Postoperative Infectious Pneumonia in Cardiothoracic Surgery: A Systematic Review and Meta-Analysis

Search strategy

A thorough and comprehensive literature search investigation was meticulously carried out across three essential and widely recognized databases: PubMed, Embase, and Scopus, encompassing a broad and diverse range of publications spanning from January 2021 up to December 2023. The final search was conducted on December 31, 2023. The following detailed and carefully crafted Boolean search string was effectively and efficiently utilized:

Only studies that were published in the English language and specifically involved human participants were included in our comprehensive analysis. This careful selection process was undertaken to ensure the relevance and applicability of the findings. In addition to this, we conducted a thorough manual review of the references listed in the studies that were ultimately included in our analysis. This meticulous approach allowed us to identify any additional articles that may be eligible for consideration in our research, thereby enriching the overall scope and depth of our investigation. We also consulted ClinicalTrials.gov and WHO ICTRP in January 2024 to identify any unpublished or ongoing studies. By carefully assessing the references and external registries, we aimed to capture a wider range of studies that could further support and enhance our findings.

Eligibility criteria

Studies were included if they:

Included studies were grouped by surgical type: CABG, valve surgery, and thoracic oncologic procedures for stratified synthesis of incidence and risk factors.

Studies were excluded if they:

Study selection

A total of 1,142 records were initially retrieved through database searches. After removing 117 duplicate entries, 1,025 records remained for title and abstract screening. Following this step, 67 full-text articles were assessed for eligibility. Of these, 6 studies met all predefined inclusion criteria and were ultimately included in the final meta-analysis. The process of study selection is illustrated in the PRISMA 2020 flow diagram ( Figure 1), which illustrates each phase of study identification, screening, eligibility assessment, and final inclusion.

Figure 1. PRISMA 2020 flow diagram of study selection process.

To minimize reporting bias, studies were excluded if they lacked clear definitions of postoperative infectious pneumonia (PIP) or reported outcomes inconsistently. A dual-reviewer screening approach was employed for both title/abstract and full-text phases. Discrepancies were resolved through consensus between reviewers to ensure methodological rigor and consistency during the selection and data extraction process. Automation tools were not used in the selection process.

Data extraction and quality assessment

Two independent reviewers performed data extraction using a standardized template. Extracted variables included: study author, year, country, surgical type, sample size, PIP incidence, and reported risk factors (with ORs and 95% CIs). Discrepancies were resolved by discussion or by a third reviewer.

Additional data items extracted included comorbidities (e.g., COPD, diabetes), surgical risk scores (when available), diagnostic definitions of PIP, use of CPB, ICU length of stay, and mechanical ventilation duration. When means and standard deviations were not available, medians and interquartile ranges were converted using Wan et al. (2014) methods.

Study quality was evaluated using the Newcastle-Ottawa Scale (NOS). Studies scoring 7 points or higher were classified as high-quality and were included in the quantitative synthesis. All studies achieved NOS scores ≥7.

Statistical analysis

A random-effects model (DerSimonian and Laird method) was used to calculate pooled odds ratios (ORs) and 95% confidence intervals (CIs), accounting for inter-study heterogeneity. The I² statistic was used to assess heterogeneity, with values >50% indicating moderate-to-high heterogeneity. We also performed sensitivity analyses, including leave-one-out tests, and compared fixed-effects versus random-effects models to assess robustness. Funnel plots were visually assessed for publication bias.

Study characteristics

Six studies, encompassing a total of 4,392 patients, were included in the final meta-analysis. The majority of studies were retrospective cohort analyses conducted across Asia, Europe, and North America. All studies applied clinically defined criteria for diagnosing postoperative infectious pneumonia (PIP) and provided extractable odds ratios (ORs) with 95% confidence intervals (CIs). Each study achieved a Newcastle-Ottawa Scale (NOS) score of ≥7, indicating high methodological quality, and no studies were excluded due to risk of bias. The incidence of postoperative infectious pneumonia (PIP) varied across studies, ranging from 12.3% to 17.5%, with the highest reported in patients undergoing esophageal cancer surgery by Raftery NB et al., a summary of study-level characteristics is presented in ( Table 1).

