Complete blood count in acute kidney injury prediction: a narrative review

Gameiro, Joana; Lopes, José António

doi:10.1186/s13613-019-0561-4

Cited by 26 publications

(17 citation statements)

References 95 publications

(100 reference statements)

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“…This likely reflects the association of lymphocyte percentage and disease severity as has been previously documented in COVID-19 disease or due to the loss of the protective effects of lymphocytes. 20,21 Pending additional study of the utility of the ML model, this could be used for resource allocation and planning, to prevent shortages of essential supplies.…”

Section: Discussionmentioning

confidence: 99%

Acute Kidney Injury in Hospitalized Patients with COVID-19

Chan

Chaudhary

Saha

et al. 2020

Preprint

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Importance: Preliminary reports indicate that acute kidney injury (AKI) is common in coronavirus disease (COVID)-19 patients and is associated with worse outcomes. AKI in hospitalized COVID-19 patients in the United States is not well-described. Objective: To provide information about frequency, outcomes and recovery associated with AKI and dialysis in hospitalized COVID-19 patients. Design: Observational, retrospective study. Setting: Admitted to hospital between February 27 and April 15, 2020. Participants: Patients aged ≥18 years with laboratory confirmed COVID-19 Exposures: AKI (peak serum creatinine increase of 0.3 mg/dL or 50% above baseline). Main Outcomes and Measures: Frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aOR) with mortality. We also trained and tested a machine learning model for predicting dialysis requirement with independent validation. Results: A total of 3,235 hospitalized patients were diagnosed with COVID-19. AKI occurred in 1406 (46%) patients overall and 280 (20%) with AKI required renal replacement therapy. The incidence of AKI (admission plus new cases) in patients admitted to the intensive care unit was 68% (553 of 815). In the entire cohort, the proportion with stages 1, 2, and 3 AKI were 35%, 20%, 45%, respectively. In those needing intensive care, the respective proportions were 20%, 17%, 63%, and 34% received acute renal replacement therapy. Independent predictors of severe AKI were chronic kidney disease, systolic blood pressure, and potassium at baseline. In-hospital mortality in patients with AKI was 41% overall and 52% in intensive care. The aOR for mortality associated with AKI was 9.6 (95% CI 7.4-12.3) overall and 20.9 (95% CI 11.7-37.3) in patients receiving intensive care. 56% of patients with AKI who were discharged alive recovered kidney function back to baseline. The area under the curve (AUC) for the machine learned predictive model using baseline features for dialysis requirement was 0.79 in a validation test. Conclusions and Relevance: AKI is common in patients hospitalized with COVID-19, associated with worse mortality, and the majority of patients that survive do not recover kidney function. A machine-learned model using admission features had good performance for dialysis prediction and could be used for resource allocation.

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Section: Discussionmentioning

confidence: 99%

Acute Kidney Injury in Hospitalized Patients with COVID-19

Chan

Chaudhary

Saha

et al. 2020

Preprint

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“…It has been confirmed that various lymphocytes including T cells and B cells both play significant role in initiation, progression and recovery of AKI [54][55][56]. Neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) were discovered correlated with AKI in many clinical settings [57][58][59][60].…”

Section: Discussionmentioning

confidence: 91%

A nomogram based on serum cystatin C for predicting acute kidney injury in patients with traumatic brain injury

Wang

Gui

et al. 2021

Renal Failure

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Background Acute kidney injury (AKI) is a common complication in traumatic brain injury (TBI) patients and is associated with unfavorable outcome of these patients. We designed this study to explore the value of serum cystatin C, an indicator of renal function, on predicting AKI after suffering TBI. Methods Patients confirmed with TBI and hospitalized in the West China Hospital of Sichuan University between January 2015 and December 2019 were included. Patients were divided into two groups according to occurrence of AKI. Univariate and multivariate logistic regression analyses were sequentially utilized to find risk factors of AKI in included TBI patients. Nomogram composed of discovered risk factors for predicting AKI was constructed. Receiver operating characteristics (ROC) curves were drawn and area under the ROC curve (AUC) were calculated to evaluate the predictive value of cystatin C alone and the constructed nomogram. Results Among 234 included TBI patients, 55 were divided into AKI group. AKI group had shorter length of stay ( p < 0.001) and higher in-hospital mortality ( p < 0.001). Multivariate logistic regression analysis showed absolute lymphocyte count ( p = 0.034), serum creatinine ( p < 0.001), serum cystatin C ( p = 0.017) and transfusion of red blood cell ( p = 0.005) were independently associated with development of AKI after TBI. While hypertonic saline use was not associated with the development of AKI ( p = 0.067). The AUC of single cystatin C and predictive nomogram were 0.804 and 0.925, respectively. Conclusion Higher serum cystatin C is associated with development of AKI in TBI patients. Predictive nomogram incorporating cystatin C is beneficial for physicians to evaluate possibilities of AKI and consequently adjust treatment strategies to avoid occurrence of AKI.

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“…Increased NLR can occur in septic patients with AKI 6 . The increase in NLR during the first 48 hours was associated with the incidence of organ failure in critically ill male trauma patients (OR 2.06 (1.04-4.06), p = 0.04) 14 . However, in our study, the highest NLR was found at the first hour of sepsis (p = 0.000).…”

Section: Discussionmentioning

confidence: 93%