Ratio Delta Research Articles

Abstract 4140169: Neonatal Electroencephalogram Alpha:Delta changes precede neurologic injury during Antegrade Cerebral Perfusion and Deep Hypothermic Circulatory Arrest

Background: Although neurologic injury commonly occurs following neonatal aortic arch reconstruction, the mechanism(s) are poorly understood. A decrease or inter-hemispheric difference in the electroencephalogram (EEG) Alpha:Delta ratio (A:D) precedes cerebral ischemia during antegrade cerebral perfusion (ACP). However, it is unknown if A:D changes precede neurologic injury during deep hypothermic circulatory arrest (DHCA). We hypothesized during DHCA, the A:D would decrease and that a significant A:D inter-hemispheric difference would precede neurologic injury. Methods: Neonates requiring aortic arch reconstruction underwent simultaneous quantitative EEG monitoring. Left vs. right hemispheric, anterior, and posterior A:Ds were recorded at baseline, arterial cannulation, cooling, ACP vs. DHCA, and the rewarming phases of the operation. Left vs. right A:D differences > 25% were considered significant for ischemia and the cumulative duration of a significant A:D inter-hemispheric difference was calculated. Post-operative neurologic injury was defined as either stroke or seizure. Results: From 86 neonates, 16.2 % (14) required DHCA and 83.8 % (72) ACP. There were no significant differences in the pre-operative demographics or baseline A:Ds between groups. Although the A:Ds remained similar during ACP, after 15 minutes the hemispheric A:Ds decreased significantly during DHCA (Figure 1). Eleven neonates (ACP-7 vs. DHCA-4) developed neurologic injury. The duration of an anterior A:D inter-hemispheric difference > 25% was significantly greater within neonates that developed neurologic injury (25 {IQR:0,65 minutes} vs. 5 {IQR: 0, 15 minutes}; p<0.001). Multivariate analysis demonstrated that the duration of an anterior A:D difference > 25% was independently associated with neurologic injury using either ACP or DHCA (Odds Ratio:1.081, 95% CI: 1.025, 1.141; p-value=0.004). Conclusion: Unlike ACP, the A:D decreased significantly during DHCA. During either DHCA or ACP, a significant anterior inter-hemispheric A:D difference was independently associated with neurologic injury and suggests the importance of quantifying the A:D during neonatal arch reconstruction.

Changes in Neonatal Intraoperative Electroencephalogram Alpha: Delta Ratios Precede Neurologic Injury.

Background: Unrecognized intraoperative cerebral ischemia during neonatal aortic arch reconstruction may precede neurologic injury. Electroencephalogram (EEG) alpha:delta ratio (A:D) changes predict cerebral ischemia; however, if A:D differences can identify ischemia during neonatal antegrade cerebral perfusion (ACP) and aortic arch reconstruction is unknown. We hypothesized that A:D changes would precede neurologic injury. Methods: Simultaneous EEG derived left versus right: hemispheric and anterior cerebral A:Ds were retrospectively measured at baseline and every 5 min during arterial cannulation, cooling, ACP, and the rewarming phases of the operation. A paired left versus right A:D difference >25% was considered significant for ischemia, and the duration of a significant and continuous A:D difference was quantified in minutes. Neonates were divided into two groups: (1) new neurologic injury (stroke or seizure) and (2) no known neurologic injury. Results: From 72 neonates, there were no significant differences in the baseline A:Ds. Seven neonates (9.7%) developed a new neurologic injury (seizure = 3, stroke = 2, seizure and stroke = 2). Male gender and longer ACP times were significantly associated with neurologic injury. In neonates with a neurologic injury, the duration of a significant and continuous A:D difference was longer within the hemispheric and anterior regions. Multivariable analysis demonstrated that a significant and continuous anterior A:D difference (odds ratio: 1.345, 95% CI 1.058-1.712; P = .01) was independently associated with neurologic injury. Conclusions: A longer continuous anterior A:D difference > 25% was independently associated with neurologic injury. Intraoperative EEG monitoring could be considered during neonatal arch reconstruction.

