Age at First Extubation Attempt and Death or Respiratory Morbidities in Extremely Preterm Infants.

OBJECTIVE: To describe the timing of first extubation in extremely preterm infants and explore the relationship between age at first extubation, extubation outcome, and death or respiratory morbidities. STUDY DESIGN: In this subanalysis of a multicenter observational study, infants with birth weights of 1250 g or less and intubated within 24 hours of birth were included. After describing the timing of first extubation, age at extubation was divided into early (within 7 days from birth) vs late (days of life 8-35), and extubation outcome was divided into success vs failure (reintubation within 7 days after extubation), to create 4 extubation groups: early success, early failure, late success, and late failure. Logistic regression analyses were performed to evaluate associations between the 4 groups and death or bronchopulmonary dysplasia, bronchopulmonary dysplasia among survivors, and durations of respiratory support and oxygen therapy. RESULTS: Of the 250 infants included, 129 (52%) were extubated within 7 days, 93 (37%) between 8 and 35 days, and 28 (11%) beyond 35 days of life. There were 93, 36, 59, and 34 infants with early success, early failure, late success, and late failure, respectively. Although early success was associated with the lowest rates of respiratory morbidities, early failure was not associated with significantly different respiratory outcomes compared with late success or late failure in unadjusted and adjusted analyses. CONCLUSIONS: In a contemporary cohort of extremely preterm infants, early extubation occurred in 52% of infants, and only early and successful extubation was associated with decreased respiratory morbidities. Predictors capable of promptly identifying infants with a high likelihood of early extubation success or failure are needed.

Automated prediction of extubation success in extremely preterm infants: the APEX multicenter study.

BACKGROUND: Extremely preterm infants are frequently subjected to mechanical ventilation. Current prediction tools of extubation success lacks accuracy. METHODS: Multicenter study including infants with birth weight ≤1250 g undergoing their first extubation attempt. Clinical data and cardiorespiratory signals were acquired before extubation. Primary outcome was prediction of extubation success. Automated analysis of cardiorespiratory signals, development of clinical and cardiorespiratory features, and a 2-stage Clinical Decision-Balanced Random Forest classifier were used. A leave-one-out cross-validation was done. Performance was analyzed by ROC curves and determined by balanced accuracy. An exploratory analysis was performed for extubations before 7 days of age. RESULTS: A total of 241 infants were included and 44 failed (18%) extubation. The classifier had a balanced accuracy of 73% (sensitivity 70% [95% CI: 63%, 76%], specificity 75% [95% CI: 62%, 88%]). As an additional clinical-decision tool, the classifier would have led to an increase in extubation success from 82% to 93% but misclassified 60 infants who would have been successfully extubated. In infants extubated before 7 days of age, the classifier identified 16/18 failures (specificity 89%) and 73/105 infants with success (sensitivity 70%). CONCLUSIONS: Machine learning algorithms may improve a balanced prediction of extubation outcomes, but further refinement and validation is required. IMPACT: A machine learning-derived predictive model combining clinical data with automated analyses of individual cardiorespiratory signals may improve the prediction of successful extubation and identify infants at higher risk of failure with a good balanced accuracy. Such multidisciplinary approach including medicine, biomedical engineering and computer science is a step forward as current tools investigated to predict extubation outcomes lack sufficient balanced accuracy to justify their use in future trials or clinical practice. Thus, this individualized assessment can optimize patient selection for future trials of extubation readiness by decreasing exposure of low-risk infants to interventions and maximize the benefits of those at high risk.

Identification of human balance control responses to visual inputs using virtual reality.

