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Cardio-centric hemodynamic management with and without adjuvant ethyl nitrite improves mean arterial pressure in rodents with chronic high-thoracic traumatic spinal cord injury

2023· article· en· W4378674478 on OpenAlexaff
Jennifer Duffy, Ryan L. Hoiland, Oliver H. Wearing, Erin Erskine, Brian K. Kwon, Christopher R. West

Bibliographic record

VenuePhysiology · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSpinal cord injuryAnesthesiaHemodynamicsBlood pressureMean arterial pressureSpinal cordHeart rateInternal medicine

Abstract

fetched live from OpenAlex

Objective: Traumatic spinal cord injury (SCI) causes an initial injury followed by a protracted phase of spinal cord tissue hypoxia. This tissue hypoxia contributes to secondary injury, leading to worse motor and cardio-autonomic outcomes in the chronic setting. No neuroprotective agents to mitigate secondary injury have been identified as efficacious in clinical trials. However, we have demonstrated that taking a cardio-centric approach to hemodynamic management following SCI by augmenting cardiac output and mean arterial pressure (MAP) with the b1-adrenoceptor agonist dobutamine (DOB), and further coupling DOB infusion with the inhalation of ethyl nitrite (ENO), an S-nitrosylating agent, is associated with improved spinal cord oxygenation in the acute phase post-SCI. Aim: To determine the influence of a cardio-centric approach to hemodynamic management with adjuvant ENO inhalation following SCI on long term outcomes. We hypothesized that treatment with DOB and ENO in the acute phase following SCI would mitigate secondary injury and improve cardiovascular outcomes in the chronic setting. Methods. A total of 34 male Wistar rats underwent a T3 contusion injury (300 kdyn) and were assigned into 4 treatment groups: control (n=6), ENO (n=6), DOB (n=12), and combined DOB and ENO (n=10). At 11-weeks post-SCI, a locomotor assessment was conducted using the Basso, Beattie and Bresnahan (BBB) locomotor rating scale. At 12-weeks post-SCI, rodents were anesthetized with intravenous urethane (2.44±0.50 g/kg) and instrumented with a solid-state pressure transducer in the carotid artery to measure MAP. Results. We observed a higher MAP in both DOB (113.6 ± 11.4 mmHg; p = 0.030) and ENO+DOB (116.7 ± 14.6 mmHg; p=0.013) treated groups when compared with controls (94.65 ± 11.62 mmHg). The MAP of ENO treated animals (91.6 ± 7.3 mmHg; P= 0.97) was not different from controls. No differences in BBB scores were found between DOB (15.17 ± 4.49), ENO+DOB (13.95 ± 3.86), ENO (12.5 ± 2.5) and control (11.8 ± 2.7)(P=0.29). Collectively, these data suggest that DOB treatment, alone or in combination with ENO, improves systemic hemodynamics in the chronic high-thoracic SCI setting US Department of Defense, ICORD Seed Grant, Craig H. Neilsen Foundation This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.355
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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