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Record W2416442771

Laparoscopic robotic pyeloplasty using the Zeus Telesurgical System.

2004· article· en· W2416442771 on OpenAlexaffabout
Patrick Luke, Andrew R. Girvan, Mohammed Al Omar, Kenneth A. Beasley, Michael Carson

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicinePyeloplastySurgeryAnastomosisPercutaneousUrinary systemHydronephrosisInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

We present the initial clinical experience using a robot to perform a laparoscopic dismembered pyeloplasty at a Canadian centre. Five patients were confirmed to have ureteropelvic junction obstructions through nuclear renography, cross sectional imaging and intravenous pyelography. After performing a retrograde ureteropyelography and double J stent placement, laparoscopic dismembered pyeloplasty was performed by a single surgeon at a remote workstation using the ZeusTM Telepresence Surgery System (Intuitive Surgicala). The mean total operative time was 225+/-48 minutes, anastomotic time was 71+/-16 minutes, and the mean time required to set-up the robot was 30+/-17 minutes. The estimated blood loss was less than 100 ml in each case. A mean total of 22+/-10 mg of morphine sulfate equivalents were used for analgesia, and the patients were discharged home after a mean of 58+/-10 hrs. There were no robotic failures, and all evaluable patients are free of pain and demonstrable obstruction. One patient developed a delayed urine leak, which resolved with percutaneous drainage. The robot provides the ability to perform complicated operations with precision through elimination of tremor, scaling of motion, and through the use of 'wristed' instruments that enhance the freedom of movement normally limited by straight-shafted laparoscopic needle drivers. The development of robotic telesurgery is still in its infancy, and the significance of its role in urologic surgery continues to be evaluated.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.031
GPT teacher head0.244
Teacher spread0.213 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2004
Admission routes2
Has abstractyes

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