Human upright balance is maintained through feedback mechanisms that use a variety of sensory modalities. Vision senses information about the position and velocity of the visual surround motion to improve balance by reducing the sway evoked by external disturbances. This study characterized the effects of visual information on human anterior-posterior body sway in upright stance by presenting perturbations through a virtual reality system. This made it possible to use a new visual perturbation signal, based on trapezoidal velocity pulses, whose amplitude and velocity could be controlled separately. To date, the influences of visual field position and velocity have only been studied independently due to the experimental limitations. The hip displacement, ankle torques, shank angles, and surface EMGs of four major ankle muscles were measured bilaterally as outputs. We found that the root mean square (RMS) hip displacement (body angle) increased systematically with visual input amplitude. However, for each amplitude, the RMS body angle increased when input velocity was changed from 2 to 5 degrees per second (dps) and then decreased from 5 to 10 dps. Spectral analysis was used to compute frequency response over a frequency range from 0.04 to 0.6 Hz. The gain of body sway relative to the perturbation increased with frequency, whereas the coherence declined. Moreover, as the stimulus amplitude increased, the gain generally decreased, whereas the mean coherence values always increased. The mean gains and mean coherence values were greatest for the velocity of 5 dps. This study presents a novel experimental approach to study human postural control and augments our knowledge of how visual information is processed in the central nervous system to maintain balance.NEW & NOTEWORTHY In this paper, we developed a new methodological approach to study the effects of visual information on dynamic body sway. We used VR to apply visual perturbations to induce AP body sway. We designed a new visual stimulus waveform based on trapezoidal velocity pulses whose peak-to-peak amplitude and velocity could be modulated independently. Subsequently, we investigated how the amplitude and velocity of visual field motion influence the postural responses evoked in healthy adults.

Patterns of muscle activation and modulation of ankle intrinsic stiffness in different postural operating conditions.

Intrinsic stiffness describes the dynamic relationship between imposed angular perturbations to a joint and the resulting torque response, due to intrinsic mechanical properties of muscles and joint, and inertia of the limbs. Recently, we showed that ankle intrinsic stiffness changes substantially with sway in normal standing. In the present study, we documented how ankle intrinsic stiffness changes with postural operating conditions. Subjects stood on an apparatus while subjected to ankle position perturbations in five conditions: normal standing, toe-up and toe-down standing, and backward and forward lean. In each condition, ankle intrinsic stiffness was estimated while its modulation with sway was accounted for. The results demonstrated that ankle intrinsic stiffness varies widely, from 0.08 to 0.75 of critical stiffness, across postural operating conditions; however, it is always smaller than the critical stiffness. Therefore, other contributions are necessary to ensure stable standing. The mean intrinsic stiffness was highest in forward lean and lowest in backward lean. Moreover, within each operating condition, the intrinsic stiffness changed with center-of-pressure position in one of three ways, each associated with a distinct muscle activation pattern; these include 1) monotonically increasing stiffness-center of pressure relation, associated with a progressive increase in triceps surae activation, 2) decreasing-increasing stiffness-center of pressure relation, associated with initial activation of tibialis anterior and later activation of triceps surae, and 3) monotonically decreasing stiffness-center of pressure relation, associated with decreasing activation of tibialis anterior. Thus intrinsic stiffness varies greatly within and across postural operating conditions, and a correct understanding of postural control requires accounting for such variations.NEW & NOTEWORTHY Ankle intrinsic stiffness changes with sway in normal standing. We quantified such changes in different postural operating conditions and demonstrated that the intrinsic stiffness changes in a manner associated with different activation patterns of ankle plantarflexors and dorsiflexors, emerging in different operating conditions. Large modulations of the intrinsic stiffness within and across postural operating conditions show that the stiffness importance and contribution change and must be accounted for in the study of postural control.

Cardiorespiratory behavior of preterm infants receiving continuous positive airway pressure and high flow nasal cannula post extubation: randomized crossover study.

