Residual Paralysis, Post AnesthesiaPINESNCT05471882
Predicting Neuromuscular Recovery in Surgical Patients Using Machine Learning
An observational study of Residual Paralysis, Post Anesthesia and Postoperative Complications, run by University Hospital Ulm at 2 sites in Germany.
Trial summary
Despite emerging efforts to decrease residual paralysis and postoperative complications with the use of quantitative neuromuscular monitoring and reversal agents their incidences remain high. In an optimal setting, neuromuscular blocking agents are dosed in a way that there is no residual block at the end of surgery. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Residual Paralysis, Post Anesthesia, Postoperative Complications, Neuromuscular Blockade
- How many people
- 240,000 participants
- Where
- 2 sitesGermany
- Study dates
- 1 Mar 2024to 1 Jan 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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
- No healthy volunteers
- Adult, Older adult
Study population: Adult patients (≥18 years) receiving non-cardiac surgery receiving neuromuscular blocking agents and with available TOF data.
Who may be able to join
- Adult patients (≥18 years) undergoing non-cardiac surgery receiving general anesthesia with intraoperative neuromuscular blocking agent administration and available TOF data.
Who cannot join
- none
Trial locations and contacts
2 sites in 1 country.
Germany2 sites
Technical University Munich
Munich, Bavaria, 81675
University Hospital Ulm
Ulm, Baden-Wurttemberg, 89073
About this study
Official title: Development and Validation of a Machine Learning Algorithm for Prediction of Complete Neuromuscular Recovery in Adult Surgical Patients
Despite emerging efforts to decrease residual paralysis and postoperative complications with the use of quantitative neuromuscular monitoring and reversal agents their incidences remain high. In an optimal setting, neuromuscular blocking agents are dosed in a way that there is no residual block at the end of surgery. The effect of neuromuscular blocking agents, however, is highly variable and is not only influenced by their dose, but also by several patient-related factors such as muscle status, metabolic activity, and anesthesia management. Accordingly, the duration of action is difficult to predict.
The PINES project will use artificial intelligence methods to develop a model that can accurately predict the course of action of neuromuscular blocking agents. It will be used to predict time to complete neuromuscular recovery (train-of-four [TOF] ratio >0.9) and may provide as a decision support in the individual management of timing and dosing of neuromuscular blocking drugs and their reversal agents.
In a secondary analysis, the association between the choice of neuromuscular blocking agent and postoperative pulmonary complications will be evaluated.
Read the detailed description
The objective of the PINES project is to identify a model that can accurately predict 1) time to complete neuromuscular recovery, 2) optimal timing and dose of neuromuscular blocking agents at each time point during surgery, and 3) TOF ratio at the estimated end of surgery to assess residual paralysis. Furthermore, a prospective clinical pilot study will be conducted to compare anesthesiologist-predicted neuromuscular recovery with that of the algorithm.
The project consists of two main objectives:
- Big data analysis
- Establishing a data warehouse: Electronic registry data will be used.
- Generation of prediction models: Classification models will first be used to identify and weight the relevant parameters collected during premedication and intraoperatively. These will form the basis for the training cohort, which can then be used to carry out a simulated real-time analysis of the data. To compare the models, the loss functions mean squared error, mean absolute error and Huber Loss will be calculated.
II. Prospective comparison of the prediction: machine-learning model vs. anesthesiologist
Using the validated final prediction model with the best accuracy, the investigators will perform a prospective clinical pilot study. The cohort will include prospectively enrolled adult surgical patients undergoing general anesthesia with a single dose of rocuronium for neuromuscular blockade. For each enrolled case, both the PINES algorithm and an experienced anesthesiologist will estimate the time to neuromuscular recovery, defined as a train-of-four (TOF) ratio > 0.9.
At anesthesia induction, following administration of the neuromuscular blocking agent, participating specialist-level anesthesiologists will prospectively estimate the time in minutes until recovery of neuromuscular transmission. The PINES machine-learning model will generate its prediction. The actual recovery time will be determined from the continuously recorded intraoperative TOF measurements.
The agreement between the predicted and observed recovery times will be assessed by calculating the difference between predicted and actual values, as well as by determining inter-rater correlation coefficients comparing anesthesiologist predictions, algorithm predictions, and the measured recovery times.
In a secondary analysis, there will be evaluated whether the choice of neuromuscular blocking agent influences postoperative pulmonary complication risk in adult patients. Confounding will be addressed using statistical methods based on a causal inference framework.
- Conditions
- Residual Paralysis, Post Anesthesia, Postoperative Complications, Neuromuscular Blockade, Quantitative Neuromuscular Monitoring
- Keywords
- Neural Networks, Computer, Monitoring, Intraoperative, Artificial Intelligence, Time Factors
- Medical subject headings
- Delayed Emergence from Anesthesia, Postoperative Complications
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Single neuromuscular blocking agent dose | Patients receiving a single dose of neuromuscular blocking agent | |
| Incremental doses of neuromuscular blocking agents | Patients receiving repetitive doses of neuromuscular blocking agents | |
| Pharmacological reversal | Patients receiving pharmacological reversal of neuromuscular block |
What is being measured
The primary outcome is the main question the study is designed to answer.
complete neuromuscular recovery
predicting the time to complete neuromuscular recovery (defined as TOF ratio >0.9) from any time point of surgery
Measured: intraoperative
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Jul 2022
- Study start1 Mar 2024
- Primary completion1 Sep 2026 (estimated)
- Study completion1 Jan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Residual Paralysis, Post AnesthesiaStudies of the same condition, open and under way.
