Effect of cryotherapy on pain scores and satisfaction levels of patients in cataract surgery under topical anesthesia: a prospective randomized double-blind trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of cryotherapy on pain scores and satisfaction levels of patients during cataract surgery under topical anesthesia. Eighty patients aged between 55 and 75 years scheduled for cataract surgery were randomly allocated to two study groups to receive topical anesthesia with cryotherapy (TC) or topical anesthesia alone (T) groups. Visual analog pain scores, patient satisfaction level, hemodynamic parameters, and quality of operating conditions were recorded. RESULTS: Cryotherapy significantly reduced VAS pain scores during surgery (P = 0.014). Although no significant difference in postoperative pain scores, opioid consumption, heart rate, and mean arterial blood pressure was seen in the postoperative period. The surgeon reported better quality of operating conditions in the TC group (P = 0.018). Cryotherapy as a complementary method with topical anesthesia reduced pain scores of patients during surgery. It also produced a better quality of operating conditions for surgeons. There was no significant difference in either postoperative pain scores or opioid consumption. Trial registration This trial was registered at Iranian clinical trial registering: IRCT registration number: IRCT2017052734091N2.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".