The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Derivation and Validation of a Simplified Predictive Index for Renal Replacement Therapy After Cardiac Surgery
Abstract
CONTEXT: A predictive index for renal replacement therapy (RRT; hemodialysis or continuous venovenous hemodiafiltration) after cardiac surgery may improve clinical decision making and research design. OBJECTIVES: To develop a predictive index for RRT using preoperative information. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort of 20 131 cardiac surgery patients at 2 hospitals in Ontario, Canada. The derivation cohort consisted of 10,751 patients at Toronto General Hospital (1999-2004). The validation cohorts consisted of 2566 patients at Toronto General Hospital (2004-2005) and 6814 patients at Ottawa Heart Institute (1999-2003). MAIN OUTCOME MEASURE: Postoperative RRT. RESULTS: RRT rates in the derivation, Toronto validation, and Ottawa validation cohorts were 1.3%, 1.8%, and 2.2%, respectively. Multivariable predictors of RRT were preoperative estimated glomerular filtration rate, diabetes mellitus requiring medication, left ventricular ejection fraction, previous cardiac surgery, procedure, urgency of surgery, and preoperative intra-aortic balloon pump. The predictive index was scored from 0 to 8 points. An estimated glomerular filtration rate less than or equal to 30 mL/min was assigned 2 points; other components were assigned 1 point each: estimated glomerular filtration rate 31 to 60 mL/min, diabetes mellitus, ejection fraction less than or equal to 40%, previous cardiac surgery, procedure other than coronary artery bypass grafting, intra-aortic balloon pump, and nonelective case. Among the 53% of patients with low risk scores (< or =1), the risk of RRT was 0.4%; by comparison, this risk was 10% among the 6% of patients with high-risk scores (> or =4). The predictive index had areas under the receiver operating characteristic curve in the derivation, Toronto validation, and Ottawa validation cohorts of 0.81, 0.78, and 0.78, respectively. When these cohorts were stratified based on index scores, likelihood ratios for RRT were more concordant than observed RRT rates. CONCLUSIONS: RRT after cardiac surgery is predicted by readily available preoperative information. A simple predictive index based on this information discriminated well between low- and high-risk patients in derivation and validation cohorts. The index had improved generalizability when used to predict likelihood ratios for RRT.
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.
Integrity signals
Registry
Cites
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.
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
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
Hosmer, D. W., & Lemeshow, S. (2000) · doi:10.1002/0471722146 · Cited by 20,302
Prediction of Creatinine Clearance from Serum Creatinine
Cockcroft, D. W., & Gault, H. (1976) · Nephron · doi:10.1159/000180580 · Cited by 15,309
Levey, A. S., Bosch, J. P., Lewis, J. B., Greene, T., Rogers, N., Roth, D., & for the Modification of Diet in Renal Disease Study Group* (1999) · Annals of Internal Medicine · doi:10.7326/0003-4819-130-6-199903160-00002 · Cited by 15,079
Levey, A. S., Coresh, J., Bolton, K., Culleton, B. F., Harvey, K. S., Ikizler, T. A., Johnson, C. A., Kausz, A., Kimmel, P. L., Kusek, J. W., et al. (2002) · University of Groningen research database (University of Groningen / Centre for Information Technology) · Cited by 11,633
Intensive insulin therapy in critically ill patients.
Van den Berghe, G., Wouters, P., Weekers, F., Verwaest, C., Bruyninckx, F., Schetz, M., Vlasselaers, D., Ferdinande, P., Lauwers, P., & Bouillon, R. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011300 · Cited by 9,977
Harrell, F. E. (2001) · Springer Series in Statistics · doi:10.1007/978-1-4757-3462-1 · Cited by 9,195
Lee, T. H., Marcantonio, E. R., Mangione, C. M., Thomas, E. J., Polanczyk, C. A., Cook, E. F., Sugarbaker, D. J., Donaldson, M. C., Poss, R., Ho, K. K. L., et al. (1999) · Circulation · doi:10.1161/01.cir.100.10.1043 · Cited by 3,771
Rosamond, W., Flegal, K., Friday, G., Furie, K., Go, A., Greenlund, K., Haase, N., Ho, M., Howard, V., Kissela, B., et al. (2007) · Circulation · doi:10.1161/circulationaha.106.179918 · Cited by 3,277
Multifactorial Index of Cardiac Risk in Noncardiac Surgical Procedures
Goldman, L., Caldera, D. L., Nussbaum, S. R., Southwick, F. S., Krogstad, D., Murray, B., Burke, D. S., O'Malley, T. A., Goroll, A. H., Caplan, C. H., et al. (1977) · New England Journal of Medicine · doi:10.1056/nejm197710202971601 · Cited by 2,751
Cited by
KDOQI US Commentary on the 2012 KDIGO Clinical Practice Guideline for Acute Kidney Injury
Palevsky, P. M., Liu, K. D., Brophy, P. D., Chawla, L. S., Parikh, C. R., Thakar, C. V., Tolwani, A. J., Waikar, S. S., & Weisbord, S. D. (2013) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2013.02.349 · Cited by 935
Acute Kidney Injury After Cardiac Surgery: Focus on Modifiable Risk Factors
Karkouti, K., Wijeysundera, D. N., Yau, T. M., Callum, J. L., Cheng, D. C., Crowther, M., Dupuis, J.-Y., Fremes, S. E., Kent, B., Laflamme, C., et al. (2009) · Circulation · doi:10.1161/circulationaha.108.786913 · Cited by 732
Self-citationCross-trial prediction of treatment outcome in depression: a machine learning approach
Chekroud, A. M., Zotti, R. J., Shehzad, Z., Gueorguieva, R., Johnson, M. K., Trivedi, M. H., Cannon, T. D., Krystal, J. H., & Corlett, P. R. (2016) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00471-x · Cited by 676
Levey, A. S., & James, M. T. (2017) · Annals of Internal Medicine · doi:10.7326/aitc201711070 · Cited by 549
Dent, C. L., Ma, Q., Dastrala, S., Bennett, M., Mitsnefes, M. M., Barasch, J., & Devarajan, P. (2007) · Critical Care · doi:10.1186/cc6192 · Cited by 483
Metadata
- Authors
- Wijeysundera, D. N., Karkouti, K., Dupuis, J.-Y., Rao, V., Chan, C. T., Granton, J. T., & Beattie, W. S.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2007-04-25
- Volume
- 297
- Issue
- 16
- Pages
- 1801
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2055675692
- Cited by
- 469
- References
- 48
- FWCI
- 12.13
- Type
- journal article
- Language
- en
- Open access
- closed
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: Derivation and Validation of a Simplified Predictive Index for Renal Replacement Therapy After Cardiac Surgery. https://app.cochat.ai/papers/10.1001/jama.297.16.1801
- The paper
- Wijeysundera, D. N., Karkouti, K., Dupuis, J.-Y., Rao, V., Chan, C. T., Granton, J. T., & Beattie, W. S. (2007). Derivation and Validation of a Simplified Predictive Index for Renal Replacement Therapy After Cardiac Surgery. JAMA. https://doi.org/10.1001/jama.297.16.1801
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.