Splanchnic-cerebral oxygenation ratio associated with packed red blood cell transfusion in preterm infants.

BACKGROUND: Splanchnic-cerebral oxygenation ratio (SCOR), the ratio of splanchnic tissue oxygen (StO2 s) to simultaneously measured cerebral tissue oxygen (StO2 c), has been described as a surrogate to detect impaired splanchnic oxygenation associated with hypoperfusion status such as necrotizing enterocolitis. This concept is based on the presumption that any change in SCOR indicates a corresponding change in splanchnic tissue oxygenation as the numerator, whereas cerebral tissue oxygenation as the denominator remains stable. However, it is questionable to utilise this concept to detect splanchnic oxygenation changes in the context of packed red blood cell transfusion (PRBCT). AIM: The current study examines the contribution of both cerebral and splanchnic oxygenation components to PRBCT-associated SCOR changes in preterm infants. DESIGN: Prospective cohort study. SETTING: Neonatal intensive care. PATIENTS: Hemodynamically stable infants: Gestation <32 weeks; birth weight <1500 g; postmenstrual age <37 weeks: tolerating ≥120 ml/kg/day feed volume. INTERVENTIONS: PRBCT at 15 ml/kg, over 4 h. MAIN OUTCOME MEASURES: Transfusion-associated changes were determined by performing mixed models for repeated measures analysis between the 4-h mean pre-transfusion values (SCOR 0, StO2 s 0, and StO2 c 0) and the post-transfusion hourly mean values for the next 28 h (SCOR 1-28, StO2 s 1-28, and StO2 c 1-28). Dunnett's method was used to adjust for the multiplicity of the p value. RESULTS: Of 30 enrolled infants 14 [46.7%] male; median [IQR] birth weight, 923 [655-1064] g; gestation, 26.4 [25.5-28.1] weeks; enrolment weight, 1549 [1113-1882] g; and postmenstrual age, 33.6 [32.4-35.0] weeks, one infant was excluded because of corrupted NIRS data. With the commencement of PRBCT, SCOR demonstrated a downward trend throughout the study period. This drift was associated with an increasing StO2 c trend, while StO2 s remained unchanged throughout the study period. CONCLUSIONS AND RELEVANCE: PRBCT-associated SCOR decrease suggests improvement in cerebral oxygenation rather than worsening splanchnic oxygenation. Our study underlines that it is necessary to determine individual components of SCOR, namely cerebral and splanchnic StO2 to understand SCOR changes in the context of PRBCT.

Cerebral and splanchnic near-infrared spectroscopic dataset in premature newborns receiving packed red blood cell transfusion.

This article presents the near-infrared spectroscopy (NIRS) dataset of cerebral (StO2c) and splanchnic (StO2s) oxygenation in 29 stable premature infants admitted to a tertiary neonatal intensive care unit who received elective packed red blood cell transfusion (PRBCT) to treat anemia of prematurity. StO2c and StO2s data were prospectively recorded continuously from at least 4 hours before the beginning of PRBCT until 24 hours after its completion, using a 4-wavelength near-infrared spectroscopy (NIRS) monitor (FORE-SIGHT® absolute cerebral oximeter, CASMED, Branford, Connecticut, 06405 USA). StO2 data were downloaded as an analog output at a sampling rate of 1000Hz and aligned along the time axis in LabChart reader format (.adicht files) using a PowerLab data acquisition system [1] (PowerLab®, ADInstruments, Sydney, Australia). The .adicht files were then converted into .mat file format using a Python script (PythonTM version 3.7.3 [2]) and resampled at 1Hz for faster processing. Data that could not be physiologically explained (e.g., the absence of variability, [3] a 30% step change in StO2 between two subsequent data points for StO2[4]), as well as the data during the period of 'cares' were presumed to be artefactual and were replaced with 'NaN' or 'Not a Number' which is recognised by Matlab [5] (MATLAB 9.3, The MathWorks, Inc., Massachusetts, United States) and ignored for all subsequent processing while maintaining the correct time point of the StO2 signals. The data were then exported into Microsoft Excel format. The splanchnic cerebral oxygenation ratio (SCOR) was calculated as the ratio of StO2s/StO2c. A 4-hour mean pre-transfusion values (StO2s 0, StO2c 0, SCOR 0) and post-transfusion hourly mean values (1-28) were determined. Secondary data were derived from a Mixed Models for Repeated Measures (MMRM) analysis with the time point fitted as a fixed effect and the infant fitted as a random effect. The MMRM was used to perform paired comparisons between pre-transfusion and each of the post-baseline values. This article only provides the NIRS data. The secondary data and demography can be found in the article "Splanchnic-Cerebral Oxygenation Ratio associated with Packed Red Blood Cell Transfusion in preterm infants", published in Transfusion Medicine. [6] The data will be of use to researchers in neonatology, transfusion medicine, and physiology to understand changes in cerebral and splanchnic oxygenation associated with PRBCT. Data collection, processing, and analysis can be remodelled in larger multicentric randomised controlled studies to evaluate the effect of transfusion and feeding on transfusion-associated necrotising enterocolitis. The data are also helpful to explore the autoregulatory behaviour of the brain and gut when the oxygen content of blood is increased by administering PRBCT.

