Massachusetts Institute of Technology

Children's Medical Center Corporation

The General Hospital Corporation

Other

Thomas Heldt

George Cheeran Verghese

Tushar Anil Parlikar

Faisal Mahmood Kashif

Baruch Shlomo Krauss

Andrew Tomas Reisner

Gireeja V Ranade

Roger Greenwood Mark

Margaret Gan Guo

Rebecca Mieloszyk

Michael Filbin

Ramakrisna Mukkamala

Syed Muhammad Imaduddin

Kerri Larovere

Max H Dunitz

Barry Kussman

Techniques for detecting embolic information for a patient. The techniques may include obtaining data identifying an ultrasound signal associated with the patient, identifying a set of candidate embolic regions in the data, identifying a set of embolic regions from among the set of candidate embolic regions, and outputting embolic information corresponding to the set of embolic regions.

Emboli detection methods to identify mechanisms of brain injury in susceptible adults and children

Systems and methods are disclosed herein for quantitatively identifying a patient's sedation level and predicting adverse events, based on one or more capnograms or outputs from a pharmacokinetic, pharmacodynamic, or ventilatory model. A sensor measures a carbon dioxide concentration of air exhaled by a patient into a breath receiver. A processor processes the sensor data to generate a capnogram including one or more respiratory cycles, computes the outputs of pharmacokinetic, pharmacodynamic, or ventilatory models, and extracts one or more of the resulting features from the capnogram and pharmacokinetic, pharmacodynamic, or ventilatory model outputs. A multi-parameter metric is computed based on the one or more extracted features and estimates the current or predicted sedation level of the patient.

Systems and methods for predicting adverse events and assessing level of sedation during medical procedures

Systems and methods are disclosed for sepsis care management. First data regarding a patient and second data regarding a clinician's treatment of a patient are received by at least one processor. The first data regarding the patient is processed to assess a likelihood that the patient would benefit from administration of each of one or more critical actions for treatment of sepsis, wherein at least one of the one or more critical actions relates to a request for at least one additional diagnostic action. A target treatment protocol, comprising a decision for each of the one or more critical actions, is determined based on the assessed likelihoods. The second data regarding a clinician's treatment of the patient is compared to the target treatment protocol and a notification is provided to the clinician if the second data is incompatible with the target treatment protocol.

System and method for sepsis care task management

A method to quantitatively predict a patient's serum lactate level, comprising measuring arterial blood pressure and heart rate from the patient, computing estimates of one or more cardiovascular parameters from the measured arterial blood pressure and heart rate, providing one or more classifiers that have been trained on a training data set including a reference set of arterial blood pressure, heart rate, and serum lactate levels and using the one or more classifiers to estimate the serum lactate level of the patient.

System and methods to predict serum lactate level

The methods and systems for estimating cardiac output and total peripheral resistance include observing arterial blood pressure waveforms to determine intra-beat and inter-beat variability in arterial blood pressure and estimating from the variability a time constant for a lumped parameter beat-to-beat averaged Windkessel model of the arterial tree. Uncalibrated cardiac output and uncalibrated total peripheral resistance may then be calculated from the time constant. Calibrated cardiac output and calibrated total peripheral resistance may be computed using calibration data, assuming an arterial compliance that is either constant or dependent on mean arterial blood pressure. The parameters of the arterial compliance may be estimated in a least-squares manner.

Systems and methods for model-based estimation of cardiac output and total peripheral resistance

Systems and methods for prediction and detection of circulatory shock using estimates or measurements of arterial blood pressure, heart rate, stroke volume, cardiac output, total peripheral resistance, cardiac ejection fraction, cardiac contractility and ventricular end-diastolic volume are provided. These estimates and measurements are used to determine a type of circulatory shock. In some embodiments, the type of circulatory shock is determined to be one of septic shock, hypovolemic shock, anaphylactic shock, hemorrhagic shock, and cardiogenic shock.

System and method for prediction and detection of circulatory shock

The systems, devices, and methods described herein provide for the estimation and monitoring of cerebrovascular system properties and intracranial pressure (ICP) from one or more measurements or measured signals. These measured signals may include central or peripheral arterial blood pressure (ABP), and cerebral blood flow (CBF) or cerebral blood flow velocity (CBFV). The measured signals may be acquired noninvasively or minimally-invasively. The measured signals may be used to estimate parameters and variables of a computational model that is representative of the physiological relationships among the cerebral flows and pressures. The computational model may include at least one resistive element, at least one compliance element, and a representation of ICP.

Systems, devices and methods for noninvasive or minimally-invasive estimation of intracranial pressure and cerebrovascular autoregulation

The methods and systems for estimating cardiac ejection fraction, cardiac contractility, and ventricular end-diastolic volume on a beat-by-beat basis include observing arterial blood pressure waveforms to determine ventricular compliances for a pressure-volume loop in the ventricle. Uncalibrated or calibrated cardiac ejection fraction may be calculated from estimates of stroke volume and the ventricular compliances. Cardiac contractility may be calculated from estimates of a ventricular compliance. Uncalibrated or calibrated ventricular end-diastolic volume may also be calculated from estimates of stroke volume and the ventricular compliances. A set of calibration parameters for calibrating cardiac ejection fraction or ventricular end-diastolic volume may be estimated in a least-squares manner.

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Cambridge, MA, United States of America

Thomas Heldt