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Context: Flossing is still a relatively new technique that has yielded varied results in the research literature; therefore, it requires further investigation. Previous research has shown that thigh tissue flossing might improve performance in countermovement jump, sprint time, maximum voluntary contraction, and rate of force development. Design. The present study aims to investigate the effect of the floss band on performance during the Wingate test (30-WAT), muscle oxygen saturation (SpO2), and total hemoglobin in vastus lateralis. Methods: Twenty-two students of physical education and sport (11 men and 11 women) were randomly selected to complete either the Wingate test with the application of a floss band in warm-up or the Wingate test without the use of a floss band, followed by the alternative 24 hours apart. Results: Throughout the testing, the floss band did not affect performance values during the Wingate test (relative peak power, relative average power, and fatigue index). However, there was a medium to large effect difference during 1 minute prior to 30-WAT (PRE), during the 30-WAT, and 10-minute recovery (REC) in values of SpO2 and total hemoglobin. Use of floss band displayed a higher SpO2 during PRE, 30-WAT, and REC by ~13.55%, d<2; ~19.06%, d = 0.89; and ~8.55%, d = 0.59, respectively. Conclusion: Collectively, these findings indicate that the application of thigh flossing during warm-up has no effect on 30-WAT performance; however, SpO2 was significantly increased in all stages of testing. This could lead to potential improvement in repeated anaerobic exercise due to increased blood flow. Increased muscle oxygen saturation can also lead to improved tissue healing as oxygen supply is essential for tissue repair, wound healing, and pain management. [ABSTRACT FROM AUTHOR]

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The relationship between the variations in ovarian hormones (i.e., estrogens and progesterone) and the hypoxic ventilatory response (HVR) remains unclear. HVR is a key adaptive mechanism to high altitude and has been proposed as a predictor for acute mountain sickness (AMS). This study aimed to explore the effects of hormonal changes across the menstrual cycle on HVR. Additionally, it assessed the predictive capacity of HVR for AMS and examined whether a particular menstrual phase could enhance its predictive accuracy. Thirteen eumenorrheic women performed a pure nitrogen breathing test near sea level, measuring HVR and cerebral oxygenation in early follicular, late follicular, and mid-luteal phases. Oxidative stress and ovarian hormone levels were also measured. AMS symptoms were evaluated after spending 14 h, including one overnight, at an altitude of 3,375 m. No differences in HVR, ventilation, peripheral oxygen saturation, or cerebral oxygenation were observed between the three menstrual cycle phases. Moreover, these parameters and the oxidative stress markers did not differ between the women with or without AMS (31% vs 69%), regardless of the menstrual cycle phase. In conclusion, ventilatory responses and cerebral oxygenation in normobaric hypoxia were consistent across the menstrual cycle. Furthermore, these parameters did not differentiate women with or without AMS. [ABSTRACT FROM AUTHOR]

Background: Identifying high-risk COVID-19 patients is critical for emergency department decision-making. Our study's primary objective was to identify new independent predictors of mortality and their predictive utility in combination with traditional pneumonia risk assessment scores and new risk scores for COVID-19 developed during the pandemic. Methods: A retrospective study was performed in two Italian University Hospitals. A multivariable logistic model was used to locate independent parameters associated with mortality. Results: Age, PaO2/FiO2, and SpO2/FiO2 ratios were found to be independent parameters associated with mortality. This study found that the Pneumonia Severity Index (PSI) was superior to many of the risk scores developed during the pandemic, for example, the International Severe Acute Respiratory Infection Consortium Coronavirus Clinical Characterisation Consortium (ISARIC 4C) (AUC 0.845 vs. 0.687, p < 0.001), and to many of the risk scores already in use, for example, the National Early Warning Score 2 (NEWS2) (AUC 0.845 vs. 0.589, p < 0.001). Furthermore, our study found that the Pneumonia Severity Index had a similar performance to other risk scores, such as CRB-65 (AUC 0.845 vs. 0.823, p = 0.294). Combining the PaO2/FiO2 or SpO2/FiO2 ratios with the risk scores analyzed improved the prognostic accuracy. Conclusions: Adding the SpO2/FiO2 ratio to the traditional, validated, and already internationally known pre-pandemic prognostic scores seems to be a valid and rapid alternative to the need for developing new prognostic scores. Future research should focus on integrating these markers into existing pneumonia scores to improve their prognostic accuracy. [ABSTRACT FROM AUTHOR]

Sleep apnea (SA) is a sleep-related breathing disorder characterized by breathing pauses during sleep. A person's sleep schedule is significantly influenced by that person's hectic lifestyle, which may include unhealthy eating habits and their line of work. Polysomnographic (PSG) sleep studies examine sleep-related disorders by recording various biosignals from the human body. However, SA classification methods could be more robust in terms of performance because they rely on feature-engineering strategies or employ a particular signal from PSG recording for diagnosis. This study aims to classify the severity of SA according to the apnea–hypopnea index (AHI) into normal, mild, and moderate-to-severe groups using oxygen saturation (SpO2), electroencephalogram (EEG), and electrocardiogram (ECG) signals. The proposed deep neural network (DNN)-bidirectional long short-term memory (DNN-BiLSTM) framework addresses the issue of low detection accuracy in analysis. The DNN-BiLSTM approach employs features extracted from a multiscale dilation attention 1D convolutional neural network (MSDA-1DCNN) as input for detection and classification purposes. The MSDA-1DCNN network extracts deep features from processed SpO2, EEG, and ECG signals. The developed firefly combined electric fish optimization (FCEFO) algorithm improves performance by optimizing the hidden neuron count of the DNN and the learning rate of the BiLSTM framework. The performance measures proved the effectiveness of the model over conventional machine and deep learning approaches. With the integration of deep features, the proposed DNN-BiLSTM model provides enhanced performance in terms of accuracy and precision. Thus, the proposed approach is progressive and can be used for medical diagnosis. [ABSTRACT FROM AUTHOR]

Leg health is an important consideration in a person's overall well-being, and knee osteoarthritis (OA) is one of the problems that reduces leg health. Thermotherapy therapy has long been recognized as one of the methods for treating knee OA pain. This study recruited 30 subjects with OA (aged 45–80, height of 155–175 cm, weight of 60–95 kg and body mass index of 18–40) to participate in a repeated measure for inter-subject and intra-subject analysis on pre- and post-treatment-based thermotherapy sessions where SpO2, pulse rate (PR) and Knee Injury and Osteoarthritis Outcome Score (KOOS) were measured within 4 weeks of explorative study. When a subject is subjected to thermotherapy, SpO2 increases and PR decreases compared with those of the control group, which did not present significant differences. The findings show a high degree of inter- and intra-subject repeatability. When a subject received thermotherapy for 4 weeks, his or her overall leg health improved, as indicated by a high KOOS and high KOOS-pain score. This is demonstrated by an increase in KOOS over the course of 4 weeks of thermotherapy. [ABSTRACT FROM AUTHOR]

