scholarly journals Risk Stratification for ECMO Requirement in COVID-19 ICU Patients Using Quantitative Imaging Features in CT Scans on Admission

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1029
Author(s):  
Eva Gresser ◽  
Jakob Reich ◽  
Bastian O. Sabel ◽  
Wolfgang G. Kunz ◽  
Matthias P. Fabritius ◽  
...  
Keyword(s):  
Resource Management ◽  
Risk Stratification ◽  
Sofa Score ◽  
Ct Scans ◽  
Imaging Features ◽  
Lung Involvement ◽  
Icu Admission ◽  
Clinical Scores ◽  
Diagnostic Potential ◽  
Ecmo Therapy

(1) Background: Extracorporeal membrane oxygenation (ECMO) therapy in intensive care units (ICUs) remains the last treatment option for Coronavirus disease 2019 (COVID-19) patients with severely affected lungs but is highly resource demanding. Early risk stratification for the need of ECMO therapy upon admission to the hospital using artificial intelligence (AI)-based computed tomography (CT) assessment and clinical scores is beneficial for patient assessment and resource management; (2) Methods: Retrospective single-center study with 95 confirmed COVID-19 patients admitted to the participating ICUs. Patients requiring ECMO therapy (n = 14) during ICU stay versus patients without ECMO treatment (n = 81) were evaluated for discriminative clinical prediction parameters and AI-based CT imaging features and their diagnostic potential to predict ECMO therapy. Reported patient data include clinical scores, AI-based CT findings and patient outcomes; (3) Results: Patients subsequently allocated to ECMO therapy had significantly higher sequential organ failure (SOFA) scores (p < 0.001) and significantly lower oxygenation indices on admission (p = 0.009) than patients with standard ICU therapy. The median time from hospital admission to ECMO placement was 1.4 days (IQR 0.2–4.0). The percentage of lung involvement on AI-based CT assessment on admission to the hospital was significantly higher in ECMO patients (p < 0.001). In binary logistic regression analyses for ECMO prediction including age, sex, body mass index (BMI), SOFA score on admission, lactate on admission and percentage of lung involvement on admission CTs, only SOFA score (OR 1.32, 95% CI 1.08–1.62) and lung involvement (OR 1.06, 95% CI 1.01–1.11) were significantly associated with subsequent ECMO allocation. Receiver operating characteristic (ROC) curves showed an area under the curve (AUC) of 0.83 (95% CI 0.73–0.94) for lung involvement on admission CT and 0.82 (95% CI 0.72–0.91) for SOFA scores on ICU admission. A combined parameter of SOFA on ICU admission and lung involvement on admission CT yielded an AUC of 0.91 (0.84–0.97) with a sensitivity of 0.93 and a specificity of 0.84 for ECMO prediction; (4) Conclusions: AI-based assessment of lung involvement on CT scans on admission to the hospital and SOFA scoring, especially if combined, can be used as risk stratification tools for subsequent requirement for ECMO therapy in patients with severe COVID-19 disease to improve resource management in ICU settings.

scholarly journals Prognostic Value of Admission Chest CT Findings for Invasive Ventilation Therapy in COVID-19 Pneumonia

Diagnostics ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1108
Author(s):  
Eva Gresser ◽  
Johannes Rueckel ◽  
Daniel Puhr-Westerheide ◽  
Vincent Schwarze ◽  
Nicola Fink ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Risk Score ◽  
Clinical Information ◽  
Ct Imaging ◽  
Chest Ct ◽  
Ct Scans ◽  
Imaging Features ◽  
Invasive Ventilation ◽  
Diagnostic Potential ◽  
Non Invasive Ventilation

