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Elderly Patients Surgical Site Infection Phenotypes Identification

NCT06612177 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 42532

Last updated 2024-10-09

No results posted yet for this study

Summary

This study utilizes Latent Class Analysis (LCA) to identify phenotypes of Surgical Site Infection (SSI) in elderly patients following non-cardiac surgery. By analyzing data from two large cohorts, the research establishes a predictive model that uncovers independent risk factors for SSI, including age, hyperlipidemia, and surgical characteristics. The model, with AUCs ranging from 0.753 to 0.791 across cohorts, offers a calibrated prediction of SSI risk. Furthermore, LCA delineates four distinct SSI subphenotypes, highlighting a critical subgroup with a higher infection rate. This subgroup presents a complex interplay of risk factors, indicating the need for tailored preventive strategies. The study's findings contribute to a nuanced understanding of SSI in elderly surgical patients and pave the way for more targeted infection control measures.

Conditions

  • Postoperative Infection
  • Geriatrics
  • Prediction
  • Surgical Site Infection

Sponsors & Collaborators

  • Weidong Mi

    lead OTHER

Eligibility

Min Age
65 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-01-01
Primary Completion
2023-12-30
Completion
2024-06-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06612177 on ClinicalTrials.gov