Aircraft pilots face a high mental workload (MW) under environmental constraints induced by high altitude and sometimes sleep restriction (SR). Our aim was to assess the combined effects of hypoxia and sleep restriction on cognitive and physiological responses to different MW levels using the Multi-Attribute Test Battery (MATB)-II with an additional auditory Oddball-like task. Seventeen healthy subjects were subjected in random order to three 12-min periods of increased MW level (low, medium, and high): sleep restriction (SR, <3 h of total sleep time (TST)) vs. habitual sleep (HS, >6 h TST), hypoxia (HY, 2 h, FIO2 = 13.6%, ~3500 m vs. normoxia, NO, FIO2 = 21%). Following each MW level, participants completed the NASA-TLX subjective MW scale. Increasing MW decreases performance on the MATB-II Tracking task (p = 0.001, MW difficulty main effect) and increases NASA-TLX (p = 0.001). In the combined HY/SR condition, MATB-II performance was lower, and the NASA-TLX score was higher compared with the NO/HS condition, while no effect of hypoxia alone was observed. In the accuracy of the auditory task, there is a significant interaction between hypoxia and MW difficulty (F(2–176) = 3.14, p = 0.04), with lower values at high MW under hypoxic conditions. Breathing rate, pupil size, and amplitude of pupil dilation response (PDR) to auditory stimuli are associated with increased MW. These parameters are the best predictors of increased MW, independently of physiological constraints. Adding ECG, SpO2, or electrodermal conductance does not improve model performance. In conclusion, hypoxia and sleep restriction have an additive effect on MW. Physiological and electrophysiological responses must be taken into account when designing a MW predictive model and cross-validation. [ABSTRACT FROM AUTHOR]

Abstract The relationship between the variations in ovarian hormones (i.e., estrogens and progesterone) and the hypoxic ventilatory response (HVR) remains unclear. HVR is a key adaptive mechanism to high altitude and has been proposed as a predictor for acute mountain sickness (AMS). This study aimed to explore the effects of hormonal changes across the menstrual cycle on HVR. Additionally, it assessed the predictive capacity of HVR for AMS and examined whether a particular menstrual phase could enhance its predictive accuracy. Thirteen eumenorrheic women performed a pure nitrogen breathing test near sea level, measuring HVR and cerebral oxygenation in early follicular, late follicular, and mid-luteal phases. Oxidative stress and ovarian hormone levels were also measured. AMS symptoms were evaluated after spending 14 h, including one overnight, at an altitude of 3,375 m. No differences in HVR, ventilation, peripheral oxygen saturation, or cerebral oxygenation were observed between the three menstrual cycle phases. Moreover, these parameters and the oxidative stress markers did not differ between the women with or without AMS (31% vs 69%), regardless of the menstrual cycle phase. In conclusion, ventilatory responses and cerebral oxygenation in normobaric hypoxia were consistent across the menstrual cycle. Furthermore, these parameters did not differentiate women with or without AMS.

Background The need of pulmonary rehabilitation (PR) for COVID-19 patients with long-term effects was desperately felt. The study’s objective was to measure the effect of PR on functional capacity and health-related quality of life (HRQOL) in patients with post COVID conditions. Methods Pulmonary medicine department of a teaching hospital conducted this pre-experimental study. The patient underwent a pre and post-assessment, including a six-minute walk test (6MWT) measuring distance, oxygen desaturation, pulse rate, and HRQOL. The intervention had six components; education to patients and caregivers, breathlessness relieving exercises, postural correction, aerobic training, strength training, and stretching exercises. These activities were carried out twice a week for eight weeks, supervised, unsupervised in homes, and a combination. Results The study enrolled 155 post-COVID patients (Males, 102 and female, 53), out of which 28 (18.1%) had mild, 55 (35.5%) had moderate and 72 (46.5%) had severe COVID. Paired t-test showed improvement in resting pulse rate (P = 0.001) and resting oxygen saturation (P < 0.0001). Distance walking for six minutes increased after rehabilitation (P < 0.0001). After eight weeks of pulmonary rehabilitation, there was an improvement (P < 0.001) in all domains of quality of life, that is, mobility, self-care, pain and discomfort, usual activity, sleep, anxiety and depression. Conclusion Pulmonary rehabilitation is beneficial for post-COVID patients in improving their quality of life and six-minute walk test parameters, resulting in improved functional capacity and overall quality of life.

Purpose: This study aims to develop sleep apnea screening models with overnight SpO2 data, and to investigate the impact of the SpO2 data granularity on model performance. Methods: A total of 7,718 SpO2 recordings from the SHHS and MESA datasets were used. Probabilistic ensemble machine learning was employed to predict sleep apnea status at three AHI cutoff points: ≥ 5, ≥ 15, and ≥ 30 events/hour. To investigate the impact of data granularity, SpO2 data were aggregated at 30, 60, and 300 s. Results: Our models demonstrated good to excellent performance on internal test, with average area under the curve (AUC) values of 0.91, 0.93, and 0.96 for cutoffs ≥ 5, ≥ 15, and ≥ 30 at data granularity of 1 s, respectively. Both sensitivity (0.76, 0.84, 0.89) and specificity (0.87, 0.86, 0.90) ranged from good to excellent across three cutoffs. Positive predictive values (PPV) ranged from excellent to fair (0.97, 0.83, 0.66), and negative predictive values (NPV) ranged from low to excellent (0.43, 0.87, 0.98). Model performance on external test slightly dropped compared to internal test, but still achieved good to excellent AUC above 0.80 across all data granularity and all the three cutoffs. Data granularity of 300 s led to a reduction in performance metrics across all cutoffs. Conclusion: Our models demonstrated superior performance across all three AHI cutoff thresholds compared to existing large sleep apnea screening models, even when considering varying SpO2 data granularity. However, lower data granularity was associated with decreased screening performance, indicating a need for further research in this area. [ABSTRACT FROM AUTHOR]

Abstract Background This study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index. Methods A retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong’s algorithm. Models were validated externally using an international database. Results Of 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO2), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO2, and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07–2.05), 0.81 (0.72–0.90), 9.13 (3.29–28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2–9.8] versus 9.6 [6.8–12.9], p

Jan Vagedes,1,2 Mohsen Sobh,2 Mohammad Oli Al Islam,2 Christian F Poets1 1Department of Neonatology, Children’s Hospital, University of Tübingen, Tübingen, Germany; 2ARCIM-Institute, Research Department, Filderklinik, Filderstadt, GermanyCorrespondence: Jan Vagedes, ARCIM Institute, Im Haberschlai 7, Filderstadt, 70794, Germany, Tel +49 711 7703-1687, Email J.Vagedes@arcim-institute.dePurpose: Clinical management decisions often rely on a patient’s SpO2 level and desaturation rate. Limitations include that measurements depend on the averaging time (AVT) used, which is particularly relevant to sleep medicine, but has yet received little attention.Methods: Cross-sectional review of studies reporting pulse oximeter saturation (SpO2) measurements published in 5 leading sleep medicine journals. All papers published between 2017 and 2023 reporting SpO2 measurements were screened regarding the AVT used.Results: Of 193 papers identified, 151 were included; of these, only 9 studies mentioned the AVT, 4 of these were published in one journal. The AVT ranged from zero (beat-to-beat-mode) to 10s, with 3s being used most often (33.3%), followed by 2s (22.2%).Conclusion: The AVT is only rarely mentioned in sleep medicine papers, despite its influence on sleep study results. Reported AVTs were heterogenous. Further research is warranted to set up guidelines for using or reporting the AVT.Keywords: pulse oximetry, averaging time, oxygen saturation, desaturation, SpO2, sleep medicine