(1) Background: To assess the value of chest CT imaging features of COVID-19 disease upon hospital admission for risk stratification of invasive ventilation (IV) versus no or non-invasive ventilation (non-IV) during hospital stay. (2) Methods: A retrospective single-center study was conducted including all patients admitted during the first three months of the pandemic at our hospital with PCR-confirmed COVID-19 disease and admission chest CT scans (n = 69). Using clinical information and CT imaging features, a 10-point ordinal risk score was developed and its diagnostic potential to differentiate a severe (IV-group) from a more moderate course (non-IV-group) of the disease was tested. (3) Results: Frequent imaging findings of COVID-19 pneumonia in both groups were ground glass opacities (91.3%), consolidations (53.6%) and crazy paving patterns (31.9%). Characteristics of later stages such as subpleural bands were observed significantly more often in the IV-group (52.2% versus 26.1%, p = 0.032). Using information directly accessible during a radiologist’s reporting, a simple risk score proved to reliably differentiate between IV- and non-IV-groups (AUC: 0.89 (95% CI 0.81–0.96), p < 0.001). (4) Conclusions: Information accessible from admission CT scans can effectively and reliably be used in a scoring model to support risk stratification of COVID-19 patients to improve resource and allocation management of hospitals.

scholarly journals Epicardial adipose tissue and severe Coronavirus Disease 19

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Hélène Bihan ◽  
Richard Heidar ◽  
Aude Beloeuvre ◽  
Lucie Allard ◽  
Elise Ouedraogo ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Epicardial Adipose Tissue ◽  
Ct Scans ◽  
Lung Involvement ◽  
Icu Admission ◽  
Anthropometric Characteristics ◽  
Automatic Software ◽  
Risk Of Disease ◽  
Key Indicators ◽  
Visceral Adipose

Abstract Background Both visceral adipose tissue and epicardial adipose tissue (EAT) have pro-inflammatory properties. The former is associated with Coronavirus Disease 19 (COVID-19) severity. We aimed to investigate whether an association also exists for EAT. Material and methods We retrospectively measured EAT volume using computed tomography (CT) scans (semi-automatic software) of inpatients with COVID-19 and analyzed the correlation between EAT volume and anthropometric characteristics and comorbidities. We then analyzed the clinicobiological and radiological parameters associated with severe COVID-19 (O2 $$\ge$$ ≥ 6 l/min), intensive care unit (ICU) admission or death, and 25% or more CT lung involvement, which are three key indicators of COVID-19 severity. Results We included 100 consecutive patients; 63% were men, mean age was 61.8 ± 16.2 years, 47% were obese, 54% had hypertension, 42% diabetes, and 17.2% a cardiovascular event history. Severe COVID-19 (n = 35, 35%) was associated with EAT volume (132 ± 62 vs 104 ± 40 cm3, p = 0.02), age, ferritinemia, and 25% or more CT lung involvement. ICU admission or death (n = 14, 14%) was associated with EAT volume (153 ± 67 vs 108 ± 45 cm3, p = 0.015), hypertension and 25% or more CT lung involvement. The association between EAT volume and severe COVID-19 remained after adjustment for sex, BMI, ferritinemia and lung involvement, but not after adjustment for age. Instead, the association between EAT volume and ICU admission or death remained after adjustment for all five of these parameters. Conclusions Our results suggest that measuring EAT volume on chest CT scans at hospital admission in patients diagnosed with COVID-19 might help to assess the risk of disease aggravation.

scholarly journals Typical and atypical CT chest imaging findings of novel coronavirus 19 (COVID-19) in correlation with clinical data: impact on the need to ICU admission, ventilation and mortality

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Doaa M. Emara ◽  
Nagy N. Naguib ◽  
M. A. Moustafa ◽  
Salma M. Ali ◽  
Amr Magdi El Abd
Keyword(s):  
Pleural Effusion ◽  
Complete Recovery ◽  
Clinical Findings ◽  
Mediastinal Lymphadenopathy ◽  
Imaging Features ◽  
Imaging Findings ◽  
Icu Admission ◽  
Mortality Outcome ◽  
Novel Coronavirus ◽  
Contrast Ct

