. It is not known, however, whether MSCs protect from ventilator-induced lung injury (VILI). This study investigated whether MSCs have a potential role in preventing or modulating VILI in healthy rats subjected to high-volume ventilation. 24 Sprague-Dawley rats (250-300 g) were subjected to high-volume mechanical ventilation (25 mL.kg(-1)). MSCs (5 x 10(6)) were intravenously or intratracheally administered (n=8 each) 30 min before starting over-ventilation and eight rats were MSC-untreated. Spontaneously breathing anesthetised rats (n=8) served as controls. After 3 h of over-ventilation or control the animals were sacrificed and lung tissue and bronchoalveolar lavage fluid (BALF) were sampled for further analysis. When compared with controls, MSC-untreated over-ventilated rats exhibited typical VILI features. Lung oedema, histological lung injury index, concentrations of total protein, interleukin-1 beta, macrophage inflammatory protein-2 and number of neutrophils in BALF and vascular cell adhesion protein-1 in lung tissue significantly increased in over-ventilated rats. All these indices of VILI moved significantly towards normalisation in the rats treated with MSCs, whether intravenously or intratracheally. Both local and systemic pre-treatment with MSCs reduced VILI in a rat model.
JTD Keywords: Acute lung injury, Cell therapy, Injurious ventilation, Lung inflammation, Lung oedema, Mechanical ventilation
Giraldo, B.F., Gaspar, B.W., Caminal, P., Benito, S., (2012). Analysis of roots in ARMA model for the classification of patients on weaning trials Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 698-701
One objective of mechanical ventilation is the recovery of spontaneous breathing as soon as possible. Remove the mechanical ventilation is sometimes more difficult that maintain it. This paper proposes the study of respiratory flow signal of patients on weaning trials process by autoregressive moving average model (ARMA), through the location of poles and zeros of the model. A total of 151 patients under extubation process (T-tube test) were analyzed: 91 patients with successful weaning (GS), 39 patients that failed to maintain spontaneous breathing and were reconnected (GF), and 21 patients extubated after the test but before 48 hours were reintubated (GR). The optimal model was obtained with order 8, and statistical significant differences were obtained considering the values of angles of the first four poles and the first zero. The best classification was obtained between GF and GR, with an accuracy of 75.3% on the mean value of the angle of the first pole.
JTD Keywords: Analytical models, Biological system modeling, Computational modeling, Estimation, Hospitals, Poles and zeros, Ventilation, Autoregressive moving average processes, Patient care, Patient monitoring, Pneumodynamics, Poles and zeros, Ventilation, ARMA model, T-tube test, Autoregressive moving average model, Extubation process, Mechanical ventilation, Optimal model, Patient classification, Respiratory flow signal, Roots, Spontaneous breathing, Weaning trials
Cagido, Viviane Ramos, Zin, Walter Araujo, Ramirez, Jose, Navajas, Daniel, Farre, Ramon, (2011). Alternating ventilation in a rat model of increased abdominal pressure Respiratory Physiology & Neurobiology , 175, (3), 310-315
During alternating ventilation (AV) one lung is inflating while the other is deflating. Considering the possible respiratory and hemodynamic advantages of AV, we investigated its effects during increased intra-abdominal pressure (IAP = 10 mmHg). In Sprague-Dawley rats (n = 6, 270–375 g) the main bronchi were independently cannulated, and respiratory mechanics determined while animals underwent different ventilatory patterns: synchronic ventilation without increased IAP (SV-0), elevated IAP during SV (SV-10), and AV with elevated IAP (AV-10). Thirty-three other animals (SV-0, n = 10; SV-10, n = 11 and AV-10, n = 12) were ventilated during 3 h. Mean arterial pressure (MAP), and lung histology were assessed. Increased IAP resulted in significantly higher elastances (p < 0.001), being AV-10 lower than SV-10 (p < 0.020). SV-10 showed higher central venous pressure (p < 0.003) than S-0; no change was observed in AV-10. Wet/dry lung weight ratio was lower in AV-10 than SV-10 (p = 0.009). Application of AV reduced hemodynamic and lung impairments induced by increased IAP during SV.
