ReviewMediastinum (Hong Kong, China)2023
The anesthetic management and the role of extracorporeal membrane oxygenation for giant mediastinal tumor surgery.
Review in Mediastinum (Hong Kong, China), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- An intermittent ascending aorta clamping strategy to rescue an emergency management of unexpected massive hemorrhage in mediastinal tumor surgery: a case report.Journal of cardiothoracic surgery · 2026Article
- Rising Above the Limits of Critical Care ECMO: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Local Anesthetic Infiltration, Awake Veno-Venous Extracorporeal Membrane Oxygenation, and Airway Management for Resection of a Giant Mediastinal Cyst: A Narrative Review and Case Report.Journal of clinical medicine · 2024Review
- Perioperative strategies and management of giant anterior mediastinal tumors: a narrative review.Mediastinum (Hong Kong, China) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mediastinal tumors are a remarkably diverse category. They include malignant and benign forms with different rates of disease progression and tissue invasion. Anesthesiologists may encounter significant difficulties in managing patients with giant mediastinal tumors due to the non-negligible occurrence of severe cardiorespiratory collapse. Respiratory complications ensue from the compression of the airways induced by the mediastinal mass: the compressive effects may be exacerbated by positioning or anesthesia induction. Furthermore, the compression or invasion of major vessels may elicit acute cardiovascular collapse. The specter of sudden cardiorespiratory deterioration should lead the anesthesiologist to careful planning: acknowledging clinical and radiological signs that may presage an increased risk of life-threatening complications is of pivotal importance. This review aims to present a strategy for treating patients with mediastinal masses, starting with the pathophysiological elements and moving through preoperative care, intraoperative behavior, and the recovery period. We will also focus on respiratory and cardiovascular issues, emphasizing the need for extracorporeal membrane oxygenation (ECMO) as a rescue and crucial component of the anesthesia strategy. Understanding the physiological alterations after anesthesia induction can aid in identifying and treating potential problems. In addition, we attempted to offer insight into multimodal anesthesia and analgesia management: we emphasize the importance of a thorough preoperative assessment and the need for reviewing extracorporeal support not just a resuscitative strategy but as an integrated component of the perioperative care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.