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Predictability of ANI (Analgesia Nociception Index) for Spinal Hypotension

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Yonsei University

Status

Enrolling

Conditions

Cesarean Section
Spinal Anesthesia

Treatments

Other: observation

Study type

Observational

Funder types

Other

Identifiers

NCT06327165
1-2023-0072

Details and patient eligibility

About

Spinal anesthesia is widely accepted as the anesthetic method of choice for Cesarean section. However, the incidence of spinal hypotension is 50-70%, and the decrease in blood pressure is often rapid and severe. Heart rate variability is influenced by various factors such as the sympathetic nervous system, parasympathetic nervous system, temperature regulation, baroreflex, and endocrine regulation, but high frequency heart rate variability above 0.15 Hz very specifically reflects the parasympathetic nervous system. The ANI monitor calculates heart rate variability mediated by changes in the parasympathetic nervous system. This study aims to determine whether ANI monitor can predict hypotension in patients undergoing a caesarean section under spinal anaesthesia while applying the preemptive vasopressor phenylephrine infusion protocol.

Enrollment

40 estimated patients

Sex

Female

Ages

20+ years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • full-term parturients undergoing cesarean delivery

Exclusion criteria

  • emergent surgery, placenta previa, Morbid obesity with a BMI ≥ 40 kg/m2, Gestational age < 36 or ≥ 41 weeks, Contraindications to spinal anesthesia, cardiac arrhythmia, implantable pacemaker, diseases affecting the autoimmune system (such as immune disease or diabetic neuropathy), use of medications affecting ANI monitoring (antimuscarinics, alpha-agonists, beta blockers), illiteracy, or foreigners

Trial design

40 participants in 1 patient group

pregnant women
Description:
Women undergoing cesarean section under spinal anesthesia with ANI monitor applied
Treatment:
Other: observation

Trial contacts and locations

1

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Central trial contact

Seung Hyun Kim, Associate Professor

Data sourced from clinicaltrials.gov

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