scholarly journals Use of Peritoneal Dialysis for Acute Kidney Injury during the COVID-19 Pandemic in New York City: A multicenter observational study

Author(s):  
Wei Chen ◽  
Nina Caplin ◽  
Osama El Shamy ◽  
Shuchita Sharma ◽  
Maryanne Y. Sourial ◽  
...  
2020 ◽  
Vol 5 (9) ◽  
pp. 1532-1534 ◽  
Author(s):  
Divya Shankaranarayanan ◽  
Sanjay P. Neupane ◽  
Elly Varma ◽  
Daniil Shimonov ◽  
Supriya Gerardine ◽  
...  

2021 ◽  
Author(s):  
Sergio Dellepiane ◽  
Akhil Vaid ◽  
Suraj K Jaladanki ◽  
Ishan Paranjpe ◽  
Steven Coca ◽  
...  

AbstractAcute Kidney Injury (AKI) is among the most common complications of Coronavirus Disease 2019 (COVID-19). Throughout 2020 pandemic, the clinical approach to COVID-19 has progressively improved, but it is unknown how these changes have affected AKI incidence and severity. In this retrospective analysis, we report the trend over time of COVID-19 associated AKI and need of renal replacement therapy in a large health system in New York City, the first COVID-19 epicenter in United States.


2021 ◽  
Author(s):  
Sergio Dellepiane ◽  
Akhil Vaid ◽  
Suraj K. Jaladanki ◽  
Steven Coca ◽  
Zahi A. Fayad ◽  
...  

2020 ◽  
Author(s):  
Nina J Caplin ◽  
Olga Zhdanova ◽  
Manish Tandon ◽  
Nathan Thompson ◽  
Dhwanil Patel ◽  
...  

The COVID-19 pandemic created an unprecedented strain on hospitals in New York City. Although practitioners focused on the pulmonary devastation, resources for the provision of dialysis proved to be more constrained. To deal with these shortfalls, NYC Health and Hospitals/Bellevue, NYU Brooklyn, NYU Medical Center and the New York Harbor VA Healthcare System, put together a plan to offset the anticipated increased needs for kidney replacement therapy. Prior to the pandemic, peritoneal dialysis was not used for acute kidney injury at Bellevue Hospital. We were able to rapidly establish an acute peritoneal dialysis program at Bellevue Hospital for acute kidney injury patients in the intensive care unit. A dedicated surgery team was assembled to work with the nephrologists for bedside placement of the peritoneal dialysis catheters. A multi-disciplinary team was trained by the lead nephrologist to deliver peritoneal dialysis in the intensive care unit. Between April 8, 2020 and May 8, 2020, 39 peritoneal dialysis catheters were placed at Bellevue Hospital. 38 patients were successfully started on peritoneal dialysis. As of June 10, 2020, 16 patients recovered renal function. One end stage kidney disease patient was converted to peritoneal dialysis and was discharged. One catheter was poorly functioning, and the patient was changed to hemodialysis before recovering renal function. There were no episodes of peritonitis and nine incidents of minor leaking, which resolved. Some patients received successful peritoneal dialysis while being ventilated in the prone position. In summary, despite severe shortages of staff, supplies and dialysis machines during the COVID-19 pandemic, we were able to rapidly implement a de novo peritoneal dialysis program which enabled provision of adequate kidney replacement therapy to all admitted patients who needed it. Our experience is a model for the use of acute peritoneal dialysis in crisis situations.


2021 ◽  
Author(s):  
Suraj K Jaladanki ◽  
Akhil Vaid ◽  
Ashwin S Sawant ◽  
Jie Xu ◽  
Kush Shah ◽  
...  

Federated learning is a technique for training predictive models without sharing patient-level data, thus maintaining data security while allowing inter-institutional collaboration. We used federated learning to predict acute kidney injury within three and seven days of admission, using demographics, comorbidities, vital signs, and laboratory values, in 4029 adults hospitalized with COVID-19 at five sociodemographically diverse New York City hospitals, between March-October 2020. Prediction performance of federated models was generally higher than single-hospital models and was comparable to pooled-data models. In the first use-case in kidney disease, federated learning improved prediction of a common complication of COVID-19, while preserving data privacy.


2020 ◽  
Vol 1 (7) ◽  
pp. e283-e289 ◽  
Author(s):  
Ania Wajnberg ◽  
Mayce Mansour ◽  
Emily Leven ◽  
Nicole M Bouvier ◽  
Gopi Patel ◽  
...  

2020 ◽  
Vol 33 (2) ◽  
pp. 140-147
Author(s):  
Ernie Yap ◽  
Marcia Joseph ◽  
Shuchita Sharma ◽  
Osama El Shamy ◽  
Alan D. Weinberg ◽  
...  

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