Comparison of venturi and peristaltic based phacoemulsification efficiency in routine femtosecond laser cataract surgery
Bibliographic record
Abstract
OBJECTIVE: To compare the efficiency of venturi and peristaltic pump phacoemulsification systems in patients undergoing routine laser cataract surgery. DESIGN: Single center, nonrandomized clinical study. PARTICIPANTS: The study compared consecutive eyes with moderate nuclear sclerosis undergoing routine laser cataract surgery at the Outpatient Eye Center, Mercy Health System, Springfield, MO, USA. METHODS: Each surgery used the same femtosecond laser settings. Surgeries were performed with either a venturi or peristaltic vacuum system by a single surgeon (WJS). The EFX, percent power, ultrasound time (UST), the total time that the phaco tip was in the eye (phaco tip in/out time, PIOT), and the surgery time (speculum in/out time) were recorded. Exclusions and intraoperative complications were also analyzed. RESULTS: 995 eyes were included in the study. The EFX in the venturi eyes (1.7 ± 1.3; n = 521) compared to peristaltic eyes (2.1 ± 1.4; n = 474) was lower (p < 0.0001). Similarly, the UST in the eyes performed with the venturi system versus the peristaltic system was reduced (32.4 ± 22.3 s vs 40.7± 25.7 s; p < 0.0001). The PIOT in the venturi group compared to the peristaltic group was less (71.1 ± 31.1 sec vs 79.1 ± 36.1 s; p = 0.0002). The case time (speculum in/out time) was lower for the venturi eyes (307.2 ± 68.8 s vs. 311.6 ± 53.6 s; p = 0.268). CONCLUSION: In eyes undergoing routine laser cataract surgery, the use of the venturi pump system was more efficient compared to the peristaltic pump system based on energy use and time, and there was no significant difference in complications.
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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 | 0.001 | 0.006 |
| 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) | 0.001 | 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".