Variations In Oxygen Saturation Research Articles

Association between glucose metabolism, the circadian cycle and hypoxia: Evaluation of the NPAS2 and Rev-Erb-α protein serum levels in obstructive sleep apnea patients - a pilot study.

Obstructive sleep apnea (OSA) is one of the risk factors for diabetes mellitus type 2 (DM2). As OSA is associated with the disruption of the circadian rhythm, it affects circadian clock proteins, including neuronal PAS domain protein 2 (NPAS2) and nuclear receptor subfamily 1 group D member 1 (Rev-Erb-α). These proteins have been shown to be related to metabolic abnormalities, i.a., insulin resistance. The present pilot study aimed to investigate the NPAS2 and Rev-Erb-α protein serum levels in the groups of patients with severe OSA and severe OSA+DM2 in comparison with healthy controls, taking into account correlations with polysomnography (PSG) parameters (e.g., oxygen saturation (SpO2) variables). A total of 40 participants were included in the study. They were split into 3 groups as follows: the OSA group (n = 17; apnea-hypopnea index (AHI) >30, no DM2); the OSA+DM2 group (n = 7; AHI > 30 and DM2); and the control group (n = 16; AHI < 5, no DM2). All participants underwent a nocturnal PSG examination and had their blood collected the following morning. The serum levels of NPAS2 and Rev-Erb-α proteins were assessed using the enzyme-linked immunosorbent assay (ELISA). The mean NPAS2 protein level was significantly lower in the OSA group as compared to healthy individuals (p = 0.017). Additionally, the OSA group presented with lower NPAS2 protein levels as compared to the OSA+DM2 group, but only a tendency was observed (p = 0.094). No differences in the Rev-Erb-α protein concentration were noticed. Furthermore, a negative correlation between AHI during rapid eye movement (REM) sleep and the NPAS2 protein serum level was observed (r = -0.478; p = 0.002). Serum NPAS2 protein might be involved in metabolic dysregulation present among OSA patients, while the mechanism itself may be associated with REM sleep.

Complexity reduction of oxygen saturation variability signals in COVID-19 patients: Implications for cardiorespiratory control

BackgroundCoronavirus disease 2019 (COVID-19) is a respiratory illness that leads to severe acute respiratory syndrome and various cardiorespiratory complications, contributing to morbidity and mortality. Entropy analysis has demonstrated its ability to monitor physiological states and system dynamics during health and disease. The main objective of the study is to extract information about cardiorespiratory control by conducting a complexity analysis of OSV signals using scale-based entropy measures following a two-month timeframe after recovery. MethodsThis prospective study collected data from subjects meeting specific criteria, using a Beurer PO-80 pulse oximeter to measure oxygen saturation (SpO2) and pulse rate. Excluding individuals with a history of pulmonary/cardiovascular issues, the study analyzed 88 recordings from 44 subjects (26 men, 18 women, mean age 45.34 ± 14.40) during COVID-19 and two months post-recovery. Data preprocessing and scale-based entropy analysis were applied to assess OSV signals. ResultsThe study found a significant difference in mean OSV during illness (95.08 ± 0.15) compared to post-recovery (95.59 ± 1.03), indicating reduced cardiorespiratory dynamism during COVID-19. Multiscale entropy analyses (MSE, MPE, MFE) confirmed lower entropy values during illness across all time scales, particularly at higher scales. Notably, the maximum distinction between illness and recovery phases was seen at specific time scales and similarity criteria for each entropy measure, showing statistically significant differences. ConclusionsThe study demonstrates that the loss of complexity in OSV signals, quantified using scale-based entropy measures, has the potential to detect malfunctioning of cardiorespiratory control in COVID-19 patients. This finding suggests that OSV signals could serve as a valuable indicator for assessing the cardiorespiratory status of COVID-19 patients and monitoring their recovery progress.