The incidence rates of PIP reported across the included studies, along with their respective 95% confidence intervals, are displayed in ( Figure 2). Each study’s point estimate is represented by a solid dot, with horizontal lines denoting the confidence intervals, reflecting statistical uncertainty. A vertical dashed red line represents the pooled mean incidence of 14.6%, serving as a comparative benchmark. Studies positioned to the right of the pooled mean indicate higher-than-average PIP incidence, while those to the left suggest lower incidence. The variability in the width of the confidence intervals reflects differences in sample size and cohort homogeneity, with narrower intervals suggesting greater statistical precision.

Figure 2. Forest plot of PIP incidence rates from six meta-analysis studies with 95% confidence intervals.

Pooled incidence of postoperative infectious pneumonia

Stratified by surgical procedure, the incidence of postoperative infectious pneumonia (PIP) was 13.5% following coronary artery bypass grafting (CABG), 15.8% after heart valve surgeries, and 17.2% after thoracic oncologic procedures such as esophagectomy.

Across the six studies, the pooled incidence of PIP following cardiothoracic surgery was 14.8% (95% CI, 10.6%–19.2%). The highest incidence was observed among patients undergoing thoracic oncologic surgeries, likely due to longer operative durations, extensive pulmonary manipulation, and higher baseline respiratory vulnerability. In contrast, lower incidence rates were reported following CABG and valve surgeries, where the extent of respiratory insult is generally reduced, allowing for more favorable postoperative recovery.

The incidence rates of postoperative infectious pneumonia (PIP) across the included studies are summarized in ( Figure 3), which presents a forest plot displaying each study’s point estimate and its 95% confidence interval (CI). The pooled mean incidence was 14.6%, indicated by a vertical red dashed line. Studies to the right of this benchmark, such as Wang D et al. (16.5%) and Raftery NB et al. (17.5%), reported above-average rates, potentially reflecting higher-risk populations or more complex thoracic procedures. In contrast, lower incidence rates around 12.3% were observed in studies like those by Fischer MO et al. and Duchnowski P et al., possibly attributable to more effective perioperative respiratory strategies or lower baseline risks. The width of the confidence intervals highlights the statistical precision, with narrower intervals—such as in Wang DS et al. and Wang D et al.—suggesting larger sample sizes and more homogeneous cohorts, while wider intervals, as seen in Raftery NB et al., reflect smaller or more heterogeneous populations.

Figure 3. Forest plot summarizing pooled odds ratios and 95% confidence intervals for major risk factors associated with postoperative infectious pneumonia (PIP).

Procedure-specific incidence rates are further detailed in ( Figure 4), revealing notable variability by surgical type: thoracic oncology procedures had the highest PIP incidence (17.2%), followed by valve surgery (15.8%) and coronary artery bypass grafting (CABG) at 13.5%. These variations underscore the influence of surgical complexity and patient vulnerability on infection risk, emphasizing the necessity for tailored perioperative strategies to mitigate PIP incidence based on procedural and patient-specific risk factors.

Figure 4. Bar chart illustrating incidence rates of postoperative infectious pneumonia stratified by type of cardiothoracic surgery.

Risk factors for postoperative infectious pneumonia

The six studies included in this meta-analysis identified multiple perioperative risk factors associated with the development of postoperative infectious pneumonia (PIP), several of which are modifiable.

Notably, the most common and significant predictors consistently reported across all studies were:

These perioperative factors were found to significantly increase the risk of developing postoperative infectious pneumonia. A detailed summary of these associations is presented in ( Table 2), which displays the pooled ORs with their 95% CIs.

Across the multiple studies, prolonged mechanical ventilation, advanced age, and pre-existing pulmonary comorbidities consistently emerged as the most significant predictors of PIP following cardiothoracic surgery. These factors were identified as critical determinants of postoperative outcomes, highlighting the complex interplay between baseline patient characteristics, intraoperative management, and postoperative infection risk.

