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in category nephrology

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1: 2019 novel coronavirus disease in hemodialysis (HD) patients: Report from one HD center in Wuhan, China
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Posted 25 Feb 2020

2019 novel coronavirus disease in hemodialysis (HD) patients: Report from one HD center in Wuhan, China
12,182 downloads medRxiv nephrology

Yiqiong Ma, Bo Diao, Xifeng Lv, Jili Zhu, Wei Liang, Lei Liu, Wenduo Bu, Huiling Cheng, Sihao Zhang, Lianhua Yang, Ming Shi, Guohua Ding, Bo Shen, Huiming Wang

Importance: The outbreak of highly contagious COVID-19 has posed a serious threat to human health, especially for those with underlying diseases. However, Impacts of COVID-19 epidemic on HD center and HD patients have not been reported. Objective: To summery an outbreak of COVID-19 epidemic in HD center. Design, Setting, and Participants: We reviewed the epidemic course from the first laboratory-confirmed case of COVID-19 infection on January 14 to the control of the epidemic on March 12 in the HD center of Renmin Hospital of Wuhan University. Total 230 HD patients and 33 medical staff were included in this study Exposures: COVID-19. Main Outcomes and Measures: Epidemiological, clinical, laboratory, and radiological characteristics and outcomes data were collected and analyzed. 19 COVID-19 HD patients, 19 non-COVID-19 HD patients and 19 healthy volunteers were enrolled for further study about the effect of SARS-CoV-2 infection on host immune responses. Results: 42 out of 230 HD patients (18.26%) and 4 out of 33 medical staffs(12.12%) were diagnosed with COVID-19 from the outbreak to March 12, 2020. 13 HD patients (5.65%), including 10 COVID-19 diagnosed, died during the epidemic. Only 2 deaths of the COVID-19 HD patients were associated with pneumonia/lung failure. Except 3 patients were admitted to ICU for severe condition (8.11%), including 2 dead, most COVID-19 diagnosed patients presented mild or none-respiratory symptoms. Multiple lymphocyte populations in HD patients were significantly decreased. HD patients with COVID-19 even displayed more remarkable reduction of serum inflammatory cytokines than other COVID-19 patients. Conclusions and Relevance: HD patients are the highly susceptible population and HD centers are high risk area during the outbreak of COVID-19 epidemic. HD Patients with COVID-19 are mostly clinical mild and unlikely progress to severe pneumonia due to the impaired cellular immune function and incapability of mounting cytokines storm. More attention should be paid to prevent cardiovascular events, which may be the collateral impacts of COVID-19 epidemic on HD patients.

2: Kidney impairment is associated with in-hospital death of COVID-19 patients
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Posted 20 Feb 2020

Kidney impairment is associated with in-hospital death of COVID-19 patients
10,299 downloads medRxiv nephrology

Yichun Cheng, Ran Luo, Kun Wang, Meng Zhang, Zhixiang Wang, Lei Dong, Junhua LI, Ying Yao, Shuwang Ge, Gang Xu

BackgroundInformation on kidney impairment in patients with coronavirus disease 2019 (COVID-19) is limited. This study aims to assess the prevalence and impact of abnormal urine analysis and kidney dysfunction in hospitalized COVID-19 patients in Wuhan. MethodsWe conducted a consecutive cohort study of COVID-19 patients admitted in a tertiary teaching hospital with 3 branches following a major outbreak in Wuhan in 2020. Hematuria, proteinuria, serum creatinine concentration and other clinical parameters were extracted from the electronic hospitalization databases and laboratory databases. Incidence rate for acute kidney injury (AKI) was examined during the study period. Association between kidney impairment and in-hospital death was analyzed. ResultsWe included 710 consecutive COVID-19 patients, 89 (12.3%) of whom died in hospital. The median age of the patients was 63 years (inter quartile range, 51-71), including 374 men and 336 women. On admission, 44% of patients have proteinuria hematuria and 26.9% have hematuria, and the prevalence of elevated serum creatinine and blood urea nitrogen were 15.5% and 14.1% respectively. During the study period, AKI occurred in 3.2% patients. Kaplan-Meier analysis demonstrated that patients with kidney impairment have higher risk for in-hospital death. Cox proportional hazard regression confirmed that elevated serum creatinine, elevated urea nitrogen, AKI, proteinuria and hematuria was an independent risk factor for in-hospital death after adjusting for age, sex, disease severity, leukocyte count and lymphocyte count. ConclusionsThe prevalence of kidney impairment (hematuria, proteinuria and kidney dysfunction) in hospitalized COVID-19 patients was high. After adjustment for confounders, kidney impairment indicators were associated with higher risk of in-hospital death. Clinicians should increase their awareness of kidney impairment in hospitalized COVID-19 patients.

3: Acute Kidney Injury in Hospitalized Patients with COVID-19
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Posted 08 May 2020

Acute Kidney Injury in Hospitalized Patients with COVID-19
3,671 downloads medRxiv nephrology

