Long-term outcomes of drainless anatomical lung resection surgery for pulmonary malignancies

The drainless technique is safe and feasible for minimally invasive anatomical lung resection surgery for pulmonary malignancies in terms of early postoperative and long-term outcomes. However, further randomized controlled studies are warranted.

Authors

Institutions

Publication Details

Journal
Journal of Cardiothoracic Surgery
Published
2025-02-03
DOI
https://doi.org/10.1186/s13019-024-03303-8
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long-term outcomes of drainless anatomical lung resection surgery for pulmonary malignancies

Mong‐Wei Lin, Ke-Cheng Chen, Shuenn‐Wen Kuo, Jang‐Ming Lee et al.
Journal of Cardiothoracic Surgery
Lung Cancer Diagnosis and Treatment
article

Long-term outcomes of drainless anatomical lung resection surgery for pulmonary malignancies

Mong‐Wei Lin, Ke-Cheng Chen, Shuenn‐Wen Kuo, Jang‐Ming Lee, Pei‐Ming Huang, Ting-Fang Kuo
article en

Abstract

The drainless technique is safe and feasible for minimally invasive anatomical lung resection surgery for pulmonary malignancies in terms of early postoperative and long-term outcomes. However, further randomized controlled studies are warranted.

Journal of Cardiothoracic SurgeryVol. 20(1)
National Taiwan University Hospital (TW)
Ministry of Health and Welfare, Ministry of Science and Technology, Taiwan
Good health and well-being
Openalex Percentile: Top 97%
Lung Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.