Deep sea cold seeps are a sink for mercury and source for methylmercury

The effect of seafloor cold seeps on the biogeochemical cycling of mercury (Hg) remains enigmatic. Here we demonstrate substantial enrichments of mercury and methylmercury, along with the presence of microbes capable of metabolizing mercury in sediments of the Haima cold seep, South China Sea, by analyzing mercury and methylmercury concentrations, mercury isotopic composition analyses and metagenomic analyses of sediment cores. Compared to the reference area, the sediments in the upper sediment column of the active-seep area were 2.4 times enriched in Hg and 10.5 times in methylmercury. The slope of the capital delta ratio of mercury 199 to mercury 201 (Δ199Hg/Δ201Hg) with 1.23 ± 0.10 in the active-seep area indicate the occurrence of dark redox reactions. Genes related to mercury methylation (hgcA), demethylation (merB) and reduction (merA) were phylogenetically associated with several bacterial and archaeal linages. We roughly estimated an additional 2,835 Mg mercury and 9 Mg methylmercury are stored in cold seep globally. In summary, we propose that cold seeps globally function as a previously unrecognized sink for mercury and source for methylmercury in the deep ocean.

Testosterone enhances adipose tissue-blood pressure axis in obese mice exposed to early life stress

Previously, we have shown that male and female mice exposed to maternal separation and early weaning (MSEW), a model of early life stress, display exacerbated obesity-induced hypertension in response to chronic high fat diet. However, only male mice showed higher sympathetic tone at baseline, along with increased neuronal activation in PVN and pressor response to the acute stimulation of TRVP1 channels with capsaicin, a mechanism known as adipose afferent reflex (AAR). The aim of this study was to investigate whether obese male MSEW mice show 1) increased intracellular calcium in response to capsaicin in neuronal cultures of dorsal ganglia root (DRG), and 2) a role for sex hormones in AAR reactivity in vivo. Six-months-old control and MSEW fed a high fat diet (HFD, 60% kcal fat) were injected with pAAV-CAG-tdTomato (59462-PHP.S, 1012 viral particles); 8 sites; 4 ul/site; bilateral). After 6 weeks, mice were decapitated and DRGs (L5-T12) were collected and placed in ice-cold HBSS solution, dissociated and mixed with Collagenase P (1 mg/ml in HBSS, 15 min, 37 oC). After 0.25% Trypsin-EDTA incubation, neurons were mechanically dissociated, collected by centrifugation and resuspended in DMEM-10% FBS, plated onto the Matrigel Basement Membrane Matrix covered coverslips and maintained at 37 oC for 15-16 hours. Neuronal cultures were incubated in Ca2+ imaging solution with 2 μM Fura-2 AM, 30 min in dark conditions. After de-estirification, intracellular Ca2+ transients were visualized by exciting Fura-2 at 340 ± 20 nm and 380 ± 20 nm using a high-speed filter changer to obtain a ratiometric value independent of indicator concentration. Emitted light was passed through a dichroic filter (400-nm high pass) and an emitter filter (520 ± 30 nm) and was digitized onto the sensor of an EMCCD camera. Background subtraction and normalization to baseline were used to quantify changes in fluorescence. Despite similar resting uncalibrated ratios of calcium levels between groups (~0.6 ratio units, n=3), sensory neurons from MSEW mice tended to display larger responses to capsaicin (50 uM), showing elevated calcium kinetics vs. controls (0.56±0.09 vs. 0.31±0.12 delta ratio, respectively, p=0.063) as well as longer transients, perhaps indicative of reduced clearance or buffering. A separate set of age-matched mice were gonadectomized. After 4 weeks, anesthetized mice were fitted with carotid artery catheter for direct blood pressure measurement in response to the infusion of perigonadal fat with capsaicin (1.5 pmol/μL during 2 minutes in 4 sites, bilaterally). Capsaicin-induced pressor response was exacerbated in intact MSEW male mice compared to intact controls (9.0±0.2 vs. 1.3±0.2 delta mmHg, respectively, n=6, p<0.05). Orchidectomy attenuated delta blood pressure in MSEW mice to 7.0±0.2 mmHg (p<0.05 vs. intact MSEW), while enhanced delta blood pressure in control mice to 7.5±0.2 mmHg (p<0.05 vs. intact control). MSEW did not influence the pressor response to perigonadal fat stimulation with capsaicin either in intact or ovariectomized obese female mice (n=4-6 per group, p>0.05), suggesting that estradiol may not to play a protective role in obese females AAR reactivity. This data indicates that testosterone could buffer the AAR reactivity of obese control mice, while MSEW exerts an opposite effect. Thus, investigating testosterone signaling on calcium handling mechanisms (i.e., buffers, pumps, ER-mediated calcium release) in sensory neurons innervating visceral fat will provide insights on the sex-specific contribution of afferent sympathoexitatory signals to obesity-hypertension in male MSEW mice. This study was supported by NIH R01 HL135158, and SALT pilot - University of Kentucky to ASL. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Pitfalls and possibilities of using Root SedLine for continuous assessment of EEG waveform-based metrics in intensive care research

