Development and Testing of a Mobile Phone App for Risk Estimation of Gas Volume Expansion and Intraocular Pressure Elevation in Patients With Intravitreous Gas or Air Tamponade: Interobserver Assessment Study
Bibliographic record
Abstract
BACKGROUND: ), patients with an intravitreous remnant of gas or air will be under high risk of intraocular pressure (IOP) elevation and subsequent vision loss owing to the expanded intravitreous gas or air when traveling post operation to a place with a significantly higher altitude. We always explain to patients why postoperative travel is potentially risky. Emergency cases of elevated IOP caused by postoperative traveling would sometimes come to surgeons. However, there have been few disease education or reference tools for both the surgeons and patients to have better communication. OBJECTIVE: The aim of this study was to introduce and evaluate a mobile phone app developed by surgeons (the authors) for preliminary risk estimation of volume expansion and IOP elevation in patients with intravitreous gas or air when traveling to a place of higher altitude. METHODS: ) was the theoretical basis of the app. Intravitreous gas or air volume and altitude values were independent factors to deduce the risk report. Consecutive patients underwent vitrectomy, and those with an intravitreous remnant of gas or air were recruited. The surgeons judged the vertical height of the fluid/gas interface through the dilated pupil; the patients were instructed to judge it according to their visual field when looking straight ahead and line it out on a chart included in the app. Finally, all the patients were required to fill a Likert scale-based questionnaire with 2 main items to evaluate the participants' user experience and attitudes toward the app. RESULTS: A total of 50 patients were included (30 males and 20 females). All patients could independently operate the app to complete the test. The median heights of the fluid/gas interface independently judged by the surgeon and patients were 40% (range: 10%-75%) and 41% (range: 9%-78%), respectively (P=.63). The median altitude of the participants' destinations was 150.0 m (range: 0-3490 m). The Bland-Altman analysis revealed a good agreement between the surgeons' and patients' judgments (bias of -0.3%), with 95% limits of agreement of -5.8% to 5.3%. Overall, the Likert scale revealed a positive attitude from the patients toward the app. CONCLUSIONS: The app is reliable for patients to have preliminary risk estimation of intravitreous gas or air volume expansion and IOP elevation if travel to a place of higher altitude is planned. The surgeons could also use it as a platform for better disease communication.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".