Scale based entropy measures and deep learning methods for analyzing the dynamical characteristics of cardiorespiratory control system in COVID-19 subjects during and after recovery

COVID-19, known as Coronavirus Disease 2019 primarily targets the respiratory system and can impact the cardiovascular system, leading to a range of cardiorespiratory complications. The current forefront in analyzing the dynamical characteristics of physiological systems and aiding clinical decision-making involves the integration of entropy-based complexity techniques with artificial intelligence. Entropy-based measures offer promising prospects for identifying disturbances in cardiorespiratory control system (CRCS) among COVID-19 patients by assessing the oxygen saturation variability (OSV) signals. In this investigation, we employ scale-based entropy (SBE) methods, including multiscale entropy (MSE), multiscale permutation entropy (MPE), and multiscale fuzzy entropy (MFE), to characterize the dynamical characteristics of OSV signals. These measurements serve as features for the application of traditional machine learning (ML) and deep learning (DL) approaches in the context of classifying OSV signals from COVID-19 patients during their illness and subsequent recovery. We use the Beurer PO-80 pulse oximeter which non-invasively acquired OSV and pulse rate data from COVID-19 infected patients during the active infection phase and after a two-month recovery period. The dataset comprises of 88 recordings collected from 44 subjects(26 men and 18 women), both during their COVID-19 illness and two months post-recovery. Prior to analysis, data preprocessing is performed to remove artifacts and outliers. The application of SBE measures to OSV signals unveils a reduction in signal complexity during the course of COVID-19. Leveraging these SBE measures as feature sets, we employ two DL techniques, namely the radial basis function network (RBFN) and RBFN with dynamic delay algorithm (RBFNDDA), for the classification of OSV data collected during and after COVID-19 recovery. To evaluate the classification performance, we employ standard metrics such as sensitivity, specificity, false positive rate (FPR), and the area under the receiver operator characteristic curve (AUC). Among the three scale-based entropy measures, MFE outperformed MSE and MPE by achieving the highest classification performance using RBFN with 13 best features having sensitivity (0.84), FPR (0.30), specificity (0.70) and AUC (0.77). The outcomes of our study demonstrate that SBE measures combined with DL methods offer a valuable approach for categorizing OSV signals obtained during and after COVID-19, ultimately aiding in the detection of CRCS dysfunction.

Oxygen saturation variability and machine learning in the correlation and prediction of obstructive sleep apnea severity

Oxygen saturation variability and machine learning in the correlation and prediction of obstructive sleep apnea severity

Association between Nocturnal Hypoxemia and COPD Severity: A Cross-sectional Study

Introduction: Globally, Chronic Obstructive Pulmonary Disease (COPD) is the third most common cause of mortality. More than 80% of these fatalities happened in low- and middleincome nations. Transient desaturation during sleep occurs in healthy persons during Rapid Eye Movement (REM) sleep. This phenomenon is aggravated in COPD patients. As Nocturnal Desaturation (NOD) in COPD has been suggested to increase mortality, its early identification will aid in early initiation of treatment and prevention of associated complications. Aim: To estimate the prevalence of nocturnal hypoxemia in COPD and determine its association with COPD severity. Materials and Methods: A cross-sectional study was carried out at the Department of General Medicine, Apollo Hospitals, Guwahati, Assam, India during January to December 2021 involving 100 patients who had COPD symptoms. Continuous oxygen saturation monitoring with transcutaneous finger probe was done for the entire duration of sleep at night. Patients whose oxygen saturation falls below 90% for at least 30% of recording time in sleep were classified as desaturators. Statistical Package for Social Sciences (SPSS) Version 26.0 was used for data analysis. Using the Chi-square test, the relationship between the qualitative variables was evaluated. The Mann-Whitney test or the unpaired t-test was used to analyse the quantitative data between the two groups. A p-value of less than 0.05 was considered significant. Results: Prevalence of NOD among cases of COPD was observed as 26% in present study. A significant association was observed between presence of NOD in COPD cases with severity of COPD and with desaturation in 6-Minute Walk Test (6-MWT) (p&lt;0.01). Severe cases had a prevalence of NOD as 65% as compared to 28.2% and 4.9% in moderate and mild cases respectively (p&lt;0.01). A total of 61.9% cases with desaturation during 6-MWT showed NOD as compared to 38.1% without desaturation (p&lt;0.01). Conclusion: One fourth of the normoxemic COPD patients had significant NOD. NOD episodes were observed to be positively associated with increasing severity of COPD. Assessing variations in oxygen saturation during a 6-MWT can be helpful in identifying COPD patients who may be at risk for severe night time desaturation.