BACKGROUND: Nasal continuous positive airway pressure (NCPAP) and high flow nasal cannula (HFNC) are modes of non-invasive respiratory support commonly used after extubation in extremely preterm infants. However, the cardiorespiratory physiology of these infants on each mode is unknown. METHODS: Prospective, randomized crossover study in infants with birth weight ≤1250 g undergoing their first extubation attempt. NCPAP and HFNC were applied randomly for 45 min each, while ribcage and abdominal movements, electrocardiogram, oxygen saturation, and fraction of inspired oxygen (FiO2) were recorded. Respiratory signals were analyzed using an automated method, and differences between NCPAP and HFNC features and changes in FiO2 were analyzed. RESULTS: A total of 30 infants with median [interquartile range] gestational age of 27 weeks [25.7, 27.9] and birth weight of 930 g [780, 1090] were studied. Infants were extubated at 5 days [2, 13] of life with 973 g [880, 1170] and three failed (10%). No differences in cardiorespiratory behavior were noted, except for longer respiratory pauses (9.2 s [5.0, 11.5] vs. 7.3 s [4.6, 9.3]; p = 0.04) and higher FiO2 levels (p = 0.02) during HFNC compared to NCPAP. CONCLUSIONS: In extremely preterm infants studied shortly after extubation, the use of HFNC was associated with longer respiratory pauses and higher FiO2 requirements.

A pilot non-inferiority randomized controlled trial to assess automatic adjustments of insulin doses in adolescents with type 1 diabetes on multiple daily injections therapy.

BACKGROUND: Multiple daily injections (MDI) therapy for type 1 diabetes involves basal and bolus insulin doses. Non-optimal insulin doses contribute to the lack of satisfactory glycemic control. We aimed to evaluate the feasibility of an algorithm that optimizes daily basal and bolus doses using glucose monitoring systems for MDI therapy users. METHODS: We performed a pilot, non-inferiority, randomized, parallel study at a diabetes camp comparing basal-bolus insulin dose adjustments made by camp physicians (PA) and a learning algorithm (LA), in children and adolescents on MDI therapy. Participants wore a glucose sensor and underwent 11 days of daily dose adjustments in either arm. Algorithm adjustments were reviewed and approved by a physician. The last 7 days were examined for outcomes. RESULTS: Twenty-one youths (age 13.3 [SD, 3.7] years; 13 females; HbA1c 8.6% [SD, 1.8]) were randomized to either group (LA [n = 10] or PA [n = 11]). The algorithm made 293 adjustments with a 92% acceptance rate from the camp physicians. In the last 7 days, the time in target glucose (3.9-10 mmol/L) in LA (39.5%, SD, 20.7) was similar to PA (38.4%, SD, 15.6) (P = .89). The number of hypoglycemic events per day in LA (0.3, IQR, [0.1-0.6]) was similar to PA (0.2, IQR, [0.0-0.4]) (P = .42). There was no incidence of severe hypoglycemia nor ketoacidosis. CONCLUSIONS: In this pilot study, glycemic outcomes in the LA group were similar to the PA group. This algorithm has the potential to facilitate MDI therapy, and longer and larger studies are warranted.

The Impact of Time Interval between Extubation and Reintubation on Death or Bronchopulmonary Dysplasia in Extremely Preterm Infants.

OBJECTIVE: To explore the relation between time to reintubation and death or bronchopulmonary dysplasia (BPD) in extremely preterm infants. STUDY DESIGN: This was a subanalysis from an ongoing multicenter observational study. Infants with birth weight ≤1250 g, requiring mechanical ventilation, and undergoing their first elective extubation were prospectively followed throughout hospitalization. Time to reintubation was defined as the time interval between first elective extubation and reintubation. Univariate and multivariate logistic regression analyses were performed to evaluate associations between time to reintubation, using different observation windows after extubation (24-hour intervals), and death/BPD (primary outcome) or BPD among survivors (secondary outcome). aORs were computed with and without the confounding effects of cumulative mechanical ventilation duration. RESULTS: Of 216 infants included for analysis, 103 (48%) were reintubated at least once after their first elective extubation. Reintubation was associated with lower gestational age/weight and greater morbidities compared with infants never reintubated. After adjusting for confounders, reintubation within observation windows ranging between 24 hours and 3 weeks postextubation was associated with increased odds of death/BPD (but not BPD among survivors), independent of the cumulative mechanical ventilation duration. Reintubation within 48 hours from extubation conferred higher risk-adjusted odds of death/BPD vs other observation windows. CONCLUSIONS: Although reintubation after elective extubation was independently associated with increased likelihood of death/BPD in extremely preterm infants, the greatest risk was attributable to reintubation within the first 48 hours postextubation. Prediction models capable of identifying the highest-risk infants may further improve outcomes.

