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Design and Development of Low-cost Portable Mechanical Ventilator
Published in Purna Chandra Mishra, Muhamad Mat Noor, Anh Tuan Hoang, Advances in Mechanical and Industrial Engineering, 2022
Ambuj Maheshwari, Saksham Agarwal, Himanshu Verma, Ateeb Ahmad Khan
It has been found that Covid 19 is a close relative of SARS and like most SARS viruses, Covid 19 affects the respiratory tract in humans. Covid 19 primarily infects the lungs in the affected individuals and severe cases cause’ death due to Acute Respiratory Distress Syndrome (ARDS) and pneumonia (Yang et al., 2020). ARDS causes dry cough, heavy breathing, breathing difficulties and increased heart rate. WHO recommends the implementation of mechanical ventilation using lower tidal volumes (4–8 mL/kg predicted body weight [PBW]) and lower inspiratory pressures (Varghese et al., 2020).
Classification of Lung Diseases Using Machine Learning Techniques
Published in Ranjeet Kumar Rout, Saiyed Umer, Sabha Sheikh, Amrit Lal Sangal, Artificial Intelligence Technologies for Computational Biology, 2023
Sudipto Bhattacharjee, Banani Saha, Sudipto Saha
Interstitial lung disease (ILD) is a common non-obstructive disease often clinically diagnosed with PFT. A study for prediction of ILD with PFT features trained SVM model and achieved AUROC of 0.85 [34]. Pulmonary hypertension (PH) is another non-obstructive disease characterized by high PAP. ML models for diagnosis of PH with echocardiography features achieved 83% accuracy (AUROC = 0.89) [36]. Here, the class labels (positive or negative) of every patient were computed by comparing the PAP values. Then, SVM and logistic regression were used for direct classification and random forest regression was used for modelling of the PAP values followed by classification on the basis of a predefined PAP threshold. Acute respiratory distress syndrome (ARDS) is associated with respiratory failure and often leads to intensive care unit admission and ventilation. A ML-based study for ARDS diagnosis among hospitalized patients using LR model achieved AUROC of 0.81 with clinical features obtained within a six hour window [73]. Here, continuous values were quantized and represented as one-hot vectors while multiple measurements within the time window were represented as a vector of summary statistics. Another study that predicted respiratory failure among hospitalized COVID-19 patients using gradient boosted decision tree model, trained with clinical data, achieved 83% accuracy (AUROC = 0.84) [21]. Pneumonia is an infectious disease that often occurs as a side-effect of any surgical procedure. Generally, pneumonia is diagnosed with imagery data. Yet, few recent studies have emerged where ML applications have used clinical features. One such study compared six ML models for prediction of pneumonia as a postoperative complication among patients who underwent liver transplant [7]. The feature set included pre-operative, intra-operative and post-operative factors including comorbidities, laboratory tests and medication. Then, a subset of 14 features, out of 142, were selected using recursive feature elimination (RFE) method [14].
Hispidulin exerts a protective effect against oleic acid induced-ARDS in the rat via inhibition of ACE activity and MAPK pathway
Published in International Journal of Environmental Health Research, 2023
Kubra Koc, Nihal Simsek Ozek, Ferhunde Aysin, Ozlem Demir, Asli Yilmaz, Mehmet Yilmaz, Fatime Geyikoglu, Huseyin Serkan Erol
Acute respiratory distress syndrome (ARDS) is a syndrome that leads to rapidly worsening respiratory failure and is associated with excessive morbidity and mortality (Pan et al. 2020; Wu et al. 2020). ARDS is caused by numerous factors such as infection, sepsis, shock, trauma, burns, severe pneumonia, non-cardiogenic pulmonary edema, progressive dyspnea, and refractory hypoxemia (Johnson and Matthay 2010). The current COVID-19 pandemic is also one of the factors that develop ARDS (Pan et al. 2020). The pathogenesis of ARDS is characterized by rapid pulmonary edema, hypoxemia, alveolar damage, oxidative stress, and inflammatory process (Gonçalves-de-Albuquerque et al. 2015). Despite a general understanding of the mechanisms of ARDS, there is a need for the development of safe and effective therapies and prevention strategies.
Polymer-based nano-therapies to combat COVID-19 related respiratory injury: progress, prospects, and challenges
Published in Journal of Biomaterials Science, Polymer Edition, 2021
The outbreak of the novel β-coronavirus (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); family: Coronaviridae) responsible for Corona Virus Infectious Disease-2019 or COVID-19 is considered the worst crisis since World War II.[1] This pandemic’s impact is frightening as the human race faces a critical situation with mandatory lockdowns with a long-lasting dent in the world economy. Critically ill patients can develop acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) (about 30–40%), which is associated with high mortality.[2] ARDS is a catastrophic disease condition characterized by noncardiogenic pulmonary edema, decrease pulmonary compliance and acute onset of hypoxic respiratory failure.[3,4] All of these complications can subsequently trigger a cascade of other severe injuries, including multiple organ failure. Unfortunately, to date, contemporary therapeutic strategies to treat ALI/ARDS have not been rewarding.[5,6] Due to the complex pathogenesis and nature of the infection, some therapeutic targets for the blockade of specific cytokines and chemokines have failed to show an optimistic outcome.[7–9] Currently, only protective lung ventilation strategies are the accepted gold standard for ARDS treatment.[10] However, targeted delivery of anti-viral drugs, proteins, peptides, and silencing RNAs is some potential therapies for ARDS treatments.[11] Despite these potential candidates’ prospects, their delivery to the lung is a significant challenge for potential use in preventing viral infection and treating the respiratory injury.[12,13] A major hurdle in lung tissue engineering is developing lung-appropriate scaffold materials for soft tissue regeneration.[14]