Post-operative mortality risk assessment for geriatric patients with hip fractures (HF) is a challenge for clinicians. Early identification of geriatric HF patients with a high risk of post-operative death is helpful for early intervention and improving clinical prognosis. However, a single significant risk factor of post-operative death cannot accurately predict the prognosis of geriatric HF patients. Therefore, our study aims to utilize a machine learning approach, random forest algorithm, to fabricate a prediction model for post-operative death of geriatric HF patients.This retrospective study enrolled consecutive geriatric HF patients who underwent treatment for surgery. The study cohort was divided into training and testing datasets at a 70:30 ratio. The random forest algorithm selected or excluded variables according to the feature importance. Least absolute shrinkage and selection operator (Lasso) was utilized to compare feature selection results of random forest. The confirmed variables were used to create a simplified model instead of a full model with all variables. The prediction model was then verified in the training dataset and testing dataset. Additionally, a prediction model constructed by logistic regression was used as a control to evaluate the efficiency of the new prediction model.Feature selection by random forest algorithm and Lasso regression demonstrated that seven variables, including age, time from injury to surgery, chronic obstructive pulmonary disease (COPD), albumin, hemoglobin, history of malignancy, and perioperative blood transfusion, could be used to predict the 1-year post-operative mortality. The area under the curve (AUC) of the random forest algorithm-based prediction model in training and testing datasets were 1.000, and 0.813, respectively. While the prediction tool constructed by logistic regression in training and testing datasets were 0.895, and 0.797, respectively.Compared with logistic regression, the random forest algorithm-based prediction model exhibits better predictive ability for geriatric HF patients with a high risk of death within post-operative 1 year. The prevalence of geriatric hip fracture (HF) patients is increasing in the rapidly aging population, which has become a growing public health concern worldwide –4. In adAs a subset of machine learning algorithms, random forest algorithm can build a mathematical model based on sample data and be used to make predictions or decisions –13. The This retrospective observational cohort study was based on data collected from January 2013 to August 2017 in West China Hospital. The inclusion criteria for this study were as follows: (1) HF patients older than 60 years. (2) Patients underwent surgical treatments. The exclusion criteria for this study were as follows: (1) High energy trauma mechanism. (2) Secondary fracture. (3) Multiple fractures. (4) Open fractures. (5) Old fracture (>7 days). (6) Pathological fracture. (7) Abdominal organ injury. (8) Incomplete clinical data. A total of 591 geriatric HF patients were enrolled in this study. Then, all cases were randomly divided into training and testing datasets at a ratio of 70:30. The patients were diagnosed with HF using physical examination combined with medical imaging (X-rays or computed tomography). The case data, including demographic variables , medical history , comorbidities , laboratory tests , and 1-year post-operative mortality, were extracted by several clinicians who had received a standardized training. The correlation analysis of all variables was also conducted.F-measure were also used to test model reliability. The procedure of establishing mortality prediction models in this study is shown in Age, BMI, time from injury to surgery, operation duration, blood loss during surgery, hospital stays, and laboratory tests were entered into the random forest procedure as continuous variables. Gender, injury side, type of fracture, type of surgery, injury side, type of fracture, type of surgery, perioperative blood transfusion, medical history, and comorbidities were entered as dichotomous variables. The data were sampled by using the random bootstrapping/bagging method. According to the characteristics of the numerous variables, classification and regression trees were performed to the classified training dataset. The input variables in the risk prediction model were ranked based on the mean decrease in accuracy and the mean decrease in the Gini coefficient. Approximately one-third of the entire data set was not randomly sampled; this out-of-bag (OOB) data served as the testing set. The number of decision trees was set at 500. The random forest algorithm was performed to select variables and create a risk prediction model. Lasso binary logistic regression was performed to compare feature selection and regularization results of the random forest algorithm. The risk prediction model constructed by random forest algorithm was then verified in the training dataset and testing dataset, respectively. Logistic regression is a linear fit of a response variable to a logarithmic probability ratio , 16. Thet-test was performed to compare continuous variables and chi-square test for categorical variables. All the statistical analyses in this study were performed using the RStudio  statistical software package, which runs R software (version 3.5.1). RStudio with library packages Boruta (CRAN.R-project.org/package=Boruta), randomforest (CRAN.R-project.org/package=randomForest), and caret (CRAN.R-project.org/package=caret) were used to construct a random forest model. In addition, RStudio with library packages glmnet (CRAN.R-project.org/package=glmnet) was used for Lasso regression. P-values < 0.05 were considered statistically significant.Descriptive statistics of continuous variables were expressed as mean, and the categorical variables were reported as numbers and percentages. Independent P < 0.001). The time from injury to surgery of all enrolled patients was 4.29 ± 2.26 days. Additionally, the time from injury to surgery in the live group was significantly lower than that of the dead group. The laboratory results revealed that the hemoglobin and albumin of the dead group were significantly lower than those of the live group.The baseline characteristics of all enrolled patients are shown in The dichotomous variables of the live and dead groups are shown in Using the random forest prediction model, all variables were tested for their ability to predict the post-operative 1-year death in geriatric HF patients. A risk prediction model was constructed based on confirmed important risk factors selected by the random forest algorithm. In the three runs with mtry values of three, four, or five, we obtained the best result of four, with a low OOB error rate of 14.49%. The ROC curves of continuous variables, prediction model constructed by random forest algorithm, and traditional logistic regression in the training dataset and testing dataset are shown in F-measure were applied in testing the reliability of prediction models in our study. The Kappa values of random forest algorithm-based prediction model and logistic regression-based prediction model in the training dataset were 1.000 and 0.521, respectively. The Kappa values of random forest algorithm-based prediction model and logistic regression-based prediction model in the testing dataset were 0.488 and 0.267, respectively. The F-measures of random forest algorithm-based prediction model and logistic regression-based prediction model in the training dataset were 1.000 and 0.610, respectively. The F-measures of random forest algorithm-based prediction model and logistic regression-based prediction model in the testing dataset were 0.560 and 0.413, respectively.The Kappa statistic and With the aging population, the number of HF patients is predicted to increase . CompareMost baseline factors of geriatric HF patients between live and dead groups were significantly different, so it is possible to use baseline factors at the onset to predict the clinical prognosis of patients. Currently, several risk prediction tools have been constructed to predict the clinical prognosis of geriatric HF patients , 19–21. Our study utilized a random forest algorithm to construct a post-operative mortality prediction model based on risk factors. Additionally, the ROC analysis results demonstrated that the random forest algorithm-based prediction model has higher predictive accuracy than logistic regression-based model in training and testing datasets. As far as we know, this study is the first attempt to utilize the random forest to predict the post-operative clinical prognosis of geriatric HF patients. The results of our study demonstrate the potential of a random forest algorithm for predicting the prognosis of geriatric fracture patients. In our opinion, as clinical research based on big data has become a trend, machine learning represented by random forests would be applied to the construction of various disease risk prediction models. The 1-year post-operative mortality is one of the important indicators for evaluating the clinical prognosis of geriatric HF patients . Our stuCurrently, many previous studies reported that many risk factors could affect post-operative 1-year mortality in geriatric HF patients, such as age, surgery delay, hemoglobin, albumin, serum sodium, C-reactive protein, parathyroid hormone, thyroid-stimulating hormone, renal failure, diabetes, metabolic syndrome –40 Tabl. All theAdditionally, our results demonstrated that hemoglobin and albumin levels were significantly associated with the 1-year post-operative mortality rate, which is supported by a previous study , 44. DelSome limitations of this study must be acknowledged. First, only geriatric HF patients who underwent surgery were examined, rather than all geriatric HF patients. Second, our study was retrospective. In our study, we included as many clinical variables as possible, but there were still a few variables that were not included, such as cardiovascular disease, C-reactive protein, thyroid-stimulating hormone, anesthesia technique, etc. Further studies are needed to investigate whether adding these clinical variables could improve the accuracy of the prediction model. Third, datasets in our study were unbalanced and not large enough. Further studies with large multicenter samples are needed to improve the accuracy of the random forest prediction model.Our study constructed a risk prediction model with high accuracy to predict the post-operative clinical prognosis of geriatric HF patients by the random forest algorithm. The random forest algorithm-based prediction model in our study could be used for the early identification of geriatric HF patients with a high risk of post-operative death and can provide important insights to doctors and nursing staff who can then adapt their diagnosis and treatment per patient by predicting risks in advance.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.This study was approved by the Institutional Ethical Review Board of West China Hospital, Sichuan University. The patients/participants provided their written informed consent to participate in this study.FX wrote the manuscript. FX, RL, and ML collected the data and assisted in the data analysis. XD, ZZ, and ZX designed and supervised this project. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China (31870961 and 81501879), the Sino-German Center for Research Promotion (GZ1219), the Science and Technology Department of Sichuan Province , and the National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University (Z2018A11).