- 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
- 240,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital Ulm
- Sponsor type
- University, hospital or other
- Collaborators
- Technical University of Munich
- Responsible party
- Principal investigator, Flora Scheffenbichler, University Hospital Ulm
- Investigators
- Manfred Blobner, MD PhD, Principal investigator, Department of Anesthesiology and Intensive Care Medicine, University of Ulm,Ulm, Germany
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05471882
- Sponsor's protocol ID
- TOF-R Prediction
- Acronym
- PINES
- Status last verified
- Dec 2025
- First submitted
- 20 Jul 2022
- Last updated
- 7 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of a Machine Learning Algorithm for Prediction of Complete Neuromuscular Recovery in Adult Surgical Patients
- ClinicalTrials.gov ID
- NCT05471882
- Acronym / sponsor ID
- PINES / TOF-R Prediction
- Conditions
- Residual Paralysis, Post Anesthesia, Postoperative Complications, Neuromuscular Blockade, Quantitative Neuromuscular Monitoring
- Keywords
- Neural Networks, Computer, Monitoring, Intraoperative, Artificial Intelligence, Time Factors
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 240,000 participants (estimated)
- Lead sponsor
- University Hospital UlmUniversity, hospital or other
- Collaborators
- Technical University of Munich
- Study start
- 1 Mar 2024 (actual)
- Primary completion
- 1 Sep 2026 (estimated)
- Study completion
- 1 Jan 2027 (estimated)
- First posted
- 25 Jul 2022 (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.
Despite emerging efforts to decrease residual paralysis and postoperative complications with the use of quantitative neuromuscular monitoring and reversal agents their incidences remain high. In an optimal setting, neuromuscular blocking agents are dosed in a way that there is no residual block at the end of surgery. The effect of neuromuscular blocking agents, however, is highly variable and is not only influenced by their dose, but also by several patient-related factors such as muscle status, metabolic activity, and anesthesia management. Accordingly, the duration of action is difficult to predict.
The PINES project will use artificial intelligence methods to develop a model that can accurately predict the course of action of neuromuscular blocking agents. It will be used to predict time to complete neuromuscular recovery (train-of-four [TOF] ratio >0.9) and may provide as a decision support in the individual management of timing and dosing of neuromuscular blocking drugs and their reversal agents.
In a secondary analysis, the association between the choice of neuromuscular blocking agent and postoperative pulmonary complications will be evaluated.
Detailed description
The objective of the PINES project is to identify a model that can accurately predict 1) time to complete neuromuscular recovery, 2) optimal timing and dose of neuromuscular blocking agents at each time point during surgery, and 3) TOF ratio at the estimated end of surgery to assess residual paralysis. Furthermore, a prospective clinical pilot study will be conducted to compare anesthesiologist-predicted neuromuscular recovery with that of the algorithm.
The project consists of two main objectives:
- Big data analysis
- Establishing a data warehouse: Electronic registry data will be used.
- Generation of prediction models: Classification models will first be used to identify and weight the relevant parameters collected during premedication and intraoperatively. These will form the basis for the training cohort, which can then be used to carry out a simulated real-time analysis of the data. To compare the models, the loss functions mean squared error, mean absolute error and Huber Loss will be calculated.
II. Prospective comparison of the prediction: machine-learning model vs. anesthesiologist
Using the validated final prediction model with the best accuracy, the investigators will perform a prospective clinical pilot study. The cohort will include prospectively enrolled adult surgical patients undergoing general anesthesia with a single dose of rocuronium for neuromuscular blockade. For each enrolled case, both the PINES algorithm and an experienced anesthesiologist will estimate the time to neuromuscular recovery, defined as a train-of-four (TOF) ratio > 0.9.
At anesthesia induction, following administration of the neuromuscular blocking agent, participating specialist-level anesthesiologists will prospectively estimate the time in minutes until recovery of neuromuscular transmission. The PINES machine-learning model will generate its prediction. The actual recovery time will be determined from the continuously recorded intraoperative TOF measurements.
The agreement between the predicted and observed recovery times will be assessed by calculating the difference between predicted and actual values, as well as by determining inter-rater correlation coefficients comparing anesthesiologist predictions, algorithm predictions, and the measured recovery times.
In a secondary analysis, there will be evaluated whether the choice of neuromuscular blocking agent influences postoperative pulmonary complication risk in adult patients. Confounding will be addressed using statistical methods based on a causal inference framework.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Single neuromuscular blocking agent dose | – | –Patients receiving a single dose of neuromuscular blocking agent |
| Incremental doses of neuromuscular blocking agents | – | –Patients receiving repetitive doses of neuromuscular blocking agents |
| Pharmacological reversal | – | –Patients receiving pharmacological reversal of neuromuscular block |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients (≥18 years) receiving non-cardiac surgery receiving neuromuscular blocking agents and with available TOF data.
Key inclusion criteria (1 listed)
- Adult patients (≥18 years) undergoing non-cardiac surgery receiving general anesthesia with intraoperative neuromuscular blocking agent administration and available TOF data.
Key exclusion criteria (1 listed)
- none
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
complete neuromuscular recovery
Time frame: intraoperative
predicting the time to complete neuromuscular recovery (defined as TOF ratio >0.9) from any time point of surgery
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 May 2026.
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.
Manfred Blobner, MD PhD principal investigator
Department of Anesthesiology and Intensive Care Medicine, University of Ulm,Ulm, Germany
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Residual Paralysis, Post Anesthesia and Postoperative Complications, run by University Hospital Ulm at 2 sites in Germany.
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: under way, not looking for participants, as of the sponsor's last update on 7 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Germany. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
complete neuromuscular recovery (time frame: intraoperative). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 7 May 2026; AzTrials last refreshed its copy on 31 Oct 2026.