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Scientific reports 11(1), 16800 (2021). doi:10.1038/s41598-021-96397-2, Published by Macmillan Publishers Limited, part of Springer Nature, [London]

Most reports on AKI claim to use KDIGO guidelines but fail to include the urinary output (UO) criterion in their definition of AKI. We postulated that ignoring UO alters the incidence of AKI, may delay diagnosis of AKI, and leads to underestimation of the association between AKI and ICU mortality. Using routinely collected data of adult patients admitted to an intensive care unit (ICU), we retrospectively classified patients according to whether and when they would be diagnosed with KDIGO AKI stage ≥ 2 based on baseline serum creatinine (Screa) and/or urinary output (UO) criterion. As outcomes, we assessed incidence of AKI and association with ICU mortality. In 13,403 ICU admissions (62.2% male, 60.8 ± 16.8 years, SOFA 7.0 ± 4.1), incidence of KDIGO AKI stage ≥ 2 was 13.2% when based only the SCrea criterion, 34.3% when based only the UO criterion, and 38.7% when based on both criteria. By ignoring the UO criterion, 66% of AKI cases were missed and 13% had a delayed diagnosis. The cause-specific hazard ratios of ICU mortality associated with KDIGO AKI stage ≥ 2 diagnosis based on only the SCrea criterion, only the UO criterion and based on both criteria were 2.11 (95% CI 1.85–2.42), 3.21 (2.79–3.69) and 2.85 (95% CI 2.43–3.34), respectively. Ignoring UO in the diagnosis of KDIGO AKI stage ≥ 2 decreases sensitivity, may lead to delayed diagnosis and results in underestimation of KDIGO AKI stage ≥ 2 associated mortality.

Current clinical diagnosis is typically based on a combination of approaches including clinical examination of the patient, clinical experience, physiologic and/or genetic parameters, high-tech diagnostic medical imaging, and an extended list of laboratory values mostly determined in biofluids such as blood and urine. One could consider this as precision medicine v1.0. However, recent advances in technology and better understanding of molecular mechanisms underlying disease will allow us to better characterize patients in the future. These improvements will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses. Treatments will be able to be chosen more "precisely", resulting in more appropriate therapy, precision medicine v2.0. In this review, we will reflect on the potential added value of recent advances in technology and a better molecular understanding of necrosis and inflammation for improving diagnosis and treatment of critically ill patients. We give a brief overview on the mutual interplay between necrosis and inflammation, which are two crucial detrimental factors in organ and/or systemic dysfunction. One of the challenges for the future will thus be the cellular and molecular profiling of necroinflammation in biofluids. The huge amount of data generated by profiling biomolecules and single cells through, for example, different omic-approaches is needed for data mining methods to allow patient-clustering and identify novel biomarkers. The real-time monitoring of biomarkers will allow continuous (re)evaluation of treatment strategies using machine learning models. Ultimately, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.

Background Acute kidney injury (AKI) occurs frequently and adversely affects patient and kidney outcomes, especially when its severity increases from stage 1 to stages 2 or 3. Early interventions may counteract such deterioration, but this requires early detection. Our aim was to evaluate whether the novel renal damage biomarker urinary chitinase 3-like protein 1 (UCHI3L1) can detect AKI stage ≥2 more early than serum creatinine and urine output, using the respective Kidney Disease | Improving Global Outcomes (KDIGO) criteria for definition and classification of AKI, and compare this to urinary neutrophil gelatinase-associated lipocalin (UNGAL). Methods This was a translational single-center, prospective cohort study at the 22-bed surgical and 14-bed medical intensive care units (ICU) of Ghent University Hospital. We enrolled 181 severely ill adult patients who did not yet have AKI stage ≥2 based on the KDIGO criteria at time of enrollment. The concentration of creatinine (serum, urine) and CHI3L1 (serum, urine) was measured at least daily, and urine output hourly, in the period from enrollment till ICU discharge with a maximum of 7 ICU-days. The concentration of UNGAL was measured at enrollment. The primary endpoint was the development of AKI stage ≥2 within 12 h after enrollment. Results After enrollment, 21 (12 %) patients developed AKI stage ≥2 within the next 7 days, with 6 (3 %) of them reaching this condition within the first 12 h. The enrollment concentration of UCHI3L1 predicted the occurrence of AKI stage ≥2 within the next 12 h with a good AUC-ROC of 0.792 (95 % CI: 0.726–0.849). This performance was similar to that of UNGAL (AUC-ROC of 0.748 (95 % CI: 0.678–0.810)). Also, the samples collected in the 24-h time frame preceding diagnosis of the 1st episode of AKI stage ≥2 had a 2.0 times higher (95 % CI: 1.3–3.1) estimated marginal mean of UCHI3L1 than controls. We further found that increasing UCHI3L1 concentrations were associated with increasing AKI severity. Conclusions In this pilot study we found that UCHI3L1 was a good biomarker for prediction of AKI stage ≥2 in adult ICU patients.

