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Record W4402513982 · doi:10.1186/s12882-024-03753-1

Association of chronic kidney disease with postoperative outcomes: a national surgical quality improvement program (NSQIP) multi-specialty surgical cohort analysis

2024· article· en· W4402513982 on OpenAlexaff
Carlos Riveros, Sanjana Ranganathan, Yash Shah, Emily Huang, Jiaqiong Xu, Enshuo Hsu, Michael Geng, Siqi Hu, Zachary Melchiode, Brian J. Miles, Nestor F. Esnaola, Zachary Klaassen, Angela Jerath, Christopher J.D. Wallis, Raj Satkunasivam

Bibliographic record

VenueBMC Nephrology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health NetworkMount Sinai HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineSpecialtyNephrologyCohortKidney diseaseDiseaseInternal medicineGeneral surgerySurgeryFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic kidney disease (CKD) is associated with higher incidence of major surgery. No studies have evaluated the association between preoperative kidney function and postoperative outcomes across a wide spectrum of procedures. We aimed to evaluate the association between CKD and 30-day postoperative outcomes across surgical specialties. METHODS: We selected adult patients undergoing surgery across eight specialties. The primary study endpoint was major complications, defined as death, unplanned reoperation, cardiac complication, or stroke within 30 days following surgery. Secondary outcomes included Clavien-Dindo high-grade complications, as well as cardiac, pulmonary, infectious, and thromboembolic complications. Multivariable regression was performed to evaluate the association between CKD and 30-day postoperative complications, adjusted for baseline characteristics, surgical specialty, and operative time. RESULTS: In total, 1,912,682 patients were included. The odds of major complications (adjusted odds ratio [aOR] 2.14 [95% confidence interval (CI): 2.07, 2.21]), death (aOR 3.03 [95% CI: 2.88, 3.19]), unplanned reoperation (aOR 1.57 [95% CI: 1.51, 1.64]), cardiac complication (aOR 3.51 [95% CI: 3.25, 3.80]), and stroke (aOR 1.89 [95% CI: 1.64, 2.17]) were greater for patients with CKD stage 5 vs. stage 1. A similar pattern was observed for the secondary endpoints. CONCLUSION: This population-based study demonstrates the negative impact of CKD on operative outcomes across a diverse range of procedures and patients.

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)0.001
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 score0.163
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.343
Teacher spread0.323 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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