Different Algorithm Models to Predict Postoperative Pneumonia in Elderly Patients
Study Details
Study Description
Brief Summary
The researchers aim to compare different algorithms to predict postoperative pneumonia in elderly patients and to assess the risk of pneumonia in elderly patients.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
Postoperative pneumonia is a common complication that increases the mortality and length of older patients. In order to better assess the risk of postoperative pneumonia in elderly patients, we plan to use database information and different algorithms, such as logistic regression, random forest, and other algorithms respectively to build models and evaluate the effects of the models.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Training set The whole cohort is randomly assigned to a training cohort and validation cohort. |
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validation set The whole cohort is randomly assigned to a training cohort and validation cohort. |
Outcome Measures
Primary Outcome Measures
- Postoperative pulmonary complications [within one week after surgery]
Secondary Outcome Measures
- Postoperative pulmonary complications [30 days after surgery]
Eligibility Criteria
Criteria
Inclusion Criteria:
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Age 65 years or older
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receiving invasive ventilation during general anesthesia for surgery
Exclusion Criteria:
-
preoperative mechanical ventilation
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procedures related to a previous surgical complication
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a second operation after surgery
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organ transplantation
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discharged within 24 hours after surgery
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cardiac and thoracic surgery
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Wuhan Union Hospital, China
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- PPC2021012