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MP16-09 SAFETY AND EFFICACY OF TRANSURETHRAL RESECTION OF BLADDER TUMOUR COMPARING SPINAL ANAESTHESIA TO SPINAL ANAESTHESIA WITH AN OBTURATOR NERVE BLOCK: A SYSTEMATIC REVIEW AND META-ANALYSIS

2021· review· en· W3190588714 on OpenAlexaboutno aff
Anil Krishan, Angus Bruce, Shehab Khashaba, Mohamed Abouelela, Syed Ali Ehsanullah

Bibliographic record

VenueThe Journal of Urology · 2021
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSpinal anesthesiaObturator nerveCINAHLResectionMEDLINEAnesthesiaNerve blockMeta-analysisSurgeryInternal medicine

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyBladder Cancer: Non-invasive II (MP16)1 Sep 2021MP16-09 SAFETY AND EFFICACY OF TRANSURETHRAL RESECTION OF BLADDER TUMOUR COMPARING SPINAL ANAESTHESIA TO SPINAL ANAESTHESIA WITH AN OBTURATOR NERVE BLOCK: A SYSTEMATIC REVIEW AND META-ANALYSIS Anil Krishan, Angus Bruce, Shehab Khashaba, Mohamed Abouelela, and Syed Ali Ehsanullah Anil KrishanAnil Krishan More articles by this author , Angus BruceAngus Bruce More articles by this author , Shehab KhashabaShehab Khashaba More articles by this author , Mohamed AbouelelaMohamed Abouelela More articles by this author , and Syed Ali EhsanullahSyed Ali Ehsanullah More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002001.09AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: To investigate whether spinal anaesthesia with an obturator nerve block (SA+ONB) can be effectively employed for transurethral resection of bladder tumours (TURBT) during the COVID-19 pandemic to improve patient outcomes whilst also avoiding aerosol-generating procedures. We aimed to compare outcomes of TURBT using spinal anaesthesia (SA) alone versus SA+ONB in terms of rates of obturator reflex, bladder perforation, incomplete tumour resection, tumour recurrence and local anaesthetic toxicity. METHODS: We conducted a comprehensive search of electronic databases (MEDLINE, PUBMED, EMBASE, CINAHL, CENTRAL, SCOPUS, Google Scholar and Web of Science), identifying studies comparing the outcomes of TURBT using spinal anaesthesia versus spinal with an obturator nerve block. The Cochrane risk-of-bias tool for RCTs and the Newcastle-Ottawa scale for observational studies were used to assess the included studies. Random effects modelling was used to calculate pooled outcome data. RESULTS: Searches of electronic databases resulted in 107 articles, from which four randomised control trials (RCTs) and three cohort studies met the eligibility criteria, enrolling a total of 448 patients. The use of spinal anaesthesia with an obturator nerve block was associated with a significantly reduced risk of obturator reflex (p <0.00001), bladder perforation (p=0.02), incomplete resection (p <0.0001) and 12-month tumour recurrence (p=0.005). Obturator nerve block was not associated with an increased risk of local anaesthetic toxicity (0/159). CONCLUSIONS: Our meta-analysis suggests that TURBT employing spinal anaesthesia with an obturator nerve block is superior to the use of spinal anaesthesia alone. During the COVID-19 pandemic, where avoidance of aerosol-generating procedures (AGPs) such as a general anaesthesia is paramount, the use of an obturator nerve block with spinal anaesthesia is essential for the safety of both patients and staff without compromising care. Further high-quality RCTs with adequate sample sizes are required to compare the different techniques of obturator nerve block as well as comparing this method to general anaesthesia with complete neuromuscular blockade. Source of Funding: Nil © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e299-e300 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Anil Krishan More articles by this author Angus Bruce More articles by this author Shehab Khashaba More articles by this author Mohamed Abouelela More articles by this author Syed Ali Ehsanullah More articles by this author Expand All Advertisement Loading ...

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.023
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.074
GPT teacher head0.358
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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