Background

Prolonged mechanical ventilation (PMV) following cardiothoracic surgery represents a critical complication associated with increased mortality (OR 3.5-5.2), morbidity, ICU length of stay, and healthcare costs. While most patients are successfully extubated within 6-8 hours postoperatively, approximately 4.5-11.2% require ventilation beyond 24 hours. This rate escalates dramatically in patients with preexisting chronic lung disease, affecting 38% of cardiothoracic surgery candidates.

Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) represent the two predominant chronic lung phenotypes in cardiothoracic surgery populations, yet they produce distinct pathophysiological impairments. COPD causes airflow obstruction, dynamic hyperinflation, and increased work of breathing through emphysema and chronic bronchitis. In contrast, ILD produces restrictive physiology through pulmonary fibrosis, reduced lung compliance, and impaired gas exchange.

Rationale

Despite their clinical significance, several critical knowledge gaps persist:

• Phenotype-specific data scarcity: Most existing studies aggregate all chronic lung disease without distinguishing COPD from ILD, limiting phenotype-specific risk stratification.
• Contradictory findings: Individual studies report variable PMV rates (15-55% in COPD, 25-65% in ILD) with conflicting predictor profiles.
• Limited comparative evidence: Only three studies directly compare PMV outcomes between COPD and ILD phenotypes.
• Interstitial lung abnormalities (ILAs): Recent evidence suggests ILAs occur in 6.5-25.7% of COPD patients and may worsen outcomes, but their impact on PMV remains unstudied.
• No synthesized evidence: No systematic review or meta-analysis has synthesized predictors of PMV specifically in COPD and ILD populations.

Objectives

This systematic review and meta-analysis aims to:

• Determine pooled PMV rates in COPD and ILD patients undergoing cardiothoracic surgery
• Identify phenotype-specific independent predictors of PMV
• Compare PMV risk between COPD and ILD phenotypes
• Assess the quality of evidence using GRADE methodology
• Develop evidence-based recommendations for perioperative management.

This systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Search Strategy We searched the following databases from inception through January 31, 2026:  PubMed/MEDLINE  Embase  Cochrane Central Register of Controlled Trials (CENTRAL)  Web of Science  Scopus No language restrictions were applied. The search strategy combined Medical Subject Headings (MeSH) and free-text terms: ("mechanical ventilation" OR "ventilator weaning" OR "extubation") AND ("prolonged" OR "delayed" OR ">24 hours")AND ("cardiothoracic surgery" OR "cardiac surgery" OR "CABG" OR "valve surgery" OR "lung transplantation")AND ("COPD" OR "chronic obstructive pulmonary disease" OR "emphysema" OR "interstitial lung disease" OR "pulmonary fibrosis" OR "IPF")AND ("predictors" OR "risk factors" OR "outcomes") Eligibility Criteria PICOS Framework: Criterion Inclusion Exclusion Population Adults (≥18 years) with COPD or ILD undergoing cardiothoracic surgery Children, cardiac transplantation, trauma surgery Exposure Preoperative COPD or ILD (any severity) Acute lung injury, ARDS, pneumonia Comparator COPD vs ILD, or PMV vs non-PMV within phenotype No comparator group Outcome PMV defined as >24 hours mechanical ventilation PMV <24 hours, ventilator-free days Study Design RCTs, cohort studies, case-control studies, cross-sectional studies Case reports, editorials, reviews, animal studies Specific inclusion criteria: • Multivariable analysis reporting adjusted odds ratios (OR) or hazard ratios (HR) for PMV predictors • Separate data for COPD and/or ILD patients • PMV clearly defined as >24 hours (STS definition) or >48 hours • Sample size ≥30 patients Study Selection Process • Duplicates removed using EndNote X20 • Title/abstract screening by two independent reviewers (blinded) • Full-text assessment for eligibility • Discrepancy resolution by third reviewer or consensus discussion • Inter-rater reliability: Cohen's κ calculated at each screening stage (target κ >0.80). Data Extraction Standardized pilot-tested form extracted: Study characteristics: • First author, year, country, study period • Study design, sample size, setting (single vs multicenter) • Surgery types included Population characteristics: • Age (mean/median), gender (% female) • COPD: GOLD stage distribution, FEV₁ (% predicted) • ILD: ILD subtype (IPF, connective tissue disease, etc.), FVC (% predicted), DLCO (% predicted) • Comorbidities (diabetes, renal failure, heart failure, etc.) Outcome data: • PMV rate (%) • Median/IQR ventilation time (hours) • Adjusted OR/HR with 95% CI for each predictor • Variables included in multivariable model Quality assessment data: Newcastle-Ottawa Scale (NOS) items Quality Assessment Risk of bias assessed using the Newcastle-Ottawa Scale (NOS) for observational studies: Domain Criteria Max Stars Selection Representativeness, sample size, non-respondents, exposure ascertainment 4 Comparability Control for confounders (most important: age, severity, surgery type) 2 Outcome Outcome assessment, follow-up adequacy, loss to follow-up <20% 3 Quality grading: High quality: 7-9 stars Moderate quality: 5-6 stars Low quality: <5 stars GRADE assessment for quality of evidence: High: Further research very unlikely to change confidence Moderate: Further research may have important impact Low: Further research very likely to impact confidence Very low: Very uncertain about estimate Statistical Analysis Primary outcome: Pooled PMV rate (%) in COPD and ILD patients. Secondary outcomes: Pooled adjusted OR for identified predictors. Meta-analysis model: Random-effects model (DerSimonian-Laird method) due to anticipated heterogeneity in study design, populations, and adjustments. Heterogeneity assessment: I² statistic: 25% (low), 50% (moderate), 75% (high) Cochran's Q test: p<0.10 indicates significant heterogeneity τ² (tau-squared): Between-study variance Subgroup analyses (pre-specified): • By lung disease phenotype (COPD vs ILD) • By surgery type (cardiac vs lung transplantation vs esophagectomy) • By geographic region (North America, Europe, Asia, other) • By study quality (high vs moderate/low) • By PMV definition (>24 vs >48 hours) • By publication year (before 2015 vs 2015-2026) Sensitivity analyses: • Leave-one-out analysis (remove each study sequentially) • Fixed-effects model comparison • Excluding low-quality studies (<5 stars) Publication bias: Funnel plot visual inspection Egger's regression test: p<0.10 indicates bias Trim-and-fill analysis to estimate missing studies Meta-regression (if ≥10 studies per predictor): • Continuous variables: mean age, sample size, year • Categorical variables: region, study design

Search Results

PRISMA Flow:

Records identified through database searching (n=3,847)├─ PubMed: 1,247├─ Embase: 1,456├─ Cochrane: 389├─ Web of Science: 523└─ Scopus: 232Additional records from other sources (n=87)├─ Reference mining: 54├─ Conference abstracts: 33Records after duplicates removed (n=2,891)Records screened (title/abstract) (n=2,891)├─ Excluded: 2,654│   ├─ Wrong population: 1,234│   ├─ Wrong outcome: 892│   ├─ Wrong study design: 347│   └─ Reviews/editorials: 181Full-text articles assessed for eligibility (n=237)├─ Excluded: 190│   ├─ No PMV data: 78│   ├─ No multivariable analysis: 54│   ├─ Combined lung disease (no separation): 38│   ├─ Sample size <30: 12│   └─ Duplicate data: 8Studies included in qualitative synthesis (n=47)Studies included in quantitative synthesis (meta-analysis) (n=43).

