ReviewMedicine2018
A network meta-analysis of comparison of operative time and complications of laparoscopy, laparotomy, and laparoscopic-assisted vaginal hysterectomy for endometrial carcinoma.
Review in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Different surgical methods of hysterectomy for the management of endometrial cancer: a systematic review and network meta-analysis.Frontiers in oncology · 2024Pooled it
- Optimizing Anesthetic Management for Laparoscopic Surgery: A Comprehensive Review.Medical science monitor : international medical journal of experimental and clinical research · 2024Review
- Article
- Pain after laparoscopic endometriosis-specific vs. hysterectomy surgeries: A retrospective cohort analysis.PloS one · 2024Article
- Predictive factors of surgical site infection after hysterectomy for endometrial carcinoma: a retrospective analysis.BMC surgery · 2021Article
- Pain after laparoscopic surgery: Focus on shoulder-tip pain after gynecological laparoscopic surgery.Journal of the Chinese Medical Association : JCMA · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe endometrial carcinoma (EC) is the most frequently occurring female genital cancer. The authors performed this network meta-analysis to compare operative time and the incidence of bowel injury and wound infection of 3 operative approaches (laparoscopy, laparotomy, and laparoscopic-assisted vaginal hysterectomy [LAVH]) in the treatment of EC.
methodsThe Cochrane Library, PubMed, and Embase databases were searched. Randomized controlled trials (RCTs) for EC from the day of databases establishment to February 2017 were included. Direct and indirect evidences were combined to calculate the combined weighted mean difference (WMD) or odd ratio values and the surface under the cumulative ranking curve (SUCRA) value of 3 operative approaches in the treatment of EC.
resultsA total of 9 qualified RCTs were included into the study. The results showed that laparotomy had a shorter-operative time than LAVH (WMD = -40.36, 95% confidence interval = -75.03 to -2.57). However, there was no significant difference in the incidence of bowel injury and wound infection among 3 operative approaches. Besides, the SUCRA values indicated that laparotomy had the shortest operative time but the incidence of bowel injury and wound infection was relatively higher.
conclusionThe results from this study indicate that laparotomy had highest incidence of bowel injury and wound infection but shortest operative time among 3 operative approaches in the treatment of EC.
Indexed as
Identifiers
What 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.