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Calculated Maximal Volume Ventilation (cMVV) as a Marker of Early Respiratory Failure in Amyotrophic Lateral Sclerosis (ALS)

Articolo
Data di Pubblicazione:
2024
Abstract:
: Respiratory failure assessment is among the most debatable research topics in amyotrophic lateral sclerosis (ALS) clinical research due to the wide heterogeneity of its presentation. Among the different pulmonary function tests (PFTs), maximal voluntary ventilation (MVV) has shown potential utility as a diagnostic and monitoring marker, able to capture early respiratory modification in neuromuscular disorders. In the present study, we explored calculated MVV (cMVV) as a prognostic biomarker in a center-based, retrospective ALS population belonging to the Piemonte and Valle d'Aosta registry for ALS (PARALS). A Spearman's correlation analysis with clinical data and PFTs showed a good correlation of cMVV with forced vital capacity (FVC) and a moderate correlation with some other features such as bulbar involvement, ALSFRS-R total score, blood oxygen (pO2), carbonate (HCO3-), and base excess (BE), measured with arterial blood gas analysis. Both the Cox proportional hazard models for survival and the time to non-invasive ventilation (NIV) measurement highlighted that cMVV at diagnosis (considering cMVV(40) ≥ 80) is able to stratify patients across different risk levels for death/tracheostomy and NIV indication, especially considering patients with FVC% ≥ 80. In conclusion, cMVV is a useful marker of early respiratory failure in ALS, and is easily derivable from standard PFTs, especially in asymptomatic ALS patients with normal FVC measures.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
amyotrophic lateral sclerosis; forced vital capacity; maximal volume ventilation; pulmonary function tests; spirometry
Elenco autori:
Manera, Umberto; Torrieri, Maria Claudia; Moglia, Cristina; Canosa, Antonio; Vasta, Rosario; Palumbo, Francesca; Matteoni, Enrico; Cabras, Sara; Grassano, Maurizio; Bombaci, Alessandro; Mattei, Alessio; Bellocchia, Michela; Tabbia, Giuseppe; Ribolla, Fulvia; Chiò, Adriano; Calvo, Andrea
Autori di Ateneo:
CALVO Andrea
CANOSA Antonio
CHIO' Adriano
MANERA Umberto
MOGLIA Cristina
VASTA Rosario
Link alla scheda completa:
https://iris.unito.it/handle/2318/1959213
Link al Full Text:
https://iris.unito.it/retrieve/handle/2318/1959213/1245854/Brian%20Sci%202024%20-%20Manera%20-%20MMV%20prognosis.pdf
Pubblicato in:
BRAIN SCIENCES
Journal
Progetto:
BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis
  • Aree Di Ricerca

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Settori (13)


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