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Introduction: The present study aimed to establish the role of lipid abnormalities and inflammatory markers for developing cardiovascular risk, as well as to address the importance of obesity as a common comorbidity in patients with obstructive sleep apnea (OSA).Methods: The study was conducted as a prospective cohort study including 120 patients with newly diagnosed OSA between 2019 and 2020, at University Clinical Hospital Center “Bezanijska kosa”, Belgrade, Serbia. The diagnosis was established by polysomnography. In all patients, sociodemographic data, respiratory, lipid, and inflammatory parameters were collected and complete echocardiographic study and 24-h blood pressure monitoring were performed.Results: The mean patient age was 55.7 ± 13.8 years. Study population was mostly male (70.0%) and obese (56.7%). At least 30 apneas or hypopneas per hour were present in 39.0% of patients. A strong positive correlation was found between OSA severity and BMI , both associated with lipid, inflammatory and respiratory parameters, and cardiovascular profile of patients with OSA . Echocardiographic study and 24-h blood pressure monitoring parameters were in turn correlated with lipid and inflammatory markers .Conclusion: The results of this study support the important role of dyslipidemia and inflammation, as well as coexistence of obesity in the pathogenesis of numerous conditions linked with an increased risk of cardiovascular morbidity and mortality in patients with OSA. Obstructive sleep apnea (OSA) is characterized by repetitive episodes of apnea due to upper airway obstruction occurring during sleeping hours. These episodes cause intermittent hypoxia which leads to oxidative stress and increased free radicals production . This isThe present study aimed to establish the role of lipid abnormalities and inflammatory markers for developing cardiovascular risk, as well as to address the importance of obesity as a common comorbidity in patients with obstructive sleep apnea.The study was conducted as a prospective cohort study including 120 patients with newly diagnosed OSA during the period between May 2019, and May 2020, at the Department of Pulmonology, Center for diagnostics and treatment of obstructive sleep apnea, of the University Clinical Hospital Center “Bezanijska kosa”, Belgrade, Serbia. This study represents an additional prospective analysis of the previous study by To establish the diagnosis of OSA and its severity, the polysomnographic study was performed with the Alice 4 Sleep System . Sleep parameters were evaluated following the 2007 American Academy of Sleep Medicine (AASM) protocol . Apnea-HSchiller AG, Baar, Switzerland) and card(X)plore . The collected data included the following echocardiographic parameters: aortic root diameter, left atrium diameter, end-diastolic and end-systolic left ventricle diameter, interventricular septum thickness, posterior wall thickness, ejection fraction, fractional shortening. Aortic root diameter was measured at the level of Valsalva’s sinuses by M-mode tracings. Mean heart rate during day and night, minimum and maximum heart rate, mean systolic blood pressure, mean diastolic blood pressure, and mean arterial pressure during day and night, as well as mean pulse pressure during day and night, were collected from 24-h blood pressure monitoring. The parameters of arterial stiffness, Augmentation Index (AIx), and Pulse Wave Velocity (PWV), were also calculated. Reference values for laboratory, respiratory, and cardiovascular parameters are provided in Demographic data , past medical history , medications, and data regarding smoking alcohol consumption, and physical activity were collected. Laboratory markers of inflammation and lipid levels were collected, including C-reactive protein, erythrocyte sedimentation rate (ESR), triglycerides, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), non-high-density lipoprotein (non-HDL) and monocyte to HDL ratio. Average and minimum oxygen saturation and percentage of time with oxygen saturation below 90% during the sleep test were registered. The echocardiographic study was performed in all participants on Toshiba TUS-AT Aplio 900/AE machine , while 24-h monitoring of arterial blood pressure was performed on MEDILOG AR12PLUS .Numerical data were presented as mean with 95% confidence interval, or median with minimum and maximum value. Categorical variables were summarized by absolute numbers with percentages. Correlations between numerical variables, AHI and BMI were assessed by the Pearson correlation coefficient. Multivariate linear regression models were used to assess predictors of AHI and BMI. In all analyses, the significance level was set at 0.05. Statistical analysis was performed using IBM SPSS statistical software .The study population included 120 patients, with a mean age of 55.7 ± 13.8 years, mostly male (70.0%). Nineteen patients (16.1%) had an AHI of less than five events per hour, 22.9% had an AHI of at least 5 events per hour, but fewer than 15, and 22.0% of patients had an AHI of at least 15 events per hour but fewer than 30. The majority of patients (39.0%) had an AHI of at least 30 events per hour. More than half (56.7%) of the study population were obese (BMI >30) and 28.7% were overweight (BMI between 25 and 30). Twenty-eight percent of the patients were active smokers, 39.4% were consuming alcohol occasionally or often, and 57.3% were physically inactive. Hypertension was present in 57.5% of the study population, 20.0% had diabetes mellitus, 16.7% of the patients had hyperlipidemia, and 11.7% had an history of myocardial infarction. More than half of the patients (56.7%) were on antihypertensive therapy and 16.7% were receiving hypolipemic therapy. Demographic data, comorbidities, use of medications, lipids and inflammation parameters in the study population, as well as their correlation with AHI and BMI are shown in p < 0.05 for all).Respiratory and cardiovascular parameters of the study population and their correlation with AHI and BMI are shown in A strong positive correlation found between AHI and BMI (r = 0.562) is presented in p = 0.004), diabetes mellitus (p = 0.038) and gender (p = 0.038) were significantly associated with AHI (p = 0.002), glucose (p = 0.003), and CRP were significant predictors of AHI, while out of respiratory parameters, ODI (p < 0.001) and average saturation (p < 0.001) were significantly associated with AHI (p = 0.002), pulse pressure at night (p = 0.004) and aortic root diameter (p < 0.001) were found to be significantly associated with AHI in multivariate linear regression model  and diabetes mellitus (p < 0.001) were significantly associated with BMI (p < 0.001), ESR (p = 0.001) and glucose (p = 0.016) were significantly associated with BMI. ODI (p = 0.029), SaO2 min (p < 0.001) and Epworth (p = 0.045) were respiratory parameters significantly associated with BMI (p = 0.001) and IVS (p = 0.018) were also found to be significantly associated with BMI in multivariate linear regression model , pulse pressure during night , and IVS thickness . HDL-c was negatively correlated with heart rate during night , aortic root diameter , but also with end-systolic left ventricle diameter , IVS thickness , and PW thickness . IVS was positively correlated with total cholesterol to HDL ratio  and LDL-c to HDL-c ratio , while EF was negatively correlated with total cholesterol to HDL ratio  and LDL-c to HDL-c ratio . Positive correlation was found between total cholesterol to HDL ratio and PW thickness   .p = 0.027), mean systolic blood pressure at night , mean total heart rate , mean total heart rate at night , mean total pulse pressure , mean total pulse pressure at night , mean total Augmentation Index , mean Augmentation Index at day , mean Augmentation Index at night , and IVS thickness . ESR was in positive correlation with mean systolic blood pressure at night , mean total pulse pressure , mean pulse pressure at night , mean total Augmentation Index , mean Augmentation Index at day , and mean Pulse Wave Velocity at night . Positive correlation was also found between monocyte to HDL ratio, AHI , mean total heart rate , mean heart rate at night , and IVS thickness   .In the present study on 120 patients with newly diagnosed OSA, we observed a strong correlation between AHI, obesity, lipid abnormalities, inflammatory markers and various cardiovascular parameters. These results are in accordance with previous studies, and provide an insight into potential pathophysiological mechanisms regarding the increased cardiovascular risk in patients with OSA.OSA is a common condition associated with an increased cardiovascular risk . IntermiGasa et al. showed that OSA in extremely obese patients was associated with major metabolic impairment caused by poorer hypertension, lipid, and glucose control (Obesity plays an important role in the pathophysiology of OSA. It is shown that increased body mass index in patients with OSA is strictly related to cardiovascular risk, unlike AHI, as presented in the study by  control . We presDudenbostel et al. reported that 90% of male patients and 77% of female patients with resistant hypertension had obstructive sleep apnea, while nocturnal hypertension is significantly higher in patients with OSA and is associated with the risk of total cardiovascular disease, cardiovascular death, heart failure, stroke and myocardial infarction (Jung et al., patients with obstructive sleep apnea had significantly higher values of CRP, which was marked as an independent risk predictor for cardiovascular morbidity (Recurrent hypoxia, continuous stimulation of the renin-angiotensin-aldosterone system, and sympathetic nervous system activation promote hypertension development in patients with OSA. Hypertension in patients with OSA is characterized by nocturnal hypertension, abnormal blood pressure variability, and relatively poor regulation with standard antihypertensive therapy . These afarction . A 20 mmfarction . Effectifarction . It is sfarction . In the orbidity . Severalorbidity .Up to 50% of patients with OSA have nocturnal arrhythmias, mostly atrial fibrillation and ventricular arrhythmias . ArrhythMaripov et al., cardiac remodeling also involves the right ventricle in terms of right ventricular dilatation, increased wall thickness, and altered right ventricular function (Obstructive sleep apnea is significantly associated with cardiac remodeling, leading to atrial dilatation, left ventricular hypertrophy, enlargement, mass increase, diastolic dysfunction, and reduction of systolic function . In our function . Our stufunction . A low vfunction . Regardifunction . These pArterial stiffness is a strong independent predictor of adverse cardiovascular events and mortality . VariousDelsart et al. demonstrated that the relationship between aortic root diameter and the severity of OSA persisted even in patients on CPAP therapy (Alegret et al. demonstrated that cholesterol is associated with increased aorta diameter and dilation (Chen et al. concluded that lipid profile had no relation to any aortic segments diameter, except HDL cholesterol that had a significantly positive effect on the diameter of ascending aorta (Aortic root diameter was significantly associated with AHI in the multivariate linear regression model. A similar conclusion was established in several studies investigating the relation between aortic root diameter and the severity of OSA . The stu therapy . It is i therapy . An incr therapy . The patdilation . Chen etng aorta . In our ng aorta .The present study has several advantages and limitations. It represents not only strong evidence of the association between various cardiovascular parameters and OSA severity but also the association with lipid abnormalities and inflammation, potentially revealing the main pathophysiological mechanisms responsible for increased cardiovascular risk. The novelty of this paperwork lies in the fact that according to common cardiovascular parameters that we observe in everyday clinical practice, we can stratify OSA patients with an increased risk of developing cardiovascular complications. Newly diagnosed patients with the severe form of obstructive sleep apnea, lipid abnormalities, and higher levels of inflammatory parameters, associated with other significant risk factors, should go through an extensive cardiovascular screening to prevent future adverse cardiovascular events. It is also important to note that by including only patients with newly diagnosed obstructive sleep apnea we prevented the possible positive effects of CPAP therapy on the improvement of cardiovascular parameters and reduction of cardiovascular risk. The main limitations of the study are the lack of 24-h ECG Holter monitoring data, the scarce number of evaluated inflammatory parameters, and the absence of follow-up regarding future adverse cardiovascular events and outcomes.In the present study on 120 patients with newly diagnosed OSA, we observed a significant correlation between OSA severity, obesity, lipid abnormalities, inflammatory markers, and various cardiovascular parameters. These results imply the inevitable role of dyslipidemia and systemic inflammation with the occurrence of atherosclerotic cardiovascular disease in patients with OSA, leading to an increased susceptibility for coronary artery disease, myocardial infarction, arrhythmias, stroke, and sudden death. Future studies should focus on the identification of credible risk predictors and the development of novel therapeutic modalities to significantly reduce the chance of future major adverse cardiovascular events.


