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Record W3176291970 · doi:10.4081/aiua.2021.2.241

Pulsed fluoroscopy in retrograde urethrograms

2021· article· en· W3176291970 on OpenAlexaff
Hazem Elmansy, Waleed Shabana, Radu Rozenberg, Abdulrahman Ahmad, Ahmed Kotb, Amer Al Aref, Walid Shahrour

Bibliographic record

VenueArchivio Italiano di Urologia e Andrologia · 2021
Typearticle
Languageen
FieldMedicine
TopicUrological Disorders and Treatments
Canadian institutionsNOSM University
Fundersnot available
KeywordsFluoroscopyMedicineRadiation exposureDemographicsRadiologyNuclear medicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: Retrograde urethrogram (RUG) is one of the corner stones for the reconstructive urologist. With hundreds of RUGs being performed yearly in busy reconstructive center, the concern for radiation exposure to the patient and the medical personnel becomes important. We propose the use of pulsed fluoroscopy to decrease the radiation exposure for patient and medical personnel. METHODS: Patients presenting to our center with urethral strictures between March 2016 and March 2019 were included in our study. The fluoroscopy machine was set for pulsed fluoroscopy at a setting of 4 pulses per second. Patient information including demographics, pre-operative diagnosis, Intra-op findings, and fluoroscopy time were recorded. RUG was performed to localize the stricture pre-operatively and post-operatively. RESULTS: A total of 185 RUG were performed between March 2016 and March 2019. The median age was 63 (14-81). The remaining 154 RUG had 77 performed pre-operatively and 77 performed post-operatively. Pathology was identified in 77 patients. Intra-operative confirmation of pre-operative finding was found in 76 patients (98.7%). Median fluoroscopy time was found to be 2.43 seconds (0.5 sec- 6.5 sec). CONCLUSIONS: Pulsed fluoroscopy reduces the radiation exposure in RUG without a reduction in the diagnostic capacity of the test. Reduction of fluoroscopy can have beneficial cumulative effect as per the ALARA principle for patients and medical personnel. Further studies with randomized control trials could be of great benefit.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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
Published2021
Admission routes1
Has abstractyes

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