Patterns of reintubation in extremely preterm infants: a longitudinal cohort study.

BackgroundThe optimal approach for reporting reintubation rates in extremely preterm infants is unknown. This study aims to longitudinally describe patterns of reintubation in this population over a broad range of observation windows following extubation.MethodsTiming and reasons for reintubation following a first planned extubation were collected from infants with birth weight ≤1,250 g. An algorithm was generated to discriminate between reintubations attributable to respiratory and non-respiratory causes. Frequency and cumulative distribution curves were constructed for each category using 24 h intervals. The ability of observation windows to capture respiratory-related reintubations while limiting non-respiratory reasons was assessed using a receiver operating characteristic curve.ResultsOut of 194 infants, 91 (47%) were reintubated during hospitalization; 68% for respiratory and 32% for non-respiratory reasons. Respiratory-related reintubation rates steadily increased from 0 to 14 days post-extubation before reaching a plateau. In contrast, non-respiratory reintubations were negligible in the first post-extubation week, but became predominant after 14 days. An observation window of 7 days captured 77% of respiratory-related reintubations while only including 14% of non-respiratory cases.ConclusionReintubation patterns are highly variable and affected by the reasons for reintubation and observation window used. Ideally, reintubation rates should be reported using a cumulative distribution curve over time.

Physiological tremor increases when skeletal muscle is shortened: implications for fusimotor control.

KEY POINTS: In tonic, isometric, plantarflexion contractions, physiological tremor increases as the ankle joint becomes plantarflexed. Modulation of physiological tremor as a function of muscle stretch differs from that of the stretch reflex amplitude. Amplitude of physiological tremor may be altered as a function of reflex pathway gains. Healthy humans likely increase their γ-static fusimotor drive when muscles shorten. Quantification of physiological tremor by manipulation of joint angle may be a useful experimental probe of afferent gains and/or the integrity of automatic fusimotor control. ABSTRACT: The involuntary force fluctuations associated with physiological (as distinct from pathological) tremor are an unavoidable component of human motor control. While the origins of physiological tremor are known to depend on muscle afferentation, it is possible that the mechanical properties of muscle-tendon systems also affect its generation, amplification and maintenance. In this paper, we investigated the dependence of physiological tremor on muscle length in healthy individuals. We measured physiological tremor during tonic, isometric plantarflexion torque at 30% of maximum at three ankle angles. The amplitude of physiological tremor increased as calf muscles shortened in contrast to the stretch reflex whose amplitude decreases as muscle shortens. We used a published closed-loop simulation model of afferented muscle to explore the mechanisms responsible for this behaviour. We demonstrate that changing muscle lengths does not suffice to explain our experimental findings. Rather, the model consistently required the modulation of  Î³-static fusimotor drive to produce increases in physiological tremor with muscle shortening - while successfully replicating the concomitant reduction in stretch reflex amplitude. This need to control γ-static fusimotor drive explicitly as a function of muscle length has important implications. First, it permits the amplitudes of physiological tremor and stretch reflex to be decoupled. Second, it postulates neuromechanical interactions that require length-dependent γ drive modulation to be independent from α drive to the parent muscle. Lastly, it suggests that physiological tremor can be used as a simple, non-invasive measure of the afferent mechanisms underlying healthy motor function, and their disruption in neurological conditions.

Prediction of Extubation readiness in extremely preterm infants by the automated analysis of cardiorespiratory behavior: study protocol.