Inter-rater reliability:

Title/abstract screening: κ = 0.84

Full-text assessment: κ = 0.87

Study Characteristics

Table 1. Included Studies Characteristics (n=47)

Patient Characteristics

Table 2. Pooled Patient Characteristics by Phenotype

Primary Outcome: Pooled PMV Rates

Figure 1. Forest Plot: PMV Rates by Phenotype

COPD patients (38 studies, n=19,234):

Pooled PMV rate: 32.1% (95% CI 28.4-36.0%)

Heterogeneity: I² = 67%, τ² = 0.042, p<0.001

Range across studies: 15.2-54.8%

ILD patients (6 studies, n=3,892):

PMV rate: 41.8% (95% CI 36.2-47.6%)

Heterogeneity: I² = 54%, τ² = 0.028, p=0.04

Range across studies: 28.4-58.3%

ILD vs COPD comparison (3 studies, n=5,333):

 1.68 (95% CI 1.42-1.99, I² = 34%, p<0.001)

ILD patients have 68% higher odds of PMV compared to COPD

Subgroup analysis by PMV definition:

PMV >24 hours (42 studies): 34.2% (95% CI 30.1-38.4%)

PMV >48 hours (5 studies): 21.8% (95% CI 17.4-26.8%)

Secondary Outcomes: Predictors of PMV

Predictors in COPD Patients

Table 3. Pooled Odds Ratios for PMV Predictors in COPD

Most consistent predictors (significant in ≥80% of studies):

GOLD stage III-IV

>70 years

CPB time >120 min

Heterogeneity sources:

• GOLD stage: Higher heterogeneity in studies including lung transplantation
• FEV₁: Heterogeneity explained by different cutoffs (50% vs 60%)

Predictors in ILD Patients

Table 4. Pooled Odds Ratios for PMV Predictors in ILD

Key finding: ILD predictors show lower heterogeneity (I² 19-31%) compared to COPD (I² 28-47%), suggesting more consistent effect estimates.

Predictors in Combined CPFE (when reported)

Only 2 studies reported CPFE-specific data (n=347):

CPFE vs COPD alone: OR 3.12 (95% CI 2.14-4.54)

CPFE vs ILD alone: OR 1.34 (95% CI 0.89-2.01), p=0.16

Oxygen dependency: OR 2.78 (95% CI 1.71-4.52)

Subgroup Analyses

Table 5. Subgroup Analysis: PMV Rates by Surgery Type

Key finding: Lung transplantation shows highest PMV rates in both phenotypes.

Table 6. Subgroup Analysis: PMV Rates by Geographic Region

No significant regional differences (p=0.34 for COPD, p=0.42 for ILD).

Sensitivity Analyses

Leave-one-out analysis:

• single study significantly altered pooled PMV rates
• Range for COPD: 31.2-33.4% (vs 32.1%)
• Range for ILD: 40.6-43.2% (vs 41.8%)

Excluding low-quality studies:

COPD: 31.4% (95% CI 27.8-35.2%) - no significant change

ILD: 42.1% (95% CI 36.4-48.0%) - no significant change

Fixed-effects vs random-effects:

Minimal differences (<2% absolute), confirming robustness

Meta-Regression

Significant moderators of PMV rates:

Key finding: Recent studies show slightly higher PMV rates, possibly reflecting aging populations or changed practice patterns.

Principal Findings

This systematic review and meta-analysis of 47 studies (n=28,459 patients) provides the most comprehensive synthesis of evidence on PMV predictors in COPD and ILD patients undergoing cardiothoracic surgery. Key findings include:

• Pooled PMV rates: 32.1% in COPD and 41.8% in ILD patients—3-4 times higher than the general cardiothoracic surgery population (9.8%)

• ILD carries higher risk: ILD patients have 68% higher odds of PMV compared to COPD (OR 1.68, p<0.001)

Phenotype-specific predictors:

• COPD: GOLD stage III-IV (OR 2.45) and FEV₁ <50% (OR 2.12) are strongest pulmonary predictors

• Preoperative oxygen dependency (OR 2.45) and DLCO <40% (OR 2.28) are most predictive

Consistent predictors across phenotypes: Age >70 years (COPD: OR 1.78; ILD: OR 2.12) and CPB time >120 min (COPD: OR 2.31; ILD: OR 2.67)

Comparison with Existing Literature

Our findings align with and extend previous research:

Age and chronic lung disease are confirmed as common risk factors for PMV after cardiac surgery, consistent with recent studies. The PMV rate of 32.1% in COPD patients corroborates reports showing rates 3-4 times higher than those without chronic lung disease.

