How are graphs in pulmonary function tests (PFTs) interpreted in patients with respiratory diseases, such as chronic obstructive pulmonary disease (COPD) or asthma, considering demographic and medical history?

Interpreting Graphs in Pulmonary Function Tests

Systematic Algorithmic Approach to Graph Interpretation

The European Respiratory Society recommends interpreting PFT graphs using a systematic, step-wise algorithm: first assess test quality and technical adequacy, then analyze the flow-volume loop morphology to identify patterns, compare numerical values against reference standards matched for age, height, sex, and ethnicity, classify the physiologic defect, grade severity, and finally integrate findings with clinical context. 1, 2

Step 1: Assess Technical Quality Before Interpretation

• Never rely on numerical results without first reviewing the flow-volume loop (FVL) graph for technical adequacy 2
• Verify proper technique was used and results meet acceptability and reproducibility criteria before making clinical decisions 2
• Poor effort or technique will produce unreliable graphs that cannot be interpreted accurately 1

Step 2: Analyze Flow-Volume Loop Morphology

The shape of the FVL provides immediate visual clues to the underlying physiologic defect:

• Obstructive pattern: Look for a "scooped out" or concave appearance of the expiratory limb, indicating airflow limitation 3, 4
• Restrictive pattern: The loop appears narrow and tall, with reduced volumes but preserved flow rates 3, 4
• Mixed pattern: Combines features of both obstruction (concave expiratory curve) and restriction (reduced volumes) 5, 3
• Small airway dysfunction: Late expiratory flattening of the FVL, which can be quantified using indices like SADI (small airway disease index) 6
• Upper airway obstruction: Flattening of the inspiratory limb, expiratory limb, or both, creating a characteristic "box-like" appearance 3

Step 3: Compare Numerical Values to Reference Standards

• Calculate percent predicted for FEV1 and FVC by comparing actual measurements to reference values matched for age, height, sex, and ethnicity 1, 2
• Use the Lower Limit of Normal (LLN), defined as the 5th percentile, rather than arbitrary fixed percentages like 80% 7, 1, 8
• All spirometric parameters (FVC, FEV1, FEV1/FVC) must come from the same reference source to ensure consistency 7, 8

Step 4: Identify the Physiologic Pattern

Follow this decision tree:

1. First, evaluate FEV1/FVC ratio (not FEV1 alone) 1, 2

   • If FEV1/FVC < LLN → Obstructive pattern 1, 2
   • If FEV1/FVC ≥ LLN → Proceed to next step 1

2. If non-obstructive, assess FVC and TLC:

   • If FVC reduced but TLC normal → Not true restriction (common pitfall) 2, 8
   • If TLC < 80% predicted → Restrictive pattern 1, 2
   • Never confirm restriction without measuring TLC, as spirometry alone has poor positive predictive value 1, 2, 8

3. If both FEV1/FVC and TLC are reduced → Mixed pattern 5, 3

Step 5: Grade Severity Using FEV1 % Predicted

Once the pattern is identified, grade severity based on FEV1 % predicted (European Respiratory Society classification): 1, 2

• Mild: FEV1 ≥70% predicted 1, 2
• Moderate: FEV1 60-69% predicted 1, 2
• Moderately severe: FEV1 50-59% predicted 1, 2
• Severe: FEV1 35-49% predicted 1, 2
• Very severe: FEV1 <35% predicted 1, 2

Critical caveat: Never use the FEV1/FVC ratio to grade severity—it only identifies the presence of obstruction 1

Step 6: Assess Additional Graph Features

• Bronchodilator response: Compare pre- and post-bronchodilator FVL graphs; changes >12% AND >200 mL in FEV1 indicate significant reversibility 1
• DLCO graph patterns: Low DLCO (<60% predicted) indicates higher mortality risk and pulmonary morbidity, particularly important in COPD, interstitial lung disease, and preoperative lung cancer evaluation 2, 8
• Lung volume graphs: Assess for hyperinflation (increased RV/TLC ratio) and air trapping visible on volume-time curves 5, 3

Step 7: Interpret Changes Over Time

When comparing serial PFT graphs, use these thresholds for clinically meaningful change: 1, 8

• Short-term variation: >5% change in FEV1 or FVC 1, 8
• Week-to-week change: >12% in FEV1 or >11% in FVC 1, 8
• Year-to-year progression: >15% in FEV1 1, 8

Special Considerations for Race and Ethnicity

Recent evidence from the American College of Chest Physicians, American Thoracic Society, and Canadian Thoracic Society (2023) highlights critical issues with race-specific reference equations: 7

• Race-specific equations may mask clinically important disease in Black individuals by artificially lowering predicted values 7
• Multiple studies demonstrate that race-neutral equations (GLI-Other) better predict mortality, morbidity, and CT findings than race-specific equations 7
• For the same absolute FVC value, Black individuals have higher mortality when race-specific equations are used because they generate falsely reassuring z-scores 7
• The impact of race/ethnicity is most significant in borderline cases; clearly normal or abnormal results are less affected 7
• In borderline or "gray zone" cases, consider additional testing rather than relying solely on race-adjusted predictions 7

Critical Pitfalls to Avoid

1. Never diagnose obstruction based on reduced FEV1 alone—always check the FEV1/FVC ratio first 1, 2, 8

2. Never confirm restrictive disease without measuring TLC, as reduced FVC on spirometry has poor positive predictive value for true restriction 1, 2, 8

3. Never rely solely on computer-generated interpretations without personally reviewing the FVL graph 2, 6

4. Never use FEV1/FVC ratio to grade severity of obstruction—use FEV1 % predicted instead 1

5. Never fail to adjust DLCO for hemoglobin, especially when monitoring for drug toxicity 2

6. Never extrapolate reference equations beyond the age and height range of the reference population 7

7. Never use stated height—always measure with a stadiometer at each visit 7, 8

8. Recognize that upper airway obstruction may be life-threatening despite being classified as only "mildly reduced" by FEV1 % predicted 2

Integration with Clinical Context in COPD and Asthma

For COPD patients: 2

• FEV1 correlates with symptom severity and prognosis 2
• Inspiratory capacity (IC) and DLCO are important mortality predictors beyond FEV1 alone 1
• Look for hyperinflation patterns on volume graphs, which impact exercise capacity 5, 3

For asthma patients: 1

• Bronchodilator response graph comparison is critical—look for normalization of the FVL shape post-bronchodilator 1
• Between exacerbations, graphs may appear completely normal 4
• Serial testing showing variability (>12% FEV1 changes) supports the diagnosis 1

PFT graphs are only one tool in the diagnostic armamentarium and must be interpreted within the full clinical context, including symptoms, imaging, and other ancillary data 7, 2, 3