Lili Chan, Kumardeep Chaudhary, Aparna Saha, Kinsuk Chauhan, Akhil Vaid, Mukta Baweja, Kirk Campbell, Nicholas Chun, Miriam Chung, Priya Deshpande, Samira S Farouk, Lewis Kaufman, Tonia Kim, Holly Koncicki, Vijay Lapsia, Staci Leisman, Emily Lu, Kristin Meliambro, Madhav C Menon, Joshua L Rein, Shuchita Sharma, Joji Tokita, Jaime Uribarri, Joseph A Vassalotti, Jonathan Winston, Kusum S Mathews, Shan Zhao, Ishan Paranjpe, Sulaiman Somani, Felix Richter, Ron Do, Riccardo Miotto, Anuradha Lala, Arash Kia, Prem Timsina, Li Li, Matteo Danieletto, Eddye Golden, Patricia Glowe, Micol Zweig, Manbir Singh, Robert Freeman, Rong Chen, Eric Nestler, Jagat Narula, Allan C Just, Carol Horowitz, Judith Aberg, Ruth JF Loos, Judy Cho, Zahi Fayad, Carlos Cordon-Cardo, Eric Schadt, Matthew Levin, David L Reich, Valentin Fuster, Barbara Murphy, John Cijiang He, Alexander W Charney, Erwin P Bottinger, Benjamin S Glicksberg, Steven G Coca, Girish N Nadkarni

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

4: Analysis of early renal injury in COVID-19 and diagnostic value of multi-index combined detection
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Posted 10 Mar 2020

Analysis of early renal injury in COVID-19 and diagnostic value of multi-index combined detection
2,959 downloads medRxiv nephrology

Xu-wei Hong, Ze-pai Chi, Guo-yuan Liu, Hong Huang, Shun-qi Guo, Jing-ru Fan, Xian-wei Lin, Liao-zhun Qu, Rui-lie Chen, Ling-jie Wu, Liang-yu Wang, Qi-chuan Zhang, Su-wu Wu, Ze-qun Pan, Hao Lin, Yu-hua Zhou, Yong-hai Zhang

ObjectivesThe aim of the study was to analyze the incidence of COVID-19 with early renal injury, and to explore the value of multi-index combined detection in diagnosis of early renal injury in COVID-19. DesignThe study was an observational, descriptive study. SettingThis study was carried out in a tertiary hospital in Guangdong, China. Participants12 patients diagnosed with COVID-19 from January 20, 2020 to February 20, 2020. Primary and secondary outcome measuresThe primary outcome was to evaluate the incidence of early renal injury in COVID-19. In this study, the estimated glomerular filtration rate (eGFR), endogenous creatinine clearance (Ccr) and urine microalbumin / urinary creatinine ratio (UACR) were calculated to assess the incidence of early renal injury. Secondary outcomes were the diagnostic value of urine microalbumin (UMA), 1-microglobulin (A1M), urine immunoglobulin-G (IGU), urine transferring (TRU) alone and in combination in diagnosis of COVID-19 with early renal injury. ResultsWhile all patients had no significant abnormalities in serum creatinine (Scr) and blood urea nitrogen (BUN), the abnormal rates of eGFR, Ccr, and UACR were 66.7%, 41.7%, and 41.7%, respectively. Urinary microprotein detection indicated that the area under curve (AUC) of multi-index combined to diagnose early renal injury in COVID-19 was 0.875, which was higher than UMA (0,813), A1M (0.813), IGU (0.750) and TRU (0.750) alone. Spearman analysis showed that the degree of early renal injury was significantly related to C-reactive protein (CRP) and neutrophil ratio (NER), suggesting that the more severe the infection, the more obvious the early renal injury. Hypokalemia and hyponatremia were common in patients with COVID-19, and there was a correlation with the degree of renal injury. ConclusionsEarly renal injury was common in patients with COVID-19. Combined detection of UMA, A1M, IGU, and TRU was helpful for the diagnosis of early renal injury in COVID-19.

5: SARS-CoV-2 receptor networks in diabetic kidney disease, BK-Virus nephropathy and COVID-19 associated acute kidney injury
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Posted 13 May 2020

SARS-CoV-2 receptor networks in diabetic kidney disease, BK-Virus nephropathy and COVID-19 associated acute kidney injury
2,820 downloads medRxiv nephrology

Rajasree Menon, Edgar A Otto, Rachel Sealfon, Viji Nair, Aaron K Wong, Chandra L Theesfeld, Xi Chen, Yuan Wang, Avinash Boppanna, Jinghui Luo, Yingbao Yang, Peter M Kasson, Jennifer A Schaub, Celine C Berthier, Sean Eddy, Chrysta C Lienczewski, Bradley Godfrey, Susan L Dagenais, Ryann Sohaney, John Hartman, Damian Fermin, Lalita Subramanian, Helen C Looker, Jennifer L Harder, Laura H. Mariani, Jeffrey B Hodgin, Jonathan Z. Sexton, Christiane E Wobus, Abhijit S Naik, Robert G Nelson, Olga G. Troyanskaya, Matthias Kretzler

COVID-19 morbidity and mortality is increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease (DKD) and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of healthy living donor (LD) and DKD kidney biopsies revealed ACE2 expression primarily in proximal tubular epithelial cells (PTEC). This cell specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin angiotensin aldosterone system inhibitors in DKD. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing PTEC in DKD (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The DKD ACE2-positive PTEC module overlapped with expression patterns seen in SARS-CoV-2 infected cells. Similar cellular programs were seen in ACE2-positive PTEC obtained from urine samples of 13 COVID-19 patients who were hospitalized, suggesting a consistent ACE2-coregulated PTEC expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19 related kidney damage.

