Smartphone adapters for flexible Nasolaryngoscopy: A systematic review
Bibliographic record
Abstract
BACKGROUND: Flexible nasolaryngoscopy is an essential component of the otolaryngological physical exam. Historically, the ability to create and share video recordings of these endoscopic exams has been limited by poor mobility of fixed endoscopy towers. The advent of smartphone endoscope adapters has allowed physicians to create and share video recordings of endoscopy in a wide variety of locations that would not have previously been feasible. This paper sought to review the literature on the effect of smartphone endoscope adapters on patient care, patient satisfaction, and resident learning. METHODS: This systematic review was conducted according to PRISMA guidelines. A systematic literature search was performed for all relevant English language studies (1946-2017) using Ovid MEDLINE, PubMed, and EMBASE. The study protocol was registered with the PROSPERO database. RESULTS: A total of 91 abstracts were identified and screened by two independent reviewers. Based on inclusion and exclusion criteria, three studies were selected and subjected to full-text extraction as well as quality assessment. These studies demonstrated high diagnostic accuracy and quality of smartphone adapter-recorded videos, and a benefit of these devices on resident education. Due to the heterogeneity of included studies' methods and measures, a meta-analysis was not possible, so a qualitative synthesis of the literature results was performed. CONCLUSION: Despite a paucity of data on the subject, the present study provided a comprehensive review of the literature, and suggested overall high diagnostic accuracy, quality, and enhancement of resident education with the use of smartphone endoscope adapters for flexible nasolaryngoscopy. TRIAL REGISTRATION: CRD42018086714.
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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".