Hierarchical improvement of regional tissue oxygenation after packed red blood cell transfusion.

BACKGROUND: It is well established that counter-regulation to hypoxia follows a hierarchical pattern, with brain-sparing in preference to peripheral tissues. In contrast, it is unknown if the same hierarchical sequence applies to recovery from hypoxia after correction of anemia with packed red blood cell transfusion (PRBCT). OBJECTIVE: To understand the chronology of cerebral and splanchnic tissue oxygenation resulting after correction of anemia by PRBCT in preterm infants using near-infrared spectroscopy (NIRS). DESIGN: Prospective cohort study. SETTING: Neonatal intensive care. PATIENTS INCLUDED: Haemodynamically stable infants: <32 weeks gestation, <37weeks postmenstrual age, <1500 grams birth weight; and ≥120 mL/kg/day feeds tolerated. INTERVENTION: PRBCT at 15 mL/Kg over 4 hours. MAIN OUTCOME MEASURES: Transfusion-associated changes were determined by comparing the 4-hour mean pre-transfusion cerebral and splanchnic fractional tissue oxygen extraction (FTOEc0; FTOEs0) with hourly means during (FTOEc1-4; FTOEs1-4) and for 24 hours after PRBCT completion (FTOEc5-28; FTOEs5-28). RESULTS: Of 30 enrolled infants, 14[46.7%] male; median[IQR] birth weight, 923[655-1064]g; gestation, 26.4[25.5-28.1]weeks; enrolment weight, 1549[1113-1882]g; and postmenstrual age, 33.6[32.4-35]weeks, 1 infant was excluded because of corrupted NIRS data. FTOEc significantly decreased during and for 24 hours after PRBCT (p < 0.001), indicating prompt improvement in cerebral oxygenation. In contrast, FTOEs showed no significant changes during and after PRBCT (p>0.05), indicating failure of improvement in splanchnic oxygenation. CONCLUSION: Improvement in regional oxygenation after PRBCT follows the same hierarchical pattern with a prompt improvement of cerebral but not splanchnic tissue oxygenation. We hypothesise that this hierarchical recovery may indicate continued splanchnic hypoxia in the immediate post-transfusion period and vulnerability to transfusion-associated necrotizing enterocolitis (TANEC). Our study provides a possible mechanistic underpinning for TANEC and warrants future randomised controlled studies to stratify its prevention.

Association of Bolus Feeding With Splanchnic and Cerebral Oxygen Utilization Efficiency Among Premature Infants With Anemia and After Blood Transfusion.