Objective. The Root SedLine device is used for continuous electroencephalography (cEEG)-based sedation monitoring in intensive care patients. The cEEG traces can be collected for further processing and calculation of relevant metrics not already provided. Depending on the device settings during acquisition, the acquired traces may be distorted by max/min value cropping or high digitization errors. We aimed to systematically assess the impact of these distortions on metrics used for clinical research in the field of neuromonitoring. Approach. A 16 h cEEG acquired using the Root SedLine device at the optimal screen settings was analyzed. Cropping and digitization error effects were simulated by consecutive reduction of the maximum cEEG amplitude by 2 µV or by reducing the vertical resolution. Metrics were calculated within ICM+ using minute-by-minute data, including the total power, alpha delta ratio (ADR), and 95% spectral edge frequency. Data were analyzed by creating violin- or box-plots. Main Results. Cropping led to a continuous reduction in total and band power, leading to corresponding changes in variability thereof. The relative power and ADR were less affected. Changes in resolution led to relevant changes. While the total power and power of low frequencies were rather stable, the power of higher frequencies increased with reducing resolution. Significance. Care must be taken when acquiring and analyzing cEEG waveforms from Root SedLine for clinical research. To retrieve good quality metrics, the screen settings must be kept within the central vertical scale, while pre-processing techniques must be applied to exclude unacceptable periods.

Evaluation of statistical downscaling techniques and projection of climate extremes in central Texas, USA

This study evaluates statistical downscaling techniques using different metrics and compares climate change signals and extreme precipitation and temperature changes under future climate change scenarios in the Bosque watershed, North-Central Texas. The study utilizes observed gridded Daymet data to assess the effectiveness of statistical downscaling techniques. It involves comparing the mean, the 90th percentile, 10th percentile, wet day frequency, and Cumulative Distribution Function (CDF) of climate model simulations before and after downscaling and the Daymet data during the historical period (1981–2005). Furthermore, the study analyzes changes in climate change signals, extreme precipitation, and temperature values under both near-future (2031–2060) and far-future (2070–2099) climate scenarios. The Ratio Delta method (DeltaSD) and Equi-Distant Quantile Mapping (EDQM) statistical downscaling techniques adjust the mean annual, the wet days frequency, the 90th and 10th percentiles, and the CDF of Global Climate Models (GCMs) simulations of historical precipitation and temperature. The downscaling techniques influenced the climate change signal and changes in extreme values in the future climate. When examining future climate projections produced using the DeltaSD method, we observe a more pronounced reduction in precipitation, while simulations generated through EDQM exhibit a higher frequency of heavy precipitation events (R10mm, R20mm) and consecutive dry days (CDD). It's worth noting that the uncertainties associated with the statistical downscaling techniques are relatively small and not statistically significant (≤0.05). In contrast, substantial and significant uncertainties arise from the choice of emission scenarios and the selection of driving GCMs. Across most climate change scenarios, there is a consistent trend towards increased temperatures and extreme temperature indices. The trend of extreme temperature indices shows variation following the choice of emission scenarios where a significant change in temperature extremes was detected under the RCP8.5 emission scenario.

Quantitative patient graph analysis for transient ischemic attack risk factor distribution based on electronic medical records

A transient ischemic attack (TIA) affects millions of people worldwide. Although TIA risk factors have been identified individually, a systemic quantitative analysis of all health factors relevant to TIA using electronic medical records (EMR) remains lacking. This study employed a data-driven approach, leveraging hospital EMR data to create a TIA patient health factor graph. This graph consisted of 737 TIA and 737 control patient nodes, 740 health factor nodes, and over 33,000 relations between patients and factors. For all health factors in the graph, the connection delta ratios (CDRs) were determined and ranked, generating a quantitative distribution of TIA health factors. A literature review confirmed 56 risk factors in the distribution and unveiled a potential new risk factor “rhinosinusitis” for future validation. Moreover, the patient graph was visualized together with the TIA knowledge graph in the Unified Medical Language System. This integration enables clinicians to access and visualize patient data and international standard knowledge within a unified graph. In conclusion, graph CDR analysis can effectively quantify the distribution of TIA risk factors. The resulting TIA risk factor distribution might be instrumental in developing new risk prediction machine learning models for screening and early detection of TIA.

