Evidence map›Paper›PMID 18763291›Full record

ArticleWorld journal of gastroenterology2008

Treatment of polycystic liver disease with resection-fenestration and a new classification.

Tuan-Jie Li, Hai-Bin Zhang, Jun-Hua Lu, Jun Zhao, Ning Yang, Guang-Shun Yang

Open access · bronzeAbstract read
In one paragraph

Article in World journal of gastroenterology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

6 authors at 3 institutions in 2 countries.

Tuan-Jie LiEastern Hepato-biliary Hospital, Second Military Medical University, Shanghai, China.
Hai-Bin Zhang
Jun-Hua Lu
Jun Zhao
Ning Yang
Guang-Shun Yang
Eastern Hepatobiliary Surgery Hospital · CNQueen Elizabeth Hospital Birmingham · GBSecond Military Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo evaluate outcomes in patients with autosomal dominant polycyst liver disease (APLD) treated by combined hepatic resection and fenestration. A new classification was recommended to presume postoperative complications and long outcome of patients.

methodsTwenty-one patients with APLD were treated by a combined hepatic resection and fenestration technique. All patients were reviewed retrospectively, and clinical symptoms, performance status and morbidity were recorded. A new classification of APLD is recommended here.

resultsAll patients were discharged when free of symptoms. The mean follow-up time was 55.7 mo and three patients had a recurrence of symptoms at 81, 68 and 43 mo after operation, respectively. The overall morbidity rate was 76.2%. Two patients with Type B-II and Type B-I developed biliary leakage. Four patients had severe ascites, including three with Type B-III and one with Type B-II. Nine patients had pleural effusion, including one with Type A-I; one with Type B-I; five with Type B-II; one with Type A-III and one with Type B-III. Three patients with Type B had recurrence of symptoms, while none with Type A had severe complications.

conclusionCombined hepatic resection and fenestration is an acceptable procedure for treatment of APLD. According to our classification, postoperative complications and long outcome can be predicted before surgery.

Indexed as

AdultCystsFemaleFollow-Up StudiesHepatectomyHumansLiver DiseasesMaleMiddle AgedPostoperative ComplicationsPredictive Value of TestsRetrospective StudiesTomography, X-Ray Computed

Identifiers

PMID18763291
PMCPMC2742936
OpenAlexW2154017638

What OpenQuestion holds

Textmetadata
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.