BACKGROUND: Extremely preterm infants (≤ 28 weeks gestation) commonly require endotracheal intubation and mechanical ventilation (MV) to maintain adequate oxygenation and gas exchange. Given that MV is independently associated with important adverse outcomes, efforts should be made to limit its duration. However, current methods for determining extubation readiness are inaccurate and a significant number of infants fail extubation and require reintubation, an intervention that may be associated with increased morbidities. A variety of objective measures have been proposed to better define the optimal time for extubation, but none have proven clinically useful. In a pilot study, investigators from this group have shown promising results from sophisticated, automated analyses of cardiorespiratory signals as a predictor of extubation readiness. The aim of this study is to develop an automated predictor of extubation readiness using a combination of clinical tools along with novel and automated measures of cardiorespiratory behavior, to assist clinicians in determining when extremely preterm infants are ready for extubation. METHODS: In this prospective, multicenter observational study, cardiorespiratory signals will be recorded from 250 eligible extremely preterm infants with birth weights ≤1250 g immediately prior to their first planned extubation. Automated signal analysis algorithms will compute a variety of metrics for each infant, and machine learning methods will then be used to find the optimal combination of these metrics together with clinical variables that provide the best overall prediction of extubation readiness. Using these results, investigators will develop an Automated system for Prediction of EXtubation (APEX) readiness that will integrate the software for data acquisition, signal analysis, and outcome prediction into a single application suitable for use by medical personnel in the neonatal intensive care unit. The performance of APEX will later be prospectively validated in 50 additional infants. DISCUSSION: The results of this research will provide the quantitative evidence needed to assist clinicians in determining when to extubate a preterm infant with the highest probability of success, and could produce significant improvements in extubation outcomes in this population. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT01909947 . Registered on July 17 2013. Trial sponsor: Canadian Institutes of Health Research (CIHR).

Construction of a comprehensive fetal monitoring database for the study of perinatal hypoxic ischemic encephalopathy.

This article describes the methods used to build a large-scale database of more than 250,000 electronic fetal monitoring (EFM) records linked to a comprehensive set of clinical information about the infant, the mother, the pregnancy, labor, and outcome. The database can be used to investigate how birth outcome is related to clinical and EFM features. The main steps involved in building the database were: (1) Acquiring the raw EFM recording and clinical records for each birth. (2) Assigning each birth to an objectively defined outcome class that included normal, acidosis, and hypoxic-ischemic encephalopathy. (3) Removing all personal health information from the EFM recordings and clinical records. (4) Preprocessing the deidentified EFM records to eliminate duplicates, reformat the signals, combine signals from different sensors, and bridge gaps to generate signals in a format that can be readily analyzed. (5) Post-processing the repaired EFM recordings to extract key features of the fetal heart rate, uterine activity, and their relations. (6) Populating a database that links the clinical information, EFM records, and EFM features to support easy querying and retrieval. •A multi-step process is required to build a comprehensive database linking electronic temporal fetal monitoring signals to a comprehensive set of clinical information about the infant, the mother, the pregnancy, labor, and outcome.•The current database documents more than 250,000 births including almost 4,000 acidosis and 400 HIE cases. This represents more than 80% of the births that occurred in 15 Northern California Kaiser Permanente Hospitals between 2011-2019. This is a valuable resource for studying the factors predictive of outcome.•The signal processing code and schemas for the database are freely available. The database will not be permitted to leave Kaiser firewalls, but a process is in place to allow interested investigators to access it.

Non-Parametric Nonlinear Parameter-Varying Parallel-Cascade Identification of Dynamic Joint Stiffness.