Correlations Between Quantitative EEG Parameters and Cortical Blood Flow in Patients Undergoing Extracorporeal Membrane Oxygenation With and Without Encephalopathy.

The neurologic examination of patients undergoing extracorporeal membrane oxygenation (ECMO) is crucial for evaluating irreversible encephalopathy but is often obscured by sedation or neuromuscular blockade. Noninvasive neuromonitoring modalities including diffuse correlation spectroscopy and EEG measure cerebral perfusion and neuronal function, respectively. We hypothesized that encephalopathic ECMO patients with greater degree of irreversible cerebral injury demonstrate less correlation between electrographic activity and cerebral perfusion than those whose encephalopathy is attributable to medications. We performed a prospective observational study of adults undergoing ECMO who underwent simultaneous continuous EEG and diffuse correlation spectroscopy monitoring. (Alpha + beta)/delta ratio and alpha/delta Rartio derived from quantitative EEG analysis were correlated with frontal cortical blood flow index. Patients who awakened and followed commands during sedation pauses were included in group 1, whereas patients who could not follow commands for most neuromonitoring were placed in group 2. (Alpha + beta)/delta ratio-blood flow index and ADR-BFI correlations were compared between the groups. Ten patients (five in each group) underwent 39 concomitant continuous EEG and diffuse correlation spectroscopy monitoring sessions. Four patients (80%) in each group received some form of analgosedation during neuromonitoring. (Alpha + beta)/delta ratio-blood flow index correlation was significantly lower in group 2 than group 1 (left: 0.05 vs. 0.52, P = 0.03; right: -0.12 vs. 0.39, P = 0.04). Group 2 ADR-BFI correlation was lower only over the right hemisphere (-0.06 vs. 0.47, P = 0.04). Correlation between (alpha + beta)/delta ratio and blood flow index were decreased in encephalopathic ECMO patients compared with awake ones, regardless of the analgosedation use. The combined use of EEG and diffuse correlation spectroscopy may have utility in monitoring cerebral function in ECMO patients.

IMPORTANCE OF BODY BALANCE DURING SLEEP: COMPARISON OF FLAT AND TRANSFORMING BEDS

Body imbalance is one cause of sleep disorders. If one continues to sleep in an unbalanced state, various diseases, as well as headaches and stress, may occur. Some studies have been conducted to solve body imbalance during sleep, but most have used spring mattresses, and because body pressure varies by user, limitations exist for balancing pressure with this type of mattress. In our study, we investigated sleep quality using a transforming bed that conformed to the body and a flat bed that did not conform, considering user body pressure on both. We evaluated sleep quality with polysomnography and the Pittsburgh Sleep Quality Index, Korean version (PSQI–K) for 30 participants. Polysomnography showed that the ratio of delta and alpha waves in flat bed sleep was high; the ratio of theta waves was higher in transforming bed sleep than it was in flat bed sleep. The PSQI–K showed that most participants had a lower sleep index when using the transforming bed than when using the flat bed. Thus, we confirmed that sleep quality using a transforming bed was better than that of a flat bed. Therefore, considering body balance during sleep can help improve sleep quality.

Stratification and temporal evolution of mixing regimes in diurnally heated river flows

Direct numerical simulations of stratified open channel flows subject to a varying surface heat flux are performed. The influence of the diurnal heating time on the spatial and temporal variation of mixing in the flow and the characteristics of the mean flow state are examined. The control parameters are the bulk stability parameter lambda_{B}, defined through the ratio of the channel height delta and a bulk Obukhov length scale mathscr{L}_{B}, and the diurnal time scale hat{t}, defined as the ratio of the heating time to an eddy turnover time. The Prandtl number Pr and Reynolds number Re_{tau} have values of 1 and 400. Simulations are performed over hat{t} = 1 to 24 and lambda_{B} = 0.6 to 26. Two key flow features are used to classify the flow regimes observed, namely the laminar layer depth (LLD) and stratified layer depth (SLD) where the LLD is defined as the depth from the free surface when the buoyancy Reynolds number Re_{B} approx 7 and the SLD is the depth from the free surface when the turbulent Froude number Fr approx 1. This study attempts to characterise how these length scales vary across the diel cycle. The LLD is a viscous length scale and a regime map of a viscous parameter, the bulk Obhukov Reynolds number Re_mathscr{L}, and hat{t} is presented to classify the LLD behaviour. A regime map of lambda _{B} and hat{t} is presented to classify the behaviour of the SLD. Three classifications for each layer depth behaviour within a diel cycle form the basis of the regime maps for this paper: a neutral flow where the LLD or SLD does not exist (denoted by NL and NS), a stratified flow where the LLD or SLD are diurnally varying (denoted as DL and DS) and a persistent layer of the LLD or SLD (denoted as PL and PS). The transition between the NL to DL is hat{t} propto Re_{mathscr{L}}^{4.5}, DL to PL is hat{t} propto Re_{mathscr{L}}^{- 0.5}, NS to DS is hat{t} propto lambda _{B}^{0} and DS to PS is hat{t} propto lambda _{B}^{1}. The regime maps may be used as a predictive tool to determine when suppressed mixing regimes occur in rivers. At each flow depth, the flow sweeps though a range of mixing states across the diel cycle. The local mixing efficiency are briefly assessed and found to scale well with the instantaneous Fr number according to the regimes proposed by Garanaik and Venayagamoorthy (J. Fluid Mech., vol. 867, 2019, pp. 323-333).

