Prospective Comparative Study on Endothelial Corneal Cell After Cataract Surgery Using Torsional vs Longitudinal Phacoemulsification
Bibliographic record
Abstract
Objectives: Our aim was to compare endothelial corneal cell changes after cataract surgery performed with Torsional and Longitudinal phacoemulsification in patient with senile cataract. Methods: In this prospective study, the patients were divided into two groups, 24 eyes underwent cataract surgery using Torsional (OZil Infiniti Vision System, Alcon) and 23 eyes using Longitudinal phacoemulsification (Stelaris, Bausch & Lomb). Preoperative, 1 day, and 1-week post-operative examinations on endothelial corneal cells were performed using specular microscope. Cataracts were subdivided according to the LOCS III grading of nucleus. Intraoperative parameters using phacoemulsification time were evaluated. Results: On the results of CCT at 1 day and 1-week post-operative, there were significant changes in group Torsional and Longitudinal 601±68.67; 562.22±45.48 (p=0.033) and 561,71±36,37; 519.52±79.93 (p = 0.015). However, there were no significant changes of CD, CV, HEX 1 day and 1 week post operatively between two groups. The phacoemulsification time was lower in group Torsional 17.11±15.86 seconds than group Longitudinal 18.53±15.46 seconds (p=0.595) but not significantly different. Conclusions: Torsional phacoemulsification outperforms the Longitudinal with a lower phacoemulsification time on soft and medium cataracts, but the differences were not significant. Torsional caused more corneal edema at 1 day and 1 week postoperative significantly and more endothelial cell losses but insignificantly.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".