Background: This study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index. Methods: A retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong's algorithm. Models were validated externally using an international database. Results: Of 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO2), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO2, and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07–2.05), 0.81 (0.72–0.90), 9.13 (3.29–28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2–9.8] versus 9.6 [6.8–12.9], p < 0.001, respectively). In the external validation population, the area under the curve (AUC) of the ROX index was 0.683 (accuracy 63%), the AIC model showed an AUC of 0.703 (accuracy 69%), and the lowest AIC model with significant p values had an AUC of 0.725 (accuracy 79%). Conclusions: In the development population of ICU patients with COVID-19, SOFA score, SpO2, and respiratory effort signals predicted the need for IMV better than the ROX index. In the external validation population, although the AUCs did not differ significantly, the accuracy was higher when using SOFA score, SpO2, and respiratory effort signals compared to the ROX index. This suggests that these variables may be more useful in predicting the need for IMV in ICU patients with COVID-19. ClinicalTrials.gov identifier: NCT05663528. [ABSTRACT FROM AUTHOR]

The main aims of the current work are to design, fabricate, and test a low-cost, easy-to-operate portable pulse oximeter device capable of providing immediate blood oxygen saturation and heart rate readings with high accuracy for various disease conditions and all age groups. It can be used in intensive care departments, operating rooms, and health centers as well as at homes. The obtained results were compared using a calibrated device produced by a reputable company. The clinical examination results were evaluated by using the Export System 13.0 statistical software program. The readings are close to each other, with an error rate of less than 1%. The obtained results show that, in the case of a respiratory disease such as chronic obstructive pulmonary or other lung diseases, the percentage of oxygen saturation decreased to between 73 to 88 %. For patients with heart disease, it was found that the oxygen saturation level changes significantly according to the type of disease. These obtained values decreased by 11.11 %, and 7.08% compared to healthy people, respectively. For the smokers, the blood oxygen saturation rate decreased by 10.47% and 8.06% compared to healthy people, respectively. For those infected with the COVID-19 epidemic, the rate of blood oxygen saturation and heart rates decreased sharply by 31.51 % and 27.03 %, and by 14.67% and 16.67 % compared to healthy people for males and females, respectively. For asthma patients, the rate of blood oxygen saturation and heart rate decreased by 2.50 %, and 4.65 %, and increased by 4.65 % and 4.76 % compared to healthy people for male and female, respectively. For physical activities, such as athletes, the rate of blood oxygen saturation and heart rate were increased by 1.05 %, 3.19 %, 23.26 %, and 28.57 % compared to healthy people for males and females, respectively. [ABSTRACT FROM AUTHOR]

We sought to assess the effects of repeated cold-water immersions (CWI) on respiratory, metabolic, and sympathoadrenal responses to graded exercise in hypoxia. Sixteen (2 female) participants (age: 21.2 ± 1.3 years; body fat: 12.3 ± 7.7%; body surface area 1.87 ± 0.16 m2, VO2peak: 48.7 ± 7.9 mL/kg/min) underwent 6 CWI in 12.0 ± 1.2 °C. Each CWI was 5 min, twice daily, separated by ≥4 h, for three consecutive days, during which metabolic data were collected. The day before and after the repeated CWI intervention, participants ran in normobaric hypoxia (FIO2 = 0.135) for 4 min at 25%, 40%, 60%, and 75% of their sea level peak oxygen consumption (VO2peak). CWI had no effect on VO2 (p > 0.05), but reduced the VE (CWI #1: 27.1 ± 17.8 versus CWI #6: 19.9 ± 12.1 L/min) (p < 0.01), VT (CWI #1: 1.3 ± 0.4 vs CWI #6: 1.1 ± 0.4 L) (p < 0.01), and VE:VO2 (CWI #1: 53.5 ± 24.1 vs CWI #6: 41.6 ± 20.5) (p < 0.01) during subsequent CWI. Further, post exercise plasma epinephrine was lower after CWI compared to before (103.3 ± 43.1; 73.4 ± 34.6 pg/mL) (p = 0.03), with no change in pre-exercising values (75.4 ± 30.7; 72.5 ± 25.9 pg/mL). While these changes were noteworthy, it is important to acknowledge there were no changes in pulmonary (VE, VT, and VE:VO2) or metabolic (VO2, SmO2, and SpO2) variables across multiple hypoxic exercise workloads following repeated CWI. CWI habituated participants to cold water, but this did not lead to adaptations during exercise in normobaric hypoxia. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to evaluate the SpO2 (transcutaneous oxygen saturation) -mortality link in elderly T2DM (diabetes mellitus type 2) patients with cerebral infarction and identify their optimal SpO2 range. Methods: In this investigation, we employed a comprehensive approach. Initially, we screened the MIMIC-IV database, identifying elderly T2DM patients with cerebral infarction, utilizing specific ICD-9 and ICD-10 codes. We then harnessed the power of restricted cubic splines to craft a visual representation of the correlation between SpO2 and 1-year mortality. To enhance our analysis, we harnessed Cox multivariate regression, allowing us to compute adjusted hazard ratios (HR) accompanied by 95% confidence intervals (CIs). Additionally, we crafted Cumulative Mortality Curve analyses, augmenting our study by engaging in rigorous subgroup analyses, stratifying our observations based on pertinent covariates. Results: In this study, 448 elderly T2DM patients with cerebral infarction were included. Within 1-year post-discharge, 161 patients (35.94%) succumbed. Employing Restricted Cubic Spline analysis, a statistically significant U-shaped non-linear relationship between admission ICU SpO2 levels and 1-year mortality was observed (P-value < 0.05). Further analysis indicated that both low and high SpO2 levels increased the mortality risk. Cox multivariate regression analysis, adjusting for potential confounding factors, confirmed the association of low (≤94.5%) and high SpO2 levels (96.5-98.5%) with elevated 1-year mortality risk, particularly notably high SpO2 levels (>98.5%) [HR = 2.06, 95% CI: 1.29-3.29, P-value = 0.002]. The cumulative mortality curves revealed the following SpO2 subgroups from high to low cumulative mortality at the 365th day: normal levels (94.5% < SpO2 ≤ 96.5%), low levels (SpO2 ≤ 94.5%), high levels (96.5% < SpO2 ≤ 98.5%), and notably high levels (>98.5%). Subgroup analysis demonstrated no significant interaction between SpO2 and grouping variables, including Sex, Age, Congestive heart failure, Temperature, and ICU length of stay (LOS-ICU; P-values for interaction were >0.05). Conclusions: Striking an optimal balance is paramount, as fixating solely on lower SpO2 limits or neglecting high SpO2 levels may contribute to increased mortality rates. To mitigate mortality risk in elderly T2DM patients with cerebral infarction, we recommend maintaining SpO2 levels within the range of 94.5-96.5%. [ABSTRACT FROM AUTHOR]

Sleep apnea is probably the most common respiratory disorder; respiration and blood oxygen saturation (SpO2) are major concerns in sleep apnea and are also the two main parameters checked by polysomnography (PSG, the gold standard for diagnosing sleep apnea). In this study, we used a simple, non-invasive monitoring system based on photoplethysmography (PPG) to continuously monitor SpO2 and heart rate (HR) for individuals at home. Various breathing experiments were conducted to investigate the relationship between SpO2, HR, and apnea under different conditions, where two techniques (empirical formula and customized formula) for calculating SpO2 and two methods (resting HR and instantaneous HR) for assessing HR were compared. Various adaptive filters were implemented to compare the effectiveness in removing motion artifacts (MAs) during the tests. This study fills the gap in the literature by comparing the performance of different adaptive filters on estimating SpO2 and HR during apnea. The results showed that up-down finger motion introduced more MA than left-right motion, and the errors in SpO2 estimation were increased as the frequency of movement was increased; due to the low sampling frequency features of these tests, the insertion of adaptive filter increased the noise in the data instead of eliminating the MA for SpO2 estimation; the normal least mean squares (NLMS) filter is more effective in removing MA in HR estimation than other filters. [ABSTRACT FROM AUTHOR]