SeizFt: Interpretable Machine Learning for Seizure Detection Using Wearables.

This work presents SeizFt-a novel seizure detection framework that utilizes machine learning to automatically detect seizures using wearable SensorDot EEG data. Inspired by interpretable sleep staging, our novel approach employs a unique combination of data augmentation, meaningful feature extraction, and an ensemble of decision trees to improve resilience to variations in EEG and to increase the capacity to generalize to unseen data. Fourier Transform (FT) Surrogates were utilized to increase sample size and improve the class balance between labeled non-seizure and seizure epochs. To enhance model stability and accuracy, SeizFt utilizes an ensemble of decision trees through the CatBoost classifier to classify each second of EEG recording as seizure or non-seizure. The SeizIt1 dataset was used for training, and the SeizIt2 dataset for validation and testing. Model performance for seizure detection was evaluated using two primary metrics: sensitivity using the any-overlap method (OVLP) and False Alarm (FA) rate using epoch-based scoring (EPOCH). Notably, SeizFt placed first among an array of state-of-the-art seizure detection algorithms as part of the Seizure Detection Grand Challenge at the 2023 International Conference on Acoustics, Speech, and Signal Processing (ICASSP). SeizFt outperformed state-of-the-art black-box models in accurate seizure detection and minimized false alarms, obtaining a total score of 40.15, combining OVLP and EPOCH across two tasks and representing an improvement of ~30% from the next best approach. The interpretability of SeizFt is a key advantage, as it fosters trust and accountability among healthcare professionals. The most predictive seizure detection features extracted from SeizFt were: delta wave, interquartile range, standard deviation, total absolute power, theta wave, the ratio of delta to theta, binned entropy, Hjorth complexity, delta + theta, and Higuchi fractal dimension. In conclusion, the successful application of SeizFt to wearable SensorDot data suggests its potential for real-time, continuous monitoring to improve personalized medicine for epilepsy.

Delta values as a prognostic marker in methanol poisoning: a retrospective cohort study

Purpose: The aim of the study was to evaluate the mortality prediction performances of delta bicarbonate, delta anion gap, and delta ratio in methanol poisoning (MP) cases.
 Materials and Methods: This clinical study, which followed a cross-sectional study design, involved patients with MP who were still alive when they initially arrived at the emergency department of a tertiary care hospital. Patients were divided into two groups mortality and non-mortality. Patients who died during treatment and follow-up were assigned to the mortality group, while others were assigned to the non-mortality group. Receiver Operating Characteristic (ROC) analysis was used to determine the cut-off in the diagnostic value measurements of biomarkers predicting mortality. 
 Results: Nine (20%) of the 45 patients in the study died during their follow-up. The two groups showed a significant difference in the averages of pH, bicarbonate (HCO3-), lactate, anion gap, delta anion gap, delta HCO3-, and delta ratio, but not in the averages of partial carbon dioxide pressure (pCO2). In predicting mortality, pH, anion gap, and delta anion gap were found to have outstanding diagnostic power (AUC>0.9), while HCO3-, delta HCO3-, delta ratio were found to have acceptable diagnostic power (AUC: 0.7-0.8). 
 Conclusion: Delta anion gap, delta bicarbonate, and delta ratio can be used as prognostic factors in predicting mortality in MP cases.

