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The Brazilian Amazon is a vast area with limited health care resources. To assess the epidemiology of critically ill acute kidney injury (AKI) patients in this area, a prospective cohort study of 1029 adult patients of the three intensive care units (ICUs) of Rio Branco city, the capital of Acre state, were evaluated from February 2014 to February 2016. The incidence of AKI was 53.3%. Risk factors for AKI included higher age, nonsurgical patients, admission to the ICU from the ward, higher Acute Physiology and Chronic Health Evaluation (APACHE) II scores at ICU admission, and positive fluid balance > 1500 ml/24 hours in the days before AKI development in the ICU, with aOR of 1.3 (95% CI 1.03-1.23), 1.47 (95% CI 1.07-2.03), 1.96 (95% CI 1.40-2.74), 1.05 (95% CI 1.03-1.08) for each unit increase, and 1.62 (95% CI 1.16-2.26), respectively. AKI was associated with higher ICU mortality (aOR 2.03, 95% CI 1.29-3.18). AKI mortality was independently associated with higher age, nonsurgical patients, sepsis at ICU admission, presence of shock or use of vasoactive drugs, mechanical ventilation and mean positive fluid balance in the ICU > 1500 ml/24 hours, both during ICU follow-up, with aOR 1.27 (95% CI 1.14-1.43) for each 10-year increase, 1.64 (95% CI 1.07-2.52), 2.35 (95% CI 1.14-4.83), 1.88 (95% CI 1.03-3.44), 6.73 (95% CI 4.08-11.09), 2.31 (95% CI 1.52-3.53), respectively. Adjusted hazard ratios for AKI mortality 30 and 31-180 days after ICU discharge were 3.13 (95% CI 1.84-5.31) and 1.69 (95% CI 0.99-2.90), respectively. AKI incidence was strikingly high among critically ill patients in the Brazilian Amazon. The AKI etiology, risk factors and outcomes were similar to those described in high-income countries, but mortality rates were higher.

OBJECTIVES: Serum creatinine (SCr) is the primary biomarker for assessing kidney function; however, it may lag behind true kidney function, especially in instances of acute kidney injury (AKI). The objective of the work is to develop Nephrocast, a deep-learning model to predict next-day SCr in adult patients treated in the intensive care unit (ICU). MATERIALS AND METHODS: Nephrocast was trained and validated, temporally and prospectively, using electronic health record data of adult patients admitted to the ICU in the University of California San Diego Health (UCSDH) between January 1, 2016 and June 22, 2024. The model features consisted of demographics, comorbidities, vital signs and laboratory measurements, and medications. Model performance was evaluated by mean absolute error (MAE) and root-mean-square error (RMSE) and compared against the prediction days SCr as a reference. RESULTS: A total of 28 191 encounters met the eligibility criteria, corresponding to 105 718 patient-days. The median (interquartile range [IQR]) MAE and RMSE in the internal test set were 0.09 (0.085-0.09) mg/dL and 0.15 (0.146-0.152) mg/dL, respectively. In the prospective validation, the MAE and RMSE were 0.09 mg/dL and 0.14 mg/dL, respectively. The models performance was superior to the reference SCr. DISCUSSION AND CONCLUSION: Our model demonstrated good performance in predicting next-day SCr by leveraging clinical data routinely collected in the ICU. The model could aid clinicians in in identifying high-risk patients for AKI, predicting AKI trajectory, and informing the dosing of renally eliminated drugs.

PURPOSE: Novel interventions for the prevention or treatment of acute kidney injury (AKI) are currently lacking. To facilitate the evaluation and adoption of new treatments, the use of the most appropriate design and endpoints for clinical trials in AKI is critical and yet there is little consensus regarding these issues. We aimed to develop recommendations on endpoints and trial design for studies of AKI prevention and treatment interventions based on existing data and expert consensus. METHODS: At the 31st Acute Disease Quality Initiative (ADQI) meeting, international experts in critical care, nephrology, involving adults and pediatrics, biostatistics and people with lived experience (PWLE) were assembled. We focused on four main areas: (1) patient enrichment strategies, (2) prevention and attenuation studies, (3) treatment studies, and (4) innovative trial designs of studies other than traditional (parallel arm or cluster) randomized controlled trials. Using a modified Delphi process, recommendations and consensus statements were developed based on existing data, with > 90% agreement among panel members required for final adoption. RESULTS: The panel developed 12 consensus statements for clinical trial endpoints, application of enrichment strategies where appropriate, and inclusion of PWLE to inform trial designs. Innovative trial designs were also considered. CONCLUSION: The current lack of specific therapy for prevention or treatment of AKI demands refinement of future clinical trial design. Here we report the consensus findings of the 31st ADQI group meeting which has attempted to address these issues including the use of predictive and prognostic enrichment strategies to enable appropriate patient selection.

BACKGROUND: Renal dysfunction is a common complication following liver transplantation (LT). This study aimed to determine whether a comprehensive assessment of kidney function using nineteen serum and urinary biomarkers (BMs) within the first 48 h post-LT could enhance the prediction of severe acute kidney injury (AKI) and the need of kidney replacement therapy (KRT) during the first postoperative week. METHODS: Blood and urine (U) samples were collected during the pre- and postoperative periods. Nineteen BMs were evaluated to assess kidney health in the first 48 h after LT. Classification and regression tree (CART) cross-validation identified key predictors to determine the best BM combination for predicting outcomes. RESULTS: Among 100 LT patients, 36 developed severe AKI, and 34 required KRT within the first postoperative week. Preoperative assessment of U neutrophil gelatinase-associated lipocalin (NGAL) and liver-type fatty acid-binding protein (L-FABP) predicted the need for KRT with 75% accuracy. The combined assessment of U osmolality (OSM), U kidney injury molecule 1 (KIM-1), and tissue inhibitor of metalloproteinase (TIMP-1) within 48 h post-LT predicted severe AKI with 80% accuracy. U-OSM alone, measured within 48 h post-LT, had an accuracy of 83% for predicting KRT need, outperforming any BM combination. CONCLUSIONS: Combined BM analysis can accurately predict severe AKI and KRT needs in the perioperative period of LT. U-OSM alone proved to be an effective tool for monitoring the risk of severe AKI, available in most centers. Further studies are needed to assess its impact on AKI progression postoperatively.Registered at Clinical Trials (clinicaltrials.gov) in March 24th, 2014 by title Acute Kidney Injury Biomarkers: Diagnosis and Application in Pre-operative Period of Liver Transplantation (AKIB) and identifier NCT02095431.