Forecasting pulmonary air leak duration following lung surgery using transpleural airflow data from a digital pleural drainage device | Zendy

Ching Yeung | Zendy; Mohsen Ghazel | Zendy; Daniel French | Zendy; Nathalie Japkowicz | Zendy; Bram Gottlieb | Zendy; Donna E. Maziak | Zendy; Andrew Seely | Zendy; Farid M. Shamji | Zendy; Sudhir Sundaresan | Zendy; Patrick J. Villeneuve | Zendy; Sebastién Gilbert | Zendy

Open Access

Forecasting pulmonary air leak duration following lung surgery using transpleural airflow data from a digital pleural drainage device

Author(s) -

Ching Yeung,

Mohsen Ghazel,

Daniel French,

Nathalie Japkowicz,

Bram Gottlieb,

Donna E. Maziak,

Andrew Seely,

Farid M. Shamji,

Sudhir Sundaresan,

Patrick J. Villeneuve,

Sebastién Gilbert

Publication year - 2018

Publication title -

journal of thoracic disease

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.682

H-Index - 60

eISSN - 2077-6624

pISSN - 2072-1439

DOI - 10.21037/jtd.2018.08.11

Subject(s) - medicine , autoregressive integrated moving average , leak , drainage , surgery , radiology , emergency medicine , time series , statistics , engineering , ecology , environmental engineering , biology , mathematics

Prolonged air leak (PAL) is often the limiting factor for hospital discharge after lung surgery. Our goal was to develop a statistical model that reliably predicts pulmonary air leak resolution by applying statistical time series modeling and forecasting techniques to digital drainage data.

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