Background It is unclear how modifications in the way to calculate serum creatinine (sCr) increase and in the cut-off value applied, influences the prognostic value of Acute Kidney Injury (AKI). We wanted to evaluate whether these modifications alter the prognostic value of AKI for prediction of mortality at 3 months, 1 and 2 years. Methods We prospectively included 195 septic patients and evaluated the prognostic value of AKI by using three different algorithms to calculate sCr increase: either as the difference between the highest value in the first 24 h after ICU admission and a pre-admission historical (ΔHIS) or an estimated (ΔEST) baseline value, or by subtracting the ICU admission value from the sCr value 24 h after ICU admission (ΔADM). Different cut-off levels of sCr increase (0.1, 0.2, 0.3, 0.4 and 0.5 mg/dl) were evaluated. Results Mortality at 3 months, 1 and 2 years in AKI defined as ΔADM > 0.3 mg/dl was 48.1 %, 63.0 % and 63.0 % vs 27.7 %, 39.8 % and 47.6 % in no AKI respectively (OR(95%CI): 2.42(1.06-5.54), 2.58(1.11-5.97) and 1.87(0.81-4.33); 0.3 mg/dl was the lowest cut-off value that was discriminatory. When AKI was defined as ΔHIS > 0.3 mg/dl or ΔEST > 0.3 mg/dl, there was no significant difference in mortality between AKI and no AKI. Conclusions The prognostic value of a 0.3 mg/dl increase in sCr, on mortality in sepsis, depends on how this sCr increase is calculated. Only if the evolution of serum creatinine over the first 24 h after ICU admission is taken into account, an association with mortality is found. Electronic supplementary material The online version of this article (doi:10.1186/s12882-015-0107-4) contains supplementary material, which is available to authorized users.

Introduction: Acute kidney injury (AKI) is common after cardiac operations. There are different risk factors or determinants of AKI, and some are related to cardiopulmonary bypass (CPB). In this study, we explored the association between metabolic parameters (oxygen delivery (DO(2)) and carbon dioxide production (VCO(2))) during CPB with postoperative AKI. Methods: We conducted a retrospective analysis of prospectively collected data at two different institutions. The study population included 359 adult patients. The DO(2) and VCO(2) levels of each patient were monitored during CPB. Outcome variables were related to kidney function (peak postoperative serum creatinine increase and AKI stage 1 or 2). The experimental hypothesis was that nadir DO(2) values and nadir DO(2)/VCO(2) ratios during CPB would be independent predictors of AKI. Multivariable logistic regression models were built to detect the independent predictors of AKI and any kind of kidney function damage. Results: A nadir DO2 level < 262 mL/minute/m(2) and a nadir DO(2)/VCO(2) ratio < 5.3 were independently associated with AKI within a model including EuroSCORE and CPB duration. Patients with nadir DO(2) levels and nadir DO(2)/VCO(2) ratios below the identified cutoff values during CPB had a significantly higher rate of AKI stage 2 (odds ratios 3.1 and 2.9, respectively). The negative predictive power of both variables exceeded 90%. The most accurate predictor of AKI stage 2 postoperative status was the nadir DO(2) level. Conclusions: The nadir DO(2) level during CPB is independently associated with postoperative AKI. The measurement of VCO(2)-related variables does not add accuracy to the AKI prediction. Since DO(2) during CPB is a modifiable factor (through pump flow adjustments), this study generates the hypothesis that goal-directed perfusion management aimed at maintaining the DO(2) level above the identified critical value might limit the incidence of postoperative AKI.