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Record W2955585530 · doi:10.1080/00016489.2019.1632484

Treatment and recurrence of traumatic versus idiopathic benign paroxysmal positional vertigo: a meta-analysis

2019· review· en· W2955585530 on OpenAlexaboutno aff
Gang Chen, Yun Li, Junzeng Si, Xuening Zhao, Tianyang Zhang, Xiaoyan Dai, Gang Yu

Bibliographic record

VenueActa Oto-Laryngologica · 2019
Typereview
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
Fundersnot available
KeywordsBenign paroxysmal positional vertigoMedicineConfidence intervalVertigoRelative riskRetrospective cohort studyMeta-analysisInternal medicineSurgery

Abstract

fetched live from OpenAlex

Background: So far, there has been a controversy surrounding repositioning difficulty and recurrence rate between traumatic benign paroxysmal positional vertigo (t-BPPV) and idiopathic BPPV (i-BPPV).Objectives: This meta-analysis was aimed to explore whether or not the differences between t-BPPV and i-BPPV in the repositioning difficulty and recurrence rate existed.Material and methods: A literature search was performed in the databases including Pubmed, Embase, CENTRAL, which completed in 21 January 2019, with no restriction of publication language. Relative risk (RR) of number of repositioning maneuvers and the recurrence rate was calculated with its 95% confidence interval. Sensitive analysis was performed simultaneously.Results: Six retrospective cohort studies were included in our meta-analysis, including 865 t-BPPV patients and 3027 i-BPPV patients. All studies were high quality according to Newcastle-Ottawa Scale (NOS) assessment. Patients with t-BPPV required more repositioning maneuvers for resolution than those with i-BPPV (RR = 3.27, 95% CI = 1.88–5.69, p < .0001), and the recurrence rate of t-BPPV was higher than that of i-BPPV (RR = 2.91, 95% CI = 2.04–4.14, p < .00001).Conclusions and significance: Compared with i-BPPV, patients with t-BPPV require more repositioning maneuvers to resolve, and the recurrence of t-BPPV was more frequent.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.279
GPT teacher head0.370
Teacher spread0.091 · 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.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations25
Published2019
Admission routes1
Has abstractyes

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