Feasibility Analysis of ECG-Based pH Estimation for Asphyxia Detection in Neonates

Birth asphyxia is a potential cause of death that is also associated with acute and chronic morbidities. The traditional and immediate approach for monitoring birth asphyxia (i.e., arterial blood gas analysis) is highly invasive and intermittent. Additionally, alternative noninvasive approaches such as pulse oximeters can be problematic, due to the possibility of false and erroneous measurements. Therefore, further research is needed to explore alternative noninvasive and accurate monitoring methods for asphyxiated neonates. This study aims to investigate the prominent ECG features based on pH estimation that could potentially be used to explore the noninvasive, accurate, and continuous monitoring of asphyxiated neonates. The dataset used contained 274 segments of ECG and pH values recorded simultaneously. After preprocessing the data, principal component analysis and the Pan-Tompkins algorithm were used for each segment to determine the most significant ECG cycle and to compute the ECG features. Descriptive statistics were performed to describe the main properties of the processed dataset. A Kruskal-Wallis nonparametric test was then used to analyze differences between the asphyxiated and non-asphyxiated groups. Finally, a Dunn-Šidák post hoc test was used for individual comparison among the mean ranks of all groups. The findings of this study showed that ECG features (T/QRS, T Amplitude, Tslope, Tslope/T, Tslope/|T|, HR, QT, and QTc) based on pH estimation differed significantly (p < 0.05) in asphyxiated neonates. All these key ECG features were also found to be significantly different between the two groups.

Development and Characterization of Interstitial-Fluid-Mimicking Solutions for Pre-Clinical Assessment of Hypoxia

Asphyxia, a leading cause of illness and death in newborns, can be improved by early detection and management. Arterial blood gas (ABG) analysis is commonly used to diagnose and manage asphyxia, but it is invasive and carries risks. Dermal interstitial fluid (ISF) is an alternative physiological fluid that can provide valuable information about a person's health. ISF is more sensitive to severe hypoxia and metabolic disorders compared to blood, making it an attractive option for minimally invasive asphyxia detection using biosensors. However, obtaining ISF samples from humans is challenging due to ethical concerns and sampling difficulties. To address this, researchers are developing ISF-mimicking solutions as substitutes for early testing and evaluation of biosensors. This paper focuses on the development of these solutions for bench-based testing and validation of continuous asphyxia-monitoring biosensors. With an understanding of the factors influencing system quality and performance, these solutions can aid in the design of biosensors for in vivo monitoring of dermal ISF. Monitoring interstitial fluid pH levels can provide valuable insights into the severity and progression of asphyxia, aiding in accurate diagnosis and informed treatment decisions. In this study, buffer solutions were prepared to mimic the pH of ISF, and their electrical properties were analyzed. The results suggest that certain buffers can effectively mimic metabolic acidosis associated with asphyxia (pH < 7.30), while others can mimic metabolic alkalosis (pH > 7.45). Overall, this research contributes to the development of ISF-mimicking solutions and lays the groundwork for biosensor systems that monitor dermal ISF in real time.

Effect of prone position on respiratory parameters, intubation and death rate in COVID-19 patients: systematic review and meta-analysis

Prone position (PP) is known to improve oxygenation and reduce mortality in COVID-19 patients. This systematic review and meta-analysis aimed to determine the effects of PP on respiratory parameters and outcomes. PubMed, EMBASE, ProQuest, SCOPUS, Web of Sciences, Cochrane library, and Google Scholar were searched up to 1st January 2021. Twenty-eight studies were included. The Cochran's Q-test and I2 statistic were assessed heterogeneity, the random-effects model was estimated the pooled mean difference (PMD), and a meta-regression method has utilized the factors affecting heterogeneity between studies. PMD with 95% confidence interval (CI) of PaO2/FIO2 Ratio in before-after design, quasi-experimental design and in overall was 55.74, 56.38, and 56.20 mmHg. These values for Spo2 (Sao2) were 3.38, 17.03, and 7.58. PP in COVID-19 patients lead to significantly decrease of the Paco2 (PMD: - 8.69; 95% CI - 14.69 to - 2.69 mmHg) but significantly increase the PaO2 (PMD: 37.74; 95% CI 7.16-68.33 mmHg). PP has no significant effect on the respiratory rate. Based on meta-regression, the study design has a significant effect on the heterogeneity of Spo2 (Sao2) (Coefficient: 12.80; p < 0.001). No significant associations were observed for other respiratory parameters with sample size and study design. The pooled estimate for death rate and intubation rates were 19.03 (8.19-32.61) and 30.68 (21.39-40.75). The prone positioning was associated with improved oxygenation parameters and reduced mortality and intubation rate in COVID-19 related respiratory failure.

ABG Assistant-Towards an Understanding of Complex Acid-Base Disorders

The ability to diagnose acid-base imbalances correctly is essential for physicians and other healthcare workers. Despite its importance, it is often considered too complex and confusing. Although most people dealing with arterial blood gases (ABGs) do not usually have problems with acid-base disorder assessment, such an analysis is also carried out by other healthcare workers for whom this can be a challenging task. Many aspects may be problematic, partly due to multiple data analysis methods and no definitive statement on which one is better. According to our survey, the correctness of arterial blood gas analysis is unsatisfactory, especially in mixed disorders, which do not always manifest an obvious set of symptoms. Therefore, ABG parameters can be used as an established biomarker panel, which is considered to be a powerful tool for personalized medicine. Moreover, using different approaches to analyze acid-base disorders can lead to varying diagnoses in some cases. Because of these problems, we developed a mobile application that can spot diagnostic differences by taking into account physiological and chemical approaches, including their variants, with a corrected anion gap. The proposed application is characterized by a high percentage of correct analyses and can be an essential aid for diagnosing acid-base disturbances.