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Record W2415338902 · doi:10.1213/ane.0000000000001096

Risk Factors Involved in Central-to-Radial Arterial Pressure Gradient During Cardiac Surgery

2015· article· en· W2415338902 on OpenAlex
Giuseppe Fuda, André Denault, Alain Deschamps, Denis Bouchard, Annik Fortier, Jean Lambert, Pierre Couture

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnesthesia & Analgesia · 2015
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsBlood pressureCardiologyMedicineCardiac surgeryPressure gradientInternal medicineSurgeryMechanicsPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: A central-to-radial arterial pressure gradient may occur after cardiopulmonary bypass (CPB), which, in some patients, may last for a prolonged time after CPB. Whenever there is a pressure gradient, the radial artery pressure measure may underestimate a more centrally measured systemic pressure, which may result in a misguided therapeutic strategy. It is clinically important to identify the risk factors that may predict the appearance of a central-to-radial pressure gradient, because more central sites of measurements might then be considered to monitor systemic arterial pressure in high-risk patients. The objective of this study was to assess preoperative and intraoperative risk factors for central-to-radial pressure gradient. METHODS: Seventy-three patients undergoing cardiac surgery using CPB were included in this prospective observational study. A significant central-to-radial arterial pressure gradient was defined as a difference of 25 mm Hg in systolic pressure or 10 mm Hg in mean arterial pressure for a minimum of 5 minutes. Preoperative data included demographics, presence of comorbidities, and medications. Intraoperative data included type of surgery, CPB and aortic clamping time, use of inotropic drugs, and vasodilators or vasopressors agents. The diameter of the radial and femoral artery was measured before the induction of anesthesia using B-mode ultrasonography. RESULTS: Thirty-three patients developed a central-to-radial arterial pressure gradient (45%). Patients with a significant pressure gradient had a smaller weight (71.0 ± 16.9 vs 79.3 ± 17.3 kg, P = 0.041), a smaller height (162.0 ± 9.6 vs 166.3 ± 8.6 cm, P = 0.047), a smaller radial artery diameter (0.24 ± 0.03 vs 0.29 ± 0.05 cm, P < 0.001), and were at a higher risk as determined by the Parsonnet score (30.3 ± 24.9 vs 17.0 ± 10.9, P = 0.007). In addition, a longer aortic clamping time (85.8 ± 51.0 vs 64.2 ± 29.3 minutes, P = 0.036), mitral and complex surgery (P = 0.007 and P = 0.017, respectively), and administration of vasopressin (P = 0.039) were identified as potential independent predictors of a central-to-radial pressure gradient. By using multivariate logistic regression analysis, the following independent risk factors were identified: Parsonnet score (odds ratio [OR], 1.076; 95% confidence interval [CI], 1.027-1.127, P = 0.002), aortic clamping time >90 minutes (OR, 8.521; 95% CI, 1.917-37.870, P = 0.005), and patient height (OR, 0.933, 95% CI, 0.876-0.993, P = 0.029). The relative risk (RR) estimates remained statistically significant for the Parsonnet score and the aortic clamping time ≥90 minutes (RR, 1.010; 95% CI, 1.003-1.018, P = 0.009 and RR, 2.253; 95% CI, 1.475-3.443, P < 0.001 respectively) while showing a trend for patient height (RR, 0.974; 95% CI, 0.948-1.001, P = 0.058). CONCLUSIONS: Central-to-radial gradients are common in cardiac surgery. The threshold for using a central site for blood pressure monitoring should be low in small, high-risk patients undergoing longer surgical interventions to avoid inappropriate administration of vasopressors and/or inotropic agents.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.244
Teacher spread0.224 · 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