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Record W2963597154 · doi:10.1177/2054358119857718

Perioperative Complications During Living Donor Nephrectomy: Results From a Multicenter Cohort Study

2019· article· en· W2963597154 on OpenAlexafffundabout
Carlos García-Ochoa, Liane S. Feldman, Christopher Nguan, Mauricio Monroy‐Cuadros, Jennifer Arnold, Neil Boudville, Meaghan S. Cuerden, Christine Dipchand, Michael K Eng, John S. Gill, William A. Gourlay, Martin Karpinski, Scott Klarenbach, Greg Knoll, Krista L. Lentine, Charmaine E. Lok, Patrick Luke, G. V. Ramesh Prasad, Alp Şener, Jessica M. Sontrop, Leroy Storsley, Darin Treleaven, Amit X. Garg

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2019
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsMcMaster UniversityUniversity of AlbertaOttawa HospitalUniversity of ManitobaUniversity of TorontoDalhousie UniversityMcGill UniversityUniversity of CalgaryUniversity of British ColumbiaWestern University
FundersCanadian Institutes of Health ResearchAstellas Pharma
KeywordsMedicineNephrectomyPerioperativeCohortCohort studyNephrologyMulticenter studySurgeryInternal medicineIntensive care medicineKidney

Abstract

fetched live from OpenAlex

BACKGROUND: While living kidney donation is considered safe in healthy individuals, perioperative complications can occur due to several factors. OBJECTIVE: We explored associations between the incidence of perioperative complications and donor characteristics, surgical technique, and surgeon's experience in a large contemporary cohort of living kidney donors. DESIGN: Living kidney donors enrolled prospectively in a multicenter cohort study with some data collected retrospectively after enrollment was complete (eg, surgeon characteristics). SETTING: Living kidney donor centers in Canada (n = 12) and Australia (n = 5). PATIENTS: Living kidney donors who donated between 2004 and 2014 and the surgeons who performed the living kidney donor nephrectomies. MEASUREMENTS: Operative and hospital discharge medical notes were collected prospectively, with data on perioperative (intraoperative and postoperative) information abstracted from notes after enrollment was complete. Complications were graded using the Clavien-Dindo system and further classified into minor and major. In 2016, surgeons who performed the nephrectomies were invited to fill an online survey on their training and experience. METHODS: Multivariable logistic regression models with generalized estimating equations were used to compare perioperative complication rates between different groups of donors. The effect of surgeon characteristics on the complication rate was explored using a similar approach. Poisson regression was used to test rates of overall perioperative complications between high- and low-volume centers. RESULTS: Of the 1421 living kidney donor candidates, 1042 individuals proceeded with donation, where 134 (13% [95% confidence interval (CI): 11%-15%]) experienced 142 perioperative complications (55 intraoperative; 87 postoperative). The most common intraoperative complication was organ injury and the most common postoperative complication was ileus. No donors died in the perioperative period. Most complications were minor (90% of 142 complications [95% CI: 86%-96%]); however, 12 donors (1% of 1042 [95% CI: 1%-2%]) experienced a major complication. No statistically significant differences were observed between donor groups and the rate of complications. A total of 43 of 48 eligible surgeons (90%) completed the online survey. Perioperative complication rates did not vary significantly by surgeon characteristics or by high- versus low-volume centers. LIMITATIONS: Operative and discharge reporting is not standardized and varies among surgeons. It is possible that some complications were missed. The online survey for surgeons was completed retrospectively, was based on self-report, and has not been validated. We had adequate statistical power only to detect large effects for factors associated with a higher risk of perioperative complications. CONCLUSIONS: This study confirms the safety of living kidney donation as evidenced by the low rate of major perioperative complications. We did not identify any donor or surgeon characteristics associated with a higher risk of perioperative complications. TRIAL REGISTRATIONS: Living Kidney Donor Study (https://clinicaltrials.gov/ct2/show/NCT00936078).

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)0.002
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 score0.015
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.011
GPT teacher head0.270
Teacher spread0.259 · 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

Citations38
Published2019
Admission routes3
Has abstractyes

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