Systemic hypoperfusion plays a pivotal role in the pathogenesis of primary open-angle glaucoma (POAG). Extreme dips in mean arterial pressure (MAP) due to high 24-h variability are associated with POAG, however, whether this is driven by diurnal or nocturnal dips remains undocumented. We aimed this study to investigate the association of POAG damage with variability and dips in the diurnal and nocturnal MAP.We conducted a retrospective longitudinal study that included 110 POAG patients who underwent 24-h ambulatory blood pressure monitoring. Our outcomes included (i) functional [visual field defects expressed as mean deviation (MD)] and (ii) structural (optic disc cupping obtained from cup-to-disc ratio) glaucoma damage. MAP variability independent of the mean (VIMmap) was computed for diurnal and nocturnal MAP. Dips were the five diurnal and three nocturnal lowest drops in MAP. We also calculated the night-to-day ratio. We applied mixed models to evaluate the progression of visual field defects and optic disc cupping in relation to diurnal and nocturnal MAP measures.P < 0.001) and diurnal MAP dips . Every 5 mmHg decrease in the nocturnal MAP level was associated with −1.14 dB changes in MD  and 0.01 larger optic disc cupping . Lower night-to-day ratio was also related to both outcomes (P ≤ 0.012). Functional glaucoma damage worsened if nocturnal hypotension was combined with high variability or extreme dips in the diurnal MAP (P ≤ 0.022).The mean age was 64.0 y (53% women). The median follow-up was 9 years. In adjusted mixed models, functional progression of glaucoma damage was associated with VIMmap . Open-angle glaucoma (OAG) is a progressive optic neuropathy characterized by loss of retinal ganglion cells and visual deterioration in eyes with or without high intraocular pressure . The patWe included patients age ≥ 18 or older with OAG from the database available at the Glaucoma Department, University Hospitals Leuven, Belgium to conduct a retrospective, observational, cohort study. We identified 476 Caucasian patients with OAG followed between 1998 and 2019 who underwent 24-h ambulatory blood pressure monitoring at the Glaucoma Department, University Hospitals Leuven. The assessment of the 24-h blood pressure was performed because patients experienced progression of glaucoma damage despite the intraocular pressure being within the normal range during follow-up. Of 476 patients, a total of 110 patients with primary open-angle glaucoma (POAG) were included in the present study. POAG was defined as glaucoma patients with maximal recorded untreated intraocular pressure level above 21 mm Hg. The Ethics Committee of the University Hospitals Leuven approved the secondary use of the data from the glaucoma patients .®) or Optical Coherence Tomography Spectralis® . The visual field was tested using the Humphrey Visual Field Analyzer HFA3®  or the Octopus 300/900 system® . Glaucoma was diagnosed following the 5th European Glaucoma Society Guidelines, as a significant optic nerve rim and retinal nerve fiber layer thinning with congruent visual field defects. The ophthalmic examination was performed by glaucoma specialists, and included measurement of best-corrected visual acuity, biomicroscopy and fundus examination by slit lamp examination and a 90-diopter lens. The intraocular pressure was measured with Goldmann applanation tonometry. Optic disc cupping was the cup-to-disc ratio estimated by glaucoma expert visual rating during the fundus examination. The optic nerve head and the retinal fiber layer were examined by Heidelberg Retinal Tomography  . The proay ratio . Night-tFor database management and statistical analysis, we used SAS software, version 9.4, maintenance level 5. Baseline characteristics were reported as arithmetic mean with standard deviation for continuous variables with normal distribution, or median with interquartile ranges for non-parametric continuous variables. Categorical data was reported as frequency and percentage (%). Our outcome was glaucoma progression assessed as longitudinal changes in the (i) mean deviation, expressed in decibels (dB) or (ii) optic disc cupping assessed as cup-to-disc ratio. We conducted unadjusted and adjusted linear mixed models to evaluate the relationship between glaucoma progression and ambulatory MAP measurements. Adjusted models accounted for variables with biological relevance and additionally accounted for the time difference between the baseline visual field test/fundus examination and ambulatory blood pressure monitoring. n = 45) patients with POAG were women  regardless of potential confounders and diurnal (P < 0.001) to –1.59 dB . Neither diurnal VIMmap nor dip measures were significantly related to the progression of structural glaucoma damage (P = 0.380), however, the predicted mean deviation was worse in relation to higher diurnal variability (P < 0.001) and lower MAP dips (P < 0.001). The predicted cup-to-disc ratio was similar across categories of diurnal MAP level  were not associated with the progression of glaucoma damage  and 0.01 larger optic disc cupping . Patients with a nocturnal MAP level below 74 mm Hg had a −7.54 dB change in the mean deviation (P = 0.005). Every 0.05 mm Hg decrease in the night-to-day ratio related to −0.98 dB change in the mean deviation  and 0.02 larger cup-to-disc ratio . In a categorical analysis of the night-to-day ratio, we did not observe a significant association of extreme dipping with glaucoma damage (P ≥ 0.051). Nocturnal VIMmap was not associated with glaucoma damage (P = 0.054). Only the duration of the nocturnal dips and dips minus the nocturnal MAP level were significantly associated with changes in the mean deviation—the estimates were −1.59 and −1.37 dB; respectively. The other nocturnal dip measures were not statistically related to glaucoma damage (P ≥ 0.224). P = 0.008) and night-to-day ratio (P = 0.030), but did not worsen for variability or dips categories  and −2.54 dB  longitudinal changes in the mean deviation.Structural glaucoma damage was only associated with low nocturnal MAP, therefore, we plotted in Our study results indicate that the diurnal profile of sporadic drops in the MAP during the daytime due to high MAP variability is related to the progression of glaucoma damage rather than the absolute diurnal MAP level. On the contrary, low nocturnal MAP level—rather than variability—was associated with functional and structural glaucomatous damage. The progression of functional glaucomatous damage worsened if nocturnal hypotension was accompanied by high variability or extreme dips in the diurnal MAP.Our finding that nocturnal hypotension was associated with the progression of functional and structural glaucomatous damage among patients with POAG is in agreement with numerous studies –6. AsideThe clinical perspective of our findings considers the identification of glaucoma patients experiencing sporadic drops in the diurnal MAP that could lead to reduced ocular perfusion pressure. It is important to differentiate between repetitive drops and diurnal hypotension—the last is more complex to recognize than nocturnal hypotension. The complexity relies on the diurnal MAP level being at the range where autoregulation plateaus are preserved . The eyeThe perfusion pressure to the eyes is physiologically lower than at the brachial level in the standing and sitting positions . This is24-h intraocular pressure was not assessed in our study. Nevertheless, it is important to put in perspective our findings with regards to 24-h intraocular pressure. Patients with glaucoma progression have more diurnal peaks and fluctuations in the intraocular pressure compared to patients without progression , 30. SucLimitation of our study includes the selection of patients with advanced POAG. The University Hospitals of Leuven is a tertiary referral center and therefore a high proportion of included patients have advanced and progressive glaucoma which limits the generalizability of our findings among patients with moderate glaucoma damage. The retrospective nature of our study and lack of 24-h intraocular pressure are also limitations for interpreting our findings. Finally, the criteria to perform ambulatory blood pressure in glaucoma patients was based on the progression of the disease despite the intraocular pressure being kept within the normal range which might represent a selection bias.Progression of glaucoma damage in patients with POAG associates with high variability and extreme dips in the diurnal MAP. Structural glaucomatous damage seems more vulnerable to occur in the presence of nocturnal MAP hypotension. Nowadays evidence focuses on nocturnal hypotension, omitting patients with OAG experiencing repetitive extreme drops in the MAP during the daytime. By implementing 24-h ambulatory blood pressure monitoring, it is possible to identify sporadic diurnal and persistent nocturnal hypotension episodes associated with glaucoma damage. In combination with 24-h intraocular pressure, ambulatory blood pressure monitoring might lead to better stratification of glaucoma risk.ingeborg.stalmans@mac.com.The datasets presented in this article are not readily available because due to the restrictions based on privacy regulations, local data sharing laws, and informed consent of the participants, data cannot be made freely available in a public repository. Requests to access the datasets should be directed to IS, The studies involving human participants were reviewed and approved by the Ethics Committee of the University Hospitals Leuven. The patients/participants provided their written informed consent to make scondary use of the data in this study.JM, JE, GM, LA-A, KK, IS, and Z-YZ contributed to the conception and design of the study. JM, JE, DW, KK, TV, SJ, PV, IS, and Z-YZ contributed to the acquisition of data. JM, JE, and Z-YZ constructed, organized, and managed the database. JM, JE, LM, and Z-YZ performed the statistical analysis. JM, JE, KK, IS, and Z-YZ wrote the draft and sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.


