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Record W2589090321 · doi:10.1213/ane.0000000000001781

Association Between Anesthesiology Volumes and Early and Late Outcomes After Cystectomy for Bladder Cancer: A Population-Based Study

2017· article· en· W2589090321 on OpenAlexaffabout
Melanie Jaeger, D. Robert Siemens, Xuejiao Wei, P. Peng, Christopher M. Booth

Bibliographic record

VenueAnesthesia & Analgesia · 2017
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsCystectomyMedicineQuartileBladder cancerProportional hazards modelAnesthesiologyPopulationPerioperativeLogistic regressionSurgeryUrologyCancerInternal medicineAnesthesiaConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Hospital and surgeon volume are related to postoperative complications and long-term survival after radical cystectomy. Here, we describe the relationships between these provider characteristics and anesthesiologist volumes on early and late outcomes after radical cystectomy for bladder cancer. METHODS: Records of treatment and surgical pathology reports were linked to the population-based Ontario Cancer Registry to identify all patients with radical cystectomy in Ontario during 1994 to 2008. Volume was divided into quartiles and determined on the basis of mean annual number of hospital/surgeon/anesthesiologist radical cystectomy cases during a 5-year study period. A composite anesthesiologist volume also was used and defined as major colorectal procedures in addition to radical cystectomy given the similar complexity of these cases. Logistic and Cox proportional hazards regression models were used to explore the associations between volume and outcomes while adjusting for potential patient-, disease-, and system-related confounders. The primary outcomes were postoperative readmission rates, postoperative mortality, and 5-year survival. RESULTS: The study included 3585 patients with radical cystectomy between 1994 and 2008. Median annual anesthesiologist radical cystectomy volume was 1 (maximum 8.8 cases/year); lowest volume quartile (Q1) <0.6 cases/year and highest volume quartile (Q4) >1.4 cases/year. The median annual composite anesthesiologist volume was 9 radical cystectomy and colorectal cases (Q1 [range 0.2-6.4 cases/year], Q4 [range 11.8-29.2 cases/year]); subsequent analyses used this composite volume. Anesthesiologist volume was associated with readmission rates at 30 days (P = .02, Q1 mean = 27% vs Q4 mean = 21%) and at 90 days (P = .01, Q1 mean = 39% vs Q4 mean = 31%). In multivariable analysis, including the adjustment for surgeon and hospital volume, the cohort of anesthesiologists who performed the lowest volume of cases annually (Q1) was associated with greater rates of readmission at 30 days (OR 1.36, 95% confidence interval [CI], 1.09-1.71, P = .04) and at 90 days (OR 1.36, 95% CI, 1.11-1.66, P = .03). Anesthesiologist volumes were not associated with postoperative mortality or long-term survival. CONCLUSIONS: Anesthesiologist case volume for radical cystectomy was low, reflecting the lack of subspecialization in urologic procedures in routine clinical practice. Lower volume anesthesia providers were associated with higher readmission rates after radical cystectomy. Further studies are needed to validate this finding and to identify the processes that may explain an association between provider volume and patient outcome.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.303
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 source (direct Gemma or distilled Codex), 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

Citations18
Published2017
Admission routes2
Has abstractyes

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