Evidence map›Paper›PMID 34797398›Full record

ArticleWorld journal of surgery2022

Post-operative Day 1 Serum Transaminase Levels in Relation to Morbidity After Liver Resection.

G W de Klein, R M Brohet, M S L Liem, J M Klaase

Abstract read
PubMed Publisher
In one paragraph

Article in World journal of surgery, 2022. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

G W de KleinDepartment of Surgery, Medisch Spectrum Twente, Koningsplein 1, 7512 KZ, Enschede, The Netherlands.
R M BrohetDepartment of Research and Innovation, Isala, Zwolle, Netherlands.
M S L LiemDepartment of Surgery, Medisch Spectrum Twente, Koningsplein 1, 7512 KZ, Enschede, The Netherlands.
J M KlaaseDepartment of Hepatobiliary Surgery and Liver Transplantation, University Medical Center Groningen, Groningen, Netherlands. j.m.klaase@umcg.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPost-operative serum transaminases have been proposed as possible early predictors of morbidity after liver resection. This study aimed to verify the clinical value of post-operative serum transaminases.

methodsClinical data from 2001 to 2016 in a single non-academic referral HPB center were collected from a prospectively held database. Post-operative day 1 serum aspartate transaminase (AST) and alanine transaminase (ALT) were tested for their relationship with post-operative major morbidity, defined by a Clavien-Dindo score 3 or higher, and mortality.

resultsFor this analysis, 371 patients were included, including 149 (40%) undergoing major liver resections. In total, 17% of the patients developed major morbidity. Stepwise logistic regression demonstrated that AST, and not ALT, is an independent predictor for major morbidity (p = 0.017). The probability of major morbidity significantly increased with increasing AST values. A threshold value of 242 U/L was found to be predictive for one or more major complications.

conclusionsIn this study, post-operative serum AST on day 1 was a predictive factor for major morbidity after liver resection. For patients with low AST value, early discharge could be considered. However, because of the substantial inter-individual variability of AST values, more studies are needed to translate these results into clinical practice.

Indexed as

HepatectomyLiverAlanine TransaminaseAspartate AminotransferasesHumansMorbidityAlanine TransaminaseAspartate Aminotransferases

Identifiers

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.