Association Between Hematological Indices of Inflammation and Pathogenesis and Prognosis of Sudden Sensorineural Hearing Loss: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Chronic inflammation has been proposed as a contributing factor in the pathogenesis of sudden sensorineural hearing loss (SSNHL). The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV) are well-established indices of inflammation, but their roles in SSNHL pathogenesis and prognosis remain controversial. This meta-analysis aimed to explore these associations. A systematic review was performed by 2 independent investigators across PubMed, Web of Science, Cochrane Library, and Embase databases. The quality of included studies was assessed using the Newcastle-Ottawa Scale. Twenty-six studies including 2392 SSNHL patients and 1865 controls were included. Recovery data were available for 1343 patients, of whom 785 recovered and 558 did not. Meta-analysis revealed that both NLR (standardized mean difference [SMD]=1.082, 95% CI=0.949, 1.216, P < .001) and PLR (SMD=0.516, 95% CI=0.333, 0.700, P < .001) were significantly elevated in SSNHL patients compared to controls. MPV (SMD=1.103, 95% CI=0.820, 1.483, P=.516) showed no significant difference. Additionally, higher NLR (SMD=-0.472, 95% CI=-0.784, -0.160, P=.003) and PLR (SMD=-0.327, 95% CI=-0.630, -0.023, P=.035) were associated with non-recovery in SSNHL, whereas differences in MPV (SMD=-0.352, 95% CI=-0.881, 0.177, P=.192) were not statistically significant. NLR and PLR may be involved in the pathogenesis of SSNHL and may serve as cost-effective and accessible prognostic markers.
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 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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".