The relative contribution of each of these key risk factors to the overall incidence of PIP is visually illustrated in ( Figure 5), which depicts the pooled effect sizes across the included studies. This graphical representation underscores the clinical impact of these variables and their importance in guiding perioperative risk stratification and targeted prevention strategies.

Figure 5. Pie chart representing the relative contribution of each key perioperative risk factor to overall postoperative pneumonia incidence.

Preventive strategies and risk factors for postoperative pneumonia in cardiothoracic surgery

Among the perioperative predictors identified in this meta-analysis, the most significant contributors to postoperative infectious pneumonia (PIP) were prolonged mechanical ventilation, advanced age, and pre-existing pulmonary disease, particularly chronic obstructive pulmonary disease (COPD). These risk factors were consistently reported across the included studies and demonstrated strong associations with increased PIP incidence. Their relative contribution to postoperative pneumonia risk is graphically represented in ( Figure 6), highlighting their weighted impact within the pooled analysis. This visualization reinforces the need for targeted perioperative strategies to address these modifiable and non-modifiable risk elements in patients undergoing cardiothoracic surgery.

Figure 6. Clinical pathway diagram integrating key preventive strategies.

To guide preventive strategies in clinical practice, a comprehensive clinical pathway diagram has been developed. This pathway emphasizes the management of modifiable risk factors through:

This integrated, multidisciplinary approach aims to improve perioperative care, reduce postoperative complication rates, and ultimately enhance patient outcomes. It highlights the critical role of coordinated teamwork among surgeons, anesthesiologists, intensivists, and respiratory therapists.

From a broader clinical and epidemiological perspective, despite variations in methodologies and regional practices, all six included studies consistently reported a high incidence of postoperative pneumonia. This finding reinforces the substantial burden this complication poses in cardiothoracic surgical populations and underscores the urgent need for standardized, evidence-based prevention protocols, including:

Adoption of these measures is essential to improving surgical outcomes and reducing the incidence of postoperative infectious pneumonia following cardiothoracic surgery.

Statistical analysis, heterogeneity, and risk of bias assessment

A random-effects model (DerSimonian and Laird) was employed to accommodate anticipated clinical and methodological heterogeneity across the included studies. The overall heterogeneity, assessed using the I² statistic, was 46%, indicating moderate variability. This heterogeneity in PIP incidence—ranging from 12.3% to 17.5%—reflects differences in patient populations, surgical complexity, and perioperative care practices across institutions. Key contributors to this heterogeneity likely include variations in surgical type (e.g., valve surgery vs. thoracic oncology), differences in institutional infection control protocols, perioperative ventilation strategies, and inconsistencies in pneumonia definitions (e.g., clinical vs. microbiological criteria).

Stratified subgroup analyses revealed higher incidence rates in patients undergoing thoracic oncologic procedures (17.2%) compared to CABG (13.5%) and valve surgery (15.8%), aligning with greater pulmonary manipulation and longer operative times. Prospective studies (e.g., Fischer, Wang D) demonstrated narrower confidence intervals, suggesting stronger methodological control and reduced bias.

No significant publication bias was detected, as indicated by the visual symmetry of the funnel plot ( Figure 7). All six included studies underwent independent quality assessment using the Newcastle-Ottawa Scale (NOS). Each study achieved a score of ≥7, reflecting high methodological rigor. The risk of bias was assessed using domain-specific criteria:

Data extraction was independently conducted by two reviewers, with complete agreement reached on all variables. Leave-one-out sensitivity analyses, comparison of fixed- vs. random-effects models, and exclusion of studies without microbiological confirmation confirmed the robustness of results. Furthermore, the uniform reporting of odds ratios (ORs) and the consistent application of standardized diagnostic criteria for PIP across studies further reinforce the internal validity and reproducibility of the pooled results. This methodological consistency contributes to the strength and reliability of the findings across a range of cardiothoracic surgical populations.

However, despite the high NOS scores, several limitations remain:

In summary, the moderate heterogeneity was anticipated and partially explained through subgroup and narrative analyses. Nevertheless, the consistency in effect direction and magnitude across studies strengthens confidence in the findings and their applicability to diverse cardiothoracic surgical populations.