ArticleJAMA network open2021
External Validation of a Prediction Model for Acute Kidney Injury Following Noncardiac Surgery.
Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Multicenter validation of a severity index model for predicting postoperative acute kidney injury.Journal of internal medicine · 2026Article
- Integration of stress hyperglycemia ratio and c-reactive protein level improves postoperative acute kidney injury risk stratification after noncardiac surgery: A nested case-control study.Pakistan journal of medical sciences · 2026Article
- Preoperative Geriatric Nutritional Risk Index Score as a Novel Predictor of Postoperative Acute Kidney Injury in Noncardiac Surgery: The NARA-AKI Cohort Study.Kidney medicine · 2025Article
- Systematic Review and Meta-Analysis of Machine Learning Models for Acute Kidney Injury Risk Classification.Journal of the American Society of Nephrology : JASN · 2025Article
- Multicenter validation of a scalable, interpretable, multitask prediction model for multiple clinical outcomes.NPJ digital medicine · 2025Article
- InfEHR: Clinical phenotype resolution through deep geometric learning on electronic health records.Nature communications · 2025Article
- Cellular senescence in renal ischemia-reperfusion injury.Chinese medical journal · 2025Review
- Prediction of acute kidney injury in the immediate postoperative period following liver resection: a retrospective cohort study.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2025Article
- Article
- Development with external validation of a prediction model for postoperative acute kidney injury following noncardiac surgery in elderly patients.BMC geriatrics · 2025Article
- SACrA score to predict the initiation of renal replacement therapy in critically ill patients: a single-center retrospective study.Renal failure · 2024Article
- Association between muscular tissue desaturation and acute kidney injury in older patients undergoing major abdominal surgery: a prospective cohort study.Journal of anesthesia · 2024Article
- The use of anti-adrenergic agents as a predictor of acute kidney injury and delayed recovery of kidney function: the NARA-AKI cohort study.Hypertension research : official journal of the Japanese Society of Hypertension · 2023Article
- Association of the perfusion index with postoperative acute kidney injury: a retrospective study.Korean journal of anesthesiology · 2023Article
- Nomogram Prediction Model of Serum Chloride and Sodium Ions on the Risk of Acute Kidney Injury in Critically Ill Patients.Infection and drug resistance · 2022Article
- The Predictive Value of Pre-operative N-Terminal Pro-B-Type Natriuretic Peptide in the Risk of Acute Kidney Injury After Non-cardiac Surgery.Frontiers in medicine · 2022Article
- Analysis of novel predictors of acute kidney injury after non-cardiac surgery: an integrative review.Jornal brasileiro de nefrologiaReview
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8 authors.
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Abstract
Importance: The Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed. Objective: To externally validate the SPARK index. Design, Setting, and Participants: This single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m2, preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021. Exposures: Risk factors for AKI included in SPARK index. Main Outcomes And Measures: PO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively. Results: Among 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m2 vs 78.2 [65.6-92.2] mL/min/1.73 m2), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28; R2 = 0.86; critical AKI: y = 0.20x + 2.08; R2 = 0.51). Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort. Conclusions and Relevance: In this study, the incidence of PO-AKI increased as the scores on the SPARK index increased. However, the predicted probability might not be accurate in cohorts with older patients with more comorbidities.
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