6: Hypokalemia in Patients with COVID-19
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Posted 16 Jun 2020

Hypokalemia in Patients with COVID-19
1,833 downloads medRxiv nephrology

Gaetano Alfano, Annachiara Ferrari, Francesco Fontana, Rossella Perrone, Giacomo Mori, Elisabetta Ascione, Magistroni Riccardo, Giulia Venturi, Simone Pederzoli, Gianluca Margiotta, Marilina Romeo, Francesca Piccinini, Giacomo Franceschi, Sara Volpi, Matteo Faltoni, Giacomo Ciusa, Erica Bacca, Marco Tutone, Alessandro Raimondi, marianna menozzi, Erica Franceschini, Gianluca Cuomo, Gabriella Orlando, Antonella Santoro, Margherita Di Gaetano, Cinzia Puzzolante, Federica Carli, Andrea Bedini, Jovana Milic, Marianna Meschiari, Cristina Mussini, Gianni Cappelli, Giovanni Guaraldi

Patients with COVID-19 may experience multiple conditions (e.g., fever, hyperventilation, anorexia, gastroenteritis, acid-base disorder) that may cause electrolyte imbalances. Hypokalemia is a concerning electrolyte disorder that may increase the susceptibility to various kinds of arrhythmia. This study aimed to estimate prevalence, risk factors and outcome of hypokalemia in a cohort of non-critically ill patients. A retrospective analysis was conducted on 290 hospitalized patients with confirmed COVID-19 infection at the tertiary teaching hospital of Modena, Italy. Hypokalemia (<3.5 mEq/L) was detected in 119 patients (41%). The decrease of serum potassium level was of mild entity (3-3.4 mEq/L) and occurred in association with hypocalcemia (P=0.001) and lower level of serum magnesium (P=0.028) compared to normokaliemic patients. Urine K: creatinine ratio, measured in a small subset of patients (n=45; 36.1%), showed an increase of urinary potassium excretion in the majority of the cases (95.5%). Causes of kaliuria were diuretic therapy (53.4%) and corticosteroids (23.3%). In the remaining patients, urinary potassium loss was associated with normal serum magnesium, low sodium excretion (FENa< 1%) and metabolic alkalosis. Risk factors for hypokalemia were female gender (P=0.002; HR 0.41, 95%CI 0.23-0.73) and diuretic therapy (P=0.027; HR 1.94, 95%CI 1.08-3.48). Hypokalemia, adjusted for sex, age and SOFA score, resulted not associated with ICU admission (P=0.131, 95% CI 0.228-1.212) and in-hospital mortality (P=0.474; 95% CI 0,170-1,324) in our cohort of patients. Hypokalemia is a frequent disorder in COVID-19 patients and urinary potassium loss may be the main cause of hypokalemia. The disorder was mild in the majority of the patients and was unrelated to poor outcomes. Nevertheless, hypokalemic patients required potassium supplements to dampen the risk of arrhythmias.

7: Characterisation of Acute Kidney Injury in Critically Ill Patients with Severe Coronavirus Disease-2019 (COVID-19)
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Posted 10 May 2020

Characterisation of Acute Kidney Injury in Critically Ill Patients with Severe Coronavirus Disease-2019 (COVID-19)
892 downloads medRxiv nephrology

Sebastien RUBIN, Arthur Orieux, Renaud Prevel, Antoine Garric, Marie-Lise Bats, Sandrine Dabernat, Fabrice Camou, Olivier Guisset, Nahema Issa, Gaelle Mourissoux, Antoine Dewitte, Olivier Joannes-boyau, Catherine Fleureau, Hadrien Roze, Cedric Carrie, Laurent Petit, Benjamin Clouzeau, Charline Sazio, Hoang-Nam Bui, Odile Pillet, Claire Rigothier, Frederic Vargas, Christian Combe, Didier Gruson, Alexandre Boyer

Background: COVID19-associated acute kidney injury frequency, severity and characterisation in critically ill patients has not been reported. Methods: Single-center cohort performed from March 3, 2020, to April 14, 2020 in 4 intensive care units in Bordeaux University Hospital, France. All patients with COVID19 and pulmonary severity criteria were included. AKI was defined using KDIGO criteria. A systematic urinary analysis was performed. The incidence, severity, clinical presentation, biological characterisation (transient vs. persistent acute kidney injury; proteinuria, hematuria and glycosuria), and short-term outcomes was evaluated. Results: 71 patients were included, with basal serum creatinine of 69 +/- 21 micromol/L. At admission, AKI was present in 8/71 (11%) patients. Median follow-up was 17 [12-23] days. AKI developed in a total of 57/71 (80%) patients with 35% Stage 1, 35% Stage 2, and 30% Stage 3 acute kidney injury; 10/57 (18%) required renal replacement therapy. Transient AKI was present in only 4/55 (7%) patients and persistent AKI was observed in 51/55 (93%). Patients with persistent AKI developed a median urine protein/creatinine of 82 [54-140] (mg/mmol) with an albuminuria/proteinuria ratio of 0.23 +/- 20 indicating predominant tubulo-interstitial injury. Only 2 (4%) patients had glycosuria. At Day 7 onset of after AKI, six (11%) patients remained dependent on renal replacement therapy, nine (16%) had SCr > 200 micromol/L, and four (7%) died. Day 7 and day 14 renal recovery occurred in 28% and 52 % respectively. Conclusion: COVID19 associated AKI is frequent, persistent severe and characterised by an almost exclusive tubulo-interstitial injury without glycosuria

8: Incidence, risk factors and mortality outcome in patients with acute kidney injury in COVID-19: a single-center observational study
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Posted 24 Jun 2020

Incidence, risk factors and mortality outcome in patients with acute kidney injury in COVID-19: a single-center observational study
882 downloads medRxiv nephrology

Gaetano Alfano, Annachiara Ferrari, Francesco Fontana, Giacomo Mori, Riccardo Magistroni, Meschiari Marianna, Franceschini Erica, Marianna Menozzi, Gianluca Cuomo, Gabriella Orlando, Antonella Santoro, Margherita Di Gaetano, Cinzia Puzzolante, Federica Carli, Andrea Bedini, Jovana Milic, Paolo Raggi, Massimo Girardis, Cristina Mussini, Gianni Cappelli, Giovanni Guaraldi