OBJECTIVE: The paper presents a method to identify ankle joint dynamic stiffness during functional tasks where intrinsic and reflex stiffness change with a time-varying scheduling variable (SV), such as joint position or torque. METHODS: The method models joint stiffness with two pathways: (1) A parameter-varying (PV) impulse response function (IRF) describing intrinsic stiffness; and (2) a reflex stiffness model comprising a PV static nonlinearity followed by a PV linear element. RESULTS: Monte-Carlo simulations demonstrated that the method accurately estimated all elements of the intrinsic and reflex pathways as they changed with a SV. Experimental results with a healthy individual subjected to large, imposed ankle movements demonstrated that: (a) Intrinsic stiffness changed substantially as a function of ankle position; elasticity was lowest near the mid-position and increased with either dorsiflexion or plantarflexion. (b) Reflex gain increased and the velocity threshold for reflex excitation decreased monotonically with ankle dorsiflexion. (c) Reflex dynamics resembled a second-order, low-pass system that was invariant with ankle position. (d) The identified PV Parallel-Cascade (PC) model accurately predicted the torque response to novel trajectories of ankle movement. CONCLUSION: The PV-PC method can accurately and reliably estimate how intrinsic and reflex stiffness change with a time-varying SV. SIGNIFICANCE: The method is novel with multiple advantages: (a) It provides a unified algorithm that characterizes the changes in the parameters of all joint stiffness elements needed to understand their role in postural/movement control; (b) It is efficient requiring only two trials; (c) The models identified can predict the joint stiffness response to novel movements informing orthoses and prostheses design.

Clinical usefulness of reintubation criteria in extremely preterm infants: a cohort study.

OBJECTIVE: To describe the thresholds of instability used by clinicians at reintubation and evaluate the accuracy of different combinations of criteria in predicting reintubation decisions. DESIGN: Secondary analysis using data obtained from the prospective observational Automated Prediction of Extubation Readiness study (NCT01909947) between 2013 and 2018. SETTING: Multicentre (three neonatal intensive care units). PATIENTS: Infants with birth weight ≤1250 g, mechanically ventilated and undergoing their first planned extubation were included. INTERVENTIONS: After extubation, hourly O2 requirements, blood gas values and occurrence of cardiorespiratory events requiring intervention were recorded for 14 days or until reintubation, whichever came first. MAIN OUTCOME MEASURES: Thresholds at reintubation were described and grouped into four categories: increased O2, respiratory acidosis, frequent cardiorespiratory events and severe cardiorespiratory events (requiring positive pressure ventilation). An automated algorithm was used to generate multiple combinations of criteria from the four categories and compute their accuracies in capturing reintubated infants (sensitivity) without including non-reintubated infants (specificity). RESULTS: 55 infants were reintubated (median gestational age 25.2 weeks (IQR 24.5-26.1 weeks), birth weight 750 g (IQR 640-880 g)), with highly variable thresholds at reintubation. After extubation, reintubated infants had significantly greater O2 needs, lower pH, higher pCO2 and more frequent and severe cardiorespiratory events compared with non-reintubated infants. After evaluating 123 374 combinations of reintubation criteria, Youden indices ranged from 0 to 0.46, suggesting low accuracy. This was primarily attributable to the poor agreement between clinicians on the number of cardiorespiratory events at which to reintubate. CONCLUSIONS: Criteria used for reintubation in clinical practice are highly variable, with no combination accurately predicting the decision to reintubate.

Comparison of Wired and Wireless Heart Rate Monitoring in the Neonatal Intensive Care Unit.

In the Neonatal Intensive Care Unit (NICU), infants' vital signs are monitored on a continuous basis via wired devices. These often interfere with patient care and pose increased risks of skin damage, infection, and tangling around the body. Recently, a wireless system for neonatal monitoring called ANNEⓇ One (Sibel Health, Chicago, USA) was developed. We designed an ongoing study to evaluate the feasibility, reliability and accuracy, of using this system in the NICU. Vital signals were simultaneously acquired by using the standard, wired clinical monitor and the ANNEⓇ device. Data from 10 NICU infants were recorded for 8 hours per day during 4 consecutive days. Initial analysis of the heart rate (HR) data revealed four problems in comparing the signals: 1) gaps in the signals - periods of time for which data were unavailable, 2) wired and wireless signals were sampled at different rates, 3) a delay between the sampled values of wired and wireless signals, and 4) this delay increased with time. To address these problems, we developed a pre-processing algorithm that interpolated samples in short gaps, resampled the signals to an equal rate, estimated the delay and drift rate between corresponding signals, and aligned the signals. Applications of the pre-processing algorithm to 40 recordings demonstrated that it was very effective. A strong agreement between wireless and wired HR signals was seen, with an average correlation of 0.95±0.04, a slope of 1.00, and a variance accounted for 89.56±7.62%. Bland-Altman analysis showed a low bias across the ensemble, with an average difference of 0.11 (95% confidence interval of -0.02 to 0.24) bpm.Clinical relevance- This algorithm provides the means for a detailed comparison of wired and wireless monitors in the NICU.