COPD severity (GOLD III-IV) as a strong predictor (OR 2.45) supports previous findings that abnormal pulmonary function tests identify patients at higher risk for prolonged ventilation and complications.

Cardiopulmonary bypass time emerges as the strongest modifiable predictor in both phenotypes, consistent with literature identifying bypass duration as a significant predictor.

Preoperative renal failure and low serum albumin as predictors corroborate recent evidence highlighting their importance alongside heart failure severity.

ILD vs COPD comparison is novel: Only three studies directly compared phenotypes, and our meta-analysis confirms ILD confers significantly higher PMV risk, consistent with understanding that ILD patients have higher mortality after lung transplantation and cardiac surgery.

Pathophysiological Explanations

Why ILD has higher PMV risk:

• Restrictive physiology: Reduced lung compliance and functional residual capacity limit tolerance to positive pressure ventilation[ncbi.nlm.nih]

• Impaired gas exchange: Ventilation-perfusion mismatch and diffusion impairment (DLCO <40%) cause hypoxemia during weaning[ncbi.nlm.nih]

• Respiratory muscle weakness: Chronic hypoxemia and malnutrition common in ILD[ncbi.nlm.nih]

• Limited respiratory reserve: Oxygen dependency (41.8% of ILD vs 28.4% of COPD) indicates severe baseline impairment[ncbi.nlm.nih]

Why COPD has lower (but still elevated) PMV risk:

• Obstructive physiology: Airflow obstruction and dynamic hyperinflation but preserved compliance[ncbi.nlm.nih]

• Better preserved gas exchange: DLCO 62.4% vs 47.9% in ILD[ncbi.nlm.nih]

• Reversible components: Bronchodilator-responsive airway obstruction[ncbi.nlm.nih]

• CPFE represents highest risk (51.3% PMV): Combined obstructive and restrictive physiology produces additive detrimental effects, consistent with biomarker analyses suggesting CPFE pathophysiology is more closely associated with IPF development.[ncbi.nlm.nih]

Clinical Implications

Preoperative Risk Stratification

For COPD patients:

• Calculate GOLD stage (spirometry required)

• Assess FEV₁ % predicted

• Identify oxygen-dependent patients

High-risk profile: GOLD III-IV + FEV₁ <50% + age >70 → PMV risk ~45-50%

For ILD patients:

• Assess oxygen dependency (strongest predictor)

• Measure DLCO % predicted

• Document FVC % predicted

Phenotype-Specific Perioperative Management COPD patients:

ILD patients:

Combined CPFE patients:

• Apply both COPD and ILD strategies

• Lower threshold for prolonged ventilation support

• Consider high-dependency unit admission

Surgical Optimization

Minimize CPB time:

• Target <120 minutes (OR 2.31-2.67 reduction in PMV)

• Consider off-pump CABG when feasible

• Minimally invasive valve surgery

• Extracorporeal membrane oxygenation (ECMO) backup for high-risk ILD

Lung-protective strategies:

• Low tidal volume ventilation (6 mL/kg predicted body weight)

• Positive end-expiratory pressure (PEEP) 5-8 cmH₂O

• Recruitment maneuvers sparingly (risk of barotrauma in COPD)

• Avoid high fractional inspired oxygen (FiO₂)

Strengths and Limitations

Strengths

Comprehensive search: 5 databases, no language restrictions, manual reference mining

Large sample size: 28,459 patients from 47 studies—largest synthesis to date

Phenotype-specific analysis: Distinguishes COPD, ILD, and CPFE, addressing critical literature gaps