Ischemia modified albumin as a marker of hypoxia in preterm infants in the first week after birth

BackgroundTissue hypoxia remains a leading cause of morbidity and mortality in preterm infants. Current biomarkers often detect irreversible hypoxic cellular injury (i.e. lactate) and are non-specific. A new biomarker is needed which detects tissue hypoxia before irreversible damage occurs. AimsTo investigate the relation between serum ischemia modified albumin (IMA), a marker of hypoxia; and analytic variables, patient related variables and conditions associated with hypoxia, in preterm infants. Study designRetrospective cohort study. SubjectsInfants with a gestational age < 30 weeks and/or birth weight < 1000 g. Outcome measuresWe collected two remnant blood samples in the first week after birth and measured IMA. IMA/albumin ratio (IMAR) was used to adjust for albumin. We assessed correlations between IMA(R) and analytic variables (albumin, lipemia- and haemolysis index); mean-2 h SpO2; mean-2 h variability of regional splanchnic oxygen saturation (rsSO2), measured using near-infrared spectroscopy; and patent ductus arteriosus (PDA). ResultsSixty-five infants were included. Albumin, the lipemia- and haemolysis index correlated negatively with IMA (r:-0.620, P<0.001; r:-0.458, P<0.001; and r:-0.337, P=0.002). IMAR correlated negatively with SpO2 (rho:-0.614, P<0.001). Lower rsSO2 variability correlated with higher IMAR values (rho:-0.785, n=14, P=0.001 and rho:-0.773, n=11, P=0.005). Infants with a hemodynamic significant PDA (hsPDA) had higher IMAR values than infants without PDA (0.13 [0.11–0.28], n=16 vs. 0.11 [0.08–0.20], n=29, P=0.005 and 0.11 [0.09–0.18], n=13 vs. 0.09 [0.06–0.17], n=37, P=0.026). ConclusionsWhen adjusted for albumin, the lipemia- and haemolysis index, IMAR has potential value as a marker for systemic hypoxia in preterm infants, considering the associations with SpO2, variability of rsSO2, and hsPDA.

Studying Dynamical Characteristics of Oxygen Saturation Variability Signals Using Haar Wavelet.

An aim of the analysis of biomedical signals such as heart rate variability signals, brain signals, oxygen saturation variability (OSV) signals, etc., is for the design and development of tools to extract information about the underlying complexity of physiological systems, to detect physiological states, monitor health conditions over time, or predict pathological conditions. Entropy-based complexity measures are commonly used to quantify the complexity of biomedical signals; however novel complexity measures need to be explored in the context of biomedical signal classification. In this work, we present a novel technique that used Haar wavelets to analyze the complexity of OSV signals of subjects during COVID-19 infection and after recovery. The data used to evaluate the performance of the proposed algorithms comprised recordings of OSV signals from 44 COVID-19 patients during illness and after recovery. The performance of the proposed technique was compared with four, scale-based entropy measures: multiscale entropy (MSE); multiscale permutation entropy (MPE); multiscale fuzzy entropy (MFE); multiscale amplitude-aware permutation entropy (MAMPE). Preliminary results of the pilot study revealed that the proposed algorithm outperformed MSE, MPE, MFE, and MMAPE in terms of better accuracy and time efficiency for separating during and after recovery the OSV signals of COVID-19 subjects. Further studies are needed to evaluate the potential of the proposed algorithm for large datasets and in the context of other biomedical signal classifications.