Timely Detection of Infants at Risk of Intrapartum Acidosis and Hypoxic-Ischemic Encephalopathy Using Cardiotocography.

This work aims to improve the intrapartum detection of fetuses with an increased risk of developing fetal acidosis or hypoxic-ischemic encephalopathy (HIE) using fetal heart rate (FHR) and uterine pressure (UP) signals. Our study population comprised 40,831 term births divided into 3 classes based on umbilical cord or early neonatal blood gas assessments: 374 with verified HIE, 3,047 with acidosis but no encephalopathy and 37,410 healthy babies with normal gases. We developed an intervention recommendation system based on a random forest classifier. The classifier was trained using classical and novel features extracted electronically from 20-minute epochs of FHR and UP. Then, using the predictions of the classifier on each epoch, we designed a decision rule to determine when to recommended intervention. Compared to the Caesarean rates in each study group, our system identified an additional 5.68% of babies who developed HIE (54.55% vs 60.23%, p < 0.01) with a specific alert threshold. Importantly, about 75% of these recommendations were made more than 200 minutes before birth. In the acidosis group, the system identified an additional 17.44% (37.15% vs 54.59%, p < 0.01) and about 2/3 of these recommendations were made more than 200 minutes before birth. Compared to the Caesarean rate in the healthy group, the associated false positive rate was increased by 1.07% (38.80% vs 39.87%, p<0.01).Clinical Relevance- This method recommended intervention in more babies affected by acidosis or HIE, than the intervention rate observed in practice and most often did so 200 minutes before delivery. This was early enough to expect that interventions would have clinical benefit and reduce the rate of HIE. Given the high burden associated with HIE, this would justify the marginal increase in the normal Cesarean rate.

Accounting for Nulliparity in the Prediction of Hypoxic-Ischemic Encephalopathy Using Cardiotocography.

Nulliparous pregnancies, those where the mother has not previously given birth, are associated with longer labors and hence expose the fetus to more contractions and other adverse intrapartum conditions such as chorioamnionitis. The objective of the present study was to test if accounting for nulliparity could improve the detection of fetuses at increased risk of developing hypoxic-ischemic encephalopathy (HIE). During labor, clinicians assess the fetal heart rate and uterine pressure signals to identify fetuses at risk of developing HIE. In this study, we performed random forest classification using fetal heart rate and uterine pressure features from 40,831 births, including 374 that developed HIE. We analyzed a two-path classification approach that analyzed separately the fetuses from nulliparous and multiparous mothers, and a one-path classification approach that included the clinical variable for nulliparity as a classification feature. We compared these two approaches to a one-path classifier that had no information about the parity of the mothers. We also compared our results to the rate of Caesarean deliveries in each group, which is used clinically to interrupt the progression towards HIE. All the classifiers detected more fetuses that developed HIE than the observed Caesarean rate, but accounting for nulliparity did not improve performance.

A HUPO test sample study reveals common problems in mass spectrometry-based proteomics.

We performed a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in liquid chromatography-mass spectrometry-based proteomics. We distributed an equimolar test sample, comprising 20 highly purified recombinant human proteins, to 27 laboratories. Each protein contained one or more unique tryptic peptides of 1,250 Da to test for ion selection and sampling in the mass spectrometer. Of the 27 labs, members of only 7 labs initially reported all 20 proteins correctly, and members of only 1 lab reported all tryptic peptides of 1,250 Da. Centralized analysis of the raw data, however, revealed that all 20 proteins and most of the 1,250 Da peptides had been detected in all 27 labs. Our centralized analysis determined missed identifications (false negatives), environmental contamination, database matching and curation of protein identifications as sources of problems. Improved search engines and databases are needed for mass spectrometry-based proteomics.