Introduction: The prevalence of interstitial lung disease (ILD) is increasing. High-resolution computerized tomography (HRCT), despite having limitations, remains the choice of method for diagnosis and assessment of severity of ILD. Objective: To determine the efficacy of 6-min walk test to assess the severity of the ILD compared to HRCT. Methodology: A cross-sectional study was done among 40 patients with ILD in a tertiary hospital in Hyderabad. The data included age, gender, smoking, HRCT, 6-min walk test, spirometry, diffusion lung capacity and medical history. Mann–Whitney U test, Kruskal–Wallis test, and ROC curve were used to determine the outcomes. Results: The mean age of participants was 57.18 + 13.01 years. 62.5% never smoked. Overall, 50% had severe ILD, and the rest had mild to moderate. The distance walked per 6-min, SpO2 before and SpO2 after, was significantly lower (p = 0.001; 0.002;

Background: The goal of this study was to assess the impact of deep local hyperthermia on oxygen (O2) saturation and infected volumes of lungs on coronavirus disease 2019 (COVID-19) cancer patients. Materials and Methods: Fifty patients who suffered from COVID-19 (according to their computed tomography (CT) images and laboratory findings) were included in this study. The mentioned patients were divided into two groups (I and II) with thirty-five participants. The infected volumes and COVID-19 infectious locations were diagnosed using their CT images, and deep local hyperthermia was performed for group II. After three consequent days, the SPO2, D-dimer, and infected volumes of lung parenchyma of both groups were compared to each other. Results: For group II, the mean ± SD (standard deviation) of O2 pressure saturation (SPO2) before/after hyperthermia was 85 ± 0.0/91.3 ± 0.5, respectively, while for group I, the mean ± SD of SPO2 before/after 3 days was 85 ± 0.0/88 ± 0.2, respectively. For infected volumes of lungs before/after hyperthermia in group II, the mean ± SD was 31.36 ± 3.13/4 ± 1.53, respectively. Nonetheless, the infected volumes of lungs for group I were 34.21 ± 3.41/10 ± 2.12 before/after three days. For group II, the amount of D-dimer before/after hyperthermia was 3200 ± 106/510 ± 121, respectively. However, for group I, it was 3100/740 before/after the consequent three days, respectively. Conclusion: Deep local lung hyperthermia for COVID-19 cancer patients is suggested, as a result of its positive impacts on SPO2 improvement and also D-dimer serum level, C-reactive protein, and Lactate dehydrogenaze reduction for the mentioned patients.

Blood oxygen saturation (SpO2) is an essential indicator of a patient's general condition. However, conventional measurement methods have some issues such as time delay and interference by ambient light. Improved measurement methods must be developed, and there are no reports on intraoral measurements of SpO2 using wearable devices. Therefore, we aimed to establish an intraoral SpO2 measurement method for the first time. Twelve healthy adults participated in this study. The following steps were taken: (1) to identify the optimal measurement location, mid-perfusion index (PI) values were measured at six places on the mucosa of the maxilla, (2) to validate the optimal measurement pressure, PI values were obtained at different pressures, and (3) using the proposed mouthpiece device, SpO2 values in the oral cavity and on the finger were analyzed during breath-holding. The highest PI values were observed in the palatal gingiva of the maxillary canine teeth, with high PI values at pressures ranging from 0.3 to 0.8 N. In addition, changes in SpO2 were detected approximately 7 s faster in the oral cavity than those on the finger, which is attributed to their proximity to the heart. This study demonstrates the advantage of the oral cavity for acquiring biological information using a novel device. [ABSTRACT FROM AUTHOR]

Background: Concerns about the adverse effects of excessive oxygen have grown over the years. This study investigated the relationship between high oxygen saturation and short-term prognosis of patients with spontaneous intracerebral hemorrhage (sICH) after liberal use of oxygen. Methods: This retrospective cohort study collected data from the Medical Information Mart for Intensive Care III (MIMIC-III) database (ICU cohort) and a tertiary stroke center (general ward cohort). The data on pulse oximetry-derived oxygen saturation (SpO2) during the first 24 h in ICU and general wards were respectively extracted. Results: Overall, 1117 and 372 patients were included in the ICU and general ward cohort, respectively. Among the patients from the ICU cohort, a spoon-shaped association was observed between minimum SpO2 and the risk of in-hospital mortality (non-linear P<0.0001). In comparison with minimum SpO2 of 93–97%, the minimum SpO2>97% was associated with a significantly higher risk of in-hospital mortality after adjustment for confounders. Sensitivity analysis conducted using propensity score matching did not change this significance. The same spoon-shaped association between minimum SpO2 and the risk of in-hospital mortality was also detected for the general ward cohort. In comparison with the group with 95–97% SpO2, the group with SpO2>97% showed a stronger association with, but non-significant risk for, in-hospital mortality after adjustment for confounders. The time-weighted average SpO2>97% was associated significantly with in-hospital mortality in both cohorts. Conclusion: Higher SpO2 (especially a minimum SpO2>97%) was unrewarding after liberal use of oxygen among patients with sICH and might even be potentially detrimental. [ABSTRACT FROM AUTHOR]

Background: Patients undergoing open abdominal surgery are the focus of this research, namely the effect of early mobilisation on postoperative pulmonary problems. Early mobilization is proposed as a potential intervention to enhance respiratory function and reduce the risk of PPCs. Purpose: The purpose of this study is to evaluate the impact of pre-operative mobilisation on the incidence of pulmonary complications in patients undergoing open abdominal surgery. Materials and Methods: This quasi-experimental study included 50 subjects who underwent open abdominal surgery at Saveetha Medical Hospital, SIMTS. Convenient sampling was used to select the participants. Measures of oxygen saturation (SPO2) and pulmonary function (FEV1) from a spirometer were employed as functional outcome indicators. After two weeks, participants were given a post-test to record their progress. Results: Data collected before and after early mobilisation exercise were analysed using a paired t-test. The experimental group showed significant improvements in SPO2, FIM, and FEV1 (P<0.0001), indicating higher values post-intervention. Post-test demonstrated higher statistical significance compared to pre-test. Conclusion: As a result, it was shown that early mobilisation Exercise is beneficial for reducing pulmonary complications after surgery. [ABSTRACT FROM AUTHOR]

Background: Among all Birth defects, Congenital Heart disease (CHD) is most common congenital anomalies with preponderance of around 6 to 8 per 1000 live births. Children born with CHD in India is more than 200,000 per year out of which one-fifth are likely to have Critical congenital heart disease(CCHDs). Methodology that have been proposed to work on early identification of congenital heart disease includes prenatal ultrasound screening, prolonged hospital stay after delivery. Pulse oximetry (SpO2) has presented as one such strategy. Pulse Oximetry is the first, relatively simple approach has been used for universal screening of congenital heart diseases. Methodology- The study was conducted on 600 neonates visiting paediatric outpatient department (OPD) and admitted in Neonatal Intensive Care Unit (NICU) at tertiary care centre between January 2020 to December 2021. All relevant information was recorded in case record form (CRF). All neonates were examined for vital parameters including Tachycardia, Tachypnea (RR>60/Min), Murmur. Pulse oximetry readings (after stable signals) were taken for right upper limb. All neonates with abnormal Pulse oximetry were subjected to observations at 6 hours after birth. Any of the readings at 6 hours were taken as positive. Results- Mean Gestational age of the newborns was 38.11 ± 0.86944 days. mean birth weight of the newborns was 2.66 ± 0.38 kg. The SpO2 levels for four limbs at 6 hrs for right upper limb were 97% ± 3.81%. Distribution of newborn according to heart rate was, 99.6% were normal while only 0.4% had tachycardia, 97.6% had normal respiratory rate, while 2.4% had tachypnoea. 0.4% babies had Murmur. Conclusion- The study concludes that use of pulse oximetry results in early detection of CHD. Pulse oximetry has an additive effect and results in more efficient screening. [ABSTRACT FROM AUTHOR]