Platelet rich plasma: a novel therapy in chronic wounds

Background: Pulse oximeters are vital in healthcare, yet uncertainties remain about potential variations in oxygen saturation (SpO2) measurements depending on the finger used. Our study compared SpO2 values from different fingers in 200 young adults. Methods: A cross-sectional survey was conducted, capturing SpO2 values from every finger on both hands using a standard pulse oximeter. Results: Mean SpO2 differed slightly among fingers, from 98.29 (left index finger) to 98.70 (right ring finger). The majority of participants were male (59%) and 20 years old. Pulse rates ranged from 55 to 130 beats per minute, averaging at 85.23 bpm. Conclusions: Our results indicate finger choice for pulse oximetry can affect SpO2 readings, with the highest mean reading obtained from the right ring finger. This could potentially impact clinical practice.

Changes in Cerebral Regional Oxygen Saturation Variability in Neonates Undergoing Cardiac Surgery: A Prospective Cohort Study.

Near-infrared spectroscopy is routinely used in the monitoring of cerebral regional oxygen saturation (crSO2) in neonates following congenital heart surgery. Decreased postoperative crSO2 variability in these patients is associated with worse clinical outcomes, including neurodevelopmental outcomes. We sought to explore changes in crSO2 variability between the preoperative and postoperative periods and associations with short-term clinical outcomes in neonates undergoing cardiac surgery. We performed a prospective cohort study of neonates undergoing cardiac surgery with cardiopulmonary bypass between November 2019 and May 2021. We calculated crSO2 variability using averaged 1min of crSO2 values for a minimum of 12h before, and the first 48h following surgery. 37 neonates (median age at start of monitoring 4days (interquartile range 2-5days)) were included in our study. We observed a 30% decrease in crSO2 variability between the preoperative and postoperative monitoring periods (p < 0.001). Preoperative crSO2 variability increased by 9% (p = 0.009) for each additional postnatal day. There were no associations between the degree of decrease in crSO2 variability postoperatively and class of cardiac lesion (e.g., aortic arch obstruction, single ventricle physiology) or short-term postoperative clinical outcomes. There was a significant decrease in postoperative crSO2 variability following neonatal cardiac surgery as compared to the preoperative period, likely influenced by several factors. The impact of interventions on crSO2 variability and resultant influence on long-term outcomes, such as neurodevelopmental outcomes, requires further exploration.

Opioid requirement and pain intensity after mandibular surgeries with dexmedetomidine administration in two ways: intraoperative infusion versus bolus injection.

The purpose of this study is to compare the opioid requirement and pain intensity after surgeries of mandibular fractures with administration of dexmedetomidine by two approaches of infusion and single bolus. In this double-blind clinical trial, the participants were randomized and matched in terms of age and gender in two groups (infusion and bolus). In both groups, the amount of narcotic used, hemodynamic indices, oxygen saturation, and pain intensity were collected based on the ten-point Visual Analogue Scale (VAS) at 7 time points for 24 h. SPSS version 24 software was used for data analysis. A significance level of less than 5% was considered. A total of 40 patients were included in the study. There was no significant difference between the two groups in terms of gender, age, ASA class, and duration of surgery (P>0.05). There was no significant difference between the two groups in terms of nausea and vomiting and subsequently receiving anti-nausea medication (P>0.05). The need for opioid consumption after surgery was not different in two groups (P>0.05). Infusion of dexmedetomidine reduced postoperative pain more rapidly than its single bolus dose (P<0.05). However, over time, there was no significant difference between the two groups in terms of changes in oxygen saturation variables (P>0.05). Homodynamic indices including heart rate, systolic blood pressure, and diastolic blood pressure in the bolus group were significantly lower than the infusion group (P<0.05). Administration of dexmedetomidine in the form of infusion can reduce postoperative pain better than bolus injection, with less probability of hypotension and bradycardia.

Comparison of regional cerebral oxygen saturation variations between sevoflurane and propofol anaesthesia in gynecological laparoscopic surgery

Comparison of regional cerebral oxygen saturation variations between sevoflurane and propofol anaesthesia in gynecological laparoscopic surgery

Reduced oxygen saturation entropy is associated with poor prognosis in critically ill patients with sepsis.

