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Record W4399884722 · doi:10.1097/cce.0000000000001111

Microvascular Autoregulation in Skeletal Muscle Using Near-Infrared Spectroscopy and Derivation of Optimal Mean Arterial Pressure in the ICU: Pilot Study and Comparison With Cerebral Near-Infrared Spectroscopy

2024· article· en· W4399884722 on OpenAlexafffund
Amirali Mirsajadi, Dustin Erickson, Soumya Alias, Logan Froese, Amanjyot Singh Sainbhi, Alwyn Gomez, Raju Majumdar, Isuru Herath, Maggie Wilson, Ryan Zarychanski, Frederick A. Zeiler, Asher A. Mendelson

Bibliographic record

VenueCritical Care Explorations · 2024
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsPan Am ClinicCancerCare ManitobaUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsMedicineSkeletal muscleCerebral autoregulationCardiologyCerebral perfusion pressureInternal medicineMean arterial pressureAutoregulationAnesthesiaBlood pressurePerfusionHeart rate

Abstract

fetched live from OpenAlex

IMPORTANCE: Microvascular autoregulation (MA) maintains adequate tissue perfusion over a range of arterial blood pressure (ABP) and is frequently impaired in critical illness. MA has been studied in the brain to derive personalized hemodynamic targets after brain injury. The ability to measure MA in other organs is not known, which may inform individualized management during shock. OBJECTIVES: This study determines the feasibility of measuring MA in skeletal muscle using near-infrared spectroscopy (NIRS) as a marker of tissue perfusion, the derivation of optimal mean arterial pressure (MAPopt), and comparison with indices from the brain. DESIGN: Prospective observational study. SETTING: Medical and surgical ICU in a tertiary academic hospital. PARTICIPANTS: Adult critically ill patients requiring vasoactive support on the first day of ICU admission. MAIN OUTCOMES AND MEASURES: Fifteen critically ill patients were enrolled. NIRS was applied simultaneously to skeletal muscle (brachioradialis) and brain (frontal cortex) while ABP was measured continuously via invasive catheter. MA correlation indices were calculated between ABP and NIRS from skeletal muscle total hemoglobin (MVx), muscle tissue saturation index (MOx), brain total hemoglobin (THx), and brain tissue saturation index (COx). Curve fitting algorithms derive the MAP with the lowest correlation index value, which is the MAPopt. RESULTS: MAPopt values were successfully calculated for each correlation index for all patients and were frequently (77%) above 65 mm Hg. For all correlation indices, median time was substantially above impaired MA threshold (24.5-34.9%) and below target MAPopt (9.0-78.6%). Muscle and brain MAPopt show moderate correlation (MVx-THx r = 0.76, p < 0.001; MOx-COx r = 0.69, p = 0.005), with a median difference of -1.27 mm Hg (-9.85 to -0.18 mm Hg) and 0.05 mm Hg (-7.05 to 2.68 mm Hg). CONCLUSIONS AND RELEVANCE: This study demonstrates, for the first time, the feasibility of calculating MA indices and MAPopt in skeletal muscle using NIRS. Future studies should explore the association between impaired skeletal muscle MA, ICU outcomes, and organ-specific differences in MA and MAPopt thresholds.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.358
Teacher spread0.283 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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