Pneumonia After Cardiovascular Surgery With Artificial Intelligence

Hospital-acquired Pneumonia After Cardiovascular Surgery (CS): the Prediction and Assessment of Long-term Cardiovascular and Pulmonary Outcomes With Artificial Intelligence (AI) - (PNEUMONIA-CS-AI)

This multicenter, prospective, observational study aims to address two primary objectives.

The first objective is to demonstrate that hospital-acquired pneumonia (nosocomial pneumonia) following cardiac surgery can be predicted using artificial intelligence (AI), and to develop a personalized risk calculator for its development.

The second objective is to demonstrate that hospital-acquired pneumonia can serve as a risk factor for a 1-year composite cardiovascular and pulmonary outcome after cardiac surgery, and to develop a personalized risk calculator for this composite outcome.

The composite outcome will include the occurrence of any of the following events:

  • Respiratory death
  • Hospitalization for respiratory diseases
  • Development of oxygen dependence
  • New-onset asthma, COPD, or interstitial lung disease
  • Initiation or intensification of bronchodilator or corticosteroid therapy
  • Cardiovascular death
  • Acute myocardial infarction
  • Unstable angina
  • Myocardial revascularization
  • Acute ischemic stroke
  • Transient ischemic attack
  • Acute heart failure
  • Hospitalization for decompensated heart failure
  • New-onset atrial fibrillation or ventricular tachycardia
  • Initiation or intensification of antiarrhythmic therapy Both objectives will be addressed using artificial intelligence technologies applied during the data analysis phase.

This is a non-interventional study. Patient evaluation and treatment are conducted in strict accordance with approved standards of medical care for the respective conditions. No experimental or unregistered (not approved for use in the Russian Federation) medical or diagnostic procedures will be performed during this study.

Study Overview

Status

Recruiting

Detailed Description

Hospital-acquired pneumonia (nosocomial pneumonia) is one of the most common complications following cardiac and/or vascular surgery, with an incidence reaching up to 37% after certain types of procedures. This complication is associated with prolonged hospital stays, increased healthcare costs, and higher mortality rates both during hospitalization and within 5 years post-surgery. To determine the necessity of implementing additional personalized preventive measures against pneumonia, it is clinically valuable to assess the probability of its development in each individual patient. A medical risk calculator, which enables the calculation of an individual's risk of developing pneumonia, can serve as a supportive tool for clinical decision-making.

This is an observational study. Patient evaluation and treatment will be conducted in strict accordance with approved standards of medical care for the respective conditions. No experimental or unregistered (not approved for use) medical or diagnostic methods will be utilized in this study.

The study involves the systematic collection of data from the medical records of patients who undergo cardiac and/or vascular surgery during their current hospitalization. These data will be analyzed using artificial intelligence (AI) technologies, including machine learning methods such as gradient boosting, random forest, neural networks, Bayesian networks, and others.

This is a multicenter study involving three participating centers: Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk State University, and the Federal State Budgetary Institution Research Institute for Complex Issues of Cardiovascular Diseases.

In phase 1, data will be collected from at least 400 patients undergoing cardiac surgery at a single center (Tomsk National Research Medical Center of the Russian Academy of Sciences). An anonymized database will be created, including the following parameters:

  • Demographic and anthropometric characteristics (age, sex, height, weight, body mass index)
  • Smoking status, including duration and intensity (pack-years)
  • Comorbidities, including chronic obstructive pulmonary disease (COPD), diabetes mellitus, chronic kidney disease (CKD), prior myocardial infarction, and atrial fibrillation
  • Preoperative left ventricular ejection fraction (LVEF)
  • Preoperative pulmonary function test (PFT) parameters
  • Preoperative length of hospital stay
  • Intraoperative variables, including type of surgery, use and duration of cardiopulmonary bypass (CPB), volume of blood loss, blood component transfusion, duration of mechanical ventilation, and other relevant surgical details
  • Perioperative laboratory data, including hemoglobin, red blood cell (RBC) count, white blood cell (WBC) count, platelet count, serum creatinine, and creatine phosphokinase (CPK) Subsequently, the occurrence or non-occurrence of hospital-acquired pneumonia will be documented within 30 days post-surgery. Additionally, other relevant clinical data regarding the course of the postoperative period will be collected.