Background Acute kidney injury (AKI) is a recently recognized complication of coronavirus disease-2019 (COVID-19). This study aims to evaluate the incidence, risk factors and case-fatality rate of AKI in patients with documented COVID-19. Methods We reviewed the health medical records of 307 consecutive patients hospitalized for symptoms of COVID-19 at the University Hospital of Modena, Italy. Results AKI was diagnosed in 69 out of 307 (22.4%) patients. The stages of AKI were stage 1 in 57.9%, stage 2 in 24.6% and stage 3 in 17.3%. Hemodialysis was performed in 7.2% of the subjects. AKI patients had a mean age of 74.7 {+/-} 9.9 years and higher serum levels of the main marker of inflammation and organ involvement (lung, liver, hearth and liver) than non-AKI patients. AKI events were more frequent in subjects with severe lung comprise. Two peaks of AKI events coincided with in-hospital admission and death of the patients. Kidney injury was associate with a higher rate of urinary abnormalities including proteinuria (0.448{+/-} 0.85 vs 0.18 {+/-} 0.29; P=<0.0001) and hematuria (P=0.032) compared to non-AKI patients. At the end of follow-up, 65.2% of the patients did not recover their renal function after AKI. Risk factors for kidney injury were age, male sex, CKD and non-renal SOFA. Adjusted Cox regression analysis revealed that AKI was independently associated with in-hospital death (hazard ratio [HR]=3.74; CI 95%, 1.34-10.46) compared to non-AKI patients. Groups of patients with AKI stage 2-3 and failure to recover kidney function were associated with the highest risk of in-hospital mortality. Lastly, long-hospitalization was positively associated with a decrease of serum creatinine, likely due to muscle depletion occurred with prolonged bed rest. Conclusions AKI was a dire consequence of patients with COVID-19. Identification of patients at high-risk for AKI and prevention of kidney injury by avoiding dehydration and nephrotoxic agents is imperative in this vulnerable cohort of patients.

9: The Chronic Kidney Disease and Acute Kidney Injury Involvement in COVID-19 Pandemic: A Systematic Review and Meta-analysis
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Posted 02 May 2020

The Chronic Kidney Disease and Acute Kidney Injury Involvement in COVID-19 Pandemic: A Systematic Review and Meta-analysis
859 downloads medRxiv nephrology

Ya-Fei Liu, Zhe Zhang, Xiao-Li Pan, Guo-Lan Xing, Ying Zhang, Zhang-Suo Liu, Sheng-Hao Tu

Aim: The aim of this study was to uncover whether kidney diseases were involved in COVID-19 pandemic from a systematic review. Methods: The studies reported the kidney outcomes in different severity of COVID-19 were included in this study. Standardized mean differences or odds ratios were calculated by employing Review Manager meta-analysis software. Results: Thirty-six trials were included in this systematic review with a total of 6395 COVID-19 patients. The overall effects indicated that the comorbidity of chronic kidney disease (CKD) (OR = 3.28), complication of acute kidney injury (AKI) (OR = 11.02), serum creatinine (SMD = 0.68), abnormal serum creatinine (OR = 4.86), blood urea nitrogen (SMD = 1.95), abnormal blood urea nitrogen (OR = 6.53), received continuous renal replacement therapy (CRRT) (OR = 23.63) was significantly increased in severe group than that in nonsevere group. Additionally, the complication of AKI (OR = 13.92) and blood urea nitrogen (SMD = 1.18) were remarkably elevated in critical group than that in severe group. Conclusion: CKD and AKI are susceptible to occur in patients with severe COVID-19. CRRT is applied frequently in severe COVID-19 patients than that in nonsevere COVID-19 patients. The risk of AKI is higher in critical group than that in severe group.

10: Assessment of medication Dosage Adjustment in Hospitalized Patients with Chronic Kidney Disease
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Posted 08 May 2020

Assessment of medication Dosage Adjustment in Hospitalized Patients with Chronic Kidney Disease
806 downloads medRxiv nephrology

Zair Hassan, Iftikhar Ali, Arslan Rahat Ullah, Raheel Ahmad, Shakeel Rehman, Azizullah Khan

In patients with renal impairment, inappropriate medication dosing can develop adverse drug reactions (ADRs) or ineffective therapy due to declined renal function. This necessitates proper renal dosing adjustment. Using a retrospective analysis of medical records, this study was proposed to evaluate medication dosage adjustment in hospitalized chronic kidney disease (CKD) patients.This retrospective review of medical records was conducted at the Institute of Kidney Disease (IKD), Peshawar. It included all CKD patients hospitalized between June 01, 2019 and May 31, 2020 and receiving at least one medication that needed adjustment. Glomerular filtration rate was calculated using Renal Disease Diet Modification (RDDM) equation, and dose suitability was established by evaluating practice with relevant guidelines. Of the total 1537 CKD patients, 231(15.03%) had evidence of dosing error, which were considered for final analysis. Overall, 1549 drugs were prescribed, 480(30.99%) drugs required dose adjustment of which 196(40.42%) were adjusted properly and the remaining 286(59.58%) were unadjusted. The most common unadjusted drugs were meropenem, cefepime, ciprofloxacin and rosuvastatin, whereas captopril, aspirin, bisoprolol, pregabalin and levofloxacin had the highest percentage of adjusted drugs. On multivariate logistic regression, the number of drugs requiring dosing adjustments and obstructive nephropathy were found to be statistically significant factors that increased the likelihood of the medication dosing errors; A unit increase in the number of drugs requiring dose adjustment increases 5.241 times the likelihood of dosing error. Similarly the presence of obstructive nephropathy (Odds ratio (OR) 0.383, 95% confidence interval (Cl) [0.153-0.960] P= 0.041) was found to be significantly associated with dosing error after adjustment for potential confounding factors.The dosing of more than half of the prescribed drugs that required adjustment in CKD were not adjusted which showed that medication dosing errors were high. This highlights the importance of medication prescription according to guidelines in CKD patients to improve the outcomes of pharmacotherapy and patients quality of life.