Abstract Background The aim of this study was to highlight the typical and atypical chest CT imaging features at first presentation in 120 patients who were proved to be COVID-19 by PCR and to correlate these findings with the need for ICU admission, ventilation, and mortality. We retrospectively included 120 patients 71 males (59.2%) and 49 females (40.8%) with a mean age of 47.2 ± 14.4 years. Patients subjected to clinical assessment, CBC, PCR for COVID-19, and non-contrast CT chest at first presentation. Typical and atypical imaging findings were reported and correlated with the clinical findings of the patients, the need for ICU admission, ventilation, and mortality. Results Clinically, fever was seen in 112 patients followed by dry cough in 108 patients and malaise in 35 patients. The final outcome was complete recovery in 113 cases and death in 7 cases. Typical CT findings included bilateral peripheral ground-glass opacities (GGO) in 74.7%, multilobar affection in 92.5% while atypical findings such as homogeneous consolidation, pleural effusion, mediastinal lymphadenopathy, and single lobar affection were found in 13.4, 5, 6.7, and 7.5% respectively. A statistically significant association between the presence of white lung, pleural effusion, peripheral GGO, and the need for ICU admission as well as mechanical ventilation was noted. The death was significantly higher among elderly patients; however, no significance was found between the imaging features and mortality. Conclusion CT features at first presentation can predict the need for ICU admission and the need for ventilation but cannot predict the mortality outcome of the patients.

scholarly journals Biomarkers and clinical scores to identify patient populations at risk of delayed antibiotic administration or intensive care admission

Critical Care ◽  
2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Juan Gonzalez del Castillo ◽  
◽  
Darius Cameron Wilson ◽  
Carlota Clemente-Callejo ◽  
Francisco Román ◽  
...  
Keyword(s):  
At Risk ◽  
Intensive Care ◽  
Disease Progression ◽  
Hospital Readmission ◽  
Mortality Rates ◽  
Antibiotic Administration ◽  
News Values ◽  
Icu Admission ◽  
Clinical Scores ◽  
Populations At Risk

Abstract Background The performance of blood biomarkers (mid-regional proadrenomedullin (MR-proADM), procalcitonin (PCT), C-reactive protein (CRP), and lactate) and clinical scores (Sequential Organ Failure Assessment (SOFA), National Early Warning Score (NEWS), and quick SOFA) was compared to identify patient populations at risk of delayed treatment initiation and disease progression after presenting to the emergency department (ED) with a suspected infection. Methods A prospective observational study across three EDs. Biomarker and clinical score values were calculated upon presentation and 72 h, and logistic and Cox regression used to assess the strength of association. Primary outcomes comprised of 28-day mortality prediction and delayed antibiotic administration or intensive care (ICU) admission, whilst secondary outcomes identified subsequent disease progression. Results Six hundred eighty-four patients were enrolled with hospitalisation, ICU admission, and infection-related 28-day mortality rates of 72.8%, 3.4%, and 4.4%, respectively. MR-proADM and NEWS had the strongest association with hospitalisation and the requirement for antibiotic administration, whereas MR-proADM alone had the strongest association with ICU admission (OR [95% CI]: 5.8 [3.1 - 10.8]) and mortality (HR [95% CI]: 3.8 [2.2 - 6.5]). Patient subgroups with high MR-proADM concentrations (≥ 1.77 nmol/L) and low NEWS (< 5 points) values had significantly higher rates of ICU admission (8.1% vs 1.6%; p < 0.001), hospital readmission (18.9% vs. 5.9%; p < 0.001), infection-related mortality (13.5% vs. 0.2%; p < 0.001), and disease progression (29.7% vs. 4.9%; p < 0.001) than corresponding patients with low MR-proADM concentrations. ICU admission was delayed by 1.5 [0.25 – 5.0] days in patients with high MR-proADM and low NEWS values compared to corresponding patients with high NEWS values, despite similar 28-day mortality rates (13.5% vs. 16.5%). Antibiotics were withheld in 17.4% of patients with high MR-proADM and low NEWS values, with higher subsequent rates of ICU admission (27.3% vs. 4.8%) and infection-related hospital readmission (54.5% vs. 14.3%) compared to those administered antibiotics during ED treatment. Conclusions Patients with low severity signs of infection but high MR-proADM concentrations had an increased likelihood of subsequent disease progression, delayed antibiotic administration or ICU admission. Appropriate triage decisions and the rapid use of antibiotics in patients with high MR-proADM concentrations may constitute initial steps in escalating or intensifying early treatment strategies.