Cerebral hypoperfusion and impaired oxygen delivery during pediatric critical illness may result in acute neurologic injury with subsequent long-term effects on neurodevelopmental outcome. Yet, the impact of norepinephrine on cerebral hemodynamics is unknown in children with shock. We aimed to describe the norepinephrine effects on cerebral perfusion and oxygenation during pediatric shock.0), and the steady-state (Tss). Cardiac output (CO) was measured using ultrasound. Cerebral perfusion was assessed on middle cerebral arteries (MCA) using transcranial doppler ultrasound. Cerebral tissue oxygen saturation (rScO2) was recorded using near infrared spectroscopy, and we calculated cerebral fractional tissue oxygen extraction (cFTOE = SpO2-rScO2/SpO2).We conducted an observational multicentre prospective study in 3 French pediatric intensive care units. Children <18 years of age excluding traumatic brain injury were included in the study if they need norepinephrine for shock. Systemic and cerebral hemodynamics were compared between the time of initiation of norepinephrine  without change of CO. MCA velocities, pulsatility index, rScO2, and cFTOE did not significantly change between T0 and Tss. Some individuals observed variations in estimated CBF, which slightly improved in 7 patients, remained unchanged in 5, and was impaired in 2. No patient experienced significant variations of rScO2.Fourteen children  were included. Norepinephrine at 0.2 μg/kg/min significantly increased mean arterial blood pressure (61 mmHg at TLow-dosing norepinephrine, despite a homogeneous and significant increase in arterial blood pressure, had little effects on cerebral perfusion and oxygenation during pediatric shock. This reinforces the need for personalized tailored therapies in this population.https://clinicaltrials.gov/ct2/show/NCT03731104.Clinicaltrials.gov, NCT 03731104. Registered 6 November, 2018.  Since the establishment of targeted guidelines for the management of septic shock, patients' survival has dramatically improved . HoweverYet, to date, the impact of norepinephrine on cerebral perfusion and oxygenation is unknown in children with shock. TCD reflects cerebral blood flow velocities which may be considered a surrogate for cerebral perfusion in stable conditions . CerebraWe aimed to describe the changes of cerebral oxygenation (using NIRS) and perfusion (using TCD) during norepinephrine infusion in critically ill children with shock.This prospective observational study  was conducted in 3 pediatric intensive care units in Paris, France. The study was allowed by a national institutional review board  before the first inclusion. Oral informed consent was obtained from the parents or legal guardians of the included children. The principal study was planned to describe cerebral circulation in children with hemodynamic failure requiring all types of vasoactive or inotropic treatments. Herein we report our results on patients with norepinephrine only.Children <18 years old were included if they needed norepinephrine for shock defined by inadequate tissue perfusion with or without arterial hypotension , 21. Cli0). All the investigators were pediatric intensivists trained in advanced ultrasound. All the patients had central line placed before norepinephrine's initiation. Norepinephrine  was infused solely via central venous catheter. The timing of initiation, initial dosing, and subsequent changes were left to the physician's decision. The need for fluid resuscitation before norepinephrine initiation was also left to the physician's discretion according to local practices and current guidelines (2) concentrations were also collected at T0 and at the end of the data collection, when available. Because of the observational nature of the study, no additional blood sample was collected during the procedure.Due to the cumbersome nature of the data collection, patients were included only on weekdays and outside of night shifts. Patients' eligibility was assessed each morning at the medical examination. When a patient met the inclusion criteria, one investigator was dedicated solely to the procedure and present in the room at the time of norepinephrine's initiation  as the dosing achieved at least 30 min following the start of treatment, or 10 min from the last dosing modification. Ultrasonography was performed using a VIVID S5TM  with a 3MHz probe. For each measure, two windows acquisitions were performed. In case of a difference of more than 20% between the 2 measures, a third one was performed and the mean was recorded. Transthoracic cardiac ultrasound was used to estimate cardiac output (CO). CO was derived from the stroke volume (SV) measured at the apical 5-chamber window, the left ventricular outflow tract (LVOT) diameter, the time velocity integral (TVI), and the heart rate (HR). CO was then calculated as CO=TVI*HR* π [LVOT diameter/2]2 and indexed to body surface area in order to obtain cardiac index (CI).Systemic  and cardiac output) and cerebral hemodynamics (perfusion and oxygenation) were assessed by the same investigator first at Tchildren : Herein 0 and Tss defined improved cerebral perfusion, whereas the opposite defined altered cerebral perfusion  segment of middle cerebral arteries (MCA). We measured systolic (Vs), diastolic (Vd), and mean (Vm) velocities, and estimated pulsatility index (PI) as PI=[Vs-Vd)]/Vm, and resistance Index (IR) as RI=[Vs-Vd]/Vs. An increase of Vm and/or a decrease of PI between Terfusion .®, Medtronics, USA). Two sensors were placed on both sides of the patient's forehead to record cerebral tissue oxygen saturation (rScO2). Significant cerebral oxygenation variations (ΔrScO2) were defined as changes of the rScO2 absolute value of more than 20% between T0 and TSS (2-rScO2)/SpO2  cerebral NIRS oximeter /SpO2 – 26.0 and Tss using paired t-test or Wilcoxon rank sum test depending on the variables' normality on histograms and Shapiro-Walk tests. A p-value < 0.05 defined statistical significance. Data were analyzed using R programming software.Results are presented with their medians and Interquartile Range (IQR) for continuous variables, and numbers and percentages for categorical variables. To assess the effect of norepinephrine for each patient, we compared the collected parameters between Tn = 12), hemorrhagic shock (n = 1) or vasodilatory shock during acute respiratory distress syndrome (n = 1). No patient received fluid expansion between T0 and TSS. Norepinephrine dosing was 0.2  μg/kg/min at Tss. TSS was achieved without modification of norepinephrine's dosing after 30 min for 11 patients. For the 3 left patients, norepinephrine's dosing needed to be increased once. TSS was achieved, respectively, at 40, 45, and 100 min after norepinephrine's initiation. Details are described in n = 5), normal (n = 5) or high (n = 4) CI  received norepinephrine and were included in this study. Indications for norepinephrine were septic shock ( = 4) CI . Individss vs. 49  mmHg at T0, p = 1.10−3) without significant change of CI and HR , decreased in 2 , and remained unchanged in 5.While blood pressure increased in all the patients, some individuals observed a moderate variations of the TCD measured CBF velocities, which slightly improved in 7  had rScOinfusion .The evolution of cerebral hemodynamics during norepinephrine infusion seemed to be highly variable between patients regarding both perfusion and oxygenation . This paAt the best of our knowledge, this study is the first to investigate the cerebral hemodynamic effects of norepinephrine in children with shock. Low-dosing norepinephrine induced a homogeneous and significant increase in arterial blood pressure, but had variable effects on cerebral perfusion and oxygenation, suggesting uncoupling between systemic and cerebral hemodynamics. The restoration of systemic macrocirculation does not always reverse tissue hypoxia. Conversely, endothelial dysfunction leading to cellular hypoxia might be present long before the alteration of macrocirculation. In critically ill children, this loss of hemodynamic coherence  is commoAs expected, our patients experienced an increase in blood pressure during norepinephrine infusion. In contrast, CI and HR remained relatively stable given the modest norepinephrine related ß1-inotropic and chronotropic effects. Norepinephrine effects on CO were however variable between individuals. Norepinephrine's cardiac effects might vary depending on the cardiac preload , ca2). It cannot be ruled out that some patients may have experienced significant CO2 variations during norepinephrine infusion, which could impact cerebral vasoreactivity. The neurological benefit of treatments targeting systemic hemodynamics in patients with preserved CAR is unknown. In this population, acute brain dysfunction may be the consequence of other pathological mechanisms , which may not be impacted by norepinephrine.Despite norepinephrine induced a homogeneous increase in MAP, cerebral perfusion assessed by TCD did not improve in the entire population. However, the patients' time course evolution suggests that the effect of norepinephrine on cerebral perfusion may differ between individuals . The bet2 and cFTOE (2) at T0  at T0 . Cerebra piglets  and in a piglets . RScO2 ie of CBF  but shou2 reflects cerebral oxymetry solely of the cortical frontal  region, and might depend on age, weight, and the presence of edema. Normal values of FTOE have not been validated in all pediatric age range outside the neonatal period. To a lesser extent, TCD might be misinterpreted in case of poor acquisition windows. Finally, the absence of patients with higher norepinephrine dosing prevents us from any conclusion about its effects in severe shocks. It is conceivable that greater amplitude of norepinephrine-induced changes in MAP could have resulted in a larger, and therefore more significant, impact on cerebral perfusion and oxygenation. We also admit that some patients probably had suitable or nearly normal cerebral flow and oxygenation at T0. If cerebral hemodynamics were not impaired at baseline due to sufficient compensatory mechanisms, this might explain the absence of norepinephrine's significant effect between T0 and TSS regarding cerebral circulation.The main limitation of the present study is the small size of the population and the heterogeneous baseline and clinical conditions that might lead to the between-subjects variability observed in cerebral hemodynamics time course. However, we did not find such variability regarding blood pressure evolution despite the population's heterogeneity. Because our study design was descriptive and exploratory only, we did not perform a formal sample size calculation. We might assume that our study lacked power to demonstrate any significant impact of norepinephrine on cerebral circulation due to this small sample size. Second, the technical limits of the devices that we used allow only an indirect estimation of cerebral hemodynamics. NIRS is presumed to assess chromophores (Hemoglobin and Deoxyhemoglobin) concentrations at a level of 2 to 4 cm from its cutaneous sensor, where the microvessels stand. Thus, measured rScODespite these limitations, the rigorous assessment of both cerebral and systemic hemodynamics changes in real time allowed us to describe for the first time the variable effects of low-dosing norepinephrine on cerebral hemodynamics, which might be unpredictable regarding the evolution of systemic hemodynamics. Physicians should be aware of this potential between-subjects variability to target therapy according to the patient's systemic, but also cerebral hemodynamics. This reinforces the need for an individualized monitoring in critically ill children. This original study emphasizes the importance of monitoring regional and cerebral circulation during pediatric shock. We believe that these preliminary results should lead to further the investigations on the cerebral effects of vasoactive and inotropic drugs in critically ill children.This study has been promoted by Assistance Publique-Hôpitaux de Paris (AP-HP).The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by French Institutional Review Board South-East IV (CPP SO IV), ref 2018-A01392-53. Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.MV-C, SR, and MO conceptualized and designed the study. MV-C, JC, MG, and P-LL performed the ultrasound exams and collected the data in ICU. MV-C performed analyses and interpretation of data and drafted the first manuscript. MO supervised the analysis and writing of the manuscript. All authors revised the article critically and approved the final version to be published.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The cardiorenal effects of sodium-glucose cotransporter 2 inhibition (empagliflozin 25 mg QD) combined with angiotensin-converting enzyme inhibition (ramipril 10 mg QD) were assessed in this mechanistic study in patients with type 1 diabetes with potential renal hyperfiltration.Thirty patients (out of 31 randomized) completed this double-blind, placebo-controlled, crossover trial. Recruitment was stopped early because of an unexpectedly low proportion of patients with hyperfiltration. Measurements were obtained after each of the 6 treatment phases over 19 weeks: (1) baseline without treatment, (2) 4-week run-in with ramipril treatment alone, (3) 4-week combined empagliflozin-ramipril treatment, (4) a 4-week washout, (5) 4-week combined placebo-ramipril treatment, and (6) 1-week follow-up. The primary end point was glomerular filtration rate (GFR) after combination treatment with empagliflozin-ramipril compared with placebo-ramipril. GFR was corrected for ramipril treatment alone before randomization. At the end of study phase, the following outcomes were measured under clamped euglycemia (4 to 6 mmol/L): inulin (GFR) and para-aminohippurate  clearances, tubular sodium handling, ambulatory blood pressure, arterial stiffness, heart rate variability, noninvasive cardiac output monitoring, plasma and urine biochemistry, markers of the renin-angiotensin-aldosterone system, and oxidative stress.2 lower GFR compared with placebo-ramipril treatment (P=0.0061) without significant changes to effective renal plasma flow. GFR decrease was accompanied by a 21.3 mL/min lower absolute proximal fluid reabsorption rate (P=0.0092), a 3.1 mmol/min lower absolute proximal sodium reabsorption rate (P=0.0056), and a 194 ng/mmol creatinine lower urinary 8-isoprostane level (P=0.0084) relative to placebo-ramipril combination treatment. Sodium-glucose cotransporter 2 inhibitor/angiotensin-converting enzyme inhibitor combination treatment resulted in additive blood pressure–lowering effects  in conjunction with a 94.5 dynes × sex/cm5 lower total peripheral resistance (P=0.0368). There were no significant changes observed to ambulatory blood pressure, arterial stiffness, heart rate variability, or cardiac output with the addition of empagliflozin.Combination treatment with empagliflozin-ramipril resulted in an 8 mL/min/1.73 mAdding sodium-glucose cotransporter 2 inhibitor treatment to angiotensin-converting enzyme inhibitor resulted in an expected GFR dip, suppression of oxidative stress markers, additive declines in blood pressure and total peripheral resistance. These changes are consistent with a protective physiologic profile characterized by the lowering of intraglomerular pressure and related cardiorenal risk when adding a sodium-glucose cotransporter 2 inhibitor to conservative therapy.https://www.clinicaltrials.gov; Unique identifier: NCT02632747.URL:  We demonstrated that the addition of empagliflozin to ramipril for 4 weeks improves surrogate measures of renoprotection in people with uncomplicated type 1 diabetes and preserved kidney function.Physiologic mechanisms of sodium-glucose cotransporter 2 inhibitors hypothesized to modulate tubuloglomerular feedback and reduce glomerular hypertension were ameliorated with the addition of empagliflozin, represented by a decreased proximal renal tubular sodium reabsorption and an anticipated dip in glomerular filtration rate.Empagliflozin, when added to ramipril, lowered blood pressure and total peripheral resistance without affecting arterial stiffness, heart rate variability, or cardiac output, suggesting a novel sodium-glucose cotransporter 2 inhibitor–mediated antihypertensive mechanism.This is the first mechanistic trial that evaluated the effect of adding sodium-glucose cotransporter 2 to angiotensin-converting enzyme inhibition on physiologic effects, including acute effects on glomerular filtration rate, which were consistent with cardiorenal protection in clinical trials that have to date only included individuals with type 2 diabetes or nondiabetic kidney disease.Given the consistency of physiologic effects across different cohorts, including in patients with type 1 diabetes, future clinical trials should continue to evaluate whether chronic sodium-glucose cotransporter 2 inhibition reduces the risk of cardiorenal complications in novel populations at high risk of kidney failure or cardiovascular disease.463Editorial, see p 1 and cardiorenal end points in patients with albuminuric chronic kidney disease.3 SGLT2i reduced glycated hemoglobin (HbA1c) by 0.7% to 1.0%, systolic blood pressure (SBP) by 3 to 5 mm Hg, and body weight by 2 to 4 kg.5The discovery that sodium-glucose cotransporter 2 (SGLT2) inhibitors (SGLT2i) reduce the risk of cardiovascular and kidney disease in patients with type 2 diabetes (T2D) has had a substantial effect on clinical practice. In cardiovascular outcome trials, these therapies reduced major adverse cardiac events, hospitalization for heart failure and kidney composite end points in patients with T2D,6 Moreover, kidney hyperfiltration is significantly attenuated with SGLT2i monotherapy.7 In light of the poor prognosis associated with hyperfiltration9 and kidney protective effects of SGLT2i in experimental models of T1D,11 these findings suggest that SGLT2i may promote a protective decrease in intraglomerular hypertension, even if used before the onset of clinical chronic kidney disease.14We previously demonstrated that SGLT2i alone exhibit similar effects on glycemic control, body weight, and blood pressure in patients with uncomplicated type 1 diabetes (T1D), a cohort that models early cardiorenal physiologic changes in patients with diabetes at a stage before the development of clinical complications.14 In addition, according to the tubular hypothesis  and leads to decreased distal Na+ delivery to the macula densa. This signal gets incorrectly sensed as a reduction in effective circulating volume leading to vasodilation of the afferent renal arterioles and thus hyperfiltration characteristic of diabetes.15 In an 8-week add-on-to-insulin study, empagliflozin induced a reduction in renal hyperfiltration16 in young patients with uncomplicated T1D and hyperfiltration that was comparable in magnitude to what has been reported with angiotensin-converting enzyme inhibition (ACEi) in a separate hyperfiltering T1D cohort.7 As with RAAS inhibitor (RAASi) monotherapy, SGLT2i did not abolish hyperfiltration, suggesting a potential kidney benefit when these therapies are combined to take advantage of both neurohormonal and tubular pathways. Whereas T1D is a good model of uncomplicated renal hemodynamic changes attributed to diabetes, such mechanisms can also apply to similar renal hemodynamic changes observed in other conditions, such as T2D or obesity.Whereas the mechanistic basis for glomerular hypertension in diabetes is complex, hyperglycemia plays an important role through neurohormonal activation and via effects on tubular function. First, the neurohormonal hypothesis of hyperfiltration suggests that activation of the renin-angiotensin-aldosterone system (RAAS) during hyperglycemia triggers vasoconstriction at the efferent renal arteriole.https://www.clinicaltrials.gov; Unique identifier: NCT02632747) was to determine the effect of a 4-week treatment with an SGLT2i, empagliflozin 25 mg QD, versus placebo, in addition to an ACEi, ramipril 10 mg QD or maximally tolerated dose, on glomerular filtration rate (GFR). Our secondary objectives were to study the effect of the addition of empagliflozin to ramipril treatment on distal sodium delivery and systemic hemodynamics. We hypothesized that adding empagliflozin treatment to a background of ramipril would decrease GFR and reduce cardiac output and arterial stiffness, leading to declines in SBP.Our aim was to investigate the additive cardiorenal hemodynamic effects of combined treatment with both agents, specifically neurohormonal suppression (with an ACEi) and activation of tubular (SGLT2i) factors, in patients with uncomplicated T1D, T2D, or obesity as mechanistic models of early cardiorenal physiologic changes before the development of clinical kidney or cardiovascular complications. The primary objective of this clinical trial . Detailed study inclusion and exclusion criteria at screening can be found in Table S1. In brief, inclusion criteria were as follows: male or female patients ≥18 years of age diagnosed with T1D ≥6 months before informed consent, patients with T2D, or obese patients without diabetes; HbA1c of 6.5% to 11.0% for patients with T1D or T2D; estimated GFR ≥60 mL/min/1.73 m²; and average blood pressure >90/60 mm Hg and ≤140/90 mm Hg. The main exclusion criteria were as follows: for patients with T1D, treatment with an antihyperglycemic agent within 3 months or history of hypersensitivity; treatment with an SGLT2i within 30 days; severe hypoglycemia that required emergency hospital treatment within 3 months before screening; or occurrence of diabetic ketoacidosis within 3 months. The local Research Ethics Board at the University Health Network  approved the protocol and all participants gave informed consent before start of study procedures. The study was conducted according to the International Conference on Harmonization on Good Clinical Practice.Thirty participants completed the study and had the primary GFR end point evaluated . This was a single-center , prospective, double-blind, randomized, placebo-controlled, crossover study, comprising 6 sequential phases over an ≈19-week time period : (1) a 2-week screening period without treatment; (2) a 4-week run-in period where patients were treated with ramipril 5 mg for 1 week and 10 mg for 3 weeks, following which patients were