Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 596

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Bedside Tool for Predicting the Risk of Postoperative Dialysis in Patients Undergoing Cardiac Surgery

Open access
Mehta, Rajendra H., Grab, Joshua D., O’Brien, Sean M., Bridges, Charles R., Gammie, James S., Haan, Constance K., Ferguson, T. Bruce, Peterson, Eric D.·2006·Circulation

Abstract

Background— Estimation of an individual patient’s risk for postoperative dialysis can support informed clinical decision making and patient counseling. Methods and Results— To develop a simple bedside risk algorithm for estimating patients’ probability for dialysis after cardiac surgery, we evaluated data of 449 524 patients undergoing coronary artery bypass grafting (CABG) and/or valve surgery and enrolled in >600 hospitals participating in the Society of Thoracic Surgeons National Database (2002–2004). Logistic regression was used to identify major predictors of postoperative dialysis. Model coefficients were then converted into an additive risk score and internally validated. The model also was validated in a second sample of 86 009 patients undergoing cardiac surgery from January to June 2005. Postoperative dialysis was needed in 6451 patients after cardiac surgery (1.4%), ranging from 1.1% for isolated CABG procedures to 5.1% for CABG plus mitral valve surgery. Multivariable analysis identified preoperative serum creatinine, age, race, type of surgery (CABG plus valve or valve only versus CABG only), diabetes, shock, New York Heart Association class, lung disease, recent myocardial infarction, and prior cardiovascular surgery to be associated with need for postoperative dialysis ( c statistic=0.83). The risk score accurately differentiated patients’ need for postoperative dialysis across a broad risk spectrum and performed well in patients undergoing isolated CABG, off-pump CABG, isolated aortic valve surgery, aortic valve surgery plus CABG, isolated mitral valve surgery, and mitral valve surgery plus CABG ( c statistic=0.83, 0.85, 0.81, 0.75, 0.80, and 0.75, respectively). Conclusions— Our study identifies the major patient risk factors for postoperative dialysis after cardiac surgery. These risk factors have been converted into a simple, accurate bedside risk tool. This tool should facilitate improved clinician–patient discussions about risks of postoperative dialysis.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1161/circulationaha.106.635573

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 596

Metadata

Authors
Mehta, R. H., Grab, J. D., O’Brien, S. M., Bridges, C. R., Gammie, J. S., Haan, C. K., Ferguson, T. B., & Peterson, E. D.
Venue
Circulation
Published
2006-11-21
Volume
114
Issue
21
Pages
2208-2216
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
OpenAlex
W2004191596
Cited by
596
References
1
FWCI
18.08
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Bedside Tool for Predicting the Risk of Postoperative Dialysis in Patients Undergoing Cardiac Surgery. https://app.cochat.ai/papers/10.1161/circulationaha.106.635573
The paper
Mehta, R. H., Grab, J. D., O’Brien, S. M., Bridges, C. R., Gammie, J. S., Haan, C. K., Ferguson, T. B., & Peterson, E. D. (2006). Bedside Tool for Predicting the Risk of Postoperative Dialysis in Patients Undergoing Cardiac Surgery. Circulation. https://doi.org/10.1161/circulationaha.106.635573

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.