Postoperative Pulmonary ComplicationsNCT05671939
Different Algorithm Models to Predict Postoperative Pulmonary Complications in Elderly Patients
An observational study of Postoperative Pulmonary Complications, run by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.
Trial summary
Although a number of clinical predictive models were developed to predict postoperative pulmonary complications, few predictive models have been used in elderly patients. In this study, the researchers aim to compare different algorithms to predict postoperative pulmonary complications in elderly patients and to… Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Postoperative Pulmonary Complications
- How many people
- 10,000 participants
- Where
- No sites listed yet
- Study dates
- Jan 2023to Mar 2023
- 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 65 years and older
- All sexes
- Older adult
Study population: older patients received general anesthesia in Wuhan Union Hospital from January 1, 2014 to December 31, 2019.
Who may be able to join
- Age 65 years or older
- receiving invasive ventilation during general anesthesia for surgery
Who cannot join
- preoperative mechanical ventilation
- procedures related to a previous surgical complication
- a second operation after surgery
- organ transplantation
- discharged within 24 hours after surgery
- cardiac surgery
Trial locations and contacts
No sites are listed yet.
About this study
Although a number of clinical predictive models were developed to predict postoperative pulmonary complications, few predictive models have been used in elderly patients. In this study, the researchers aim to compare different algorithms to predict postoperative pulmonary complications in elderly patients and to assess the risk of postoperative pulmonary complications in elderly patients.
Read the detailed description
Postoperative pulmonary complications occur frequently, which is an important cause of death and morbidity. Age has been an important predictor of postoperative pulmonary complications. As the world's population ages, more and more older people are undergoing surgery as indications for surgery expand. In order to better assess the risk of postoperative pulmonary complications in elderly patients, we plan to use database information and different algorithms such as logistic regression, random forest, and other algorithms to build models respectively and evaluate the effects of the models.
- Conditions
- Postoperative Pulmonary 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 |
|---|---|---|
| Training set | The whole cohort is randomly assigned to a training cohort and validation cohort. | |
| validation set | The whole cohort is randomly assigned to a training cohort and validation cohort. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Postoperative pulmonary complications
Measured: within one week after surgery
Secondary outcomes (1)
Postoperative pulmonary complications
Measured: 30 days after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Jan 2023
- Study startJan 2023 (estimated)
- Primary completionJan 2023 (estimated)
- Study completionMar 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Postoperative Pulmonary ComplicationsStudies 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
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05671939
- Sponsor's protocol ID
- PPC20221201
- Status last verified
- Dec 2022
- First submitted
- 2 Jan 2023
- Last updated
- 5 Jan 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 5 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Different Algorithm Models to Predict Postoperative Pulmonary Complications in Elderly Patients
- ClinicalTrials.gov ID
- NCT05671939
- Acronym / sponsor ID
- PPC20221201
- Conditions
- Postoperative Pulmonary Complications
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyUniversity, hospital or other
- Study start
- Jan 2023 (estimated)
- Primary completion
- Jan 2023 (estimated)
- Study completion
- Mar 2023 (estimated)
- First posted
- 5 Jan 2023 (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.
Although a number of clinical predictive models were developed to predict postoperative pulmonary complications, few predictive models have been used in elderly patients. In this study, the researchers aim to compare different algorithms to predict postoperative pulmonary complications in elderly patients and to assess the risk of postoperative pulmonary complications in elderly patients.
Detailed description
Postoperative pulmonary complications occur frequently, which is an important cause of death and morbidity. Age has been an important predictor of postoperative pulmonary complications. As the world's population ages, more and more older people are undergoing surgery as indications for surgery expand. In order to better assess the risk of postoperative pulmonary complications in elderly patients, we plan to use database information and different algorithms such as logistic regression, random forest, and other algorithms to build models respectively and evaluate the effects of the models.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Training set | – | –The whole cohort is randomly assigned to a training cohort and validation cohort. |
| validation set | – | –The whole cohort is randomly assigned to a training cohort and validation cohort. |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Age groups
- Older adult
- Study population
- older patients received general anesthesia in Wuhan Union Hospital from January 1, 2014 to December 31, 2019.
Key inclusion criteria (2 listed)
- Age 65 years or older
- receiving invasive ventilation during general anesthesia for surgery
Key exclusion criteria (6 listed)
- preoperative mechanical ventilation
- procedures related to a previous surgical complication
- a second operation after surgery
- organ transplantation
- discharged within 24 hours after surgery
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
Postoperative pulmonary complications
Time frame: within one week after surgery
1 secondary outcome
Postoperative pulmonary complications
Time frame: 30 days after surgery
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Jan 2023.
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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.
Questions about this trial
What is this clinical trial studying?
An observational study of Postoperative Pulmonary Complications, run by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.
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 2 inclusion and 6 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 5 Jan 2023. Status can change between updates, so confirm with the study contact before making plans.
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 Qingping Wu, PhD (13971605283, wqp1968@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Postoperative pulmonary complications (time frame: within one week after surgery). 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 5 Jan 2023.