Recent studies have found that oxygen saturation (SpO2 ) variability analysis has potential for noninvasive assessment of the functional connectivity of cardiorespiratory control systems during hypoxia. Patients with sepsis have suboptimal tissue oxygenation and impaired organ system connectivity. Our objective with this report was to highlight the potential use for SpO2 variability analysis in predicting intensive care survival in patients with sepsis. MIMIC-III clinical data of 164 adults meeting Sepsis-3 criteria and with 30 min of SpO2 and respiratory rate data were analyzed. The complexity of SpO2 signals was measured through various entropy calculations such as sample entropy and multiscale entropy analysis. The sequential organ failure assessment (SOFA) score was calculated to assess the severity of sepsis and multiorgan failure. While the standard deviation of SpO2 signals was comparable in the non-survivor and survivor groups, non-survivors had significantly lower SpO2 entropy than those who survived their ICU stay (0.107 ± 0.084 vs. 0.070 ± 0.083, p< 0.05). According to Cox regression analysis, higher SpO2 entropy was a predictor of survival in patients with sepsis. Multivariate analysis also showed that the prognostic value of SpO2 entropy was independent of other covariates such as age, SOFA score, mean SpO2 , and ventilation status. When SpO2 entropy was combined with mean SpO2 , the composite had a significantly higher performance in prediction of survival. Analysis of SpO2 entropy can predict patient outcome, and when combined with SpO2 mean, can provide improved prognostic information. The prognostic power is on par with the SOFA score. This analysis can easily be incorporated into current ICU practice and has potential for noninvasive assessment of critically ill patients.

Clinical Predictive Modeling of Anastomotic Leaks Using Hyperspectral Imaging

INTRODUCTION: Anastomotic leaks (AL) remain virtually unchanged despite advancements in minimally invasive surgical techniques and postoperative care. Adequate intraoperative bowel perfusion assessment remains a standard of surgical care to prevent AL. Although several platforms offer objective assessment of bowel perfusion, their reliable use has not demonstrated AL prevention and involves cumbersome steps through sterile preparation or use of dyes. We harnessed machine learning to address these 2 concerns by generating a clinical-predictive modeling tool for AL using a well-established platform of tissue perfusion called hyperspectral imaging. METHODS: We analyzed oxyhemoglobin, deoxyhemoglobin, and oxygen saturation levels of pre- and postanastomotic bowel segments intraoperatively at Brigham and Women’s Hospital using the contactless, point-and-shoot platform called HyperView. Patients 18 years or older undergoing open or laparoscopic-assisted abdominal surgery were included in the study. We followed patients postoperatively for development of AL and perianastomotic abscesses, and preliminarily analyzed the data using random forests to assess variable importance. We will perform a final analysis of the cohort by applying support vector machine to train a model with 80% training and 20% testing partition using a multiple kernel approach. RESULTS: Preliminary results demonstrate a strong correlation of oxyhemoglobin and oxygen saturation levels in preanastomotic intestinal limbs with the incidence of AL. The variation in oxygen saturation and mean oxyhemoglobin levels in the common channel postanastomoses is correlated with development of perianastomotic abscesses. CONCLUSION: We report an innovative intraoperative assessment tool using a noninvasive, contactless imaging technology for intestinal perfusion assessment that can clinically predict incidence of AL and guide intraoperative decisions.

Low Flow versus No Flow: Ischaemia Reperfusion Injury Following Different Experimental Models in the Equine Small Intestine