Multi-Chain Semi-Markov Analysis of Intrapartum Cardiotocography.

Visual assessment of the evolution of fetal heart rate (FHR) and uterine pressure (UP) patterns is the standard of care in the intrapartum period. Unfortunately, this assessment has high levels of intra- and inter-observer variability. This study processed and analyzed FHR and UP patterns using computerized pattern recognition tools. The goal was to evaluate differences in FHR and UP patterns between fetuses with normal outcomes and those who developed hypoxic-ischemic encephalopathy (HIE). For this purpose, we modeled the sequence of FHR patterns and uterine contractions using Multi-Chain Semi-Markov models (MCSMMs). These models estimate the probability of transitioning between FHR or UP patterns and the dwell time of each pattern. Our results showed that in comparison to the control group, the HIE group had: (1) more frequent uterine contractions during the last 12 hours before birth; (2) more frequent FHR decelerations during the last 12 hours before birth; (3) longer decelerations during the last eight hours before birth; and (4) shorter baseline durations during the last five hours before birth. These results demonstrate that the fetuses in the HIE group were subject to a more stressful environment than those in the normal group. Clinical Relevance- Our results revealed statistically significant differences in FHR/UP patterns between the normal and HIE groups in the hours before birth. This indicates that features derived using MCSMMs may be useful in a machine learning framework to detect infants at increased risk of developing HIE allowing preventive interventions.

Proteomic analysis of the transitional endoplasmic reticulum in hepatocellular carcinoma: an organelle perspective on cancer.

The transitional endoplasmic reticulum (tER) is composed of both rough and smooth ER membranes and thus participates in functions attributed to both these two subcellular compartments. In this paper we have compared the protein composition of tER isolated from dissected liver tumor nodules of aflatoxin B1-treated rats with that of tER from control liver. Tandem mass spectrometry (MS), peptide counts and immunoblot validation were used to identify and determine the relative expression level of proteins. Inhibitors of apoptosis (i.e. PGRMC1, tripeptidyl peptidase II), proteins involved in ribosome biogenesis (i.e. nucleophosmin, nucleolin), proteins involved in translation (i.e. eEF-2, and subunits of eIF-3), proteins involved in ubiquitin metabolism (i.e. proteasome subunits, USP10) and proteins involved in membrane traffic (i.e. SEC13-like 1, SEC23B, dynactin 1) were found overexpressed in tumor tER. Transcription factors (i.e. Pur-beta, BTF3) and molecular targets for C-Myc and NF-kappa B were observed overexpressed in tER from tumor nodules. Down-regulated proteins included cytochrome P450 proteins and enzymes involved in fatty acid metabolism and in steroid metabolism. Unexpectedly expression of the protein folding machinery (i.e. calreticulin) and proteins of the MHC class I peptide-loading complex did not change. Proteins of unknown function were detected in association with the tER and the novel proteins showing differential expression are potential new tumor markers. In many cases differential expression of proteins in tumor tER was comparable to that of corresponding genes reported in the Oncomine human database. Thus the molecular profile of tumor tER is different and this may confer survival advantage to tumor cells in cancer.

Methods for combining peptide intensities to estimate relative protein abundance.

MOTIVATION: Labeling techniques are being used increasingly to estimate relative protein abundances in quantitative proteomic studies. These techniques require the accurate measurement of correspondingly labeled peptide peak intensities to produce high-quality estimates of differential expression ratios. In mass spectrometers with counting detectors, the measurement noise varies with intensity and consequently accuracy increases with the number of ions detected. Consequently, the relative variability of peptide intensity measurements varies with intensity. This effect must be accounted for when combining information from multiple peptides to estimate relative protein abundance. RESULTS: We examined a variety of algorithms that estimate protein differential expression ratios from multiple peptide intensity measurements. Algorithms that account for the variation of measurement error with intensity were found to provide the most accurate estimates of differential abundance. A simple Sum-of-Intensities algorithm provided the best estimates of true protein ratios of all algorithms tested.