Valdery Moura Junior

Valdery Moura Junior
Massachusetts General Hospital | MGH · Department of Neurology

MSc, MBA

About

23
Publications
2,367
Reads
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159
Citations
Introduction
McCance Center for Brain Health, Massachusetts General Hospital, Harvard Medical School | PhD Candidate, Bayes Business School, City, University of London
Additional affiliations
August 2013 - February 2022
Massachusetts General Hospital
Position
  • Director of Data Science Technology
Education
March 2016 - December 2022
City, University of London
Field of study
  • Management (Data Driven HealthCare Management)
September 2007 - April 2010
Universidade Católica de Brasília
Field of study
  • Computer Science / Knowledge Management
July 2005 - December 2006
Fundação Getulio Vargas
Field of study
  • Strategic Management

Publications

Publications (23)
Article
Background and Objectives Delayed cerebral ischemia (DCI) is the leading complication of subarachnoid hemorrhage (SAH). Because DCI was traditionally thought to be caused by large vessel vasospasm, transcranial Doppler ultrasounds (TCDs) have been the standard of care. Continuous EEG has emerged as a promising complementary monitoring modality and...
Article
Using observational data and variation in hospital admissions across days of the week, we examined the association between ED boarding time and development of delirium within 72 hours of admission among patients aged 65+ years admitted to an inpatient neurology ward. We exploited a natural experiment created by potentially exogenous variation in bo...
Article
Objective: To determine the dose-response relation between epileptiform activity burden and outcomes in acutely ill patients. Methods: Single center retrospective analysis of 1967 neurologic, medical and surgical patients who underwent > 16 hours of continuous EEG between 2011-2017. We developed an AI algorithm to annotate 11.02 terabytes of EEG...
Article
Introduction: Delayed cerebral ischemia (DCI) is the leading complication of subarachnoid hemorrhage (SAH). Because DCI was traditionally thought to be caused by large vessel vasospasm, transcranial Doppler ultrasounds (TCDs) have been the standard of care. Continuous EEG has emerged as a promising complementary monitoring modality and predicts inc...
Article
Objective To investigate whether epileptiform discharge burden can identify those at risk for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH). Methods Retrospective analysis of 113 moderate to severe grade SAH patients who had continuous EEG (cEEG) recordings during their hospitalization. We calculated the burden of epileptifor...
Article
Background/Objectives Clinical seizures following acute ischemic stroke (AIS) appear to contribute to worse neurologic outcomes. However, the effect of electrographic epileptiform abnormalities (EAs) more broadly is less clear. Here, we evaluate the impact of EAs, including electrographic seizures and periodic and rhythmic patterns, on outcomes in...
Article
Background Burst suppression in mechanically ventilated intensive care unit (ICU) patients is associated with increased mortality. However, the relative contributions of propofol use and critical illness itself to burst suppression; of burst suppression, propofol, and critical illness to mortality; and whether preventing burst suppression might red...
Article
Objectives: Electroencephalogram features predict neurologic recovery following cardiac arrest. Recent work has shown that prognostic implications of some key electroencephalogram features change over time. We explore whether time dependence exists for an expanded selection of quantitative electroencephalogram features and whether accounting for t...
Article
Full-text available
Objective To characterize the amount of EEG suppression achieved in refractory status epilepticus (RSE) patients treated with pharmacologically-induced coma (PIC). Methods We analyzed EEG recordings from 35 RSE patients between 21–84 years-old who received PIC that target burst suppression and quantified the amount of EEG suppression using the bur...
Poster
Introduction Intravenous third-line anesthetic agents (IV-TLA) are typically titrated in refractory status epilepticus (RSE) without evidence-based treatment guidelines. This study sought to evaluate quantitative EEG features and IV-TLA weaning during RSE management to characterize factors related to successful weaning. Methods From a single-center...
Article
OBJECTIVE To validate a system to detect ventilator associated events (VAEs) autonomously and in real time. DESIGN Retrospective review of ventilated patients using a secure informatics platform to identify VAEs (ie, automated surveillance) compared to surveillance by infection control (IC) staff (ie, manual surveillance), including development an...
Article
Full-text available
Background Criteria defining Ventilator Associated Events (VAEs) are objective and often available in the electronic health record (EHR) data. The use of ventilation data extracted directly from the patient’s bedside monitor to allow for real-time surveillance, however, has not been previously incorporated into electronic surveillance approaches. H...
Article
Full-text available
Background: Pressure ulcers resulting from continuous EEG (cEEG) monitoring in hospitalized patients have gained attention as a preventable medical complication. We measured their incidence and risk factors. Methods: We performed an observational investigation of cEEG-electrode-related pressure ulcers (EERPU) among acutely ill patients over a 22...
Article
Objective: To identify whether abnormal neural activity, in the form of epileptiform discharges and rhythmic or periodic activity, which we term here ictal-interictal continuum abnormalities (IICAs), are associated with delayed cerebral ischemia (DCI). Methods: Retrospective analysis of continuous electroencephalography (cEEG) reports and medica...
Data
Survey attrition. Note: It demonstrates the attrition from 6075 to 2716 patients.
Data
Demographic and clinical predictors of cost-related medication nonadherence. Notes: It graphically represents the logistic regression using demographic and clinical characteristics in the model to predict the odds of cost-related medication nonadherence. Red line represent 95% CIs. The patients whose preferred language was English (OR: 0.46 [0.25–0...
Article
Objective: To determine whether patients could self-report physical and mental health assessments in the waiting room and whether these assessments would be associated with modified Rankin Scale (mRS) and Quality of Life in Epilepsy (QOLIE-10) scores. Methods: We offered iPad-based surveys to consecutive adult neurology patients at check-in to c...
Article
Full-text available
Objective Many effective medical therapies are available for treating neurological diseases, but these therapies tend to be expensive and adherence is critical to their effectiveness. We used patient-reported data to examine the frequency and determinants of financial barriers to medication adherence among individuals treated for neurological disor...
Conference Paper
Aim: To develop an automated system to monitor sedation levels in intensive care unit patients using heart rate variability (HRV). Methods: We developed an automatic sedation level prediction system using HRV as input to a support vector machine learning algorithm. Our data consisted of electrocardiogram recordings from a heterogeneous group of 50...
Article
Full-text available
The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and under...
Conference Paper
Burst suppression is actively studied as a control signal to guide anesthetic dosing in patients undergoing medically induced coma. The ability to automatically identify periods of EEG suppression and compactly summarize the depth of coma using the burst suppression probability (BSP) is crucial to effective and safe monitoring and control of medica...
Conference Paper
In this study we have developed a supervised learning to automatically detect with high accuracy EEG reports that describe seizures and epileptiform discharges. We manually labeled 3,277 documents as describing one or more seizures vs no seizures, and as describing epileptiform discharges vs no epileptiform discharges. We then used Naïve Bayes to d...

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