Evidence map›Paper›PMID 39011180›Full record

ArticleCureus2024

Accurate Preoperative and Intraoperative Evaluation Reduces Surgical Costs and Patient Invasiveness in Ventriculoperitoneal Shunt Revision.

Marina Takahashi, Taijun Hana, Shota Tanaka, Nobuhito Saito

Abstract readCase Reports
In one paragraph

Article in Cureus, 2024. 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
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.

  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.

Marina TakahashiDepartment of Neurosurgery, The University of Tokyo Hospital, Tokyo, JPN.
Taijun HanaDepartment of Neurosurgery, The University of Tokyo Hospital, Tokyo, JPN.
Shota TanakaDepartment of Neurosurgery, The University of Tokyo Hospital, Tokyo, JPN.
Nobuhito SaitoDepartment of Neurosurgery, The University of Tokyo Hospital, Tokyo, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ventriculoperitoneal (VP) shunt is one of the most common surgical procedures in neurosurgery, frequently resulting in malfunctions. Shunt malfunctions, which can include mechanical failure, obstruction, infection, or disconnection, occur in a significant percentage of patients, often necessitating multiple revisions. These revisions can lead to increased healthcare costs due to additional surgeries or treatments. Therefore, addressing the economic impacts of these revisions is crucial. Our report presents a cost-effective approach to shunt revisions, demonstrated through a case study of an 82-year-old woman with hydrocephalus. Although initially treated with a VP shunt, she required a revision after six years due to shunt malfunction. Through comprehensive preoperative and intraoperative evaluations, including a shuntogram with iodine contrast and meticulous examination, we identified the cause of malfunction as a connective tissue sac blocking the peritoneal catheter. The surgery involved flushing the catheter lumen with saline to confirm the obstruction and careful removal of the obstructive tissue. This accurate diagnosis facilitated a minimally invasive revision, enabling the reuse of existing shunt components and avoiding the need for new devices, thus reducing costs and surgical invasiveness. Our study serves as a call to action for healthcare providers and surgeons to consider more cost-effective and patient-friendly approaches in managing VP shunt malfunctions, ultimately benefiting both the healthcare system and the patients it serves.

Indexed as

hydrocephalusmedical economyshunt revisionsurgical costventriculoperitoneal shunt

Identifiers

PMID39011180
PMCPMC11247248

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Registered trials

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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.