Copper isotope delta measurements in high purity materials: CCQM-P213 pilot study

Main textAccurate and precise isotope ratio measurements of heavy elements are playing an increasingly important role in modern analytical sciences and have numerous applications. Today, isotope ratio measurements are typically performed with two principal techniques: thermal ionization mass spectrometry (TIMS) and multiple collector-inductively coupled plasma mass spectrometry (MC-ICP-MS). To obtain accurate results by mass spectrometry, isotopic certified reference materials (iCRMs) are needed for mass bias correction and for the validation of the method used for analysis. Thus, it is of paramount importance to achieve measurement comparability of all data reported, and to assess measurement capability of each CRM producer/National Metrology Institute (NMI). Therefore, the international comparison (CCQM-P213) was performed to assess the analytical capabilities of NMIs for the accurate determination of copper isotope ratio delta values in high purity materials. The study was proposed by the coordinating laboratories National Research Council Canada (NRC), National Institute of Standards and Technology (NIST), Bundesanstalt für Materialforschung und -prüfung (BAM) and Physikalisch-Technische Bundesanstalt (PTB) as an activity of the Isotope Ratio Working Group (IRWG) of the Consultative Committee for Amount of Substance - Metrology in Chemistry and Biology (CCQM). Participants included six NMIs and one designated institute (DI) from the six countries. Although no measurement method was prescribed by the coordinating laboratories, MC-ICP-MS with either standard-sample bracketing (SSB) or combined SSB with internal normalization (C-SSBIN) models for mass bias correction were recommended. Results obtained from the six NMIs and one DI were in good agreement.To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Association between Hepatic Venous Congestion and Adverse Outcomes after Cardiac Surgery.

Hepatic venous flow patterns reflect pressure changes in the right ventricle and are also markers of systemic venous congestion. Fluid management is crucial in patients undergoing cardiac surgery. Our goal was to determine which factors are associated with the increased congestion of the liver as measured by Doppler ultrasound in patients undergoing cardiac surgery. This prospective, observational study included 41 patients without preexisting liver disease who underwent cardiac surgery between 1 January 2021 and 30 September 2021 at a tertiary heart center. In addition to routine echocardiographic examination, we recorded the maximal velocity and velocity time integral (VTI) of the standard four waves seen in the common hepatic vein (flow profile) using Doppler ultrasound preoperatively and at the 20-24th hour of the postoperative period. The ratios of the retrograde and anterograde hepatic venous waves were calculated, and the waveforms were compared to the baseline value and expressed as a delta ratio. Demographic data, pre- and postoperative echocardiographic parameters, intraoperative variables (procedure, cardiopulmonary bypass time), postoperative factors (fluid balance, vasoactive medication requirement, ventilation time and parameters) and perioperative laboratory parameters (liver and kidney function tests, albumin) were used in the analysis. Of the 41 patients, 20 (48.7%) were males, and the median age of the patients was 65.9 years (IQR: 59.8-69.9 years). Retrograde VTI growth showed a correlation with positive fluid balance (0.89 (95% CI 0.785-0.995) c-index. After comparing the postoperative echocardiographic parameters of the two subgroups, right ventricular and atrial diameters were significantly greater in the "retrograde VTI growth" group. The ejection fraction and decrement in ejection fraction to preoperative parameters were significantly different between the two groups. (p = 0.001 and 0.003). Ventilation times were longer in the retrograde VTI group. The postoperative vs. baseline delta VTI ratio of the hepatic vein correlated with positive fluid balance, maximum central venous pressure, and ejection fraction. (B = -0.099, 95% CI = -0.022-0.002, p = 0.022, B = 0.011, 95% CI = 0.001-0.021, p = 0.022, B = 0.091, 95% CI = 0.052-0.213, p = 0.002, respectively.) Conclusion: The increase of the retrograde hepatic flow during the first 24 h following cardiac surgery was associated with positive fluid balance and the decrease of the right ventricular function. Measurement of venous congestion or venous abdominal insufficiency seems to be a useful tool in guiding fluid therapy and hemodynamic management.

Building Practical Risk Prediction Models for Nasopharyngeal Carcinoma Screening with Patient Graph Analysis and Machine Learning.

