Prediction of Block Height of Spinal Anesthesia

Taipei Veterans General Hospital

Status: Unknown

Conditions: Anesthesia; Reaction

Treatments: Other: Machine learning methods

Study type: Observational

Funder types: Other

Identifiers

NCT05024838

2020-01-004CC

Details and patient eligibility

About

Spinal anesthesia is one of the most used techniques for surgery. Anesthesiologists usually check the block height (dermatome) of spinal anesthesia before surgery start. More than 20 factors have been postulated to alter spinal anesthetic block height. We would like to use machine learning to comprehensively consider various factors such as physiological parameters and different drug characteristics to establish a predictive model to evaluate the sensory blockade of spinal anesthesia.

Full description

This is an observational study of the retrospective collection of patient data.

The investigators retrospectively collected the electronic medical record of patients receiving spinal anesthesia from July 1, 2018, to Dec 31, 2018. Anesthesia-related factors such as anesthesiologist's expertise, injection site, patient position, the dosage of local anesthetics, needle size, the direction of needle bevel, and basic demographic information of the patients were used for data analysis. Patients less than 18 years old were excluded from this study. Twenty percent of the dataset was used as a testing dataset, and the remaining were used for model training. The investigators will utilize four machine learning algorithms as XGBoost (Extreme Gradient Boosting), AdaBoost (Adaptive Boosting), Random Forest (RF), and support vector machine (SVM). Model performances were evaluated visually with a confusion matrix.

Enrollment: 3,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Patients receiving spinal anesthesia from July 1, 2018, to Dec 31, 2018, with available electronic medical records.

Exclusion criteria

• Age <18 years

Trial design

3,000 participants in 1 patient group

Spinal anesthesia

Description:

The investigators retrospectively collected the electronic medical record of patients receiving spinal anesthesia from July 1, 2018, to Dec 31, 2018. Patients less than 18 years old were excluded from this study.

Treatment:

Other: Machine learning methods