ArticleCurrent medical science2022
Establishment of an Assessment System for the Prediction of Severe Post-operative Complications after Hepatectomy Based on Preoperative Parameters.
Article in Current medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveAt present, there is no appropriate system to evaluate the severe complications of liver surgery through the preoperative factors. This study aimed to design and verify a risk assessment system for the prediction of severe post-operative complications after a hepatectomy based on the preoperative parameters.
methodsA retrospective analysis was performed on 1732 patients who had undergone liver surgery. The severity of the complications was graded by Accordion Severity Grading of post-operative complications. The variables were screened by multivariate analysis, and graded scores were assigned to the selected variables. A logistic regression equation was used to form the liver operation risk formula (LORF) for the prediction of severe post-operative complications. The LORF was verified by the receiver operating characteristic (ROC) curve.
resultsThe multivariate correlation analysis revealed the independent influencing factors of the severe post-operative complications of liver surgery were Child-Pugh grade (OR=4.127; P<0.001), medical diseases requiring drug treatment (OR=3.092; P<0.001), the number of liver segments to be removed (OR=2.209; P=0.006), organ invasion (OR=4.538; P=0.024), and pathological type (OR=4.023; P=0.002). The binomial logistic regression model was established to obtain the calculation formula (LORF) of the severe complication risk. The area under the ROC curve (AUC) of the LORF was 0.815. The cut-off value of the expected probability of severe complications was 0.3225 (32.25%). Furthermore, in the validation data set, the corresponding AUC of the LORF was 0.829.
conclusionAs a novel and simplified assessment system, the LORF could effectively predict the severe post-operative complications of liver surgery through the preoperative factors, and therefore it could be used to evaluate the risk of severe liver surgical complications before surgery.
Indexed as
Identifiers
36166136What OpenQuestion holds
Registered trials
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.