From data to prediction: Digital chest drain insights into postoperative recovery after lung cancer surgery

Abstract

Objective

Prolonged air leak is one of the major complications following lung cancer surgery and objectively measured digital drainage data have been investigated as predictive factors. With this scoping review, we aim to provide a comprehensive overview of risk factors, derived from digital drainage data, for predicting postoperative (drainage) course after pulmonary resection in patients with lung cancer.

Methods

MEDLINE and EMBASE were systematically searched for studies that investigated digital drainage data after lung cancer surgery. Systematic reviews, editorials, commentaries, and reports in languages other than English were excluded. Data on general study information, characteristics of the procedures, digital drainage parameters, and clinical postoperative outcomes were extracted.

Results

Twenty-three studies were included, comprising 3,649 patients. Four different digital drainage systems were used. Maximum air flow exceeding 100–200 ml/min (5 studies), variable air leak patterns (3 studies), and less negative intrapleural/differential pressure (7 studies) were associated with prolonged air leak. A mean air flow of <50 ml/min was associated with spontaneous air leak resolution (1 study). However, chest tube management was heterogeneous, with different suction levels and chest tube removal criteria being applied.

Conclusions

Mean and maximum air flow, air leak patterns, and intrapleural/differential pressure derived from digital drainage data can be considered as possible predictors for postoperative prolonged air leak after lung cancer surgery. However, definitive evidence on the use of these predictive factors in a future risk prediction model could not be provided, due to a lack of homogeneity in the chest tube strategies used in the reviewed studies.