Evidence map›Paper›PMID 30540577›Full record

ReviewCurrent opinion in anaesthesiology2019

Precise anesthesia in thoracoscopic operations.

Ming-Hui Hung, Jin-Shing Chen, Ya-Jung Cheng

Open access · hybridAbstract readReview
In one paragraph

Review in Current opinion in anaesthesiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 2 countries.

Ming-Hui HungDepartment of Anesthesiology.
Jin-Shing ChenDepartment of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Ya-Jung ChengDepartment of Anesthesiology.
National Taiwan University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThe current review focuses on precise anesthesia for video-assisted thoracoscopic surgery (VATS) with the goal of enhanced recovery. RECENT

findingsVATS has become an established and widely used minimally invasive approach with broad implementation on a variety of thoracic operations. In the current environment of enhanced recovery protocols and cost containment, minimally invasive VATS operations suggest adoption of individualized tailored, precise anesthesia. In addition to a perfect lung collapse for surgical interventions with adequate oxygenation during one lung ventilation, anesthesia goals include a rapid, complete recovery with adequate postoperative analgesia leading to early discharge and minimized costs related to postoperative inpatient services. The components and decisions related to precise anesthesia are reviewed and discussed including: letting patients remain awake versus general anesthesia, whether the patient should be intubated or not, operating with or without muscle relaxation, whether to use different separation devises, operating with different local and regional blocks and monitors.

conclusionThe determining factors in designing a precise anesthesic for VATS operations involve consensus on patients' tolerance of the associated side effects, the best practice or techniques for surgery and anesthesia, the required postoperative support, and the care team's experience.

Indexed as

Airway ManagementAnalgesiaAnesthesiaAnestheticsClinical Decision-MakingHospital CostsHumansLength of StayMonitoring, IntraoperativePostoperative PainPostoperative PeriodThoracic Surgery, Video-AssistedTime FactorsAnesthetics

Identifiers

PMID30540577
PMCPMC6326264
OpenAlexW2904421424

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.