To expand nasopharyngeal carcinoma (NPC) screening to larger populations, more practical NPC risk prediction models independent of Epstein-Barr virus (EBV) and other lab tests are necessary. Patient data before diagnosis of NPC were collected from hospital electronic medical records (EMR) and used to develop machine learning (ML) models for NPC risk prediction using XGBoost. NPC risk factor distributions were generated through connection delta ratio (CDR) analysis of patient graphs. By combining EMR-wide ML with patient graph analysis, the number of variables in these risk models was reduced, allowing for more practical NPC risk prediction ML models. Using data collected from 1,357 patients with NPC and 1,448 patients with control, an optimal set of 100 variables (ov100) was determined for building NPC risk prediction ML models that had, the following performance metrics: 0.93-0.96 recall, 0.80-0.92 precision, and 0.83-0.94 AUC. Aided by the analysis of top CDR-ranked risk factors, the models were further refined to contain only 20 practical variables (pv20), excluding EBV. The pv20 NPC risk XGBoost model achieved 0.79 recall, 0.94 precision, 0.96 specificity, and 0.87 AUC. This study demonstrated the feasibility of developing practical NPC risk prediction models using EMR-wide ML and patient graph CDR analysis, without requiring EBV data. These models could enable broader implementation of NPC risk evaluation and screening recommendations for larger populations in urban community health centers and rural clinics. These more practical NPC risk models could help increase NPC screening rate and identify more patients with early-stage NPC.

The Generation of a Lung Cancer Health Factor Distribution Using Patient Graphs Constructed From Electronic Medical Records: Retrospective Study.

Electronic medical records (EMRs) of patients with lung cancer (LC) capture a variety of health factors. Understanding the distribution of these factors will help identify key factors for risk prediction in preventive screening for LC. We aimed to generate an integrated biomedical graph from EMR data and Unified Medical Language System (UMLS) ontology for LC, and to generate an LC health factor distribution from a hospital EMR of approximately 1 million patients. The data were collected from 2 sets of 1397 patients with and those without LC. A patient-centered health factor graph was plotted with 108,000 standardized data, and a graph database was generated to integrate the graphs of patient health factors and the UMLS ontology. With the patient graph, we calculated the connection delta ratio (CDR) for each of the health factors to measure the relative strength of the factor's relationship to LC. The patient graph had 93,000 relations between the 2794 patient nodes and 650 factor nodes. An LC graph with 187 related biomedical concepts and 188 horizontal biomedical relations was plotted and linked to the patient graph. Searching the integrated biomedical graph with any number or category of health factors resulted in graphical representations of relationships between patients and factors, while searches using any patient presented the patient's health factors from the EMR and the LC knowledge graph (KG) from the UMLS in the same graph. Sorting the health factors by CDR in descending order generated a distribution of health factors for LC. The top 70 CDR-ranked factors of disease, symptom, medical history, observation, and laboratory test categories were verified to be concordant with those found in the literature. By collecting standardized data of thousands of patients with and those without LC from the EMR, it was possible to generate a hospital-wide patient-centered health factor graph for graph search and presentation. The patient graph could be integrated with the UMLS KG for LC and thus enable hospitals to bring continuously updated international standard biomedical KGs from the UMLS for clinical use in hospitals. CDR analysis of the graph of patients with LC generated a CDR-sorted distribution of health factors, in which the top CDR-ranked health factors were concordant with the literature. The resulting distribution of LC health factors can be used to help personalize risk evaluation and preventive screening recommendations.

Numerical Investigation of Regime Transition in Canopy Flows

We have carried out highly resolved simulations of turbulent open channel flows. The channel wall is covered with different filamentous layers sharing the same thickness (h=0.1H, where H is the open channel height) and bulk Reynolds number (i.e., Re_b=U_bH/nu , , U_b is the bulk velocity and nu the kinematic fluid viscosity). The layers are composed of rigid, slender cylindrical filaments mounted perpendicular to the bottom wall. We have selected two layer configurations characterised by filament spacing ratios of Delta S/H=pi /24simeq 0.13 and Delta S/H=pi /32simeq 0.098. The geometrical features of the two layers, allow to classify them as transitional canopies (lambda =dh/Delta S^2simeq 0.15, where d is the filament diameter, i.e. dh is the filament frontal area) (Monti et al. 2020), which is defined as the separation between the sparse-dense asymptotic regimes, proposed by Nepf (2012). While the physical characterisation of the two asymptotic regimes is fairly understood, the transitional conditions remain an open question since the physical characteristics unique to the sparse and dense scenarios coexist in the transitional regime. By resolving every single filament with the aid of an immersed boundary technique in the framework of a Large Eddy formulation, we report the physical mechanisms that emerge at the onset of different regimes (chosen values of lambda fall on the verge between a dense and a sparse condition) and verify the criterion associated with the inception of the transition regime.