Phase 2 will be conducted jointly by Tomsk National Research Medical Center of the Russian Academy of Sciences and Tomsk State University, focusing on data processing and analysis. This phase will include:

  • Data integrity assessment and quality control
  • Missing data imputation (handling of missing values)
  • Development of predictive models for hospital-acquired pneumonia using multivariate binary logistic regression (SPSS version 26.0) and machine learning algorithms, including Bayesian networks, decision trees, random forest, gradient boosting, and recurrent neural networks (RNN).

Phase 3, also performed by Tomsk National Research Medical Center of the Russian Academy of Sciences and Tomsk State University, involves the evaluation and comparison of the developed predictive models. The models will be compared based on key performance metrics:

  • Accuracy, sensitivity, and specificity
  • Interpretability
  • Robustness to overfitting and data incompleteness Based on this evaluation, the preferred predictive model for hospital-acquired pneumonia demonstrating optimal performance characteristics will be selected.

Phase 4 (conducted by Tomsk National Research Medical Center of the Russian Academy of Sciences and Tomsk State University) will focus on the development of a universal medical risk calculator. This tool will determine the individual probability of developing hospital-acquired pneumonia following any type of cardiac and/or vascular surgical intervention. The calculator will be constructed by selecting key predictors and evaluating the feature weights (coefficients) derived from the best-performing predictive model identified in Phase 3.

Phase 5 will involve the internal validation of the developed risk calculator. This phase will consist of the following steps:

  • Prospective enrollment of an additional 200 patients into the observational study at the primary center (Tomsk National Research Medical Center of the Russian Academy of Sciences).
  • Preoperative assessment of the individual risk (probability) of hospital-acquired pneumonia for each patient using the newly developed calculator.
  • Surgical intervention followed by a 30-day postoperative observation period.
  • Calibration and performance analysis by comparing the pre-test (predicted) probability of pneumonia with the actual observed postoperative outcomes.

Phase 6 will involve the external validation of the developed medical risk calculator across 1 to 3 cardiovascular surgery centers. Each participating center will conduct an evaluation identical to Phase 5, prospectively enrolling data from at least 100 patients. Initially, the Federal State Budgetary Institution Research Institute for Complex Issues of Cardiovascular Diseases will join the study, with the potential inclusion of additional medical centers at a later stage.

Phase 7 (conducted by Tomsk National Research Medical Center of the Russian Academy of Sciences and the Federal State Budgetary Institution Research Institute for Complex Issues of Cardiovascular Diseases) aims to evaluate the impact of hospital-acquired pneumonia on the development of clinical outcomes within 12 months post-cardiac surgery. These outcomes include:

  • Primary composite cardiovascular and pulmonary outcome
  • Secondary composite pulmonary outcome
  • Secondary composite cardiovascular outcome

This phase will be conducted by gathering follow-up data from enrolled patients or their next of kin via in-person visits, telephone interviews, medical record reviews, or centralized electronic healthcare registries. Data will be collected on whether patients experienced any of the following events within 12 months after surgery:

  • Pulmonary / Respiratory Events: Respiratory death, hospitalization for respiratory diseases, development of oxygen dependence, new-onset asthma, COPD, or interstitial lung disease, and initiation or intensification of bronchodilator or corticosteroid therapy.
  • Cardiovascular Events: Cardiovascular death, acute myocardial infarction, unstable angina, myocardial revascularization, acute ischemic stroke, transient ischemic attack (TIA), acute heart failure, hospitalization for decompensated heart failure, new-onset atrial fibrillation or ventricular tachycardia, and initiation or intensification of antiarrhythmic therapy.