11: Deep learning driven quantification of interstitial fibrosis in kidney biopsies
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Posted 04 Jan 2021

Deep learning driven quantification of interstitial fibrosis in kidney biopsies
781 downloads medRxiv nephrology

Yi Zheng, Clarissa A. Cassol, Saemi Jung, Divya Veerapaneni, Vipul C Chitalia, Kevin Ren, Shubha S. Bellur, Peter Boor, Laura M. Barisoni, Sushrut S. Waikar, Margrit Betke, Vijaya B. Kolachalama

Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA estimation using computational techniques can reduce this variability and provide quantitative assessment by capturing the pathologic features. Using trichrome-stained whole slide images (WSIs) processed from human renal biopsies, we developed a deep learning (DL) framework that captured finer pathological structures at high resolution and overall context at the WSI-level to predict IFTA grade. WSIs (n=67) were obtained from The Ohio State University Wexner Medical Center (OSUWMC). Five nephropathologists independently reviewed them and provided fibrosis scores that were converted to IFTA grades: <=10% (None or minimal), 11-25% (Mild), 26-50% (Moderate), and >50% (Severe). The model was developed by associating the WSIs with the IFTA grade determined by majority voting (reference estimate). Model performance was evaluated on WSIs (n=28) obtained from the Kidney Precision Medicine Project (KPMP). There was good agreement on the IFTA grading between the pathologists and the reference estimate (Kappa=0.622{+/-}0.071). The accuracy of the DL model was 71.8{+/-}5.3% on OSUWMC and 65.0{+/-}4.2% on KPMP datasets, respectively. Identification of salient image regions by combining microscopic and WSI-level pathological features yielded visual representations that were consistent with the pathologist-based IFTA grading. Our approach to analyzing microscopic- and WSI-level changes in renal biopsies attempts to mimic the pathologist and provides a regional and contextual estimation of IFTA. Such methods can assist clinicopathologic diagnosis. Translational statementPathologists rely on interstitial fibrosis and tubular atrophy (IFTA) to indicate chronicity in kidney biopsies and provide a prognostic indicator of renal survival. Although guidelines for evaluation of IFTA exist, there is variability in IFTA estimation among pathologists. In this work, digitized kidney biopsies were independently reviewed by five nephropathologists and majority voting on their ratings was used to determine the IFTA grade. Using this information, a deep learning model was developed that captured microscopic and holistic features on the digitized biopsies and accurately predicted the IFTA grade. The study illustrates that deep learning can be utilized effectively to perform IFTA grading, thus enhancing conventional clinicopathologic diagnosis.

12: Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict rapid progression of diabetic kidney disease
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Posted 02 Jun 2020

Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict rapid progression of diabetic kidney disease
763 downloads medRxiv nephrology

Lili Chan, Girish N Nadkarni, Fergus Fleming, James R McCullough, Patti Connolly, Gohar Mosoyan, Fadi El Salem, Michael W. Kattan, Joseph A Vassalotti, Barbara Murphy, Michael J. Donovan, Steven G Coca, Scott Damrauer

Importance: Diabetic kidney disease (DKD) is the leading cause of kidney failure in the United States and predicting progression is necessary for improving outcomes. Objective: To develop and validate a machine-learned, prognostic risk score (KidneyIntelXTM) combining data from electronic health records (EHR) and circulating biomarkers to predict DKD progression. Design: Observational cohort study Setting: Two EHR linked biobanks: Mount Sinai BioMe Biobank and the Penn Medicine Biobank. Participants: Patients with prevalent DKD (G3a-G3b with all grades of albuminuria (A1-A3) and G1 & G2 with A2-A3 level albuminuria) and banked plasma. Main outcomes and measures: Plasma biomarkers soluble tumor necrosis factor 1/2 (sTNFR1, sTNFR2) and kidney injury molecule-1 (KIM-1) were measured at baseline. Patients were divided into derivation [60%] and validation sets [40%]. A composite primary end point of rapid kidney function decline (RKFD) (estimated glomerular filtration rate (eGFR) decline of [&ge;]5 ml/min/1.73m2/year), [&ge;]40% sustained decline, or kidney failure within 5-years. A machine learning model (random forest) was trained and performance assessed using standard metrics. Results: In 1146 patients with DKD the median age was 63, 51% were female, median baseline eGFR was 54 ml/min/1.73 m2, urine albumin to creatinine ratio (uACR) was 61 mg/g, and follow-up was 4.3 years. 241 patients (21%) experienced RKFD. On 10-fold cross validation in the derivation set (n=686), the risk model had an area under the curve (AUC) of 0.77 (95% CI 0.74-0.79). In validation (n=460), the AUC was 0.77 (95% CI 0.76-0.79). By comparison, the AUC for an optimized clinical model was 0.62 (95% CI 0.61-0.63) in derivation and 0.61 (95% CI 0.60-0.63) in validation. Using cutoffs from derivation, KidneyIntelX stratified 47%, 37% and 16% of validation cohort into low-, intermediate- and high-risk groups, with a positive predictive value (PPV) of 62% (vs. 41% for KDIGO) in the high-risk group and a negative predictive value (NPV) of 91% in the low-risk group. The net reclassification index for events into high-risk group was 41% (p<0.05). Conclusions and Relevance: A machine learned model combining plasma biomarkers and EHR data improved prediction of adverse kidney events within 5 years over KDIGO and standard clinical models in patients with early DKD.

