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Record W2977709582

Meta-analysis of comparison two decompression surgical treatment for syringomyelia associated with Chiari Imalformation

2013· article· en· W2977709582 on OpenAlexaboutno aff
SU Xin-we

Bibliographic record

VenueZhonghua linchuang yishi zazhi · 2013
Typearticle
Languageen
FieldMedicine
TopicSpinal Dysraphism and Malformations
Canadian institutionsnot available
Fundersnot available
KeywordsForamen magnumSyringomyeliaMedicineDecompressionSurgeryMagnetic resonance imagingRadiology
DOInot available

Abstract

fetched live from OpenAlex

Objective To evaluate the therapeutic effects of foramen magnum decompression and foramen magnum decompression add cerebellar tonsillar resection on syringomyelia associated with chiari malformation. Methods Searched the English or Chinese data base on line, according to inclusion and exclusion criteria collect the literature, evaluate the included studies using the Newcastle-Ottawa Scale, then the data were analyzed using Revman 5.0 software. Results Eight studies involving 714 patients were included. The results of meta-analyses: there was no significant difference in short-term clinical improvement between two surgical treatments(P=0.29); Compared the rate of fever, there was statistically significant differences(RR=0.54, 95% CI 0.31 to 0.96, P=0.04); Postoperative follow-up the clinical improvement, there was statistically significant differences(OR=0.51, 95% CI 0.35 to 0.74, P=0.0005); Follow up the syringomyelia disappear rate there was statistically significant differences(OR=0.21, 95% CI 0.12 to 0.37, P0.00001). Conclusions Compared with Foramen magnum decompression, Foramen magnum decompression add cerebellar tonsillar resection have a good result of the follow-up clinical improvement and syringomyelia disappear rate, but have a high rate of fever. There was no difference in short-term clinical improvement between two surgical treatments. Because the lower quality of included studies, a large sample studies are need to further checking the conclusions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.109
GPT teacher head0.357
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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