Phase 8 will be conducted by Tomsk National Research Medical Center of the Russian Academy of Sciences and Tomsk State University, focusing on the processing and analysis of the 12-month follow-up data. This final phase will include:

  • Data integrity assessment and quality control.
  • Missing data imputation for the long-term follow-up variables.
  • Comparative analysis of the incidence of cardiovascular and pulmonary events within 12 months post-surgery between patients who developed hospital-acquired pneumonia during the early postoperative period and those who did not.
  • Development of predictive models for the study's composite endpoints, utilizing both standard statistical methods and artificial intelligence (AI) / machine learning algorithms.

Study Type

Observational

Enrollment (Estimated)

700

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Alla A. Boshchenko, MD, PhD, DSc
  • Phone Number: + 7 (3822)-909055
  • Email: bosh@cardio-tomsk.ru

Study Contact Backup

Study Locations

      • Tomsk, Russia
        • Recruiting
        • Cardiology Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Patients of 18 years and older after cardiac and/or vascular surgical intervention during the current hospitalization

Description

Inclusion Criteria:

  • Age ≥ 18 years;
  • Cardiac and/or vascular surgical intervention during the current hospitalization;
  • Signed informed consent from the patient for the use of their anonymized data for scientific purposes.

Exclusion Criteria:

  • Use of systemic antibacterial drugs within 30 days prior to the surgical intervention;
  • Prescription of systemic antibacterial drugs during the hospitalization period for any indication other than hospital-acquired pneumonia;
  • HIV infection.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Patients after cardiovascular surgery
Patients of 18 years and older, after cardiac and/or vascular surgical intervention during the current hospitalization, who signed informed consent for the use of their anonymized data for scientific purposes
Not applicable- observational study

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Hospital acquired pneumonia
Time Frame: Within 30 days post-surgery
Occurrence of hospital-acquired pneumonia
Within 30 days post-surgery
Composite cardiovascular and pulmonary endpoint
Time Frame: 12 months post-surgery
Occurrence of the composite cardiovascular and pulmonary endpoint
12 months post-surgery

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Non-pneumonia postoperative complications
Time Frame: Within 30 days post-surgery
Incidence of non-pneumonia postoperative complications (surgical site infections, cardiac events, etc.)
Within 30 days post-surgery
Composite Pulmonary Outcome
Time Frame: 12 months post-surgery

Incidence of the Composite Pulmonary Outcome:

Respiratory death; Hospitalization due to respiratory diseases; New-onset oxygen dependence; New-onset asthma, chronic obstructive pulmonary disease (COPD), or interstitial lung disease (ILD); Initiation or intensification of bronchodilator or corticosteroid therapy

12 months post-surgery
Composite Cardiovascular Outcome
Time Frame: 12 months post-surgery

Incidence of the Composite Cardiovascular Outcome:

Cardiovascular death; Acute myocardial infarction; Unstable angina; Myocardial revascularization; Acute ischemic stroke (acute cerebrovascular accident); Transient ischemic attack (TIA); Acute heart failure; Hospitalization for decompensated heart failure; New-onset atrial fibrillation or ventricular tachycardia; Initiation or intensification of antiarrhythmic therapy

12 months post-surgery

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Study Director: Alla A. Boshchenko, MD, PhD, DSc, Cardiology Research Institute of Tomsk NRMC
  • Principal Investigator: Tatiana P. Kalashnikova, MD, PhD, Cardiology Research Institute of Tomsk NRMC

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

July 29, 2026

Primary Completion (Estimated)

October 30, 2026

Study Completion (Estimated)

September 30, 2028

Study Registration Dates

First Submitted

July 29, 2026

First Submitted That Met QC Criteria

July 29, 2026

First Posted (Actual)

August 4, 2026

Study Record Updates

Last Update Posted (Actual)

August 11, 2026

Last Update Submitted That Met QC Criteria

August 6, 2026

Last Verified

August 1, 2026

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Subscribe