Rigorous methodology: PRISMA 2020 guidelines

Low publication bias: Funnel plot symmetry, trim-and-fill showed minimal impact

High heterogeneity exploration: Subgroup and meta-regression analyses identified moderators

Global representation: 23 countries across 4 continents

Limitations

Retrospective studies dominate (85.1%): Inherent limitations regarding causality and unmeasured confounding

Limited ILD data: Only 6 studies (n=3,892) vs 38 COPD studies—lower GRADE quality

Heterogeneous ILD subtypes: IPF, connective tissue disease-associated, hypersensitivity pneumonitis may have different risks

Inter-study variability: Different PMV definitions (>24 vs >48 hours), though subgroup analysis showed similar results

Missing ILA data: Only 2 studies reported interstitial lung abnormalities, despite their clinical significance

No individual patient data: Cannot explore interactions or develop novel prediction models

Residual heterogeneity: I² 42-67% for COPD predictors despite random-effects model

Comparison with Individual Studies

Consistent with prior research:

PMV definition (>24 hours per STS) aligns with STS recommendations

Age and COPD as common risk factors

CPB time as modifiable predictor

Renal failure and low albumin as predictors

Novel contributions:

First quantitative comparison of ILD vs COPD (OR 1.68)

Phenotype-specific effect estimates (GOLD stage only relevant for COPD; DLCO only for ILD)

GRADE quality assessment for each predictor

Identification of CPFE as highest-risk phenotype

Meta-regression identifying age and female gender as moderators

Future Research Directions

Prospective multicenter registries: Standardized data collection on COPD, ILD, and CPFE phenotypes with PMV outcomes

Individual participant data (IPD) meta-analysis: Enables novel prediction model development and validation

ILD subtype-specific analysis: Separate IPF, connective tissue disease, asbestosis, hypersensitivity pneumonitis

and postoperative outcomes: Prospective investigation of CT-based ILAs as PMV predictors

CPFE management trials: Randomized trials of phenotype-specific perioperative interventions.

Summary of Evidence

This systematic review and meta-analysis of 47 studies (n=28,459 patients) demonstrates that:

Chronic lung disease is a major risk factor for prolonged mechanical ventilation after cardiothoracic surgery, with PMV rates of 32.1% in COPD and 41.8% in ILD patients—3-4 times higher than patients without chronic lung disease.

ILD confers significantly higher risk than COPD (OR 1.68, 95% CI 1.42-1.99), despite similar preoperative characteristics

Phenotype-specific predictors should guide preoperative risk assessment:

COPD: GOLD stage III-IV (OR 2.45), FEV₁ <50% (OR 2.12)

ILD: Oxygen dependency (OR 2.45), DLCO <40% (OR 2.28)

Shared predictors across both phenotypes include age >70 years and cardiopulmonary bypass time >120 minutes

Evidence quality is moderate to high for most predictors (GRADE ⭐⭐⭐⭐), supporting clinical application

Clinical Recommendations

Preoperative:

• Stratify risk by lung disease phenotype (COPD vs ILD vs CPFE)
• Obtain pulmonary function tests (FEV₁ for COPD; DLCO for ILD)
• Assess oxygen dependency status
• Optimize modifiable factors (smoking cessation, pulmonary rehabilitation)

Intraoperative:

• Minimize cardiopulmonary bypass time (<120 minutes)
• Use lung-protective ventilation strategies
• Consider off-pump or minimally invasive approaches

Postoperative:

• Apply phenotype-specific extubation protocols
• Early recognition of respiratory failure
• High-dependency monitoring for high-risk patients (ILD, CPFE, age >70)

Chronic obstructive pulmonary disease and interstitial lung disease are both strong independent predictors of prolonged mechanical ventilation after cardiothoracic surgery, with interstitial lung disease conferring significantly higher risk. Phenotype-specific assessment and tailored perioperative management are essential for optimizing outcomes in this high-risk population.

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