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🧑🏼‍💻 Research - October 12, 2024

Noninvasive diagnostic modalities and prediction models for detecting pulmonary hypertension associated with interstitial lung disease: a narrative review.

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⚡ Quick Summary

This narrative review highlights the urgent need for noninvasive diagnostic tools to detect pulmonary hypertension (PH) in patients with interstitial lung disease (ILD). The study emphasizes that while estimated right ventricular pressure (RVSP) via Doppler echocardiography is the most predictive factor, there is currently no single test that can accurately diagnose PH in this patient population.

🔍 Key Details

  • 📊 Literature Review: 39 articles reviewed from PubMed and Scopus.
  • 🧩 Focus: Noninvasive diagnostic modalities and prediction models for PH in ILD.
  • ⚙️ Main Finding: RVSP remains the most predictive factor for PH.
  • 🏆 Limitations: No single noninvasive test can accurately diagnose PH.

🔑 Key Takeaways

  • 📊 High prevalence: PH is common in patients with ILD, leading to increased morbidity and mortality.
  • 💡 RVSP: Estimated via Doppler echocardiography is the most reliable indicator of PH.
  • 👩‍🔬 Composite scores: Existing scores lack external validation and generalizability.
  • 🏥 Early detection: Noninvasive tools may help in earlier identification of PH.
  • 🤖 Future research: Artificial intelligence could enhance diagnostic accuracy.
  • 🌍 Clinical relevance: Findings could improve patient management in specialized centers.

📚 Background

Pulmonary hypertension (PH) is a serious condition that significantly impacts patients with interstitial lung disease (ILD). The complexity of diagnosing PH in these patients necessitates the development of effective noninvasive screening tools. Given the high morbidity and mortality associated with PH, timely detection is crucial for improving patient outcomes.

🗒️ Study

This review critically evaluates the current landscape of noninvasive diagnostic modalities and prediction models for detecting PH in patients with ILD. The authors conducted a comprehensive literature search, identifying 39 relevant studies that provide insights into the effectiveness of various diagnostic approaches.

📈 Results

The review found that while RVSP on Doppler echocardiography is the most predictive factor for PH, estimating it can be challenging due to suboptimal imaging conditions in patients with extensive lung disease. Additionally, most existing composite scores derived from retrospective studies lack validation in external cohorts, limiting their clinical applicability.

🌍 Impact and Implications

The findings of this review underscore the need for improved noninvasive diagnostic strategies for PH in ILD patients. By enhancing early detection capabilities, healthcare providers can better manage patients at risk for severe PH, potentially leading to improved outcomes. The exploration of artificial intelligence in this field holds promise for more tailored and accurate diagnostic approaches in the future.

🔮 Conclusion

This narrative review highlights the critical gap in noninvasive diagnostic tools for detecting PH in patients with ILD. While current methods show promise, further research is needed to validate existing scores and explore innovative technologies, such as artificial intelligence, to enhance diagnostic accuracy. The future of PH detection in ILD patients looks promising, and continued efforts in this area are essential for improving patient care.

💬 Your comments

What are your thoughts on the current state of noninvasive diagnostics for pulmonary hypertension? We invite you to share your insights and engage in a discussion! 💬 Leave your comments below or connect with us on social media:

Noninvasive diagnostic modalities and prediction models for detecting pulmonary hypertension associated with interstitial lung disease: a narrative review.

Abstract

Pulmonary hypertension (PH) is highly prevalent in patients with interstitial lung disease (ILD) and is associated with increased morbidity and mortality. Widely available noninvasive screening tools are warranted to identify patients at risk for PH, especially severe PH, that could be managed at expert centres. This review summarises current evidence on noninvasive diagnostic modalities and prediction models for the timely detection of PH in patients with ILD. It critically evaluates these approaches and discusses future perspectives in the field. A comprehensive literature search was carried out in PubMed and Scopus, identifying 39 articles that fulfilled inclusion criteria. There is currently no single noninvasive test capable of accurately detecting and diagnosing PH in ILD patients. Estimated right ventricular pressure (RVSP) on Doppler echocardiography remains the single most predictive factor of PH, with other indirect echocardiographic markers increasing its diagnostic accuracy. However, RVSP can be difficult to estimate in patients due to suboptimal views from extensive lung disease. The majority of existing composite scores, including variables obtained from chest computed tomography, pulmonary function tests and cardiopulmonary exercise tests, were derived from retrospective studies, whilst lacking validation in external cohorts. Only two available scores, one based on a stepwise echocardiographic approach and the other on functional parameters, predicted the presence of PH with sufficient accuracy and used a validation cohort. Although several methodological limitations prohibit their generalisability, their use may help physicians to detect PH earlier. Further research on the potential of artificial intelligence may guide a more tailored approach, for timely PH diagnosis.

Author: [‘Arvanitaki A’, ‘Diller GP’, ‘Gatzoulis MA’, ‘McCabe C’, ‘Price LC’, ‘Wort SJ’]

Journal: Eur Respir Rev

Citation: Arvanitaki A, et al. Noninvasive diagnostic modalities and prediction models for detecting pulmonary hypertension associated with interstitial lung disease: a narrative review. Noninvasive diagnostic modalities and prediction models for detecting pulmonary hypertension associated with interstitial lung disease: a narrative review. 2024; 33:(unknown pages). doi: 10.1183/16000617.0092-2024

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