Geriatrics, Postoperative Infection, Prediction
Conditions
Keywords
postoperative infectious complications, elderly patients, retrospective study, prediction model, calculator
Brief summary
The investigators established a first-ever convenient scoring system for clinicians to assess the risk of Postoperative infectious complications (PICs) for elderly patients. Our scoring system can aid in the early detection of potential risks for postoperative infections. Higher-score patients were more likely to experience postoperative infections.
Detailed description
Background: Postoperative infectious complications (PICs) are related to increased morbidity, mortality, and costs, especially in elderly patients. However, published prediction models of PICs are rarely based on elderly patients. Objective: The study wanted to identify practical and valuable variables that could be used to predict postoperative infections and establish a convenient scoring system for clinicians to assess the risk of such conditions in elderly patients. Methods: Data from 2 population-based cohorts of elderly patients undergoing non-cardiac and non-neurology surgery were used to derive and validate multivariable logistic regression models. The risk prediction models were derived from 37230 patients hospitalized in the First Medical Center of the Chinese PLA General Hospital (January 2012 - August 2018). The risk prediction models were externally validated with data from a cohort of 10252 patients hospitalized in Henan Provincial People's Hospital (November 2014 to May 2022).
Interventions
None listed
Sponsors
Study design
Eligibility
Inclusion criteria
1. age ≥ 65 years and 2. patients undergoing surgery with anesthesia.
Exclusion criteria
1. patients undergoing neurosurgery or cardiac surgery, 2. preoperative infectious diseases, and 3. patients with ≥50% of data missing.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Postoperative Infectious Complications Calculator for Elderly Patients | January 2012 - August 2018 | A Derivation and External Validation of Prediction Models based on two centers large sample |
Countries
China