ArticleInsights into imaging2015
Multidetector CT imaging of complications after laparoscopic nephron-sparing surgery.
Article in Insights into imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 7 citations in OpenAlex.
- Pre-gerotal fat patch-A novel alternative to haemostatic agents during partial nephrectomy.BJUI compass · 2023Article
- Complications after Nephron-sparing Interventions for Renal Tumors: Imaging Findings and Management.Radiographics : a review publication of the Radiological Society of North America, Inc · 2023Article
- Application of Contrast-Enhanced Ultrasonography (CEUS) in the Assessment of Kidney Wound Recovery After Nephron-Sparing Surgery.Cancer management and research · 2021Article
- Surgical margin follow-up after nephron-sparing surgery: the possible role of CEUS.Journal of ultrasound · 2020Article
- Renal artery embolization for iatrogenic renal vascular injuries management: 5 years' experience.The British journal of radiology · 2020Article
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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeLaparoscopic nephron-sparing surgery (L-NSS) is increasingly performed to treat localised renal lesions. However, the associated morbidity is non-negligible, with a rate of major complications approaching 10 %. METHODS AND
resultsThis paper provides an overview of indications, surgical techniques and results of L-NSS; explains the incidence, risk factors and manifestations of postoperative complications; discusses the preferred multidetector computed tomography (CT) acquisition techniques; illustrates the appearance of normal postoperative images following L-NSS; and reviews, with example images, the most common and unusual iatrogenic complications. These include haematuria, haemorrhage, vascular injuries, infections and urinary leaks. Most emphasis is placed on CT, which provides rapid, reliable triage and follow-up of iatrogenic complications after L-NSS, identifying occurrences that require transarterial embolisation or repeated surgery.
conclusionsMultidetector CT allows precise assessment of the surgical resection site; detection of pneumoperitoneum and subcutaneous emphysema; quantification of retroperitoneal blood; and identification of active bleeding, pseudoaneurysms, arterio-venous fistulas, abscess collections and extravasated urine. TEACHING POINTS: • Laparoscopic nephron-sparing surgery (NSS) is increasingly performed to treat renal lesions. • Radiologists are increasingly requested to investigate suspected post-surgical NSS complications. • Post-NSS complications include haemorrhage, haematuria, vascular injuries, infections and urinary leaks. • Multidetector CT allows choice between conservative treatment, transarterial embolisation or surgery.
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.