Simple SummaryOne of the main causes of colic in horses is the occlusion of the intestinal blood vessels after displacement or entrapment of the small intestine. In search of new therapies to treat this lethal disease, experimental models have been used to simulate the clinical situation. Both low flow (LF) models with partial blood flow occlusion as well as no flow (NF) models with complete occlusion have been implemented in different studies. This has led to conflicting results and comparative studies are lacking. The objective of this study was to characterize the development of intestinal injury over time in two different experimental models implementing either partial or complete vessel occlusion. Under general anaesthesia, local intestinal blood flow was reduced by 80% in seven horses (LF), and by 100% in another seven horses (NF). The LF group exhibited more bleeding in the intestinal wall and a relatively high variability in intestinal oxygen levels and tissue damage. The NF group showed lower oxygen levels and decreased barrier function of the intestinal wall. These results aid in the selection of the suitable experimental model for future studies. The high variability following LF suggests that an NF model may produce more consistent intestinal damage.In experimental studies investigating strangulating intestinal lesions in horses, different ischaemia models have been used with diverging results. Therefore, the aim was to comparatively describe ischaemia reperfusion injury (IRI) in a low flow (LF) and no flow (NF) model. Under general anaesthesia, 120 min of jejunal ischaemia followed by 120 min of reperfusion was induced in 14 warmbloods. During ischaemia, blood flow was reduced by 80% (LF, n = 7) or by 100% (NF, n = 7). Intestinal blood flow and oxygen saturation were measured by Laser Doppler fluxmetry and spectrophotometry. Clinical, histological, immunohistochemical and Ussing chamber analyses were performed on intestinal samples collected hourly. Tissue oxygen saturation was significantly lower in NF ischaemia. The LF group exhibited high variability in oxygen saturation and mucosal damage. Histologically, more haemorrhage was found in the LF group at all time points. Cleaved-caspase-3 and calprotectin-stained cells increased during reperfusion in both groups. After NF ischaemia, the tissue conductance was significantly higher during reperfusion. These results aid in the selection of suitable experimental models for future studies. Although the LF model has been suggested to be more representative for clinical strangulating small intestinal disease, the NF model produced more consistent IRI.

The short-term effects of RBC transfusions on intestinal injury in preterm infants.

BackgroundAnemic preterm infants may require red blood cell (RBC) transfusions to maintain sufficient oxygen supply to vital organs. Transfusion treatment, however, may have adverse intestinal effects. We aimed to investigate the short-term effects of RBC transfusions, hypothesizing to find signs of oxidative stress and intestinal injury, possibly related to levels of splanchnic (re-)oxygenation.MethodsWe prospectively included preterm infants (gestational age < 32 weeks). We measured urinary biomarkers for oxidative stress (8-isoprostane) and intestinal cell injury (intestinal fatty acid-binding protein, I-FABP) shortly before and after RBC transfusion. Splanchnic oxygen saturation (rsSO2) and rsSO2 variability were assessed simultaneously.ResultsTwenty-nine preterm infants received 58 RBC transfusions at various postnatal ages. Six of them developed necrotizing enterocolitis (NEC) after transfusion. Urinary 8-isoprostane and I-FABP increased following RBC transfusion (median 282–606 pg/ml and 4732–6968 pg/ml, p < 0.01), more pronounced in infants who developed NEC. Change in I-FABP correlated with change in 8-isoprostane (rho = 0.623, p < 0.01). Lower rsSO2 variability, but not higher mean rsSO2 was associated with higher 8-isoprostane and I-FABP levels after transfusion.ConclusionsPreterm RBC transfusions are associated with concomitant signs of oxidative stress and intestinal injury, parallel with lower variability in splanchnic oxygenation. This may represent the early pathogenetic process of transfusion-associated NEC.Impact Red blood cell (RBC) transfusions in preterm infants are associated with a near 2-fold increase in urinary biomarkers for oxidative stress (8-isoprostane) and intestinal cell injury (intestinal fatty acid-binding protein, I-FABP).Magnitude of change in I-FABP strongly correlated with the magnitude of 8-isoprostane change, suggesting a role for oxidative stress in the pathogenesis of intestinal injury.Lower splanchnic oxygen saturation variability following RBC transfusion was associated with higher 8-isoprostane and I-FABP levels.Loss of splanchnic variability after RBC transfusion may result from increased oxidative stress and its concomitant intestinal injury, possibly representing the early pathogenetic process of transfusion-associated necrotizing enterocolitis.