Importance: The pathogenesis of transfusion-associated necrotizing enterocolitis remains elusive. Splanchnic hypoperfusion associated with packed red blood cell transfusion (PRBCT) and feeding has been implicated, but studies of splanchnic tissue oxygenation with respect to feeding plus PRBCT are lacking. Objective: To investigate the oxygen utilization efficiency of preterm gut and brain challenged with bolus feeding during anemia and after transfusion using near-infrared spectroscopy. Design, Setting, and Participants: This prospective cohort study conducted from September 1, 2014, to November 30, 2016, at a tertiary neonatal intensive care unit included 25 hemodynamically stable infants with gestational age less than 32 weeks, birth weight less than 1500 g, and postmenstrual age younger than 37 weeks. Data analysis was performed from August 1, 2017, to October 31, 2018. Exposures: Infants received PRBCT (15 mL/kg for 4 hours) and at least 120 mL/kg daily of second hourly bolus feedings. Main Outcomes and Measures: Splanchnic fractional tissue oxygen extraction (FTOEs) and cerebral fractional tissue oxygen extraction (FTOEc) measures were made during 75-minute feeding cycles that comprised a 15-minute preprandial feeding phase (FP0) and 4 contiguous 15-minute postprandial feeding phases (FP1, FP2, FP3, and FP4; each 15 minutes long). The intraindividual comparisons of feeding-related changes were evaluated during the pretransfusion epoch (TE0: 4 hours before onset of transfusion) and 3 TEs after transfusion (TE1: first 8 hours after PRBCT completion; TE2: 9-16 hours after PRBCT completion; and TE3: 17-24 hours after PRBCT completion). Results: Of 25 enrolled infants (13 [52%] female; median birth weight, 949 g [interquartile range {IQR}, 780-1100 g]; median gestational age, 26.9 weeks [IQR, 25.9-28.6 weeks]; median enrollment weight, 1670 g [IQR, 1357-1937 g]; and median postmenstrual age, 34 weeks [IQR, 32.9-35 weeks]), 1 infant was excluded because of corrupted near-infrared spectroscopy data. No overall association was found between FTOEs and FPs in a multivariable repeated-measures model that accounted for transfusion epochs (primary analysis approach) (FP0: mean estimate, 11.64; 95% CI, 9.55-13.73; FP1: mean estimate, 12.02; 95% CI, 9.92-14.11; FP2: mean estimate, 12.77; 95% CI, 10.68-14.87; FP3: mean estimate, 12.54; 95% CI, 10.45-14.64; FP4: mean estimate, 12.98; 95% CI, 10.89-15.08; P = .16 for the FP association). However exploratory analyses of postprandial changes in FTOEs undertaken for each transfusion epoch separately found evidence of increased postprandial FTOEs during TE1 (mean [SD] FTOEs, 10.55 [5.5] at FP0 vs 13.21 [5.96] at FP4, P = .046). The primary and exploratory analyses found no association between FTOEc and feeding phases, suggesting that cerebral oxygenation may be protected. Conclusions and Relevance: The findings suggest that enteral feeding may be associated with gut ischemia and potentially transfusion-associated necrotizing enterocolitis. The postprandial changes in FTOEs appear to warrant further investigation in larger randomized studies.

Optimising the Apnoea Classification Performance of a Neural Network Classifier Processing ECG-Oximetry Signals.

In this paper we investigate using principal components analysis to optimize the performance of a neural network system processing simultaneously acquired electrocardiogram (ECG) and oximetry signals. The algorithm identifies epochs of normal breathing, central apnoea (CA), and obstructive apnoea (OA) by processing a pooled feature set containing information capturing the desaturations from the oximeter sensor as well as time and spectral features from the ECG. Training and testing of the system was facilitated with a dataset of 125 scored polysomnogram recordings with accompanying respiratory event annotations. When classifying the three epoch types, our system achieved a specificity of 91%, a sensitivity to CA of 28% and sensitivity to OA of 63%. A sensitivity of 81% was achieved when the CA and OA epochs were combined into one class.

Prediction of MAS Therapy Response in Obstructive Sleep Apnoea Patients using Clinical Data.

Mandibular Advancement Splint (MAS) is an oral appliance based treatment to Obstructive Sleep Apnoea (OSA) patients that is only effective for some patients. We present an investigation to predict MAS treatment response in OSA patients. A unique dataset in a large number (n=543 patients) consisting of convenient measurement such as demographic, anthropometric and Polysomnography (PSG) variables was utilised. Treatment Responders were defined as those with ≥50% reduction in Apnoea Hypopnoea Index (AHI) resulting in an AHI of less than 10 after the treatment process. Leaveone-out cross validation results using a Quadratic Neural Network showed an overall accuracy of 63%, with 63% sensitivity and 63% specificity for correctly predicting treatment response which is an improvement on previously published results.

A low-complexity algorithm for detection of atrial fibrillation using an ECG.

