We study the resuscitation and management of patients who require cardiopulmonary resuscitation (CPR). The primary factors contributing to mortality often stem from brain injury or the onset of multiple organ failure. Our research projects explore innovative strategies aimed at enhancing CPR outcomes.
The University of Pittsburgh is one of 11 hub sites for the SIREN Emergency Care Clinical Trials Network, which seeks to improve the outcomes of patients with neurologic, cardiac, respiratory, hematologic and trauma emergencies by identifying effective treatments administered in the earliest stages of critical care.
Ongoing Studies
- Influence of Cooling duration on Efficacy in Cardiac Arrest Patients Trial (ICECAP)
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A multicenter, randomized, adaptive allocation clinical trial to determine if increasing durations of induced hypothermia are associated with an increasing rate of good neurological outcomes and to identify the optimal duration of induced hypothermia for neuroprotection in comatose survivors of cardiac arrest.
Site Principal Investigator: Clifton Callaway, MD, PhD
- PREcision Care in Cardiac ArrEst Trial (PRECICECAP)
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A multicenter, observational substudy to the ICECAP trial to define patterns of post-arrest injury (phenotypes) that predict optimal duration of induced hypothermia after cardiac arrest.
Principal Investigator: Jonathan Elmer, MD, MS
- Patterns of Survivors' Recovery Trajectories in the ICECAP Trial (POST-ICECAP)
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Many patients now survive out-of-hospital cardiac arrest (OHCA), however gaps in knowledge about long-term outcomes result in a fragmented and underdeveloped continuum of care to achieve recovery. Recovery is defined as significant improvement in functional and cognitive outcomes, and health- related quality of life (HRQoL). OHCA Survivors with favorable recovery patterns may potentially go back to work and/or social roles. Prior studies assessing recovery domains after OHCA are small, limited to single centers, and short-term outcomes i.e., 1-3 months. Identifying individual patient patterns of recovery over longer-term, and the ability to predict who will be likely to need more intensive support after discharge would allow interventions to be targeted more efficiently. It is also crucial that we offer patients and their families the best information available about a patient's prospects for continued recovery even in the absence of modifiable intervention targets.
This study will be among the first to focus on a new equitable science of OHCA survivorship itself, seeking empirically derived targets for preserving or restoring recovery. Our single-center pilot study has found that nearly one-third of the OHCA survivors had clinically important differences between long-term (12 months) and short-term (3 months) functional outcomes with large between-individual variability in recovery (i.e., improvement or worsening). We found that inpatient acute rehabilitation was associated with better functional recovery patterns at 12 months compared to other dispositions, but Black race and Hispanic/Latinx had worse recovery patterns than non-Hispanic Whites. To fill this gap, we propose an ancillary study to the NINDS/NHLBI-funded ICECAP trial, conducted within the 60 sites of the NIH emergency care trials network, to describe recovery (functional outcome [primary], Cognition, and HRQoL outcomes [secondary]) in a large, well-characterized, racially/ethnically diverse, representative cohort of US OHCA patients.
We will enroll 1,000 who were screened for ICECAP and survive to hospital discharge. The parent ICECAP trial includes a telephone follow-up visit at 1 month and an in-person visit at 3 months. The ancillary study will add two telephone/videoconferencing visits at 6 and 9 months and an in-person visit at 12 months after OHCA. For Aim 1, we will describe between-patient variability in recovery (i.e., improvement in functional, cognitive, and HRQoL outcomes) from 3 to 12 months after OHCA, and test whether changes are associated with illness severity scores, and critical care interventions performed during the acute care stay. Aim 2 will test whether receipt of acute inpatient rehabilitation (vs outpatient therapy/no therapy/skilled nursing facility) within 1 month of hospital discharge is associated with greater improvement in recovery outcomes from 3 to 12 months. Finally, in Aim 3, we will test whether non-Hispanic Black and Hispanic/Latinx patients have less favorable changes in recovery outcomes between 3 and 12 months and explore mechanisms for such disparities.
Principal Investigator: Clifton Callaway, MD, PhD
Site Principal Investigator: Kelly Sawyer, MD, MS
- Optimizing Recovery prediction after Cardiac Arrest (ORCA)
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This project will leverage expertise in post-arrest critical care, information science, statistical modeling and machine learning to make a system that rapidly delivers actionable prognostic knowledge. We have cleaned, organized and aggregated a large, highly multivariate time series database with physiological and clinical information with over 170,000 hours of quantitative electroencephalographic (EEG) features for >1,850 post- arrest patients. We will refine and optimize analytical tools that predict recovery in this patient population more rapidly and accurately than clinical experts. We will use innovative approaches to minimize risk of bias during training of models introduced by outcome labels created by fallible human providers.
In Aim 1 of this proposal, we will use novel approaches to create informative and interpretable features from heterogeneous clinical data including EEG waveforms, vital signs, medications and laboratory test results. We will use deep learning to identify interpretable and parsimonious sets of these features that predict outcome. We will train, test and compare the performance of multiple analytical tools.
In Aim 2, we will prospectively compare the best performing model(s) against a panel of expert clinicians. Models that confidently identify patients with near-zero prospect of recovery with greater sensitivity or faster than expert clinicians can serve as decision support systems. Improving the speed and accuracy of post-arrest prognostication will save lives, allow appropriate resources to be directed to patients who are likely to benefit, avoid long and difficult care for patients who cannot recover, and spare families the agony of uncertainty.
Principal Investigator: Jonathan Elmer, MD, MS