scholarly journals Interim-analysis of the COSA (COVID-19 patients treated with the Seraph® 100 Microbind® Affinity filter) registry

2021 ◽  
Author(s):  
Julius J Schmidt ◽  
Dan Nicolae Borchina ◽  
Mariet van´t Klooster ◽  
Khalida Bulhan-Soki ◽  
Reuben Okioma ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Sofa Score ◽  
Cox Regression ◽  
Treatment Time ◽  
Outcome Data ◽  
Adverse Outcomes ◽  
Icu Patients ◽  
Icu Admission ◽  
Late Initiation ◽  
Bacterial Superinfection

Abstract Background The Seraph®100 Microbind Affinity Blood Filter® is a hemoperfusion device that is licensed for the reduction of pathogens, including several viruses, in the blood. It received Emergency Use Authorization (EUA) for the treatment of severe coronavirus disease 2019 (COVID-19) by the FDA. Several studies have shown that the blood viral load of SARS-CoV-2 correlates with adverse outcomes and removal of the nucleocapsid of the SARS-CoV-2 virus by the Seraph®100 has been recently demonstrated. The aim of this registry was to evaluate safety and efficacy of Seraph®100 treatment for COVID-19 patients. Methods Twelve hospitals from six countries representing two continents documented patient and treatment characteristics as well as outcome parameters without reimbursement. Additionally, mortality and safety results of the device were reported. One hundred-and-two treatment sessions in 82 patients were documented in the registry. Four patients were excluded from mortality analysis due to incomplete outcome data, which were available in the other 78 patients. Results Overall, a 30-day mortality rate of 46.2% in the 78 patients with complete follow up was reported. Median treatment time was 5.00 [4.00–13.42] h. and 43.1% of the treatments were performed as hemoperfusion only. Adverse events of the Seraph®100 treatment were reported in 8.8% of the 102 treatments and represented premature end of treatment due to circuit failure. Patients that died were treated later in their ICU stay and onset of COVID symptoms. They also had higher ferritin levels. Multivariate Cox regression revealed that delayed Seraph®100 treatment after ICU admission (&gt;60 hours) as well as bacterial superinfection were associated with mortality. While average predicted mortality rate according to SOFA score in ICU patients was 56.7% the observed mortality was 50.7%. In non-ICU patients 4C-Score average predicted a mortality rate of 38.0% while the observed mortality rate was 11.1% Conclusions The treatment of COVID-19 patients with Seraph®100 is well tolerated and the circuit failure rate was lower than previously reported for KRT in COVID-19 patients. Mortality corelated with late initiation of Seraph treatment after ICU admission and bacterial superinfection infection. Compared to predicted mortality according to 4C-Score and SOFA Score, mortality of Seraph®100 treated patients reported in the registry was lower.

scholarly journals Improved Detection of Air Trapping on Expiratory Computed Tomography Using Deep Learning

2020 ◽  
Author(s):  
Sundaresh Ram ◽  
Benjamin A. Hoff ◽  
Alexander J. Bell ◽  
Stefanie Galban ◽  
Aleksa B. Fortuna ◽  
...  
Keyword(s):  
Relative Volume ◽  
Ct Scans ◽  
Radiographic Assessment ◽  
Dice Coefficient ◽  
Air Trapping ◽  
Linear Mixed Effects ◽  
Limited Efficacy ◽  
Clinical Scores ◽  
Standard Techniques ◽  
Radiologic Evidence

ABSTRACTBackgroundRadiologic evidence of air trapping (AT) on expiratory CT scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression.ObjectiveTo investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques.Materials and MethodsPaired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model.ResultsQAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach.ConclusionThe CNN model effectively delineated air trapping on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring air trapping in CF patients.

Characterization of undiagnosed pancreatic ductal adenocarcinoma on CT scans.

