Anesthesia; ReactionNCT05024838
Prediction of Block Height of Spinal Anesthesia
An observational study of Anesthesia; Reaction, run by Taipei Veterans General Hospital, Taiwan at 1 site in Taiwan.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Anesthesia; Reaction
- What is being tested?
- Machine learning methods
- Type of treatment
- Injection or infusion
- How many people
- 3,000 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Oct 2020to Jul 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients receiving spinal anesthesia due to the need for surgical intervention with available electronic medical records.
Who may be able to join
- Patients receiving spinal anesthesia from July 1, 2018, to Dec 31, 2018, with available electronic medical records.
Who cannot join
- Age <18 years
Trial locations and contacts
1 site in 1 country.
Taiwan1 site, 1 recruiting
- Recruiting
Department of Anesthesiology, Taipei Veterans General Hospital
Taipei, 112
Hung-Wei Cheng, MD, +886938593113, hwc1127@gmail.com
About this study
Official title: Prediction of Block Height of Spinal Anesthesia Via Machine Learning Approach
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.
Read the detailed 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.
- Conditions
- Anesthesia; Reaction
- Being tested
- Machine learning methods
- Keywords
- Spinal anesthesia, Machine learning, Sensory blockade
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Machine learning methodsOther
This is an observational study of the retrospective collection of patient data. 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.
| Study group | Role | What they receive |
|---|---|---|
| Spinal anesthesia | 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. Receives: Other: Machine learning methods |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensory blockade height of spinal anesthesia
The record of sensory blockade level was extracted from retrospective electronic medical records as the primary outcome.
The investigators would like to use machine learning methods to consider various factors such as physiological parameters of patients, different drug characteristics, and different anesthesia providers to establish a predictive model to evaluate the sensory blockade of spinal anesthesia.
Measured: From time of starting spinal anesthesia until the time of testing blockage height, assessed up to 10 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Aug 2021
- Study start1 Oct 2020
- Primary completionJul 2022 (estimated)
- Study completionJul 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Anesthesia; ReactionStudies of the same condition, open and under way.
- More trials run by Taipei Veterans General Hospital, TaiwanThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Taipei Veterans General Hospital, Taiwan
- Sponsor type
- Other government
- Responsible party
- Sponsor
- Investigators
- Hung-Wei Cheng, MD, Principal investigator, Taipei Veteran General Hospital, Taiwan
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05024838
- Sponsor's protocol ID
- 2020-01-004CC
- Status last verified
- Aug 2021
- First submitted
- 22 Aug 2021
- Last updated
- 27 Aug 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Fanning N, Arzola C, Balki M, Carvalho JC. Lumbar dural sac dimensions determined by ultrasound helps predict sensory block extent during combined spinal-epidural analgesia for labor. Reg Anesth Pain Med. 2012 May-Jun;37(3):283-8. doi: 10.1097/AAP.0b013e31824b30d2.
PubMed 22476235Heng Sia AT, Tan KH, Sng BL, Lim Y, Chan ESY, Siddiqui FJ. Hyperbaric versus plain bupivacaine for spinal anesthesia for cesarean delivery. Anesth Analg. 2015 Jan;120(1):132-140. doi: 10.1213/ANE.0000000000000443.
PubMed 25625258Greene NM. Distribution of local anesthetic solutions within the subarachnoid space. Anesth Analg. 1985 Jul;64(7):715-30. No abstract available.
PubMed 3893222Horstman DJ, Riley ET, Carvalho B. A randomized trial of maximum cephalad sensory blockade with single-shot spinal compared with combined spinal-epidural techniques for cesarean delivery. Anesth Analg. 2009 Jan;108(1):240-5. doi: 10.1213/ane.0b013e31818e0fa6.
PubMed 19095857Kozanhan B, Bardak O, Sami Tutar M, Ozler S, Yildiz M, Solak I. The influence of Body Roundness Index on sensorial block level of spinal anaesthesia for elective caesarean section: an observational study. J Obstet Gynaecol. 2020 Aug;40(6):772-778. doi: 10.1080/01443615.2019.1647523. Epub 2019 Aug 30.
PubMed 31469024Kuok CH, Huang CH, Tsai PS, Ko YP, Lee WS, Hsu YW, Hung FY. Preoperative measurement of maternal abdominal circumference relates the initial sensory block level of spinal anesthesia for cesarean section: An observational study. Taiwan J Obstet Gynecol. 2016 Dec;55(6):810-814. doi: 10.1016/j.tjog.2015.04.009.