OBJECTIVES: We present a method for automatic processing of single-lead electrocardiogram (ECG) with duration of up to 60 s for the detection of atrial fibrillation (AF). The method categorises an ECG recording into one of four categories: normal, AF, other and noisy rhythm. For training the classification model, 8528 scored ECG signals were used; for independent performance assessment, 3658 scored ECG signals. APPROACH: Our method was based on features derived from RR interbeat intervals. The features included time domain, frequency domain and distribution features. We assessed the performance of three different classifiers (linear and quadratic discriminant analysis, and quadratic neural network (QNN)) on the training set using 100-fold cross-validation. The QNN was selected as the highest performing classifier, and a further performance assessment on the test data made. MAIN RESULTS: On the test set, our method achieved an F1 score for the normal, AF, other and noisy classes of 0.90, 0.75, 0.68 and 0.32, respectively. The overall F1 score was 0.78. SIGNIFICANCE: The computational cost of our algorithm is low as all features are derived from RR intervals and are processed by a single hidden layer neural network. This makes it potentially suitable for low-power devices.

Enhanced detection of sleep apnoea using heart-rate, respiration effort and oxygen saturation derived from a photoplethysmography sensor.

This paper presents a study on identifying sleep apnoea using the photoplethysmography (PPG) measurements, which is obtained from the SpO2 sensor. Using a database of polysomnogram (PSG) records of 52 patients, the heart rate and breathing effort information was derived from the PPG measurements and then features are extracted and processed by a classifier to detect one-minute epochs of sleep apnoea. The ground truth labels for the epochs were determined by trained technicians using the full PSG signal. Pulse oximetry (SpO2) measurements from the same sensor are also used in the classification process for comparison and in combination with the PPG results. The results show that both the heart rate and respiratory effort information derived from the PPG signal were able to detect apnoeic epochs with some success. The best classification performance of 87% for correctly labelling the epochs was obtained when the SpO2 features and the PPG features were combined.

Sleep apnoea diagnosis using respiratory effort-based signals - a comparative study.

A measure of the respiratory effort during a sleep study is an important contributor to the diagnosis of sleep apnoea. A common way of measuring respiratory effort is with bands with stretch sensors placed around the chest and/or abdomen. An alternative, and more convenient method from the patient's perspective, is via the ECG derived respiration (EDR) signal which provides an estimate of the respiratory effort at each heartbeat. In this study we performed a side-by-side comparison of the discrimination information for identifying epochs of sleep apnoea contained in the chest respiratory effort signal and three methods of calculating the EDR signal. Using simultaneously recorded chest band and ECG signals extracted from overnight polysomnogram (PSG) data from 8 subjects (4 controls, 4 apnoeas. MIT PhysioNet Apnea-ECG database), we extracted identical features from the two sensors and used the features to train a linear discriminant classifier to classify one-minute epochs as being apneic or normal. Ground truth labelling of each epoch was achieved with an expert using the full PSG as a reference. Our cross validation results revealed that the full respiratory effort signal resulted in an accuracy of 87% in correctly identifying the epoch label. When the respiratory signal was resampled at each heartbeat (as occurs with the EDR signal) the accuracy was 86%, suggesting that the sampling process inherent to the EDR signal does not materially affect its discrimination ability. The best EDR method was based on the calculating the QRS area for every heart and achieved an accuracy of 81%. Our results suggest that, while there is some information loss in the EDR estimation process, the EDR signal is a convenient and useful signal for sleep apnoea diagnosis.

An ECG oximetry system for identifying obstructive and central apnoea events.

An automatic algorithm for processing simultaneously acquired electrocardiogram (ECG) and oximetry signals that identifies epochs of pure central apnoea, epochs containing obstructive apnoea and epochs of normal breathing is presented. The algorithm uses time and spectral features from the ECG derived heart-rate and respiration information, as well as features capturing desaturations from the oximeter sensor. Evaluation of performance of the system was achieved by using leave-one-record-out cross validation on the St. Vincent's University Hospital / University College Dublin Sleep Apnea Database from the Physionet collections of recorded physiologic signals. When classifying the three epoch types, our system achieved a specificity of 80%, a sensitivity to central apnoea of 44% and sensitivity to obstructive apnoea of 35%. A sensitivity of 81% was achieved when the central and obstructive epochs were combined into one class.