ArticleCureus2024
Incidental Dural Tears During Lumbar Spine Surgery: Prevalence and Evaluation of Management Outcomes.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 1 citations in OpenAlex.
- Tubular spinal micro decompression surgery with integrated 2D camera visualization: initial experience and feasibility in Tanzania.Acta neurochirurgica · 2026Article
- A systematic review of biportal endoscopic spinal surgery with interbody fusion.Asian spine journal · 2025Article
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
introductionIncidental dural tears (IDTs) are sometimes observed as an intraoperative complication associated with lumbar spine surgery. Commonly, this complication is recognized and repaired during surgery, but if it is undiagnosed or inadequately treated, a variety of consequences may occur. Many techniques have been developed to treat cerebrospinal fluid (CSF) leakage, and each has its limitations. Objectives: To assess the prevalence of incidental dural tears in lumbar spine surgeries and evaluate the outcomes of the sandwich technique in the management of this complication.
methodsA total of 92 patients who underwent lumbar spine surgery at the Royal Rehabilitation Center in Amman from January 2018 to December 2021 were retrospectively reviewed. Patients were divided into two groups: group A (patients without IDT) and group B (patients with IDT), where group B was repaired using the sandwich technique. The follow-up period was six months. Further, the sandwich technique involves repairing the dural defect with interlocking sutures, painting medical glue around the dural incision, covering this with gelatin sponge, and finally covering the gelatin sponge with medical glue again.
resultsThe overall prevalence of IDT in the study group was 14.1%. IDT was more common among elderly patients above the age of 60 (17.2%), females (16.7%), patients with multiple lumbar levels treated (66.7%), open approaches (21%), and those who had previous spinal surgery (72.7%). Most IDTs were diagnosed and managed intraoperatively (84.6%). Among those patients, only one complained of a surgical site infection. Patients in group B had a significantly higher postoperative length of hospital stay, amount of drainage, and operative time compared to group A (P<0.001). Regarding postoperative pain, patients in group B had significantly higher pain on the Numerical Pain Scale at day three post-operation compared to patients in group A (P<0.001).
conclusionBased on our results, the sandwich technique was effective in the management and prevention of CSF leakage. Further prospective studies with long-term follow-up are needed to confirm our findings.
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.