In this paper, we developed ensemble classifiers with SpO2 signals for sleep apnea screening. The ensemble classifiers (eclf) were built on top of five base classifiers, including logistic regression (LR), random forest (RF), support vector machine (SVM), linear discrimination analysis (LDA), and light gradient boosting machine (LGMB). Performance evaluation showed that when heavier weights were assigned to the LR and SVM classifiers, the ECLF achieved a better balance between sensitivity (0.81 ± 0.02) and specificity (0.80 ± 0.02) while maintaining the overall performance as measured by AUC (0.81 ± 0.01). [ABSTRACT FROM AUTHOR]

To compare pulse oximetry performance during simulated conditions of motion and low perfusion in three commercially available devices: GE HealthCare CARESCAPE ONE TruSignal SpO2 Parameter, Masimo RADICAL-7 and Medtronic Nellcor PM1000N. After IRB approval, 28 healthy adult volunteers were randomly assigned to the motion group (N = 14) or low perfusion (N = 14) group. Pulse oximeters were placed on the test and control hands using random assignment of digits 2–5. Each subject served as their own control through the series of repeated pair-wise measurements. Reference co-oximetry oxyhemoglobin (SaO2) measurements from the radial artery were also obtained in the motion group. SpO2 readings were compared between the test and control hands in both groups and to SaO2 measurements in the motion group. Accuracy was assessed through testing of accuracy root-mean squared (ARMS) and mean bias. In the simulated motion test group the overall Accuracy Root Mean Square (ARMS) versus SaO2 was 1.88 (GE), 1.79 (Masimo) and 2.40 (Nellcor), with overall mean bias of − 0.21 (Masimo), 0.45 (GE), and 0.78 (Nellcor). In the motion hand, ARMS versus SaO2 was 2.45 (GE), 3.19 (Masimo) and 4.15 (Nellcor), with overall mean bias of − 0.75 (Masimo), − 0.01 (GE), and 0.04 (Nellcor). In the low perfusion test group, ARMS versus the control hand SpO2 for low PI was 3.24 (GE), 3.48 (Nellcor) and 4.76 (Masimo), with overall bias measurements of − 0.53 (Nellcor), 0.96 (GE) and 1.76 (Masimo). Experimental results for all tested devices met pulse oximetry regulatory and testing standards requirements. Overall, SpO2 device performance across the three devices in this study was similar under both motion and low perfusion conditions. SpO2 measurement accuracy degraded for all three devices during motion as compared to non-motion. Accuracy also degraded during normal to low, very low, or ultra low perfusion and was more pronounced compared to the changes observed during simulated motion. While some statistically significant differences in individual measurements were found, the clinical relevance of these differences requires further study. [ABSTRACT FROM AUTHOR]

ObjectiveThis study aimed to evaluate the SpO2 (transcutaneous oxygen saturation) -mortality link in elderly T2DM (diabetes mellitus type 2) patients with cerebral infarction and identify their optimal SpO2 range.MethodsIn this investigation, we employed a comprehensive approach. Initially, we screened the MIMIC-IV database, identifying elderly T2DM patients with cerebral infarction, utilizing specific ICD-9 and ICD-10 codes. We then harnessed the power of restricted cubic splines to craft a visual representation of the correlation between SpO2 and 1-year mortality. To enhance our analysis, we harnessed Cox multivariate regression, allowing us to compute adjusted hazard ratios (HR) accompanied by 95% confidence intervals (CIs). Additionally, we crafted Cumulative Mortality Curve analyses, augmenting our study by engaging in rigorous subgroup analyses, stratifying our observations based on pertinent covariates.ResultsIn this study, 448 elderly T2DM patients with cerebral infarction were included. Within 1-year post-discharge, 161 patients (35.94%) succumbed. Employing Restricted Cubic Spline analysis, a statistically significant U-shaped non-linear relationship between admission ICU SpO2 levels and 1-year mortality was observed (P-value < 0.05). Further analysis indicated that both low and high SpO2 levels increased the mortality risk. Cox multivariate regression analysis, adjusting for potential confounding factors, confirmed the association of low (≤94.5%) and high SpO2 levels (96.5–98.5%) with elevated 1-year mortality risk, particularly notably high SpO2 levels (>98.5%) [HR = 2.06, 95% CI: 1.29–3.29, P-value = 0.002]. The cumulative mortality curves revealed the following SpO2 subgroups from high to low cumulative mortality at the 365th day: normal levels (94.5% < SpO2 ≤ 96.5%), low levels (SpO2 ≤ 94.5%), high levels (96.5% < SpO2 ≤ 98.5%), and notably high levels (>98.5%). Subgroup analysis demonstrated no significant interaction between SpO2 and grouping variables, including Sex, Age, Congestive heart failure, Temperature, and ICU length of stay (LOS-ICU; P-values for interaction were >0.05).ConclusionsStriking an optimal balance is paramount, as fixating solely on lower SpO2 limits or neglecting high SpO2 levels may contribute to increased mortality rates. To mitigate mortality risk in elderly T2DM patients with cerebral infarction, we recommend maintaining SpO2 levels within the range of 94.5–96.5%.

Penelitian ini mengembangkan sistem pemantauan HeartRate dan SPO2 berbasis Raspberry Pi untuk lansia. Sistem ini memberikan pendampingan kesehatan real-time dan peringatan dini terhadap kondisi yang mengkhawatirkan. Menggunakan sensor MAX30102 yang terhubung ke Arduino Uno dengan Raspberry Pi sebagai gateway, sistem ini dapat mengukur HeartRate dan SPO2 dengan akurasi tinggi. Perangkat keras terdiri dari Raspberry Pi, Arduino Uno, sensor MAX 30102, dan modul GPS, sementara perangkat lunak dikembangkan dengan Python dan mencakup modul pengolahan data, pengiriman data, dan antarmuka pengguna real-time. Uji coba melibatkan lansia sebagai subjek, dan hasilnya menunjukkan akurasi yang memadai. Aplikasi monitoring yang digunakan mudah digunakan dan memberikan informasi yang jelas. Secara keseluruhan, sistem ini memberikan pendampingan kesehatan yang efektif dan diharapkan dapat meningkatkan kualitas hidup lansia serta mempermudah pemantauan kesehatan mereka.

