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Tesi etd-06262025-211214


Tipo di tesi
Tesi di laurea magistrale LM6
Autore
SANTINI, ARIANNA
URN
etd-06262025-211214
Titolo
M-AERIALS Project “Multiparametric Assessment of Early Respiratory Involvement in ALS”: A Comparative Longitudinal Study of ENG, Ultrasound, and Spirometry
Dipartimento
RICERCA TRASLAZIONALE E DELLE NUOVE TECNOLOGIE IN MEDICINA E CHIRURGIA
Corso di studi
MEDICINA E CHIRURGIA
Relatori
relatore Prof. Siciliano, Gabriele
Parole chiave
  • Amyotrophic Lateral Sclerosis
  • early diagnosis
  • predictive modeling
  • respiratory decline
Data inizio appello
15/07/2025
Consultabilità
Non consultabile
Data di rilascio
15/07/2095
Riassunto
Given the clinical relevance of respiratory failure in Amyotrophic Lateral Sclerosis (ALS) and the importance of early intervention, this study explored strategies to improve early detection. It compared less invasive alternatives—phrenic nerve conduction studies (Compound Muscle Action Potential, CMAP) and diaphragm/intercostal ultrasound (Thickening Fraction, TF)—to traditional spirometry (Peak Expiratory Flow Maximum, PEF), the gold standard for initiating non-invasive ventilation.
At baseline, CMAP and ultrasound-derived parameters showed significant diagnostic accuracy in detecting respiratory decline. Notably, intercostal TF increased in early dysfunction, suggesting compensatory intercostal muscle activation in response to emerging diaphragmatic weakness. Our data supported the role of diaphragmatic ultrasound and CMAP in detecting early respiratory decline through intercostal compensation, indicating these measures as early markers of respiratory dysfunction.
The study also examined whether some clinical features were linked to earlier respiratory decline. Univariate and multivariate analyses found that higher DYALS scores were significantly associated with abnormal CMAP and TF values, suggesting that bulbar involvement may predict early respiratory compromise. Overall, these findings support integrating neurophysiological and ultrasound data with clinical profiling to better identify ALS patients at risk of respiratory failure.

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