A Systematic Review and Meta‐Analysis of Management Options for Empty Nose Syndrome: A Proposed Management Algorithm
Bibliographic record
Abstract
OBJECTIVE: Empty nose syndrome (ENS) is an acquired condition characterized by paradoxical nasal obstruction and sensation of nasal dryness often accompanied by psychological disorders such as depression or anxiety, typically occurring after the loss of inferior turbinate tissue or volume in the setting of prior sinonasal surgery. This review aims to identify and evaluate the reported management options. DATA SOURCES: PubMed, Scopus, and Web of Science. REVIEW METHODS: The terms "empty nose syndrome" OR "atrophic rhinitis" were used in a systematic search of original articles since the year 1990, yielding 1432 individual studies. These were screened on the Covidence platform for inclusion if any intervention was reported for the treatment of ENS. A pooled analysis of standardized mean differences (SMDs) combined with a random effects model was employed to report outcomes in Empty Nose 6-Item Questionnaire (ENS6Q), Sino-Nasal Outcome Test (SNOT), anxiety, and depression scores. RESULTS: A total of 35 articles were included, comprising 957 individual ENS patients. Surgical interventions mostly in the form of meatus augmentation implants accounted for 26 out of the 36 articles. The remaining ten articles included medical and psychological management options. SMD in SNOT, ENS6Q, anxiety, and depression scores were reported and demonstrated statistically significant improvements in follow-up periods of up to 1 year. All articles reported favorable outcomes following their chosen interventions. CONCLUSION: There is a paucity of evidence on the management of ENS and an absence of randomized controlled trials. Surgical intervention appears to be the current mainstay of treatment, but there is a potential role for psychological and medical management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".