13: COVID-19 and Acute Kidney Injury requiring Kidney Replacement Therapy: A Bad Prognostic Sign.
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Posted 13 May 2020

COVID-19 and Acute Kidney Injury requiring Kidney Replacement Therapy: A Bad Prognostic Sign.
750 downloads medRxiv nephrology

Rahul Shekhar, Shubhra Upadhyaya, Silvi Shah, Devika Kapuria

The development of acute kidney injury in patients with COVID-19 is estimated to about 0.5% from earlier studies from China. The incidence of AKI in patients with COIVID-19 in the largest inpatient series in the United States is 22.2%3. Development of AKI requiring kidney replacement therapy in hospitalized patients is a bad prognostic sign. Out of Fifty patients admitted to our hospital with COVID-19 13/50(26%) developed AKI. All patients required hospitalization in intensive care unit care and 12/13 required initiation of kidney replacement therapy. The median age was 41 years (31-85 years) and 50% were men. Common comorbidities were obesity (83%), diabetes (42%), and hypertension (25%). 10/12 (83%) patients were hypoxemic and required oxygen therapy. 11/12 (92%) patients required invasive ventilation. Majority of patients had elevated neutrophils counts (81.8%) and low lymphocyte counts (81.8%). All patients had chest x-ray findings suggestive of pneumonia. 11/12(91.6%) developed septic shock requiring vasopressors. Review of UA showed all patient (9/9) had active urine sediments with blood but 7/9 of them have sterile pyuria. At the end of study period, 1 patient remained hospitalized. 10/11(90%) patients died and one patient was discharged home with resolution of AKI. Median length of stay was 13 days. The exact mechanism of AKI is not well understood in COVID-19 but can be due to acute tubular necrosis due to septic shock because of cytokine storm in severe COVID-19 or direct invasion by SARS-CoV-2 on podocytes and proximal renal tubular cells. Our findings suggest poor prognosis despite continuous kidney replacement therapies in patients who develop AKI with COVID-19.

14: Preprint server use in kidney disease research: a rapid review
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Posted 23 Mar 2020

Preprint server use in kidney disease research: a rapid review
702 downloads medRxiv nephrology

Caitlyn Vlasschaert, Cameron Giles, Swapnil Hiremath, Matthew B. Lanktree

Purpose of reviewPreprint servers including arXiv and bioRxiv have disrupted the scientific communication landscape by providing rapid access to pre--peer reviewed research. MedRxiv is a recently launched free online repository for preprints in the health sciences. We sought to summarize potential benefits and risks to preprint server use, from both the researcher and end--user perspective, and evaluate the uptake of preprint servers in the nephrology community. Sources of InformationWe performed a rapid review of articles describing preprint servers and their use. We approached the 20 highest impact nephrology journals regarding their policy towards the use of preprint servers. We evaluated the average time from study completion to publication of impactful articles in nephrology. Finally, we evaluated the number of nephrology articles submitted to preprint servers. FindingsTo date over 600 kidney--related articles have been uploaded to bioRxiv and medRxiv. The average time from study completion to publication was over 10 months. 16 of the top 20 nephrology journals currently accept research submitted to a preprint server. Transparency and collaboration, visibility and recognition, and rapid dissemination of results were identified as benefits of preprint servers. Concerns exist regarding the potential risk of non--peer reviewed medical research being publicly available. LimitationsPreprint servers remain a recent phenomenon in health sciences and their long-- term impact on the medical literature remains to be seen. ImplicationsThe quantity of research submitted to preprint servers is likely to continue to grow. The model for dissemination of research results will need to adapt to incorporate preprint servers.

15: Kidney function on admission predicts in-hospital mortality in COVID-19
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Posted 20 Jun 2020

Kidney function on admission predicts in-hospital mortality in COVID-19
679 downloads medRxiv nephrology

Sinan Trabulus, Cebrail Karaca, İlker İnanç Balkan, Mevlut Tamer Dincer, Ahmet Murt, SG Ozcan, Rıdvan Karaali, Bilgul Mete, Alev Bakir, Mert Ahmet Kuskucu, Mehmet Riza Altiparmak, Fehmi Tabak, Nurhan Seyahi

Background Recent data have reinforced the concept of a reciprocal relationship between COVID-19 and kidney function. However, most studies have focused on the effect of COVID-19 on kidney function, whereas data regarding kidney function on the COVID-19 prognosis is scarce. Therefore, in this study, we aimed to investigate the association between eGFR on admission and the mortality rate of COVID-19. Methods We recruited 336 adult consecutive patients (male 57.1%, mean age 55.0 {+/-}15.9) that were hospitalized with the diagnosis of COVID-19 in the tertiary care university hospital. Data were collected from the electronic health records of the hospital. On admission, eGFR was calculated using the CKD-EPI formula. Acute kidney injury was defined according to the KDIGO criteria. Binary logistic regression and Cox regression analyses were used to assess the relationship between eGFR on admission and in-hospital mortality of COVID-19. Results Baseline eGFR was under 60 mL/min/1.73m2 in 61 patients (18.2%). Acute kidney injury occurred in 29.1% of the patients. In-hospital mortality was calculated as 12.8%. Age-adjusted and multivariate logistic regression analysis (p:0.005, odds ratio:0.974, CI:0.956-0.992) showed that baseline eGFR was independently associated with mortality. Additionally, age-adjusted Cox regression analysis revealed a higher mortality rate in patients with an eGFR under 60 mL/min/1.73m2. Conclusions On admission eGFR seems to be a prognostic marker for mortality in patients with COVID-19; We recommend to determine eGFR in all patients on admission and use it as an additional tool for risk stratification. Close follow-up should be warranted in patients with reduced eGFR.

