Development and External Validation a Novel Inflammation-Based Score for Acute Kidney Injury and Prognosis in Intensive Care Unit Patients

Hematological Ratios Are Associated with Acute Kidney Injury and Mortality in Patients That Present with Suspected Infection at the Emergency Department

The early recognition of acute kidney injury (AKI) is essential to improve outcomes and prevent complications such as chronic kidney disease, the need for renal-replacement therapy, and an increased length of hospital stay. Increasing evidence shows that inflammation plays an important role in the pathophysiology of AKI and mortality. Several inflammatory hematological ratios can be used to measure systemic inflammation. Therefore, the association between these ratios and outcomes (AKI and mortality) in patients suspected of having an infection at the emergency department was investigated. Data from the SPACE cohort were used. Cox regression was performed to investigate the association between seven hematological ratios and outcomes. A total of 1889 patients were included, of which 160 (8.5%) patients developed AKI and 102 (5.4%) died in <30 days. The Cox proportional-hazards model revealed that the neutrophil-to-lymphocyte ratio (NLR), segmented-neutrophil-to-monocyte ratio (SMR), and neutrophil-lymphocyte-platelet ratio (NLPR) are independently associated with AKI <30 days after emergency-department presentation. Additionally, the NLR, SMR and NLPR were associated with 30-day all-cause mortality. These findings are an important step forward for the early recognition of AKI. The use of these markers might enable emergency-department physicians to recognize and treat AKI in an early phase to potentially prevent complications.

Development and External Verification of a Nomogram for Patients with Persistent Acute Kidney Injury in the Intensive Care Unit

Background

We aimed to identify the affecting features of persistent acute kidney injury (pAKI) for patients in intensive care units (ICU).

Methods

The Medical Information Mart for Intensive Care IV (MIMIC-IV) database and eICU Collaborative Research Database (eICU-CRD) were used to identify AKI patients with and without duration of more than 48 hours. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine (SVM-RFE) were utilized to screen for the significant clinical indexes associated with pAKI. Predictive nomogram was created based on the above informative parameters to predict the probability of pAKI.

Results

LASSO regression and SVM-RFE revealed that serum albumin, chronic kidney disease, AKI stage, sequential organ failure assessment score, lactate and renal replacement therapy during the first day were significantly associated with pAKI in the training cohort. The predictive nomogram based on the six predictors exhibited good predictive performance as calculated by C-index 0.730 (95% CI 0.710-0.749) in the training group, 0.702 (95% CI 0.672-0.722) in the internal validation set and 0.704 (0.677-0.731) in the external validation cohort for the prediction of pAKI. Moreover, the predictive nomogram exhibited not only encouraging calibration ability, but also great clinical utility in the training group, in the internal validation group as well as in the external validation cohort.

Conclusion

Serum albumin, CKD, AKI stage, SOFA score, lactate, RRT during the first day were closely associated with pAKI in patients in ICU. The predictive nomogram for pAKI manifested good predictive ability for the identification of ICU patients with pAKI.