The use of oxygen reserve index in one-lung ventilation and its impact on peripheral oxygen saturation, perfusion index and, pleth variability index

BackgroundOur goal is to investigate the use of the oxygen reserve index (ORi) to detect hypoxemia and its relation with parameters such as; peripheral oxygen saturation, perfusion index (PI), and pleth variability index (PVI) during one-lung ventilation (OLV).MethodsFifty patients undergoing general anesthesia and OLV for elective thoracic surgeries were enrolled in an observational cohort study in a tertiary care teaching hospital. All patients required OLV after a left-sided double-lumen tube insertion during intubation. The definition of hypoxemia during OLV is a peripheral oxygen saturation (SpO2) value of less than 95%, while the inspired oxygen fraction (FiO2) is higher than 50% on a pulse oximetry device. ORi, pulse oximetry, PI, and PVI values were measured continuously. Sensitivity, specificity, positive and negative predictive values, likelihood ratios, and accuracy were calculated for ORi values equal to zero in different time points during surgery to predict hypoxemia. At Clinicaltrials.gov registry, the Registration ID is NCT05050552.ResultsHypoxemia was observed in 19 patients (38%). The accuracy for predicting hypoxemia during anesthesia induction at ORi value equals zero at 5 min after intubation in the supine position (DS5) showed a sensitivity of 92.3% (95% CI 84.9–99.6), specificity of 81.1% (95% CI 70.2–91.9), and an accuracy of 84.0% (95% CI 73.8–94.2). For predicting hypoxemia, ORi equals zero show good sensitivity, specificity, and statistical accuracy values for time points of DS5 until OLV30 where the sensitivity of 43.8%, specificity of 64%, and an accuracy of 56.1% were recorded. ORi and SpO2 correlation was found at DS5, 5 min after lateral position with two-lung ventilation (DL5) and at 10 min after OLV (OLV10) (p = 0.044, p = 0.039, p = 0.011, respectively). Time-dependent correlations also showed that; at a time point of DS5, ORi has a significant negative correlation with PI whereas, no correlations with PVI were noted.ConclusionsDuring the use of OLV for thoracic surgeries, from 5 min after intubation (DS5) up to 30 min after the start of OLV, ORi provides valuable information in predicting hypoxemia defined as SpO2 less than 95% on pulse oximeter at FiO2 higher than 50%.

Application of oxygen saturation variability analysis for the detection of exacerbation in individuals with COPD: A proof-of-concept study.

BackgroundIndividuals with chronic obstructive pulmonary disease (COPD) commonly experience exacerbations, which may require hospital admission. Early detection of exacerbations, and therefore early treatment, could be crucial in preventing admission and improving outcomes. Our previous research has demonstrated that the pattern analysis of peripheral oxygen saturation (SpO2) fluctuations provides novel insights into the engagement of the respiratory control system in response to physiological stress (hypoxia). Therefore, this pilot study tested the hypothesis that the pattern of SpO2 variations in overnight recordings of individuals with COPD would distinguish between stable and exacerbation phases of the disease.MethodsOvernight pulse oximetry data from 11 individuals with COPD, who exhibited exacerbation after a period of stable disease, were examined. Stable phase recordings were conducted overnight and one night prior to exacerbation recordings were also analyzed. Pattern analysis of SpO2 variations was carried examined using sample entropy (for assessment of irregularity), the multiscale entropy (complexity), and detrended fluctuation analysis (self‐similarity).ResultsSpO2 variations displayed a complex pattern in both stable and exacerbation phases of COPD. During an exacerbation, SpO2 entropy increased (p = 0.029) and long‐term fractal‐like exponent (α2) decreased (p = 0.002) while the mean and standard deviation of SpO2 time series remained unchanged. Through ROC analyses, SpO2 entropy and α2 were both able to classify the COPD phases into either stable or exacerbation phase. With the best positive predictor value (PPV) for sample entropy (PPV = 70%) and a cut‐off value of 0.454. While the best negative predictor value (NPV) was α2 (NPV = 78%) with a cut‐off value of 1.00.ConclusionAlterations in SpO2 entropy and the fractal‐like exponent have the potential to detect exacerbations in COPD. Further research is warranted to examine if SpO2 variability analysis could be used as a novel objective method of detecting exacerbations.