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 380-380
Author(s):  
John Chang ◽  
Madelyn Bartels ◽  
Kelsey Beyer ◽  
Ashley Maitland ◽  
Richard Taft Peterson ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
The Body ◽  
Ct Scans ◽  
Ductal Adenocarcinoma ◽  
Imaging Features ◽  
Cognitive Errors ◽  
Radiologic Findings ◽  
Stage 1 ◽  
Improved Technology ◽  
Radiologic Features

380 Background: Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths. At present, the best 5-year survival is 25% for resectable PDAC. For small (1 cm) stage 1 PDAC, resection has resulted in much better survival. The goal of this study was to evaluate the appearance and location of early undiagnosed PDAC on computed tomography scans (CT) prior to diagnosis with the goal of minimizing missing early PDAC. We also categorize the errors as either perceptive or cognitive. Methods: PDAC cases were retrospectively reviewed from 1/1/2012 through 12/31/2018 from our tumor registry, identifying 81 cases with paired CT scans both at the time of and prior to diagnosis. Among these, 31 contained imaging features considered diagnostic or suspicious for early PDAC(38%). These “errors” were classified by radiologic features and as well as by location. In addition, errors were classified into “perceptive errors" when the first study was read as normal, and as “cognitive errors” when the report noted an abnormality but failed to note suspicion for malignancy. Results: Among the 31 undiagnosed PDAC, 18 had features of an identifiable mass (58%), 9 had pancreatic ductal dilatation (29%), and 4 had evidence of perivascular soft tissue (13%). 44% of undiagnosed tumors were located in the head-neck, 39% in the body, and 17% in the tail. Perceptive errors were found in 58% and 42% were cognitive. No significant differences were seen between perceptive and cognitive errors based on suspicious features. Conclusions: Radiologic findings of early PDAC was retrospectively evident in more than one third of cases in which prior imaging was performed. These findings are most often masses or ductal dilatation. Location of these undiagnosed tumors were distributed throughout the gland. This study identifies the radiologic features of undiagnosed PDAC which may provide an opportunity for future prospective studies and improved technology which may improve early detection of pancreatic cancer.

Calcium supplementation prolongs the time of hospitalization and has a double effect on mortality in septic patients: A retrospective study from MIMIC-III

2020 ◽  
Author(s):  
Wencheng He ◽  
Youzhong An ◽  
Lei Huang ◽  
Hua Luo ◽  
Jingying Chen ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Sofa Score ◽  
Calcium Supplementation ◽  
Double Effect ◽  
Calcium Supplement ◽  
Electrolyte Disturbance ◽  
Icu Admission ◽  
Supplement Group ◽  
Failure Assessment ◽  
Mimic Iii

Abstract Background Hypocalcemia is a common electrolyte disturbance in sepsis, calcium administration in those patients remains a controversial issue. The aim of this study was to assess the association of calcium supplementation with the time of hospitalization and mortality in septic patients. Method 5761 eligible septic patients, including 2689 with calcium supplementation and 3072 without calcium supplementation, were extracted from the MIMIC-III database. A total of 1463 pair patients were included in the analysis after propensity score matching according to the age, sex, SOFA score and lactate on first ICU admission. We compared the length of stay (LOS) in the intensive care unit (ICU) and hospital, as well as the 28-day and hospital mortality, which stratified the analysis according to the Sequential Organ Failure Assessment (SOFA) score, and the iCa on the first ICU admission between the matched groups. Results The results showed that either a too-low or a too-high iCa increased the risk for septic patients, but the minimum of the mortality curve in the non-calcium supplement group was locally in the mild hypocalcemia range. Regardless of the SOFA score and iCa, the LOS in both the ICU and hospital were higher in the calcium supplement group than in the non-calcium supplement group. Overall, the 28-day and hospital mortality were greater but not statistically significant in the calcium supplement group than in the non-calcium supplement group (14.83% vs 13.39%, p=0.416; 16.20% vs 13.88%, p=0.079, respectively). However, the survival analysis stratified by SOFA score showed that calcium supplementation reduced mortality when the patient’s SOFA score was >8 (p=0.028), while it worsen the outcome when the SOFA score was ≤4 (p<0.001) and had no significant effect with SOFA scores from 5~8 (p=0.556). Conclusion Our findings suggest that mild hypocalcemia may be protective in septic patients and that calcium supplementation may prolong hospitalization and have a double effect on mortality. The SOFA score may be a valuable clinical index for calcium administration decision making.

