Prediction of Local Anaesthetic Dosing During Labour Epidural Analgesia

NCT07614516 | Not Yet Recruiting

• 1 other identifier: 27389
• Study Type: observational
• Target: 12,500
• Locations: 1 country
• Sites: 1

Brief Summary

Epidural analgesia is the gold standard for controlling labour pain. However, labour pain happens during neuraxial analgesia, due to anaesthetic, obstetric, maternal factors. The investigators hypothesized that relevant variables, able to predict the local anaesthetic (LA) requirement during labour, can be identified at admission and each parturient may therefore be accordingly classified in "low-requirement" and "high-requirement". In this way, a predictive score may be developed, and the analgesic regimen may be matched to the individual patient, thus ensuring a timely and appropriate treatment of patients likely to require higher doses of LA, while minimizing potentially side effects of excessive treatment in the low-dose group.

Conditions

Labour Analgesia

Keywords

Machine Learning; Anesthesia, Obstetric; Anesthesia, Epidural; Anesthetics, Local

Outcome Measures

Primary Outcomes (1)

• Machine-learning algorithm able to predict the LA consumption

  To develop a machine-learning algorithm able to predict the mean hourly cumulative LA consumption administered via the epidural catheter from the catheter placement up to delivery, expressed as time-weighted LA consumption per hour (mg/h) in patients receiving top-up analgesia or the need for adjunctive rescue LA boluses in patients receiving PIEB (Programmed Intermittent Epidural Bolus) analgesia.

  From the epidural catheter placement to delivery.

Secondary Outcomes (23)

• Clinical score

  At admission in the Labour Suite and before the epidural catheter is placed

• Time-dependent AUC of LA manual boluses

  From epidural catheter placement to delivery.

• Total LA consumption

  From epidural catheter placement to delivery.

• Ratio of time to first bolus demand to duration of labor

  From epidural catheter placement to delivery.

• Total demand of LA boluses

  From epidural catheter placement to delivery.

Study Arms (1)

All parturients between January 2020 and March 2026

All parturients who delivered via vaginal route or intrapartum caesarean section and received neuraxial analgesia (epidural analgesia (EA) or combined spinal-epidural \[CSE\] analgesia or dural puncture epidural (DPE)) in Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, between January 1st, 2020 and March 01th, 2026 (including follow-up data), meeting the inclusion criteria. Labour analgesia was maintained through manual top-up boluses or PIEB (Programmed Intermittent Epidural Bolus).

Other: Machine-learning prediction model

Interventions

Machine-learning prediction model OTHER

A machine-learning prediction model will be developed to anticipate the parturient's requirement of LA at admission in the Labour Suite, according to demographic, obstetric and anaesthetic features ongoing before administration of the first epidural bolus.

All parturients between January 2020 and March 2026

Eligibility Criteria

• Age: 18 Years+
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

All parturients who delivered via vaginal route or intrapartum caesarean section and received neuraxial analgesia (epidural analgesia (EA) or combined spinal-epidural \[CSE\] analgesia or dural puncture epidural (DPE)) in Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, between January 1st, 2020 and March 01th, 2026 (including follow-up data), meeting the inclusion criteria.

You may qualify if:

• Parturients receiving neuraxial analgesia for labour, as clinical practice

You may not qualify if:

• Planned caesarean delivery

Sponsors & Collaborators

• Fondazione Policlinico Universitario Agostino Gemelli IRCCS: lead

Study Sites (1)

Fondazione Policlinico Universitario A. Gemelli IRCCS

Rome, RM, 00168, Italy

Location

Central Study Contacts

Bruno A Zanfini, MD

CONTACT

06 3015 3105; brunoantonio.zanfini@policlinicogemelli.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: May 8, 2026
• First Posted: May 29, 2026
• Study Start: June 13, 2026
• Primary Completion (Estimated): September 30, 2026
• Study Completion (Estimated): October 31, 2026
• Last Updated: May 29, 2026

Record last verified: 2026-05

Locations

IT (1)