Evidence map›Paper›PMID 36244982›Full record

ArticleJA clinical reports2022

Successful management of a patient with preoperative respiratory failure due to a solid giant retroperitoneal tumor: a case report.

Hirotaka Kinoshita, Eiji Hashiba, Satoshi Uchida, Kazuyoshi Hirota

Open access · goldAbstract read
In one paragraph

Article in JA clinical reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 77% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

4 authors at 2 institutions in 1 country.

Hirotaka KinoshitaDepartment of Anesthesiology, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, 036-8562, Japan. hirotakak@hirosaki-u.ac.jp.ORCID http://orcid.org/0000-0003-4490-3941
Eiji HashibaDivision of Intensive Care, Hirosaki University Hospital, 53 Hon-cho, Hirosaki, 036-8563, Japan.
Satoshi UchidaDepartment of Anesthesiology, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, 036-8562, Japan.
Kazuyoshi HirotaDepartment of Anesthesiology, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, 036-8562, Japan.
Hirosaki University · JPHirosaki University Hospital · JP

Funding

Japan Society for the Promotion of Science 21K16556
6 · The paper itself

Abstract

backgroundWe report the successful preoperative management of respiratory failure in a patient with a solid giant retroperitoneal tumor with a hemodynamic monitoring system and nasal high-flow therapy (NHFT). CASE PRESENTATION: Twenty days before his scheduled resection of a giant retroperitoneal liposarcoma, a 64-year-old man presented with dyspnea. After admission to our intensive care unit, he received NHFT and hemodynamic therapy using a LiDCOrapid V3™ monitor (Masimo Japan, Tokyo). NHFT and intense diuresis improved his respiratory condition. The tumor resection was performed on the 5th day. He was discharged to the general ward with an oxygen nasal cannula on the second postoperative day. Although preoperative transthoracic echography showed mild aortic regurgitation and moderate mitral regurgitation, the degree of regurgitation had become trivial about 1-month post-surgery.

conclusionsA cause of preoperative respiratory failure associated with a giant retroperitoneal tumor might be not only diaphragmatic compression but also heart failure and excess fluid volume.

Indexed as

Giant tumorHemodynamic systemNasal high-flow therapyRespiratory failureROX index

Identifiers

PMID36244982
PMCPMC9573809
OpenAlexW4306367143

What OpenQuestion holds

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LicenceCC BY
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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.