randomly assigned to follow either sequence A or B; (3) a 4-week period 1, where patients in sequence A were treated with empagliflozin 25 mg QD combined with ramipril 10 mg QD and patients in sequence B were treated with placebo combined with ramipril 10 mg QD; (4) a 4-week washout period where patients were only treated with ramipril 10 mg QD; (5) a 4-week period 2, where patients in sequence A were treated with placebo and ramipril 10 mg QD and patients in sequence B were treated with empagliflozin 25 mg QD and ramipril 10 mg QD; and (6) a 1-week posttreatment follow-up period.The study was registered at Table S2). During the clamp procedures, blood glucose was maintained at a stable level as described previously.17 Clamped euglycemia was maintained to reduce the background glycemic variability and the effect hyperglycemia could have on the outcome measures. For example, acute induction of modest hyperglycemia can induce a hyperfiltration response,18 raise blood pressure, and influence circulating neurohormonal mediators.19 Maintaining a physiologic state of euglycemia allowed us to isolate the effects of modulating tubuloglomerular feedback while minimizing neurohormonal activation by systemic hyperglycemia. In normoglycemic, nondiabetic participants, the clamp procedures were not planned as part of the physiologic studies.At the completion of the baseline, run-in, and periods 1 and 2, patients underwent full-day cardiorenal physiology assessments under controlled euglycemic clamp conditions (4 to 6 mmol/L) for ≈4 hours preceding and during all investigations  and high-sodium (>140 mmol/day) diet for 7 days leading up to the 4 physiology assessment visits. Participants were also asked to avoid alcohol and tobacco for at least 48 hours and to fast for a minimum of 12 hours before all physiologic assessment study visits. Treatment compliance was assessed on the basis of tablet count of dispensed and returned medication and was required to be 80% to 120% of the treatment dose.20 Mean baseline GFR and ERPF values were calculated as a mean of 2 independent clearance periods on each of the physiology assessment visits. Filtration fraction, renal blood flow, and renal vascular resistance (RVR) were calculated as described in Table S3.After stabilization of the ambient euglycemic clamp, a third intravenous line was used to infuse inulin and para-aminohippurate (PAH). First, the infusion was primed with 25% inulin (60 mg/kg) and 20% PAH (8 mg/kg), followed by a continuous infusion to maintain plasma concentrations at 20 mg/dL and 1.5 mg/dL, respectively. After a 90-minute equilibration period, blood samples were collected for inulin, PAH, and hematocrit with additional blood being drawn 30 minutes later. GFR and effective renal plasma flow (ERPF) were estimated under steady-state conditions of infusing inulin and PAH, respectively.22 Patients were instructed to take a single lithium carbonate tablet (300 mg) at 22:00 hours  the night before physiologic study visits. Blood and urine samples were collected after euglycemia was achieved during the physiologic study visits for sodium, lithium, and creatinine measurements. The following tubular sodium handling measures were calculated as described in Table S3:23 fractional sodium excretion, fractional lithium excretion, absolute proximal fluid reabsorption rate, absolute proximal Na reabsorption rate, fractional proximal fluid reabsorption, distal Na delivery, absolute distal Na reabsorption rate, and fractional distal Na reabsorption.Tubular sodium handling was assessed using established sodium and lithium clearance techniques.Ambulatory blood pressure monitoring (ABPM) was performed for 24 hours before each physiologic assessment study visit. The ABPM device was programmed to measure blood pressure every 20 minutes throughout the day and night. Mean blood pressure was analyzed during daytime, nighttime, awake time, sleep time, and through to peak time.Mean arterial pressure, blood pressure, and heart rate were measured by an automated sphygmomanometer over the right brachial artery  throughout the physiologic assessment study days.During each physiologic assessment study day, following the glucose clamp, right radial artery and carotid waveforms were recorded with a high-fidelity micromanometer and using the validated transfer function, corresponding central aortic pressure waveform data were generated . Augmentation index, an estimate of systemic arterial stiffness, was calculated as the difference between the second systolic peak and inflection point, expressed as a percentage of the central pulse pressure corrected to an average heart rate of 75 beats per minute. The aortic pulse wave velocity was measured using the same device by sequentially recording ECG-gated right carotid and radial artery waveforms. The average of 2 vascular measurements was reported.After completion of arterial stiffness testing, heart rate variability testing was performed using AtCor software . The average of two 10-minute segments was recorded. Vagal tone (root mean square successive difference) and sympathetic activity  measures were obtained at each of the 2 periods and the results were then averaged.24 Four sensor pads were applied above and below the heart on the chest. Each sensor pad contained an outer transmitting sensor and an inner receiving sensor. The NICOM monitor induced a 75-KHz AC current to the thorax by means of the outer sensors and received the voltage through the inner sensors. The sensors can detect a time delay or phase shift between the induced current and the received voltage. Stroke volume was derived on the basis of consecutive measurements of the phase shift. NICOM measurements were performed for 10 minutes and in duplicate and the mean of the measurements was reported. Weight, waist circumference, fasting plasma glucose, and HbA1c were measured during each physiologic assessment study visit.Noninvasive cardiac output monitoring  was used to measure cardiac output, cardiac power output index, stroke volume, total peripheral resistance, total peripheral resistance index, and thoracic fluid content during each of the physiologic assessment study visits. The NICOM monitoring system is on the basis of bioreactance technology.25 In addition, blood samples for angiotensin II, angiotensinogen, aldosterone, plasma renin concentration, 8-hydroxydeoxyguanosine, and 8-isoprostane were collected to determine the effect of treatment interventions on these measures.26 At corresponding time intervals, urine samples were collected to assess for nitric oxide (NO), 8-hydroxydeoxyguanosine, 8-isoprostane, and cyclic guanosine monophosphate.25 All urinary values were corrected for urinary creatinine at the time of collection and were expressed as a ratio relative to the amount of urinary creatinine excreted at the collection time points. In the 24 hours leading up to physiologic assessments, participants also completed a 24-hour timed urine collection, which was analyzed for volume and glucose excretion.During the steady-state euglycemic clamp conditions, inulin and PAH blood samples were collected to assess renal clearance measures according to standard methods.Plasma renin concentrations were measured with a sandwich chemiluminescence immunoassay kit . For measurements of 8-hydroxydeoxyguanosine, a Phenomenex Strata-X-A SPE plate, an AB Sciex 5500 Triple Quad spectrometer, and AB Sciex software were used. Aldosterone was measured using chromatography and mass spectrometry and enzyme-linked immunosorbent assay was used to measure urine cyclic guanosine monophosphate, 8-isoporastane nitric oxide, angiotensin II, and angiotensinogen. A 24-hour urine glucose level was assessed by standard laboratory methods. HbA1c was measured by high-performance liquid chromatography.² compared with placebo-ACEi, with an intraindividual standard deviation of 17.5 mL/min/1.73 m². With a 2-sided test with α=0.05 and >80% power, the sample size would have been 34 patients with hyperfiltration. Because of the unexpectedly low proportion of patients with hyperfiltration in the recruited cohort, study recruitment was stopped before reaching the planned sample size. Whereas the original hypothesis, related to the primary end point, was planned to be tested on the population with hyperfiltration as the primary analysis, this was not possible. However, a secondary analysis, prespecified in all versions of the protocol, was conducted on the overall trial population. This analysis was secondary in nature, but exploratory in relation to the predefined hypothesis regarding hyperfiltration. Secondary analyses were not part of the power or sample size calculations.The primary end point of this study was GFR after a 4-week treatment with empagliflozin-ramipril combination compared with placebo-ramipril. GFR values were corrected for randomization at the end of the run-in period. The sample size calculation was powered to detect a reduction of GFR with SGLT2i-ACEi by an additional clinically relevant 15 mL/min/1.73 mA random-effects crossover model, which is a mixed-effects model for repeated measures for a crossover design using restricted maximum likelihood, was used. The model uses a random effect for patient, fixed effects for the class variables treatment and period, and a fixed effect for the continuous variable randomization baseline of the end point. The model structure also gives rise to an implicit compound symmetry covariance structure for between-patient variance and consequently within-patient and between-patient variance is assumed to be independent under this model. The Kenward-Roger approximation was used to estimate denominator degrees of freedom and adjust standard errors. Significance tests were on the basis of least-squares means using a 2-sided α=0.05 (2-sided 95% CIs).