Randomized Trials of Neurosurgical Interventions: A Systematic Appraisal is a research paper published in Neurosurgery (2004). On theSindex it has a DataRank of 0.500. It has been cited 27 times.
ObjectiveTo systematically appraise the study design and quality of reporting of randomized controlled trials (RCTs) on neurosurgical procedures and to identify potential defects and biases.MethodsRandomized controlled trials with at least five patients comparing any neurosurgical procedure against another procedure, nonsurgical treatment, or no treatment were retrieved from MEDLINE, EMBASE, and the Cochrane Library. We analyzed study design, quality of reporting, and trial results.ResultsThe median sample size in the 108 eligible reports was 68 patients. Ninety-nine trials (91.7%) reported inclusion and exclusion criteria, 55 (50.9%) mentioned the randomization mode, and 87 (80.6%) adequately described withdrawals, but only 31 (28.7%) described allocation concealment, only 23 (21.3%) gave power calculations, and only 20 (18.5%) were adequately powered. Significant efficacy or trend for efficacy was claimed in 46 reports (42.6%), and no difference between the compared procedures was found in 60 trials (55.6%). Trials with a larger sample size were more likely to report withdrawals (P = 0.02) and power calculations (P = 0.006). Only 14 trials (13.6%) were double-blind, and this was less frequent in longer trials (P = 0.02). Among quality criteria, only the reporting of randomization mode improved significantly over time (P = 0.015).ConclusionSeveral aspects of the design and reporting of randomized controlled trials on neurosurgical procedures can be improved. Larger, adequately powered, and accurately reported trials are needed.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.500
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.