Evidence map›Paper›PMID 38429060›Full record

ArticleBMJ case reports2024

Tuberculous peritonitis diagnosed following laparoscopic examination for suspected advanced ovarian cancer.

Mizuki Nonaka, Hiroaki Ishida, Megumi Manrai, Akiko Takashima

Open access · hybridAbstract readCase Reports
In one paragraph

Article in BMJ case reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 institution in 1 country.

Mizuki NonakaDepartment of Obstetrics and Gynecology, Toho University Medical Center, Sakura, Japan.
Hiroaki IshidaDepartment of Obstetrics and Gynecology, Toho University Medical Center, Sakura, Japan ishida-04@sakura.med.toho-u.ac.jp.ORCID http://orcid.org/0000-0002-0629-3284
Megumi ManraiDepartment of Obstetrics and Gynecology, Toho University Medical Center, Sakura, Japan.
Akiko TakashimaDepartment of Obstetrics and Gynecology, Toho University Medical Center, Sakura, Japan.
Toho University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Laparoscopy for intra-abdominal exploration and tissue sampling is useful in advanced ovarian cancers, in which it is presumed to be difficult to achieve complete tumour reduction in the initial surgery. This is a report of a case of suspected advanced ovarian cancer in a patient, who underwent laparoscopic screening and was later pathologically diagnosed with tuberculous peritonitis. A woman in her 50s visited her local doctor with constipation. Since imaging showed massive ascites she was referred for further evaluation. We initially suspected advanced ovarian cancer due to the presence of massive ascites and multiple peritoneal nodules. However, histopathological examination indicated that the nodules were tubercles, and the patient was subsequently diagnosed with tuberculous peritonitis. It is important to be aware that tuberculosis peritonitis can be misdiagnosed or mistaken for advanced ovarian cancer. Preoperative diagnosis of tuberculous peritonitis is often difficult. Tuberculous peritonitis should be considered if intraoperative findings show diffuse nodular disseminated lesions.

Indexed as

Genital Neoplasms, MaleLaparoscopyOvarian NeoplasmsPeritonitis, TuberculousAscitesCarcinoma, Ovarian EpithelialFemaleHumansPeritoneumCancer - see OncologyTuberculosis

Identifiers

PMID38429060
PMCPMC10910656
OpenAlexW4392360613

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.