Feasibility and potential of a bedside mini-EEG for diagnosing delirium superimposed on dementia

ObjectiveDelirium superimposed on dementia (DSD) is difficult to diagnose because symptoms of delirium might be interpreted as symptoms of dementia. To improve diagnostic accuracy, we investigated the potential of a brief point-of-care EEG measurement. MethodsThirty older patients were included, all with Major Neurocognitive Disorder (i.e. dementia) according to DSM-5 criteria. EEG was registered at right prefrontal and right temporal site, with eyes either open or closed for three minutes, simultaneously with the Discomfort Scale for Dementia of Alzheimer Type. The Confusion Assessment Method for the Intensive Care Unit was administered to determine the presence of symptoms of a delirium at the time of EEG administration. Video registrations were reviewed independently by two delirium experts. ResultsHigher activities of delta and theta1, and lower activities of theta2, alpha, and beta activity, were found in DSD when compared to dementia only. The ratio of delta and theta power during eyes-open conditions had the highest accuracy (AUC = 0.80 [0.63–0.94]; p <.001) to distinguish DSD from dementia alone. All subjects were on benzodiazepines and half on clozapine, thus the effects of psychotropics on EEG cannot be fully excluded. ConclusionsA brief point-of-care EEG at two sites of the head has the potential to aid in the detection of DSD. SignificanceThe diagnostic accuracy of EEG in recognizing or excluding delirium in patients who already have dementia is of large potential given the lack of proper diagnostic tools.

A novel graph methodology for analyzing disease risk factor distribution using synthetic patient data

Understanding the spectrum of risk factors affecting a patient’s specific disease can help personalize disease screening recommendations. Is it possible to use synthetic patient data to develop a novel graph methodology for visualizing and identifying potential risk factors for any given disease? This study simulated an electronic medical record (EMR) database with 150K synthetic patients generated by the Synthea tool; it constructed the patient health factor graph in the Neo4j graph database for lung cancer as an example target disease. The graph contained over 990,000 relations between the factor nodes and the patient nodes, and it was connected to Unified Medical Language System (UMLS) lung cancer subgraph. Such an integrated biomedical graph was able to view and compare patient health factors and biomedical knowledge in the same graph. Through graph search, the connection delta ratio (CDR) was calculated for each factor node as a simple measure of factor–disease relationship strength. Ranking health factors by CDR produced a distribution of potential risk factors. The top-ranked factors were largely verified by and consistent with reports in literature, demonstrating the validity of this graph method. Once validated in real patient data, the new graph method may have significant implications in identifying potential risk factors for personalized disease screening recommendations and personalized medicine.

A case–case study on the effect of primary and booster immunization with China-produced COVID-19 vaccines on prevention of pneumonia and viral load among vaccinated persons infected by Delta and Omicron variants

ABSTRACT Using a three-prefecture, two-variant COVID-19 outbreak in Henan province in January 2022, we evaluated the associations of primary and booster immunization with China-produced COVID-19 vaccines and COVID-19 pneumonia and SARS-CoV-2 viral load among persons infected by Delta or Omicron variant. We obtained demographic, clinical, vaccination, and multiple Ct values of infections ≥3 years of age. Vaccination status was either primary series ≥180 days prior to infection; primary series <180 days prior to infection, or booster dose recipient. We used logistic regression to determine odds ratios (OR) of Delta and Omicron COVID-19 pneumonia by vaccination status. We analysed minimum Ct values by vaccination status, age, and variant. Of 826 eligible cases, 405 were Delta and 421 were Omicron cases; 48.9% of Delta and 19.0% of Omicron cases had COVID-19 pneumonia. Compared with full primary vaccination ≥180 days before infection, the aOR of pneumonia was 0.48 among those completing primary vaccination <180 days and 0.18 among booster recipients among these Delta infections. Among Omicron infections, the corresponding aOR was 0.34 among those completing primary vaccination <180 days. There were too few (ten) Omicron cases among booster dose recipients to calculate a reliable OR. There were no differences in minimum Ct values by vaccination status among the 356 Delta cases or 70 Omicron cases. COVID-19 pneumonia was less common among Omicron cases than Delta cases. Full primary vaccination reduced pneumonia effectively for 6 months; boosting six months after primary vaccination resulted in further reduction. We recommend accelerating the pace of booster dose administration.