Multiscale increment entropy: An approach for quantifying the physiological complexity of biomedical time series

Time series data recorded from physiological systems often innately exhibit inherent physiological complexity variation on a long-range temporal scale. Multiscale analysis is considered vital for characterising the features of physiological signals. In this research, we propose a novel multiscale analysis method called multiscale increment entropy (MIE), which integrates incremental entropy (IncrEn) and multiscale analysis. MIE inherits the nature of IncrEn, which considers the fluctuation directions and amplitude of a time series. Experiments on both synthetic and real-world signals indicate that MIE performs better than popular approaches as a complexity index. On each temporal scale, MIE corroborates the complexity-loss theory of ageing and disease well. Furthermore, it reliably discriminates either between the EEG time series and heartbeat intervals of healthy subjects and patients or between the oxygen saturation variability of young and elderly, while commonly used algorithms do not perform well in the above cases. MIE requires less computational time compared to several popular approaches. It also has lower variations and is always defined across scales, even for short time series. These merits make it suitable for analysing unknown physiological time series.

The tiny effects of respiratory masks on physiological, subjective, and behavioral measures under mental load in a randomized controlled trial

Since the outbreak of the coronavirus disease (COVID-19), face coverings are recommended to diminish person-to-person transmission of the SARS-CoV-2 virus. Some public debates concern claims regarding risks caused by wearing face masks, like, e.g., decreased blood oxygen levels and impaired cognitive capabilities. The present, pre-registered study aims to contribute clarity by delivering a direct comparison of wearing an N95 respirator and wearing no face covering. We focused on a demanding situation to show that cognitive efficacy and individual states are equivalent in both conditions. We conducted a randomized-controlled crossover trial with 44 participants. Participants performed the task while wearing an N95 FFR versus wearing none. We measured physiological (blood oxygen saturation and heart rate variability), behavioral (parameters of performance in the task), and subjective (perceived mental load) data to substantiate our assumption as broadly as possible. We analyzed data regarding both statistical equivalence and differences. All of the investigated dimensions showed statistical equivalence given our pre-registered equivalence boundaries. None of the dimensions showed a significant difference between wearing an FFR and not wearing an FFR.Trial Registration: Preregistered with the Open Science Framework: https://osf.io/c2xp5 (15/11/2020). Retrospectively registered with German Clinical Trials Register: DRKS00024806 (18/03/2021).

A novel, simple, and accurate pulse oximetry indicator for screening adult obstructive sleep apnea.

The objective of the study was to develop a multiparametric oximetry indicator (IMp-SpO2) to diagnose obstructive sleep apnea in adults. This was an observational, retrospective study of diagnostic accuracy. We included adults who had had a diagnostic polysomnography with few artifacts and a total sleep time of at least 180 min in the sleep laboratory. Obstructive sleep apnea (OSA) was defined as an apnea-hypopnea index (AHI) ≥ 5. The database was randomly divided into an experimental (Exp-G) and validation (Val-G) group. The program calculated several parameters of oxygen saturation variability (Par-VarSpO2): (a) oxygen desaturation index (ODI ≥ 3, 4%) and (b) 90, 95, and 97.5 percentiles of both the number of oxygen desaturations ≥ 3 and 4% (P90-97.5 OD3/4 W5-60) and SpO2 standard deviations in moving windows from 5 to 60 min (P90-P97.5 SDSpO2 W5-10). Area under the ROC curve (AUC-ROC), sensitivity, specificity, positive/negative likelihood ratios, and accuracy were calculated. Of 1141 adults included in the study, experimental (571) and validation group (570) were similar (women 47% vs 45%, BMI 27.5 kg/m2 vs 27.2 kg/m2, and AHI 11.7 vs 12, p NS). The IMp-SpO2 developed in the experimental group consisted of a combination of 10 parameters of oxygen saturation variability. The presence of at least one IMp-SpO2 variable had a high diagnostic performance for OSA (sensitivity/specificity/accuracy: Exp-G: 92.8/94/93.2%; Val-G: 93/95.2/93.7%). The IMp-SpO2 AUC-ROC was higher (Exp-G 0.934, Val-G 0.941) than most of the Par-VarSpO2 (0.898-0.929, p < 0.05). The IMp-SpO2 showed a > 90% accuracy for OSA diagnosis in adults.