16: Impact of COronaVirus Disease -2019 (COVID-19) pandemic on Haemodialysis care delivery pattern in Karnataka, India- a cross-sectional, questionnaire based survey.
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Posted 27 Jul 2020

Impact of COronaVirus Disease -2019 (COVID-19) pandemic on Haemodialysis care delivery pattern in Karnataka, India- a cross-sectional, questionnaire based survey.
647 downloads medRxiv nephrology

Anupama Y J, Arvind Conjeevaram, Ravindra Prabhu A, Manjunath Doshetty, Sanjay Srinivasa, Venkatesh Moger

The COVID-19 pandemic has disrupted health care delivery globally. Patients on in-centre haemodialysis(HD) are particularly affected due to their multiple hospital visits and the need for uninterrupted care for their well-being and survival. We studied the impact of the pandemic and the national policy for pandemic control on the HD care delivery in Karnataka state in India in April 2020, when the first and second national lockdown were in place. An online, questionnaire based survey of dialysis facilities was conducted and the responses analysed. The questions were pertaining to the key areas such as changes in number of dialysis treatments, frequency, duration, expenses, transportation to and from dialysis units, impact on availability of consumables, effect on dialysis personnel and on machine maintenance. 62 centres participated. Median of dialysis treatments for the months of March and April 2020 were 695.5 and 650 respectively. Reduction in dialysis treatments was noted in 29(46.8%) facilities , decreased frequency reported by 60 centres. In at least 35(56.5%) centres, dialysis patients had to bear increased expenses. Cost and availability of dialysis consumables were affected in 40(64.5%) and 55(88.7%) centres respectively. Problems with transportation and movement restriction were the two key factors affecting both patients and dialysis facilities.This survey documents the collateral impact of COVID -19 on the vulnerable group of patients on HD, even when not affected by COVID. It identifies the key areas of challenges faced by the patients and the facilities and implores the care-providers for finding newer avenues for mitigation of the problems. Key words: COVID-19, India, Haemodialysis , dialysis care delivery, questionnaire-based survey

17: Comparison of psychological distress and demand induced by COVID-19 during the lockdown period in patients undergoing peritoneal dialysis and hemodialysis: a cross-section study in a tertiary hospital
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Posted 17 Apr 2020

Comparison of psychological distress and demand induced by COVID-19 during the lockdown period in patients undergoing peritoneal dialysis and hemodialysis: a cross-section study in a tertiary hospital
613 downloads medRxiv nephrology

Zi Li, Xiaoxiao Xia, Xiaofang Wu, Xueli Zhou, Zhiyun Zang, Li Pu

Background: Since the outbreak of COVID-19 in December 2019, it has spread rapidly and widely, bringing great psychological pressure to the public. In order to prevent the epidemic, lockdown was required in many areas of China, which led to inconvenience of treatment for dialysis patients. To explore the psychological distress and the psychological demand induced by COVID-19 in the patients undergoing dialysis and compare the difference between hemodialysis (HD) and peritoneal (PD) patients during the lockdown period. Methods: Questionnaires were given to the dialysis patients in West China Hospital of Sichuan University. The Impact of Event Scale (IES) was used to investigate the patients' trauma-related distress in response to COVID-19. Results: 232 eligible respondents were enrolled in this cross-section study, consisting of 156 PD patients and 76 HD patients. The median IES score for all the enrolled patients was 8.00 (2.00-19.00), which belonged to the subclinical dimension of post-traumatic stress symptoms. HD patients had a significant higher IES score than PD patients (11.50 vs 8.00) (p<0.05). HD patients already got more psychological support from the medical staff. There was no significant difference on further demand of psychological support between the two groups. In the multivariate regression analysis, we found that dialysis vintage, the impact of COVID-19 on the severity of illness and daily life, and confidence in overcoming the disease contributed to IES score (p<0.05). Conclusions: HD patients had more severe trauma-related stress symptoms than PD patients. When major public healthy events occurred, careful psychological estimate and sufficient psychological support should be provided to the dialysis patients, especially to the HD patients.

18: Organising outpatient dialysis services during the COVID-19 pandemic. A simulation and mathematical modelling study.
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Posted 27 Apr 2020

Organising outpatient dialysis services during the COVID-19 pandemic. A simulation and mathematical modelling study.
578 downloads medRxiv nephrology

Michael Allen, Amir Bhanji, Jonas Willemsen, Steven Dudfield, Stuart Logan, Tom Monks