²). Thus, because of the unexpectedly low proportion of patients with hyperfiltration, the study recruitment was stopped before recruitment of the planned sample size and analysis of patients with hyperfiltration compared with normofiltration was not pursued, and no patients with T2D or obesity only were recruited. The study population therefore comprised a homogeneous group of 30 patients with T1D  exhibited baseline hyperfiltration . No other significant changes in the renal hemodynamic or tubular sodium handling measures were observed after ramipril treatment  compared with an increase of 3 mL/min/1.73 m2 with placebo . There were no other significant differences in tubular sodium handling measures observed between the 2 groups.Ramipril treatment for 4 weeks during the run-in period significantly decreased RVR . There were no significant differences observed between the addition of empagliflozin or placebo to ramipril on other measures of the NICOM, arterial stiffness, heart rate variability, or ABPM outcomes.The addition of empagliflozin treatment for 4 weeks to the background of ramipril resulted in additional declines in SBP, DBP, and mean arterial pressure compared with placebo (P < 0.0001). There were no significant differences in weight, waist circumference, or fasting plasma glucose level changes between the empagliflozin and placebo groups.Ramipril treatment for 4 weeks during the run-in period did not significantly change weight, waist circumference, or fasting plasma glucose level . A fungal infection and a vulvovaginal mycotic infection were also reported during empagliflozin treatment in 1 patient each (3.2%). Ketosis (β-hydroxybutyrate >1.5 mmol/L) occurred in 6 patients (19.4%) during empagliflozin treatment and in 1 patient (3.3%) during placebo treatment. There were no episodes of ketoacidosis during placebo or empagliflozin treatment. Hypoglycemia occurred in 1 patient (3.3%) and only during placebo treatment, but not during empagliflozin treatment. Dizziness and thirst occurred in 2 patients (6.5%), each during empagliflozin treatment. Hypotension was reported in 1 patient during the empagliflozin treatment (3.2%). Aside from dysuria in 1 patient (3.2%) during empagliflozin treatment, there were no other reported adverse events related to renal function. The overall incidence of reported adverse effects for the 31 patients who took study drug is reported in Table 13 Animal data are supported by observations in dedicated cardiovascular and renal outcome trials, where a large proportion of patients with T2D are on a background of RAASi. In these trials, SGLT2i also exhibited significant additive cardiorenal protection.3 The original aim of this study was to determine whether combined blockade of neurohormonal (RAASi) and tubular (SGLT2i) factors will reduce hyperfiltration and lead to additive beneficial effects in patients with renal hyperfiltration versus patients with normofiltration. The small number of recruited patients with hyperfiltration (n=2) precluded a direct comparison between patients with normofiltration and hyperfiltration. Nevertheless, our findings in this mechanistic study, as related to patients with T1D and preserved kidney function, will help to improve the understanding of the physiologic interaction between SGLT2i and RAASi and its effect on cardiorenal function. SGLT2i therapies are not approved for clinical use in patients with T1D in most countries. The totality of data generated in our cohort of uncomplicated patients with T1D serves as a mechanistic model without confounding comorbidities to help clarify the early renal and cardiovascular changes in diabetes or obesity and help guide research to address pathophysiologic dysregulations and treatment modalities in this context.Combination SGLT2i-ACEi therapy in animal models of T2D was shown to result in additive nephroprotective effects, including reductions in blood pressure, proteinuria, glomerular injury, and renal fibrosis that were greater than those observed with the use of either drug class alone.Our first major observation was that GFR decreased modestly with the addition of empagliflozin to ramipril treatment in our cohort of patients with T1D under euglycemic clamp conditions. Whereas pretreatment with ramipril alone decreased RVR, adding empagliflozin did not result in further RVR changes, suggesting that SGLT2i may act by mechanisms other than increasing afferent renal arteriole resistance in patients without hyperfiltration. SGLT2i blocks sodium reabsorption at the proximal tubule, as was evident with the decreased absolute proximal sodium and fluid reabsorption rate and increased fractional sodium and lithium excretion, which was not observed with RAASi. Therefore, our data uniquely identify that SGLT2i and RAASi target separate pathologic mechanisms in the kidney and may be used in combination for a synergistic effect on renal hemodynamic function.27 Our findings are further supported by the RED study in 44 patients with T2D and preserved kidney function treated with SGLT2i on the background of RAASi.28 Similar to our observations, SGLT2i treatment in the RED cohort resulted in a decrease in GFR without significant changes to renal blood flow or RVR, suggesting a lack of effect on preglomerular factors. Therefore, whereas the effect of SGLT2i on afferent renal tone is evident in hyperfiltration, the mechanisms of SGLT2i in people with longer duration of diabetes and normofiltration may differ. In the RED study, the release of prostaglandins with SGLT2i was hypothesized to vasodilate the efferent renal arteriole in the context of afferent renal arteriole vasoconstriction, thereby leading to overall maintenance of kidney perfusion. Balanced preglomerular and postglomerular factors might also explain why SGLT2i do not induce acute kidney injury in large T2D trials, but instead induce their effects by a dose-dependent mechanistic eGFR dip as a result of renal hemodynamic changes over a wide range of GFR values, followed by a greater preservation of renal function over time.31 Even though the mechanism responsible for changes in GFR may differ in people with hyperfiltration compared with those without hyperfiltration, the acute hemodynamic change in GFR—likely reflective of reduced glomerular pressure—is consistent across T1D, T2D, and nondiabetic chronic kidney disease.32 On the basis of our current findings, this GFR dip also occurs in people with T1D who are already taking a standard of care RAASi.Our findings also have important safety implications. In patients with normal GFR, kidney function was maintained with SGLT2i when combined with RAASi. In our previous study, GFR was reduced with SGLT2i only in patients with T1D and hyperfiltration, but not in those with normofiltration.34 and therefore pharmacologic inhibition of NO synthase in humans reduces GFR by a modest 10 to 12 mL/min/1.73 m2.36 In patients with uncomplicated T1D treated with only empagliflozin, however, there were no significant changes to NO.20 A physiologic interaction between intrarenal RAAS and NO bioactivity may affect the effects of combination treatment observed in our cohort. For example, intrarenal RAAS activation inhibits neuronal NO synthase leading to exaggerated vasoconstriction mediated by tubuloglomerular feedback.37 Given that we did not observe an obvious effect on tubuloglomerular feedback or RVR, the relationship between NO bioactivity, oxidative stress, and the acute decrease in GFR when SGLT2i is added to RAASi merits further investigation.Whereas the mechanisms responsible for GFR reduction with SGLT2i remain incompletely understood, a significant decrease in urinary 8-isoprostane was observed when empagliflozin was added to ramipril treatment, suggesting a decrease in renal oxidative stress. Combination treatment also significantly decreased cyclic guanosine monophosphate, the downstream signaling molecule of NO, a neurohormonal factor that contributes to preglomerular vasoconstriction. Animal models suggest that NO is released during tubuloglomerular feedback activation, contributing to a decrease in vasoconstriction39 The reduction in blood pressure during the clinic visits was accompanied by a significant increase in blood urea nitrogen and a numerical nonsignificant increase in hematocrit. These changes are likely to reflect a mild hemoconcentration effect because these changes in clinical markers of hemoconcentration are most closely linked with plasma volume contraction rather than increased hematopoiesis.40 Furthermore, in our study cohort, aldosterone levels nearly doubled and an increase in plasma renin concentration was observed when SGLT2i was added to ACEi treatment. A rise in circulating RAAS mediators may be of particular importance in patients concomitantly treated with RAASi and may reflect both pharmacologic RAAS blockade and plasma volume contraction. It is less clear, however, whether a decrease in plasma volume contributed to blood pressure lowering because no changes to weight or thoracic fluid content were observed. Results of the DAPASALT trial in patients with type 2 diabetes with preserved kidney function showed that SGLT2i treatment for 2 weeks with dapagliflozin reduced blood pressure without affecting natriuresis or volume status.41 In our cohort of patients, the blood pressure lowering with the addition of empagliflozin to ramipril may have been related to an observed decline in total peripheral resistance.Our second major observation was the additive reductions in SBP and DBP during clinic visits when empagliflozin was combined with ramipril, which is consistent with previous trials in patients with T2D.42 Therefore, there may be a limitation to the decrease in arterial stiffness in patients with uncomplicated T1D, and once pretreated with RAASi, no further effect on stiffness may be anticipated.In this study, treatment with ramipril alone decreased carotid augmentation index, and the addition of empagliflozin did not lead to a further reduction in arterial stiffness measurements. This finding contrasts with the decrease in arterial stiffness observed when patients with uncomplicated T1D are treated with an SGLT2i alone.Empagliflozin was generally well tolerated in this short-duration and well-controlled mechanistic trial, aside from 2 serious adverse events that occurred during placebo treatment and were deemed unrelated to therapy. Ketosis was reported in 6 patients with T1D during SGLT2i treatment without any incidents of diabetic ketoacidosis; this observation emphasizes the need for careful monitoring of ketosis and adequate diabetic ketoacidosis risk mitigation when patients with T1D are given an SGLT2i in context of well-controlled experimental settings.The main limitation of our study is the lack of patients with hyperfiltration, whom we hypothesized would benefit most hemodynamically when SGLT2i was added to ACEi treatment. Although we observed a lowering of GFR, it is likely that this effect would have been even greater in patients with higher baseline GFR especially in the hyperfiltration range. The low incidence of hyperfiltration may be a result of improved glycemic control in clinical practice, although the mean baseline HbA1c of 8.1% was suboptimal. Moreover, our measurements were conducted under clamped euglycemia, which decreases the chance of exhibiting elevated GFR levels. Future work may instead focus on the effect of adding SGLT2i to ACEi treatment on hyperfiltration induced by hyperglycemia, which could more actively reflect ambient glycemic conditions in clinical practice, characterized by periodic hyperglycemia. We were also unable to examine the effect of adding SGLT2i to ACEi treatment on albuminuria because of the low burden of kidney disease; albuminuria was absent at baseline in the majority of patients. Although we recognize the limitations imposed by the small sample size, we minimized the potential effect of the small sample size by using a prestudy preparation phase to control for factors influencing our physiologic measurements, such as dietary sodium intake. Variability was also decreased by the crossover study design, in which each participant acted as his or her own control.We have demonstrated mechanistically that adding SGLT2i to ACEi treatment is associated with a significant kidney hemodynamic effect characterized by a modest decrease in GFR that was not observed when adding placebo to ACEi. Adding SGLT2i to ACEi also led to an additive blood pressure–lowering effect, which may be mediated in part by a decline in total peripheral resistance. Our results are