TO020POTENTIAL INTERPRETATIONS OF CRITERIA FOR AKI BY AUTOMATED DECISION SUPPORT ALGORITHMS: IMPACT ON AKI INCIDENCE

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Jill Vanmassenhove ◽  
Johan Steen ◽  
Johan Decruyenaere ◽  
Dominique Benoit ◽  
Eric Adriaan J Hoste ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Serum Creatinine ◽  
Sofa Score ◽  
Kidney Injury ◽  
Baseline Serum ◽  
Icu Admission ◽  
And Gender ◽  
Definition Of ◽  
The Impact

Abstract Background and Aims The reported incidence of Acute Kidney Injury (AKI) at the intensive care unit (ICU) is variable. Although the Kidney Disease Improving Global Outcome (K-DIGO) improved harmonisation of this definition, there is remaining variability in the actual implementation of this AKI definition, with variable interpretation of the urinary output (UO) criterion, and of the baseline serum creatinine (Screa) criterion. This hampers progress of our understanding of the clinical concept AKI and leads to confusion and unclarity when interpreting models to predict AKI or associated outcomes. With the advent of big data and artificial intelligence based decision algorithms, this problem will only become more of interest, as the user will not know what exactly the construct AKI in the application used means and represents. Therefore, we intended to explore the impact of different interpretations of the Screa and the UO criterium as presented in the K-DIGO definition on the incidence of AKI stage 2. Method We included all patients of an electronic health data system applied in a tertiary ICU between 2013 and 2017. Sequential Organ Failure Assessment (SOFA) score was calculated, and gender, age, weight and mortality at ICU and in hospital were extracted. All serum creatinine (sCrea) values during ICU stay and hospitalisation were extracted, as were UO data, with their time stamps. In addition, all available Screa data up to 1 year before ICU admission were retrieved from a dataset external to the ICU. AKI was defined according to KDIGO stage 2, using different possible interpretations of the Screa and/or the UO criterion. For the evolution of Screa as compared to a baseline value, we sued either a value directly available to ICU staff (def 1), a presumed eGFR of 75ml/min (def 2), the first available value after admission to ICU (def 3), the lowest value during the current hospitalisation before ICU admission (def 4), the lowest value before the hospitalisation episode as found in an external dataset (def 5). For the UO criterion, we also applied two criteria in line with K-DIGO stage 2: a UO below 6ml/kg during a 12 hour block (def 6) or a UO below 0.5ml/kg/hour during each of 12 consecutive one hour intervals (def 7). Def 8 identified patients who did not comply with any of the definitions (1-7), so who had no AKI according to any definition. Definition 9 and 10 identified patients who complied with at least one out of the Screa criteria 1-5 (def 9) or out of the UO criteria (def 10). Definition 11 identified patients who complied both with at least one Screa and one UO criterium. Results Our dataset included 16433 ICU admissions (34.7% female, age 60.7±16.4 years). Overall, 8.1% of patients died at ICU, and another 5.2% during their hospitalisation. The SOFA score at admission was 6.9±4.1. The incidence of AKI according to the stage 2 definition of K-DIGO varied according to the interpretation of the diagnostic criteria from 4.3% when baseline creatinine was defined as the first ICU value, to 35.3% when the UO criterium was interpreted as a UO below 6ml/kg over a 12 hour block (fig). Only half of patients (53.7%) did not comply with any of the definitions (def 8), 10.9% and 19.7% complied with one of the Screa (def 9) OR one of the UO criteria (def 10) respectively, and 15.7% complied with both (def 11). There was substantial reclassification across the different definitions. Conclusion Unclarity on the actual interpretation of the Screa and UO criteria used in the K-DIGO definition of AKI leads to substantial differences in incidence of AKI, and also with substantial reclassification according to different definitions. This is especially concerning in an era of big data and automated decision support, as clinicians might not know which construct of AKI is actually being represented.

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