Background This study presents two simulation modelling tools to support the organisation of networks of dialysis services during the COVID-19 pandemic. These tools were developed to support renal services in the South of England (the Wessex region caring for 650 patients), but are applicable elsewhere. Methods A discrete-event simulation was used to model a worst case spread of COVID-19 (80% infected over three months), to stress-test plans for dialysis provision throughout the COVID-19 outbreak. We investigated the ability of the system to manage the mix of COVID-19 positive and negative patients, and examined the likely effects on patients, outpatient workloads across all units, and inpatient workload at the centralised COVID-positive inpatient unit. A second Monte-Carlo vehicle routing model estimated the feasibility of patient transport plans and relaxing the current policy of single COVID-19 patient transport to allow up to four infected patients at a time. Results If current outpatient capacity is maintained there is sufficient capacity in the South of England to keep COVID-19 negative/recovered and positive patients in separate sessions, but rapid reallocation of patients may be needed (as sessions are cleared of negative/recovered patients to enable that session to be dedicated to positive patients). Outpatient COVID-19 cases will spillover to a secondary site while other sites will experience a reduction in workload. The primary site chosen to manage infected patients will experience a significant increase in outpatients and in-patients. At the peak of infection, it is predicted there will be up to 140 COVID-19 positive patients with 40 to 90 of these as inpatients, likely breaching current inpatient capacity (and possibly leading to a need for temporary movement of dialysis equipment). Patient transport services will also come under considerable pressure. If patient transport operates on a policy of one positive patient at a time, and two-way transport is needed, a likely scenario estimates 80 ambulance drive time hours per day (not including fixed drop-off and ambulance cleaning times). Relaxing policies on individual patient transport to 2-4 patients per trip can save 40-60% of drive time. In mixed urban/rural geographies steps may need to be taken to temporarily accommodate renal COVID-19 positive patients closer to treatment facilities. Conclusions Discrete-event simulation simulation and Monte-Carlo vehicle routing model provides a useful method for stress-testing inpatient and outpatient clinical systems prior to peak COVID-19 workloads.

19: Artificial Intelligence for COVID-19 Risk Classification in Kidney Disease: Can Technology Unmask an Unseen Disease?
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Posted 17 Jun 2020

Artificial Intelligence for COVID-19 Risk Classification in Kidney Disease: Can Technology Unmask an Unseen Disease?
573 downloads medRxiv nephrology

Caitlin Monaghan, John W Larkin, Sheetal Chaudhuri, Hao Han, Yue Jiao, Kristine Marie Bermudez, Eric D Weinhandl, Ines A Dahne-Steuber, Kathleen Belmonte, Luca Neri, Peter Kotanko, Jeroen P Kooman, Jeffrey L Hymes, Robert J Kossmann, Len A Usvyat, Franklin W Maddux

Background: We developed two unique machine learning (ML) models that predict risk of: 1) a major COVID-19 outbreak in the service county of a local HD population within following week, and 2) a hemodialysis (HD) patient having an undetected SARS-CoV-2 infection that is identified after following 3 or more days. Methods: We used county-level data from United States population (March 2020) and HD patient data from a network of clinics (February-May 2020) to develop two ML models. First was a county-level model that used data from general and HD populations (21 variables); outcome of a COVID-19 outbreak in a dialysis service area was defined as a clinic being located in one of the national counties with the highest growth in COVID-19 positive cases (number and people per million (ppm)) in general population during 22-28 Mar 2020. Second was a patient-level model that used HD patient data (82 variables) to predict an individual having an undetected SARS-CoV-2 infection that is identified in subsequent [&ge;]3 days. Results: Among 1682 counties with dialysis clinics, 82 (4.9%) had a COVID-19 outbreak during 22-28 Mar 2020. Area under the receiver operating characteristic curve (AUROC) for the county-level model was 0.86 in testing dataset. Top predictor of a county experiencing an outbreak was the COVID-19 positive ppm in the general population in the prior week. In a select group (n=11,664) used to build the patient-level model, 28% of patients had COVID-19; prevalence was by design 10% in the testing dataset. AUROC for the patient-level model was 0.71 in the testing dataset. Top predictor of an HD patient having a SARS-CoV-2 infection was mean pre-HD body temperature in the prior week. Conclusions: Developed ML models appear suitable for predicting counties at risk of a COVID-19 outbreak and HD patients at risk of having an undetected SARS-CoV-2 infection.

20: Incidence and risk factors of kidney impairment on patients with COVID-19: a systematic review and meta-analysis
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Posted 03 Jun 2020

Incidence and risk factors of kidney impairment on patients with COVID-19: a systematic review and meta-analysis
566 downloads medRxiv nephrology

Qixin Yang, Xiyao Yang

Background: The novel coronavirus is pandemic around the world. Several researchers have given the evidence of impacts of COVID-19 on the respiratory, cardiovascular and gastrointestinal system. Studies still have debated on kidney injury of COVID-19 patients. The purpose of the meta-analysis was to evaluate the association of kidney impairment with the development of COVID-19. Methods: The PubMed, Embase and MedRxiv databases were searched until April 1, 2020. We extracted data from eligible studies to summarize the clinical manifestations and laboratory indexes of kidney injury on COVID-19 infection patients and further compared the prevalence of acute kidney injury (AKI) and the mean differences of three biomarkers between in ICU/severe and non-ICU/non-severe cases. Heterogeneity was evaluated using the I2 method. Results: In the sum of 19 studies with 4375 patients were included in this analysis. The pooled prevalence of AKI, increased serum creatinine (Scr), increased blood urea nitrogen (BUN), increased D-dimer, proteinuria and hematuria in patients with COVID-19 were 7.7%, 6.6%, 6.2%, 49.8%, 42% and 30.3% respectively. Moreover, the means of Scr, BUN and D-dimer were shown 6-folds, 1.8-folds and 0.68-folds, respectively, higher in ICU/severe cases than in corresponding non-ICU/non-severe patients. The prevalence of AKI was about 17 folds higher in ICU/severe patients compared with the non-ICU/non-severe cases. Conclusions: Overall, we assessed the incidences of the clinic and laboratory features of kidney injury in COVID-19 patients. And kidney dysfunction may be a risk factor for COVID-19 patients developing into the severe condition. In reverse, COVID-19 can also cause damage to the kidney.

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