Background: Diabetes mellitus is the most common chronic metabolic disorder that increases both susceptibility and mortality rates in patients with the coronavirus disease 2019 (COVID-19). We conducted a study on diabetic patients with COVID-19 to investigate the relationship between laboratory indicators and peripheral oxygen saturation (SPO2 ). Methods: In this analytical-cross-sectional study, the required information of diabetic patients with COVID-19 admitted to Taleghani educational hospital in Abadan from March 20, 2020 to March 19, 2021 was obtained by referring to the hospital information system of Abadan University of Medical Sciences and patient files. Results: Two hundred patients were studied, of which 88 (44%) were men and 112 (56%) were women. The mean age of the studied patients was 60.57±14.84. Among all the investigated markers, blood urea nitrogen (BUN), serum glutamate oxalate transaminase (SGOT), serum glutamic-pyruvic transaminase (SGPT), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), lactate dehydrogenase (LDH), and respiratory rate (RR) were higher than the normal range, while SPO2 was lower than the normal range. Based on the linear regression analysis results, a significant relationship was observed between the decrease in SPO2 of patients with disease outcome, duration of hospitalization in the intensive care unit (P

Introduction: Sedation and analgesia are integral parts of patient care in intensive care units. These medications are routinely administered to mechanically ventilated patients to reduce pain, anxiety, improve patient comfort, to allow the patient to tolerate the physical environment and unpleasant procedures, avoiding awareness during ICU stay, reduce the requirement for the use of neuromuscular blocking agents and to contribute in maintaining metabolic and haemodynamic homeostasis. Materials and Methods: After approval by the Institutional ethical committee the study was conducted in the Main ICU of Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh. All the patients who were admitted in the main ICU were eligible for the study. After taking informed written consent, 70 adult patients who were haemodynamically stable and require sedation were studied. Patients were stabilized after admitting in the ICU. The demographic data including the admission diagnosis, admitting unit were collected. APACHE IIscore was calculated in first 24 hours. BIS electrodes were applied to the forehead of each patient after skin preparation to ensure low impedance and a good quality of signal. BIS offers continuous monitoring of sedation for 24 hours. Baseline BIS score and RSS, RASS scores were collected. Results: Seventy critically ill sedated patients were studied prospectively in MICU, PGIMER, Chandigarh. From January to December 2014. The mean patient age was 38.8 ± 16.5 years (range: 18- 92 years). 35 (50%) patients were male and 35 (50%) were female patients. The median APACHE score of the 70 patients was 11 with IQR of 8-13. Parameters like SBP, DBP, HR, SpO2, temperature; blood gases and electrolytes were assessed for normality by Shapiro Francia test. However, none of them showed normal distribution. The BIS, RSS, RASS of the patients during the study period are given in the table 1, and figures 1, 2, 3. Conclusion: We found significantly better correlation between RSS & RASS compared to RSS & BIS and RASS & BIS. This concludes that RSS and RASS are not a good substitute for BIS. Whereas RSS and RASS can be substituted each other. We found negligible correlation between BIS and clinical scores to APACHE. Hence we can conclude no influence of change in APACHE on BIS and clinical sedation scores (RSS and RASS). [ABSTRACT FROM AUTHOR]

Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate, ECG, nasal/oral airflow, temperature, light sensor, and fall detection sensor. Different researchers have done different work in the field of health monitoring with sensor networks. Different researchers used built-in apps, such as some used a small number of parameters, while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate, and outdated tools for study development. While no efficient, cheap, and updated work is proposed in the field of sensor-based health monitoring systems. Therefore, this study developed an android-based mobile system that can remotely monitor electrocardiograms (ECGs), pulse oximetry, heart rate, and body temperature. The microcontroller's Wi-Fi device is used to manage wireless data transport. The findings of the patient are saved on the Firebase server for further usage in the mobile app. The performance of the proposed device is tested on ten numbers of different patients age-wise in terms of beats per minute (BPM), ECG, Temperature, and SpO2. This system uses temperature, pulse, ECG, blood pressure, and eye blink sensors. This device makes the usage of a tiny pulse sensor that has been designed to provide an accurate and optimal readout of the pulse rate and a temperature sensor is also included. With the help of an MCU, our system measures the pulse rate in beats per minute (bpm), blood oxygen level temperature measurements, and ECG readings and communicates this information to the Firebase server. To check the performance of the proposed system first, the BPM parameter was checked on the cardiac monitor. Then, the proposed model is tested on different patients age-wise. The simulation result shows that the BPM reading is not much different than the BPM of the cardiac monitor. According to the simulation findings, the proposed model achieved the best performance as compared to commercially available devices. [ABSTRACT FROM AUTHOR]

Background: Epidural anesthesia is a technique for perioperative pain management with multiple applications in anesthesiology. It is useful as a primary aesthetic, Aside from the benefit of potentially providing excellent analgesia, its use reduces the exposure to other anesthetics and analgesics, decreasing side effects. It has also shown to decrease cortisol levels, expedite the return of bowel function, decrease the incidence of PE and DVT in the post-operative period, and shorten lengths of in-hospital stay. Present study was undertaken to evaluate the efficacy of epidural anesthesia with 0.25% bupivcacine for lower abdominal surgeries and its effect on blood pressure and SPO2. Present study was undertaken to evaluate the efficacy of epidural anesthesia with 0.25%bupivcacine for lower abdominal surgeries and its effect on blood pressure and SPO2. Methods: We evaluated the characteristics of epidural block including onset, duration of action, hemodynamic changes, ease of performance, efficacy, adverse effects and complication in 50 children aged between 4 to 14 years. The epidural block was performed in lateral position with 19G Tuohy's needle in L4-L5 space and 19 G epidural catheter was threaded after detecting the ES by LOR technique. The dose of 0.25% bupivacaine was age in years/10 per spinal segment (> 10 yrs) and I ml/kg up to 20ml (< 10 yrs). Results: Efficacy, safety, and ease of performance were satisfactory in most children. The mean diastolic blood pressure showed statistically significant decreases starting from 5th min after administration of epidural anesthesia. This decrease was maintained till about 45 min and subsequently started increasing from 60th min onwards. The mean SP02 showed a statistically significant increase from 5 min and was maintained throughout the study period. All patients had received supplemental oxygen through mask throughout the study period. Conclusion: Epidural anesthesia with 0.25% hyperbaric bupivacaine in the appropriate dosage is a safe technique in pediatric patients undergoing lower abdominal surgeries and its effect on blood pressure and SPO2 is satisfactory. [ABSTRACT FROM AUTHOR]

Introduction: Yoga is known to promote health and wellness in all. Pranava Pranayama is a useful sound based yogic breathing technique with reported benefits such as potentiating vagal tone. Subjects and Methods: This single blinded randomized self-controlled cross-over study was done with 58 participants. The immediate effect of Pranava Pranayama on saturation of oxygen in the blood (SpO2) and heart rate (HR) was determined before and after intervention using pulse oximeter. To avoid extraneous influences due to recording on different days, one half of the subjects were randomized to perform quiet sitting on day 1 while other half did Pranava Pranayama which was then reversed on day 2. Results: Intra group comparison showed significant changes (p < 0.001) in both SpO2 and HR following Pranava Pranayama whereas in the quiet sitting group, there was an insignificant fall in the SpO2 readings but HR was found significant (p < 0.001). Intergroup comparison showed significant differences between groups (p-0.032). Discussion: Cardiovascular changes following Pranava Pranayama may be as a result of audible chanting improving baroreflex sensitivity along with increased endogenous nitric oxide production. This promotes vasodilatation resulting in reduction of BP. The decrease in vascular resistance and an increase in capillary perfusion results in increased oxygen saturation with lesser demand on the heart. Conclusion: This study provides evidence that Pranava Pranayama is an effective technique in enhancing SpO2 and our findings may have therapeutic applications especially in the current pandemic situation. [ABSTRACT FROM AUTHOR]

