A Mysterious Role of Arginine Vasopressin Levels in Ménière's Disease—Meta-analysis of Clinical Studies
Bibliographic record
Abstract
OBJECTIVE: There are contradicting claims that patients with Ménière's disease (MD) have elevated levels of arginine vasopressin (AVP). The results of published studies regarding the difference of AVP level between MD patients and non-MD control subjects are inconsistent. We propose that the discrepancy of AVP levels during different MD phases may be a potential reason. Thus, we conducted a meta-analysis to analyze the precise estimate of this hypothesis. DATA SOURCES: PubMed, Medline, and Cochrane databases from the earliest publication, up until September 2016; references from meta-analyses and related review articles. STUDY SELECTION AND DATA EXTRACTION: Clinical studies that reported AVP level in MD patients and non-MD controls were independently reviewed according to the inclusion criteria. The Newcastle-Ottawa Scale was used to assess quality of studies. DATA SYNTHESIS: Random effects model was used to calculate the weighted mean difference. CONCLUSION: Eight studies met the inclusion criteria. AVP levels of MD patients in acute phase (WMD = 2.29, 95% CI = 0.84-3.74, Z = 3.10, p = 0.002) were significantly higher than non-MD subjects. For MD patients in remission phase the difference of AVP levels between the MD patients and the non-MD controls was found (WMD = 0.54, 95% CI = -0.06 to 1.02, Z = 2.20, p = 0.03). However, AVP level was not an ideal biomarker of MD patients. Regardless of MD phase, there were no significant differences in the AVP level of MD patients (WMD = 0.27, 95% CI = -0.10 to 0.64, Z = 1.43, p = 0.15). Future investigations with larger sample sizes are needed to verify the results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.047 | 0.075 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.053 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".