Association of time-temperature curves with outcomes in temperature management for cardiac arrest.

Abstract

Background/purpose

Cardiac arrest is a common cause of death and neurological injury; therapeutic cooling for neuroprotection is standard of care. Despite numerous and ongoing trials targeting a specified cooling temperature for a target duration, the concept of temperature dose-the duration spent at a given depth of hypothermia-is not as well explored.

Methods

In this retrospective study, we examined 66 patients 18 years of age or older undergoing therapeutic hypothermia for cardiac arrest between 2007 and 2010 to assess the relationship of temperature dose with outcomes. Demographic, clinical, outcome and temperature data were collected. Demographic and clinical data underwent bivariate regression analysis for association with outcome. Time-temperature curves were divided into pre-determined temperature thresholds and assessed by logistic regression analysis for association with outcome. A second, multivariate regression analysis was performed controlling for factors associated with poor outcomes.

Results

Old age was significantly associated with poor outcome and a shockable arrest rhythm was significantly associated with positive outcome. Subjects spent an average of 2.82 hours below 35°C, 7.31 hours ≥35°C to ≤36.5°C, 24.75 hours >36.5 to <38.0°C and 7.06 hours ≥38°C. Logistic regression analysis revealed borderline significant positive association between good outcome and time at a cooling depth (35°C-36.5°C, p=0.05); adjusted for old age, the association became significant (p=0.04).

Conclusion

Controlling for old age, longer durations between >35°C, ≤36.5°C during therapeutic hypothermia for cardiac arrest were significantly associated with good clinical outcomes. Time spent within a given temperature range may be useful for measuring the effect of temperature management.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1136/bmjno-2022-000273

Publication Info

Luedke, Matthew William, Carmelo Graffagnino, B Grace McKinney, Jill Piper, Edwin Iversen and Brad Kolls (2022). Association of time-temperature curves with outcomes in temperature management for cardiac arrest. BMJ neurology open, 4(1). p. e000273. 10.1136/bmjno-2022-000273 Retrieved from https://hdl.handle.net/10161/25095.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Luedke

Matthew William Luedke

Associate Professor of Neurology

I have diverse research interests and collaborations.  Clinical research interests include epilepsy quality-of-life interventions and therapeutics and acute care neurological issues like post-cardiac arrest management and quality-of-care issues.  I work with the Duke hyperbaric chamber team on clinical neurophysiological monitoring of ketone-related research.  

Graffagnino

Carmelo Graffagnino

Professor of Neurology

As an neurointensivist with subspecialty training in cerebrovascular disease and neurocritical care my research focus is on the application of neurocritical care interventions to help patients with acute strokes and head injuries. My current research focuses both on improving and innovation of new therapies for patients with acute stroke as well as improving the systems of care that deliver life saving treatments to patients with stroke. 

Current research studies include the use of neuroprotection strategies such as inhaled Nitric Oxide to protect the brain after removal of large vessel clots. I also involved in helping to develop and test new thrombolytic agents for use in acute stroke. 

I am also working with a multidisciplinary team of systems of care experts at DCRI to re-engineer our stroke system of care across the heart of the Stroke Belt through a project called IMPROVE-Stroke Care which is leveraging novel informatics data systems to deliver state of the art care for patients with acute stroke. 

I am also working with a number of colleagues in Neurology, Neurosurgery and Emergency medicine to apply the concept of system re-engineering to improve the outcomes of patients with acute traumatic brain injury in East Africa (Uganda, Kenya and Tanzania)

Iversen

Edwin Severin Iversen

Research Professor of Statistical Science

Bayesian statistical modeling with application to problems in genetic
epidemiology and cancer research; models for epidemiological risk
assessment, including hierarchical methods for combining related
epidemiological studies; ascertainment corrections for high risk
family data; analysis of high-throughput genomic data sets.

Kolls

Bradley Jason Kolls

Associate Professor of Neurology

As a neurointensivist, I am interested in improving our ability to monitor brain function and impact of therapy on our patients in the critical care setting. To this end I am developing new approaches to patient monitoring that will integrate patient physiologic monitoring with brain activity recorded by electroencephalography (EEG). On the basic science side I am interested in the central nervous system's response to injury. Although much attention has been focused on closed head injury as of late, stroke and brain hemorrhage are just as common in the civilian population and pose many of the same clinical challenges as traumatic brain injury. Using mouse models of clinically relevant brain injury, including models of stroke, subarachnoid hemorrhage, lobar hemorrhage, closed head injury and penetrating brain injury, we can explore the key molecular events that lead to edema, secondary brain injury, hyperexcitability and epilepsy, and other sequelae which contribute to poor patient recovery, and significant morbidity following brain injury. By investigating the underlying mechanisms that contribute to these adaptive changes using electrophysiology and molecular biology approaches we can then find ways to prevent them from becoming maladaptive and develop new therapies for our patients with head injuries.


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