Objective. The objective of this research was to detect cases of newborns at risk of congenital critical heart disease through neonatal cardiac screening tests using the instrument called "pulse oximeter" manufactured by Masimo SET, as part of the collaboration between the Newborn Foundation, the Autonomous University of Ciudad Juarez and the Autonomous University of Queretaro. Method. A total of 547 newborns were screened from December 2019 to March 2021 at Femap Hospital (Ciudad Juarez, Mexico), following the Newborn Foundation algorithm to detect arterial oxygen saturation (SpO2) in the right hand and foot; a saturation lower than 95% would be an indicator of heart disease risk. Results. Four risky cases of congenital critical heart disease were detected Using the pulse oximeter, referred to as a gold standard test (echocardiography). After the procedure, one case was confirmed positive by the specialist. With the data obtained, correlations and statistical associations were calculated using variables of SpO2 (dependent), height, weight, and age in hours of the newborn (independent). A positive correlation between hand SpO2 and foot SpO2 values was confirmed. Finally, SpO2 prediction graphs were obtained, where it was observed that the age in hours and the weight of the newborn (independent variables) influence the SpO2 variable, showing these maximum and minimum values. [ABSTRACT FROM AUTHOR]

Recent developments in the field of internet innovation have made it feasible for new methods to be developed for the delivery of medical care. Sharing of resources may be encouraged via the use of network infrastructure and shared points of access. Patient data and clinical information make the Internet an ideal tool for the many applications that include remote patient monitoring. In this paper, we provide an experimental model that was developed for monitoring and checking on the patient's current state of health using sensors. The framework is dependent on an e-health sensor that is connected to a cloud platform. The cloud platform is responsible for collecting the data that is gathered from the sensors through the Arduino microcontroller. The data collected by the sensors includes readings from body temperature, heart rate, and oxygen. The data then is easily available for further processing, including the analysis of certain correlations between the measured parameters and the health status of the patients. [ABSTRACT FROM AUTHOR]

Background: In December 2019, a new virus, the coronavirus disease 2019 (COVID-19) was identified as the cause of a cluster of cases of pneumonia of unknown etiology in Wuhan, China. The COVID-19 disease increases cardiovascular events both directly and indirectly. This study aimed to investigate the laboratory diagnostic markers of cardiovascular patients with COVID-19 in Ayatollah Taleghani hospital in Abadan from March 20, 2020 to March 19, 2021. Materials and Methods: This study is a cross-sectional analytical study. Some demographic, laboratory, and clinical information of 200 cardiovascular patients with COVID-19 admitted to Taleghani hospital, Abadan, was received randomly by referring to the medical records section and medical records section and health information system (HIS) as well as searching in the patient records. Inclusion criteria included cardiovascular patients with COVID-19 who had been admitted to Ayatollah Taleghani hospital in Abadan with the diagnosis of a cardiologist and infectious disease specialist, and those whose information was available in HIS. The results were analyzed using SPSS software version 24. Results: The mean age of cardiovascular patients with COVID-19 was reported to be 66.98±18.14. The results revealed that the mean of fasting blood sugar (FBS), serum glutamic oxaloacetic transaminase (SGOT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), creatinine (Cr), blood urea nitrogen (BUN), and erythrocyte sedimentation rate (ESR) was higher than the normal level in these patients. In addition, the mean oxygen saturation (SpO2) was observed to be lower than normal. Reducing the level of SpO2 to less than 90% was significantly related to increasing age, death, patients with a history of lung disease, the duration of hospitalization in ICU, and intubation. This reduction also led to an increase in respiratory rate (RR), LDH, ESR, and C-reactive protein (CRP+1) in cardiovascular patients with COVID-19. Conclusion: In cardiovascular patients with COVID-19, FBS, some kidney markers, liver markers, and inflammatory markers were observed to be higher than normal, and a significant relationship was observed between the reduction of SpO2 and some laboratory diagnostic markers, which requires extensive studies with larger sample size.

Pulse oximetry is often regarded as the fifth vital sign. Based on the absorption of near-infrared light, any changes in the concentration of oxyhemoglobin influence the reading on the pulse oximeter. We present one such case of a 30-year-old lady with leprosy on multiple drug therapy that showed low SpO2 readings not associated with respiratory distress and did not improve with oxygenation. She was found to have dapsone-induced methemoglobinemia, which was reversed after 48 h of stopping the drug intake.

In this experimental study, we investigate the high frequency and power of near-infrared radiation embedded in impedance cardiography (ICG) with physiological signal monitoring using electrocardiographic (ECG) and pulse oximeter oxygen saturation (SpO2) sensors as well as sympathetic and parasympathetic activity analyses. This high-performance sensor system has three physiological sensing channels and a drive system. This monitoring system includes ECG, SpO2, and ICG sensors, processors, wireless communication modules, and power management modules. Compared with other portable products, physiological sensors can minimize cost and space. Power consumption and function/efficiency are all very sensitive. The sampling rate of the processor is 2500/s. The wireless communication module is a Wi-Fi communication system. The power management module supplies a continuous 5 V, 3 A power supply. A cardiovascular disease treatment drive system can supply a high frequency of operation based on the multichannel data fusion of the physiological monitoring module with a cloud artificial intelligence feedback information system with output voltage and power in the range from 0 to ±52 V. The frequency is 0.3-10 MHz. The physiological signal monitoring system can operate at a frequency of 3 MHz with a voltage amplitude of ±52 V. [ABSTRACT FROM AUTHOR]

Introduction: Yoga is known to promote health and wellness in all. Pranava Pranayama is a useful sound based yogic breathing technique with reported benefits such as potentiating vagal tone. Subjects and Methods: This single blinded randomized self-controlled cross-over study was done with 58 participants. The immediate effect of Pranava Pranayama on saturation of oxygen in the blood (SpO2) and heart rate (HR) was determined before and after intervention using pulse oximeter. To avoid extraneous influences due to recording on different days, one half of the subjects were randomized to perform quiet sitting on day 1 while other half did Pranava Pranayama which was then reversed on day 2. Results: Intra group comparison showed significant changes (p < 0.001) in both SpO2 and HR following Pranava Pranayama whereas in the quiet sitting group, there was an insignificant fall in the SpO2 readings but HR was found significant (p < 0.001). Intergroup comparison showed significant differences between groups (p-0.032). Discussion: Cardiovascular changes following Pranava Pranayama may be as a result of audible chanting improving baroreflex sensitivity along with increased endogenous nitric oxide production. This promotes vasodilatation resulting in reduction of BP. The decrease in vascular resistance and an increase in capillary perfusion results in increased oxygen saturation with lesser demand on the heart. Conclusion: This study provides evidence that Pranava Pranayama is an effective technique in enhancing SpO2 and our findings may have therapeutic applications especially in the current pandemic situation.

Background: The novel Coronavirus is belonging to the family of SARS & MERS-CoV, the impact of the earlier is more dreadful as demonstrated by the steady increase in morbid cases. The average incubation period of COVID-19 is 1–14 days with a mean of 6 days. Aim - To evaluate predictors of mortality among COVID-19 patients. Objectives – 1. To assess risk predictors associated with mortality among COVID-19 patients 2. To a suggest prediction model for preventing mortality in future outbreaks. Materials and Methods: Study design – A case-control study. Study place -Tertiary care center, Nanded, Maharashtra. The present study included 400 cases that died off due to Covid-19 and 400 controls survived COVID-19 disease in a 1:1 proportion. Results: On admission, a significant difference was observed among cases and controls with reference to the percentage of SpO2 (p < 0.05). The proportion of associated co-morbidities among cases was very high i.e., 75.75% as compared to controls with a proportion of 29.25% co-morbidities. The median days of hospital stay were significantly lower in cases compared to controls (3 days vs 12 days, P < 0.001). Conclusion: Length of hospital stay (in days) was showing a significant difference among cases and control (3 days Vs 12 days); hospital stay was less (median 3 days) for cases, as they reported late and thus died earlier; hence concluded that early hospital admission will decrease chances of death due to COVID-19.