supportive of a cardiorenal protective physiologic mechanism for use of SGLT2i when added to ACEi to lower intraglomerular pressure and reduce cardiorenal risks in people with diabetes.The authors thank James Bell for statistical assistance during study design. Editorial assistance, supported financially by Boehringer Ingelheim, was provided by Paul Lidbury of Elevate Scientific Solutions during the preparation of this manuscript. The authors were responsible for all content and editorial decisions. Drs Lytvyn, Kimura, Soleymanlou, and Cherney researched data and wrote the manuscript. N. Peter performed statistical analysis. V. Lai researched data and Dr Perkins contributed to discussion and reviewed and edited the manuscript. All authors approved the final version of the manuscript.Boehringer Ingelheim and the Canadian Institutes of Health Research provided support for this study to Dr Cherney. Dr Cherney also is supported by a Department of Medicine, University of Toronto Merit Award, Diabetes Canada, the Heart and Stroke Richard Lewar Centre of Excellence, and the Heart and Stroke Foundation of Canada.Dr Lytvyn, V. Lai, J. Tse, and L. Cham have no conflicts of interest to disclose. N. Peter is a statistical consultant for Boehringer Ingelheim. Dr Perkins reports consultancy agreements with Abbott, Boehringer Ingelheim, and Insulet; receiving research funding from the Bank of Montreal and Novo Nordisk; receiving honoraria from Abbott, Insulet, Medtronic, Novo Nordisk, and Sanofi; and serving as a scientific advisor or member of Abbott, Boehringer Ingelheim, Insulet, and Sanofi. Drs Kimura and Soleymanlou are employees of Boehringer Ingelheim. Dr Cherney has received honoraria from Boehringer Ingelheim-Lilly, Merck, AstraZeneca, Sanofi, Mitsubishi-Tanabe, AbbVie, Janssen, Bayer, Prometric, BMS, Maze, CSL Behring, and Novo Nordisk and has received operational funding for clinical trials from Boehringer Ingelheim-Lilly, Merck, Janssen, Sanofi, AstraZeneca, and Novo Nordisk.Figures S1 and S2Tables S1–S3


Acute Kidney Injury (AKI) in COVID-19 patients is associated with increased morbidity and mortality. In the present study, we aimed to develop a prognostic score to predict AKI development in these patients.This was a retrospective observational study of 2334 COVID 19 patients admitted to 23 different hospitals in Brazil, between January 10th and August 30rd, 2020. The primary outcome of AKI was defined as any increase in serum creatinine (SCr) by 0.3 mg/dL within 48 h or a change in SCr by ≥ 1.5 times of baseline within 1 week, based on Kidney Disease Improving Global Outcomes (KDIGO) guidelines. All patients aged ≥ 18 y/o admitted with confirmed SARS-COV-2 infection were included. Discrimination of variables was calculated by the Receiver Operator Characteristic Curve (ROC curve) utilizing area under curve. Some continuous variables were categorized through ROC curve. The cutoff points were calculated using the value with the best sensitivity and specificity.n = 678). The risk of AKI was 33% (n = 376), 78% (n = 293) of which did not require dialysis. Overall mortality was 11% (n = 127), while for AKI patients, mortality rate was 21% (n = 80). Variables selected for the logistic regression model and inclusion in the final prognostic score were the following: age, diabetes, ACEis, ARBs, chronic kidney disease and hypertension.A total of 1131 patients with COVID-19 admitted to the ICU were included. Patients mean age was 52 ± 15,8 y/o., with a prevalence of males 60% (AKI development in COVID 19 patients is accurately predicted by common clinical variables, allowing early interventions to attenuate the impact of AKI in these patients. SARS-COV-2 was initially described in December 2019 in Wuhan, China and rapidly escalated to a pandemic in March 2020 –6.AKI is of particular interest and is associated with greater incidence, morbidity and mortality in COVID-19 patients, especially in cases with serious pulmonary disease and need for mechanical ventilation, probably as a result of the kidney-lung relationship previously described by other authors , 8. ReceBased on numerous studies, researchers believe that angiotensin-converting enzyme (ACE2) receptor serves as a co-transporter for SARS-COV-2 to enter the cells. Although the etiology of renal damage in patients with COVID-19 is multifatorial and associated with multiple mechanisms such as hypovolemia, rhabdomyolysis, microthrombosis, inflammation and virus-induced damage to tubular cells –17, it iRecently some prognostic scores to predict the development of critical illness and need for mechanical ventilation have been proposed and validated for COVID-19 patients. Unfortunately, the natural course of AKI development were not mentioned in these studies, precluding any clinical decision about the profile of AKI patients during hospitalization for COVID-19 , 26.The objective of this study was to describe the risk factors associated with AKI in COVID 19 patients admitted to Intensive Care Unit (ICU) and to develop a specific prognostic score with clinical variables (including ACE and ARB use) that could accurately identify high-risk patients for AKI development during hospitalization for COVID-19 related complications.This was a retrospective observational study of 2334 COVID-19 patients admitted to 23 different private hospitals in Brazil, between January 10th and August 30rd, 2020. The study was approved by the National Teaching and Ethical Committee (CONEP) under number: 29496920.8.0000.5262 and informed consent was waived due to the observational nature of the study.The primary outcome of AKI was defined as any increase in serum creatinine (SCr) by 0.3 mg/dL within 48 h or a change in SCr by ≥ 1.5 times of baseline within 1 week, based on Kidney Disease Improving Global Outcomes (KDIGO) guidelines. The lowest SCr reading during hospitalization was used as the baseline for AKI definition. The staging of AKI was also defined according to the KDIGO criteria . We did All patients aged ≥ 18 y/o admitted with confirmed SARS-COV-2 infection were consecutively included. We defined confirmed infection as positive reverse transcriptase-polymerase chain reaction (RT-PCR) from a nasal or throat swab together with clinical symptons or radiological findings suggestive of COVID-19 infection. Data were collected by a highly trained team and included demographic data such as comorbidities and use of medications, in addition to laboratory data at the time of ICU admission and outcomes such as need for mechanical ventilation or vasopressors, hospital discharge and death.The continuous variables were submitted to Kolmogorov–Smirnov and Shapiro–Wilk tests and their values were expressed as median and 25th/75th percentiles or as mean and standard deviation for parametric and non-parametric variables, respectively.The categorical variables were submitted to Pearson’s chi square or Fisher’s exact test, if applicable, and were presented as absolute values and percentages. Discrimination of was calculated using the ROC (Receiver Operating Characteristic) curve and the categorization of some continuous variables was also performed using the ROC curve. The cut-off scores for each clinical variable were calculated using the p value with the best specificity and sensitivity for that particular variable.The candidate variables for the multivariable model were included at the p-value of 0.2 in the univariable analysis and a step-by-step method was used to select each significant variable for the final logistic regression model, with the calculations of corresponding adjusted odds ratios (ORs) and 95% confidence intervals (CI).The AKI Score variables were those that resulted from the COX Regression, being excluded one by one (step by step) until all predictor variables reached significance. The candidate variables for the model were those that reached significance as a value of p <  = 0.2 on the Kaplan–Meier Survival Curve using the Log-Rank test. The cutoff points of the continuous variables used in the AKI score were obtained through the ROC curve, corresponding to the highest value of the sum of sensitivity + specificity of all possible cut-off points obtained on the curve.Variables with missing data up to 10% were: ACEi, ARB, Hypertension and Platelets. Variables with missing data from 10.1% to 20% were: Sodium, Potassium, pH and PCO2. There were no variables with more than 20% missing data of clinical relevance. After this classification, the following criterion was adopted: Variables with up to 10% of missing data were not considered influential and variables with missing data between 10.1% and 20% were performed Canonical Correlation  with Wilk's lambda test to investigate possible biases of association of the missing data with the other variables and with the outcome of the study. Finally, all missing data were submitted to the “Full informationmaximum-likelihood (FIML)”.p ≤ 0,05.Analyses were performed using SPSS 21.0 IBM ® and GraphPad Prism 5.0 GraphPad ® and statistical significance was considered with n = 678). Most common comorbidities included hypertension 63.8% (n = 722) and diabetes 23.7% (n = 269). A total of 49% (n = 556) of patients were taking angiotensin converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARBs) prior to ICU admission. 16% (n = 185) of patients were on vasopressors and 19% (n = 220) were on mechanical ventilation at ICU admission , 78% (n = 293) of which did not require dialysis and 22% (n = 83) presented dialytic AKI. Overall mortality was 11% (n = 127), while for AKI patients, mortality rate was 21% (n = 80).The risk of AKI was 33%  and chronic kidney disease (CKD); ICU admission variables: need for mechanical ventilation or vasopressors, serum potassium > 4.2 mEq/L, serum sodium < 140 mEq/L, pH < 7.35, pCo2 > 48 mmHg, c-reactive protein (CRP) > 8.7 mg/dL and lymphocytes < 720  is a well known risk factor for AKI development in different clinical scenarios . In our At the beginning of COVID-19 pandemics, it was unclear if the use of ACEi or ARBs were associated with increased risk of complications and/or severe disease. Indeed, recent studies confirmed that when compared to untreated subjects, those using either ACEi or ARBs showed a similar risk of critical or lethal clinical course associated with COVID-19 infection , 40–42. The comparison between our score and previous prognostic scores developed to predict complications such as need for mechanical ventilation, ICU transfer or death is not feasible because of different end points. In a recent review, Lombardi e cols . studiedThe limitations of the present study are related to the lack of external validity to evaluate model performance in different settings and also limited to ICU patients, precluding any conclusion about the risk profile to AKI development in distinct scenarios such as wards or emergency departments.Our study identified the main risk factors for the development of AKI in patients with COVID-19 admitted to the Intensive Care Unit and also developed a prognostic score capable of identifying patients at high risk for AKI, facilitating the adoption of preventive measures that minimize the risk of this complication in COVID-19 patients.