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Record W2751634293 · doi:10.1016/j.jcma.2017.07.001

Pupillary response to nitrous oxide administration in cataract surgery under general anesthesia

2017· article· en· W2751634293 on OpenAlexaff
Mansoor Masjedi, Alireza Ghanbari, Hossein Haddad Bakhodaei, Tahere Jowkar, Vahhab Hosseni, Mahnaz Rakhshan

Bibliographic record

VenueJournal of the Chinese Medical Association · 2017
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsCommunity Based Research Centre
Fundersnot available
KeywordsMedicineAnesthesiaCataract surgeryNitrous oxideIsofluraneTracheal intubationPupillary responsePupilIntubationPhacoemulsificationSurgeryVisual acuity

Abstract

fetched live from OpenAlex

BACKGROUND: Despite recent innovations in cataract surgery, pupillary diameter is one of the most important affecting factors in outcome of this surgery. As cataract surgery is performed ideally when the pupil is sufficiently dilated, anesthesia may contribute significantly in success or failure of this operation. This study was performed to evaluate the effect of nitrous oxide on pupillary diameter in cataract surgery under general anesthesia. METHODS: Forty patients with cataract, scheduled for operation under general anesthesia, were randomly allocated into two groups. After induction of anesthesia, anesthesia was maintained with isoflurane and nitrous oxide - oxygen (60%-40%) in group 1 versus oxygen 100% in group 2. Pupillary diameter, heart rate and blood pressure were monitored and recorded, before induction of anesthesia, just before tracheal intubation, and one and 5 min after laryngoscopy and tracheal intubation. RESULTS: Statistical analysis of the results using Mann-Whitney test showed no significant difference in pupillary diameter between two the groups. CONCLUSION: According to the results of this study, nitrous oxide has no effect on pupillary diameter of patients under general anesthesia, so it could be safety used, in this regard, in ophthalmic operations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.297
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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