JTD Keywords: Alternating ventilation, Respiratory mechanics, Intra-abdominal pressure, Hemodynamic, Mechanical ventilation, Animal model
Garde, A., Schroeder, R., Voss, A., Caminal, P., Benito, S., Giraldo, B., (2010). Patients on weaning trials classified with support vector machines Physiological Measurement , 31, (7), 979-993
The process of discontinuing mechanical ventilation is called weaning and is one of the most challenging problems in intensive care. An unnecessary delay in the discontinuation process and an early weaning trial are undesirable. This study aims to characterize the respiratory pattern through features that permit the identification of patients' conditions in weaning trials. Three groups of patients have been considered: 94 patients with successful weaning trials, who could maintain spontaneous breathing after 48 h ( GSucc ); 39 patients who failed the weaning trial ( GFail ) and 21 patients who had successful weaning trials, but required reintubation in less than 48 h ( GRein ). Patients are characterized by their cardiorespiratory interactions, which are described by joint symbolic dynamics (JSD) applied to the cardiac interbeat and breath durations. The most discriminating features in the classification of the different groups of patients ( GSucc , GFail and GRein ) are identified by support vector machines (SVMs). The SVM-based feature selection algorithm has an accuracy of 81% in classifying GSucc versus the rest of the patients, 83% in classifying GRein versus GSucc patients and 81% in classifying GRein versus the rest of the patients. Moreover, a good balance between sensitivity and specificity is achieved in all classifications.
JTD Keywords: Mechanical ventilation, Weaning, Support vector machines, Joint symbolic dynamics
Dellaca, R. L., Gobbi, A., Govoni, L., Navajas, D., Pedotti, A., Farre, R., (2009). A novel simple Internet-based system for real time monitoring and optimizing home mechanical ventilation International Conference on Ehealth, Telemedicine, and Social Medicine: Etelemed 2009, Proceedings International Conference on eHealth, Telemedicine, and Social Medicine (ed. Conley E.C., Doarn, C., HajjamElHassani, A.), IEEE Compuer Soc (Cancun, Mexico) , 209-215
The dissemination of the available telemedicine systems for the optimization of home mechanical ventilation (HMV) is prevented by the need of complex infrastructures. We developed a device which, once connected to Internet through the mobile phone network, allows an authorized physician connected to Internet to monitor the ventilator signals and modify the settings in real-time without the need of external data servers. The system was evaluated during experiments performed by tele-controlling a mechanical ventilator in Barcelona from Milano. A bench study verified the reliability and robustness of the system while an in-vivo test showed that it was possible to monitor and tele-control the ventilator to maintain the oxygen saturation of a rat ventilated in Barcelona subjected to interventions. Given that the system avoids the need for any complex telemedicine architecture and allows an individual and independent ventilator tele-control, it can be a new helpful tool to optimize HMV.
JTD Keywords: Home mechanical ventilation, Non-invasive mechanical ventilation, Telemedicine
Almendros, I., Gutierrez, P. T., Closa, D., Navajas, D., Farre, R., (2008). One-lung overventilation does not induce inflammation in the normally ventilated contralateral lung Respiratory Physiology & Neurobiology , 162, (1), 100-102
The aim was to assess whether induction of ventilator-induced lung injury (VILI) in one lung triggers a concomitant inflammatory response in the normally ventilated contralateral lung. To this end, a differential ventilator was used in 6 rats. One lung was normally ventilated (3.5 ml/kg b.w.) and the contralateral lung was overstretched (15 ml/kg b.w.). Six control rats were normally ventilated (3.5 ml/kg b.w. each lung). After 3h, edema and gene expression of MIP-2 in the lung, and plasma and liver TNF-alpha were assessed. Overexpression of MIP-2 and edema were found in the overventilated lung but not in the normally ventilated contralateral lung. No detectable levels of circulating and liver TNF-alpha were detected. These data do not support the hypothesis of an early positive feedback in the lung inflammation during the mechanical ventilation.
JTD Keywords: Mechanical ventilation, Lung injury, Lung edema, Lung over stretch, High volume ventilation, Differential ventilation