Trial reportJAMA network open2026
Early Nephrology Consultation and Acute Kidney Injury in Hospitalized Patients: A Randomized Clinical Trial.
Trial report in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03590028 (An Early Real-Time Electronic Health Record Risk Algorithm for the Prevention and Treatment of Acute Kidney Injury), which is not on this map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
An Early Real-Time Electronic Health Record Risk Algorithm for the Prevention and Treatment of Acute Kidney Injury: A Randomized Trial of an Early Standardized, Personalized Nephrology Intervention
Who cites it
1 citing paper in PubMed.
- Current and Future Applications of AI-Driven Predictive Modeling and a Proposed Framework for AI-Bioprognostics in Kidney Care.Risk management and healthcare policy · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To determine whether a structured early nephrology consultation triggered by a machine-learning acute kidney injury (AKI) risk score (electronic signal to prevent AKI [ESTOP-AKI]) in patients at high risk for stage 2 AKI improves patient outcomes. Design, Setting, and Participants: This randomized clinical trial was conducted at the University of Chicago, Illinois, from March 13, 2019, to August 21, 2024, in hospitalized patients with no serum creatinine (SCr)-based AKI and an ESTOP-AKI score more than 0.01. Intervention: Patients were randomized to receive a structured early nephrology consultation (ENC) from an attending nephrologist or usual care (UC). The ENC included an in-person assessment and recommendations regarding volume status, kidney perfusion, medication dosing and selection, electrolytes, nutritional needs, and further testing. Patients in the UC arm only received a nephrology consultation when clinically requested by the primary team. Main Outcomes and Measures: The primary outcome was the peak change in SCr from enrollment (ΔSCr) during the 7-day follow-up. Secondary outcomes included development of AKI, need for kidney replacement therapy, and inpatient and 90-day mortality. Results: Of the 180 patients randomized (median [IQR] age, 62.5 [50.0-71.0] years; 102 males [56.7%]), 89 (49.4%) received ENC, and 91 (50.6%) received UC. There was no significant adjusted mean (SE) difference in the 7-day ΔSCr between the ENC and UC groups, adjusted for the ESTOP risk group (0.04 [0.07] mg/dL vs -0.03 [0.07] mg/dL; P = .30), among the 70 patients (38.9%) in the development of stage 1 or higher AKI (37 [42%] vs 33 [36%]; P = .47) or among the 29 patients (16.1%) with stage 2 or higher AKI (17 [19%] vs 12 [13%]; P = .28). During the study period, there were 121 ENC consultations containing 270 recommendations compared with 19 UC consultations and 36 recommendations. Medication dosage and discontinuation, diuretics or fluids, and vasopressor recommendations were more likely to be completely followed in the UC arm (15 of 22 [68%]) compared with in the ENC arm (48 of 116 [41%]). Over the 90-day follow-up, there was no significant difference in readmission rates (ENC: 30 [34.1%] vs UC: 40 [44.4%]; P = .21) or 90-day mortality (ENC: 13 [14.8%] vs UC: 17 [18.7%]; P = .62) between the ENC and UC arms. Conclusions and Relevance: In this randomized clinical trial of structured ENC triggered by a machine-learning AKI risk score, there was no difference in ΔSCr. AKI consultation recommendations were not followed the majority of time; whether increasing adherence to recommendations could improve outcomes deserves further study. Trial Registration: ClinicalTrials.gov Identifier: NCT03590028.
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