Continuous noninvasive blood gas estimation in critically ill pediatric patients with respiratory failure.

Patients supported by mechanical ventilation require frequent invasive blood gas samples to monitor and adjust the level of support. We developed a transparent and novel blood gas estimation model to provide continuous monitoring of blood pH and arterial CO in between gaps of blood draws, using only readily available noninvasive data sources in ventilated patients. The model was trained on a derivation dataset (1,883 patients, 12,344 samples) from a tertiary pediatric intensive care center, and tested on a validation dataset (286 patients, 4030 samples) from the same center obtained at a later time.

Early prediction of hemodynamic interventions in the intensive care unit using machine learning.

Background: Timely recognition of hemodynamic instability in critically ill patients enables increased vigilance and early treatment opportunities. We develop the Hemodynamic Stability Index (HSI), which highlights situational awareness of possible hemodynamic instability occurring at the bedside and to prompt assessment for potential hemodynamic interventions.

Methods: We used an ensemble of decision trees to obtain a real-time risk score that predicts the initiation of hemodynamic interventions an hour into the future.

Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome.

Heterogeneous patient populations, complex pharmacology and low recruitment rates in the Intensive Care Unit (ICU) have led to the failure of many clinical trials. Recently, machine learning (ML) emerged as a new technology to process and identify big data relationships, enabling a new era in clinical trial design. In this study, we designed a ML model for predictively stratifying acute respiratory distress syndrome (ARDS) patients, ultimately reducing the required number of patients by increasing statistical power through cohort homogeneity.

Cardiac arrhythmia detection using deep learning: A review.

Due to its simplicity and low cost, analyzing an electrocardiogram (ECG) is the most common technique for detecting cardiac arrhythmia. The massive amount of ECG data collected every day, in home and hospital, may preclude data review by human operators/technicians. Therefore, several methods are proposed for either fully automatic arrhythmia detection or event selection for further verification by human experts.

Prevalence and Temporal Distribution of Extrasystoles in Septic ICU Patients: The Feasibility of Predicting Fluid Responsiveness Using Extrasystoles.

Background: Extrasystoles may be useful for predicting the response to fluid therapy in hemodynamically unstable patients but their prevalence is unknown. The aim of this study was to estimate the availability of extrasystoles in intensive care unit patients diagnosed with sepsis. The study aim was not to validate the fluid responsiveness prediction ability of extrasystoles.

An ensemble boosting model for predicting transfer to the pediatric intensive care unit.

Background: Early deterioration indicators have the potential to alert hospital care staff in advance of adverse events, such as patients requiring an increased level of care, or the need for rapid response teams to be called. Our work focuses on the problem of predicting the transfer of pediatric patients from the general ward of a hospital to the pediatric intensive care unit.

Objectives: The development of a data-driven pediatric early deterioration indicator for use by clinicians with the purpose of predicting encounters where transfer from the general ward to the PICU is likely.

A clinical prediction model to identify patients at high risk of hemodynamic instability in the pediatric intensive care unit.

Background: Early recognition and timely intervention are critical steps for the successful management of shock. The objective of this study was to develop a model to predict requirement for hemodynamic intervention in the pediatric intensive care unit (PICU); thus, clinicians can direct their care to patients likely to benefit from interventions to prevent further deterioration.

Methods: The model proposed in this study was trained on a retrospective cohort of all patients admitted to a tertiary PICU at a single center in the United States, and validated on another retrospective cohort of all patients admitted to the PICU at a single center in the United Kingdom.

TMS perturbs saccade trajectories and unmasks an internal feedback controller for saccades.

When we applied a single pulse of transcranial magnetic stimulation (TMS) to any part of the human head during a saccadic eye movement, the ongoing eye velocity was reduced as early as 45 ms after the TMS, and lasted ∼32 ms. The perturbation to the saccade trajectory was not due to a mechanical effect of the lid on the eye (e.g.

'Staircase' square-wave jerks in early Parkinson's disease.

Background/aims: Visually guided saccades and gaze-fixation ability were recorded in patients with early Parkinson's disease (PD).

Methods: Magnetic search coil system was used to measure horizontal and vertical eye positions.

Results: 'Staircase' visually guided saccades (multiple hypometric saccades separated by an intersaccadic interval) and 'staircase' square-wave jerks (SWJ) were present in all patients.

Temporal discounting of reward and the cost of time in motor control.

Why do movements take a characteristic amount of time, and why do diseases that affect the reward system alter control of movements? Suppose that the purpose of any movement is to position our body in a more rewarding state. People and other animals discount future reward as a hyperbolic function of time. Here, we show that across populations of people and monkeys there is a correlation between discounting of reward and control of movements.

Cerebellar contributions to adaptive control of saccades in humans.

The cerebellum may monitor motor commands and through internal feedback correct for anticipated errors. Saccades provide a test of this idea because these movements are completed too quickly for sensory feedback to be useful. Earlier, we reported that motor commands that accelerate the eyes toward a constant amplitude target showed variability.

The intrinsic value of visual information affects saccade velocities.

Let us assume that the purpose of any movement is to position our body in a more advantageous or rewarding state. For example, we might make a saccade to foveate an image because our brain assigns an intrinsic value to the information that it expects to acquire at the endpoint of that saccade. Different images might have different intrinsic values.