Can lung ultrasound predict high-flow nasal cannula (HFNC) therapy failure in patients?

Lung Ultrasound as a Predictor of High-Flow Nasal Cannula Therapy Failure

Lung ultrasound combined with respiratory rate monitoring is an effective tool for predicting high-flow nasal cannula (HFNC) therapy failure in patients with acute hypoxemic respiratory failure. While several predictive tools exist, monitoring diaphragmatic function via ultrasound alongside clinical parameters provides valuable information to guide timely escalation of respiratory support.

Predictive Tools for HFNC Failure

ROX Index: Primary Clinical Predictor

• The ROX index (ratio of SpO2/FiO2 to respiratory rate) is the most validated clinical predictor of HFNC failure 1
• A ROX index ≤ 4.88 after 12 hours of HFNC therapy indicates high risk for failure and need for mechanical ventilation 1
• ROX index demonstrates excellent prediction accuracy with an area under the curve (AUC) of 0.74 1

Ultrasound-Based Predictors

• Diaphragmatic ultrasound measurements show promise as complementary tools:
  • Diaphragmatic contraction speed by ultrasound has 89% sensitivity and 57% specificity for predicting HFNC failure 2
  • Can be measured in both supine and prone positions to assess diaphragmatic function 2
  • Provides direct visualization of respiratory muscle function and effort

Ventilatory Parameters

• Respiratory rate alone is a strong predictor of HFNC failure:
  • Respiratory rate >30 breaths/min at 12 hours of HFNC use indicates higher likelihood of failure 3
  • Respiratory rate monitoring at 12 hours (AUC 0.81) and 18 hours (AUC 0.85) outperforms oxygenation parameters in some studies 3
• Modified ventilatory ratio (VRm) with a cutoff value >2.68 shows high diagnostic accuracy (AUC 0.93) for predicting HFNC failure 4

Clinical Application Algorithm

1. Initial Assessment (at HFNC initiation):

   • Document baseline respiratory rate, SpO2/FiO2 ratio, and arterial blood gas values
   • Perform baseline lung and diaphragmatic ultrasound if available

2. Early Monitoring (first 6 hours):

   • Calculate ROX index hourly
   • Monitor for persistent tachypnea (RR >30)
   • Assess work of breathing clinically

3. Critical Assessment (at 12 hours):

   • Calculate ROX index (critical decision point)
   • If ROX ≤4.88: Consider escalation to NIV or intubation 1
   • If ROX >4.88: Continue HFNC with close monitoring
   • Perform diaphragmatic ultrasound to assess contraction speed and excursion

4. Ultrasound Integration:

   • Poor diaphragmatic contraction speed on ultrasound + low ROX index = highest risk for failure 2
   • Normal diaphragmatic function + ROX >4.88 = high likelihood of HFNC success

Special Considerations

• Patient-specific factors affecting prediction:

  • Obesity increases risk of HFNC failure (higher BMI correlates with failure) 3
  • Higher severity scores at admission (APACHE II >12) indicate greater risk 3
  • Altitude may affect predictive value of oxygenation parameters 3

• Cirrhosis/liver failure patients:

  • HFNC may be preferred over NIV in patients with cirrhosis and encephalopathy due to lower risk of aspiration 5
  • Close monitoring is essential as delayed intubation in progressive respiratory failure increases mortality 5
  • A model based on respiratory rate and oxygenation can guide decision-making regarding the need for mechanical ventilation 5

Pitfalls and Caveats

• Delayed intubation risk: Overreliance on HFNC without proper monitoring may delay necessary intubation, potentially increasing mortality 5, 6
• Gray zone decisions: When ROX index falls in an indeterminate range, incorporate diaphragmatic ultrasound and VRm index for additional decision support 4
• Monitoring frequency: Single measurements are less reliable than trends over time; serial assessments provide more accurate prediction
• Underlying etiology: Predictive accuracy may vary based on the cause of respiratory failure (pneumonia, ARDS, COVID-19)

The European Respiratory Society guidelines suggest HFNC over conventional oxygen therapy in acute hypoxemic respiratory failure, but emphasize the importance of close monitoring for failure 5. Using these predictive tools helps clinicians identify patients who are likely to fail HFNC therapy early, allowing for timely escalation of respiratory support and potentially reducing mortality.