PubMed 28040125
Study at a glance
From the registry record, last updated by the sponsor on 27 Aug 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prediction of Block Height of Spinal Anesthesia Via Machine Learning Approach
- ClinicalTrials.gov ID
- NCT05024838
- Acronym / sponsor ID
- 2020-01-004CC
- Conditions
- Anesthesia; Reaction
- Keywords
- Spinal anesthesia, Machine learning, Sensory blockade
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Taipei Veterans General Hospital, TaiwanOther government
- Study start
- 1 Oct 2020 (actual)
- Primary completion
- Jul 2022 (estimated)
- Study completion
- Jul 2022 (estimated)
- First posted
- 27 Aug 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Spinal anesthesia | – | Other: Machine learning methodsThe 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients receiving spinal anesthesia due to the need for surgical intervention with available electronic medical records.
Key inclusion criteria (1 listed)
- Patients receiving spinal anesthesia from July 1, 2018, to Dec 31, 2018, with available electronic medical records.
Key exclusion criteria (1 listed)
- Age <18 years
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Machine learning methodsThis is an observational study of the retrospective collection of patient data. 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. | Other | Spinal anesthesia |
Primary outcome
Sensory blockade height of spinal anesthesia
Time frame: From time of starting spinal anesthesia until the time of testing blockage height, assessed up to 10 minutes
The record of sensory blockade level was extracted from retrospective electronic medical records as the primary outcome. The investigators would like to use machine learning methods to consider various factors such as physiological parameters of patients, different drug characteristics, and different anesthesia providers to establish a predictive model to evaluate the sensory blockade of spinal anesthesia.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Aug 2021.
- Background: PubMed 22476235Fanning N, Arzola C, Balki M, Carvalho JC. Lumbar dural sac dimensions determined by ultrasound helps predict sensory block extent during combined spinal-epidural analgesia for labor. Reg Anesth Pain Med. 2012 May-Jun;37(3):283-8. doi: 10.1097/AAP.0b013e31824b30d2.
- Background: PubMed 25625258Heng Sia AT, Tan KH, Sng BL, Lim Y, Chan ESY, Siddiqui FJ. Hyperbaric versus plain bupivacaine for spinal anesthesia for cesarean delivery. Anesth Analg. 2015 Jan;120(1):132-140. doi: 10.1213/ANE.0000000000000443.
- Background: PubMed 3893222Greene NM. Distribution of local anesthetic solutions within the subarachnoid space. Anesth Analg. 1985 Jul;64(7):715-30. No abstract available.
- Background: PubMed 19095857Horstman DJ, Riley ET, Carvalho B. A randomized trial of maximum cephalad sensory blockade with single-shot spinal compared with combined spinal-epidural techniques for cesarean delivery. Anesth Analg. 2009 Jan;108(1):240-5. doi: 10.1213/ane.0b013e31818e0fa6.
- Background: PubMed 31469024Kozanhan B, Bardak O, Sami Tutar M, Ozler S, Yildiz M, Solak I. The influence of Body Roundness Index on sensorial block level of spinal anaesthesia for elective caesarean section: an observational study. J Obstet Gynaecol. 2020 Aug;40(6):772-778. doi: 10.1080/01443615.2019.1647523. Epub 2019 Aug 30.
- Background: PubMed 28040125Kuok CH, Huang CH, Tsai PS, Ko YP, Lee WS, Hsu YW, Hung FY. Preoperative measurement of maternal abdominal circumference relates the initial sensory block level of spinal anesthesia for cesarean section: An observational study. Taiwan J Obstet Gynecol. 2016 Dec;55(6):810-814. doi: 10.1016/j.tjog.2015.04.009.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Hung-Wei Cheng, MD principal investigator
Taipei Veteran General Hospital, Taiwan
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Anesthesia; Reaction, run by Taipei Veterans General Hospital, Taiwan at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 27 Aug 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Hung-Wei Cheng, MD (886-2-28757549, hwc1127@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensory blockade height of spinal anesthesia (time frame: From time of starting spinal anesthesia until the time of testing blockage height, assessed up to 10 minutes). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05024838, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Aug 2021.