Abstract Background We established 1-h and 1-day survival models after terminal extubation to optimize ventilator use and achieve a balance between critical care for COVID-19 and hospice medicine. Methods Data were obtained from patients with end-of-life status at terminal extubation from 2015 to 2020. The associations between APACHE II scores and parameters with survival time were analyzed. Parameters with a p-value ≤ 0.2 in univariate analysis were included in multivariate models. Cox proportional hazards regression analysis was used for the multivariate analysis of survival time at 1 h and 1 day. Results Of the 140 enrolled patients, 76 (54.3%) died within 1 h and 35 (25%) survived beyond 24 h. No spontaneous breathing trial (SBT) within the past 24 h, minute ventilation (MV) ≥ 12 L/min, and APACHE II score ≥ 25 were associated with shorter survival in the 1 h regression model. Lower MV, SpO2 ≥ 96% and SBT were related to longer survival in the 1-day model. Hospice medications did not influence survival time. Conclusion An APACHE II score of ≥ 25 at 1 h and SpO2 ≥ 96% at 1 day were strong predictors of disposition of patients to intensivists. These factors can help to objectively tailor pathways for post-extubation transition and rapidly allocate intensive care unit resources without sacrificing the quality of palliative care in the era of COVID-19. Trial registration They study was retrospectively registered. IRB No.: 202101929B0.

The effects of oxygen gas injection starting on day 17 of incubation (D17) in a chick shell-less culture system (cSLC) on the subsequent embryo development were examined on day 19 of incubation (D19). On D19 of cSLC, the plasma phosphorus and total cholesterol concentrations of the embryos were significantly higher (P0.05). The percutaneous oxygen saturation was lower in D17-cSLC embryos before oxygen gas supplementation than in the IC (P

Optical fibres enable to design of new textile-based sensors for an unobtrusive, continuous, and long-term acquisition of photoplethysmography (PPG) signals. However, no research has been done about the accuracy of measuring blood oxygen saturation (SpO2) and the feasibility of PPG-based blood pressure measurement. This proof-ofconcept study examined these aspects for a woven sensing patch applied on the forehead in five healthy participants. During a controlled desaturation study, SpO2 estimation revealed an amplitude of the root-mean-squared error (ARMS) of 3.6%, and acceptable signal quality for blood pressure estimation was achieved for 40% of all data. These results indicate that textile-based sensors can reach the required PPG signal quality to simultaneously estimate multiple vital signs, including blood pressure.

One of the most major and common health crises which occur across all the hospitals, worldwide, is seen to be sepsis that occurs in patients. However, despite its wide prevalence no novel tool has been devised for predicting its occurrence. An accurate and early prediction of sepsis in the patients could significantly help the physicians administer proper treatment and decrease the uncertain diagnosis. Some machine‐learning‐based models or schemes can help in identifying the potential clinical variables and display a better performance compared to the prevailing conventional low‐performance models. In this study, a machine learning‐based scheme for fast and accurate sepsis identification was proposed. This scheme employed the power spectrum and mean estimation for data record intervals, which were then classified for reaching the final decision. For a 72‐h interval, the obtained detection accuracy was 94.2% that shows very good sign to use it as a fast and robust sepsis identification. [ABSTRACT FROM AUTHOR]

Despite several targeted antiviral drugs against SARS-CoV-2 currently being available, the application of type I interferons (IFNs) still deserves attention as an alternative antiviral strategy. This study aimed to assess the therapeutic effectiveness of IFN-α in hospitalized patients with COVID-19-associated pneumonia. The prospective cohort study included 130 adult patients with coronavirus disease (COVID-19). A dose of 80,000 IU of IFN-α2b was administered daily intranasally for 10 days. Adding IFN-α2b to standard therapy reduces the length of the hospital stay by 3 days (p < 0.001). The level of CT-diagnosed lung injuries was reduced from 35% to 15% (p = 0.011) and CT injuries decreased from 50% to 15% (p = 0.017) by discharge. In the group of patients receiving IFN-α2b, the SpO2 index before and after treatment increased from 94 (92–96, Q1–Q3) to 96 (96–98, Q1–Q3) (p < 0.001), while the percentage of patients with normal saturation increased (from 33.9% to 74.6%, p < 0.05), but the level of SpO2 decreased in the low (from 52.5% to 16.9%) and very low (from 13.6% to 8.5%) categories. The addition of IFN-α2b to standard therapy has a positive effect on the course of severe COVID-19. [ABSTRACT FROM AUTHOR]

Background: The novel Coronavirus is belonging to the family of SARS & MERS-CoV, the impact of the earlier is more dreadful as demonstrated by the steady increase in morbid cases. The average incubation period of COVID-19 is 1-14 days with a mean of 6 days. Aim - To evaluate predictors of mortality among COVID-19 patients. Objectives -- 1. To assess risk predictors associated with mortality among COVID-19 patients 2. To a suggest prediction model for preventing mortality in future outbreaks. Materials and Methods: Study design -- A case-control study. Study place -Tertiary care center, Nanded, Maharashtra. The present study included 400 cases that died off due to Covid-19 and 400 controls survived COVID-19 disease in a 1:1 proportion. Results: On admission, a significant difference was observed among cases and controls with reference to the percentage of SpO2 (p < 0.05). The proportion of associated co-morbidities among cases was very high i.e., 75.75% as compared to controls with a proportion of 29.25% co-morbidities. The median days of hospital stay were significantly lower in cases compared to controls (3 days vs 12 days, P < 0.001). Conclusion: Length of hospital stay (in days) was showing a significant difference among cases and control (3 days Vs 12 days); hospital stay was less (median 3 days) for cases, as they reported late and thus died earlier; hence concluded that early hospital admission will decrease chances of death due to COVID-19. [ABSTRACT FROM AUTHOR]

In this work, we design a multisensory IoT-based online vitals monitor (hereinafter referred to as the VITALS) to sense four bedside physiological parameters including pulse (heart) rate, body temperature, blood pressure, and peripheral oxygen saturation. Then, the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery. The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment, a powerful microcontroller, a reliable wireless communication module, and a big data analytics system. It extracts human vital signs in a pre-programmed interval of 30 min and sends them to big data analytics system through the WiFi module for further analysis. We use Apache Kafka (to gather live data streams from connected sensors), Apache Spark (to categorize the patient vitals and notify the medical professionals while identifying abnormalities in physiological parameters), Hadoop Distributed File System (HDFS) (to archive data streams for further analysis and long-term storage), Spark SQL, Hive and Matplotlib (to support caregivers to access/visualize appropriate information from collected data streams and to explore/understand the health status of the individuals). In addition, we develop a mobile application to send statistical graphs to doctors and patients to enable them to monitor health conditions remotely. Our proposed system is implemented on three patients for 7 days to check the effectiveness of sensing, data processing, and data transmission mechanisms. To validate the system accuracy, we compare the data values collected from established sensors with the measured readouts using a commercial healthcare monitor, the Welch Allyn® Spot Check. Our proposed system provides improved care solutions, especially for those whose access to care services is limited. [ABSTRACT FROM AUTHOR]