The Aftermath of Coronavirus Disease 2019

Devastation or a New Dawn for Nephrology?

Rajiv Agarwal

Disclosures

Nephrol Dial Transplant. 2020;35(6):904-907. 

In This Article

Innovation

As noted above, a ventilator for $100 with an open-source design developed by a team at MIT is an example of innovation that had the potential to impact respiratory failure in low- and middle-income countries. The virus brought the most innovative ideas to the forefront. The first set of tests required to detect COVID-19 required hours and sometimes days to be reported. This was impeding the fight against the virus. Abbott Diagnostics, a Chicago-based company, established a rapid test that could be performed using a point-of-care device, most units of which were already in use in urgent care facilities, where they were used to diagnose influenza A and B, Strep A and respiratory syncytial virus.[8] A positive test could be available in 5 min and a negative test in 13 min. A low-cost COVID-19 test was developed in India and the team was led by a woman in late-stage pregnancy; she delivered a baby soon after submitting the test for approval.[9] The cost of this test was one-third of what was being paid from tests coming from outside the country.

During the COVID-19 pandemic, a company that makes Internet-connected thermometers created a map of the USA by zip code to monitor influenza-like illness.[10] The aggregate, anonymized map provides different levels of information. Areas where illness is unusually high indicate early indicators of COVID-19 spread. Trends are color coded to visualize whether school closures and social distancing are working. This innovation has the potential to transform the health of dialysis patients.

Monitoring the health of entire dialysis units across the country is possible and desirable. With the large wealth of vital sign and temperature data within each dialysis unit, such anonymized monitoring may signal early changes in the health of the unit. Each 1% increase in quarterly influenza-like illness associates with a 1.5–2.0% increase in all-cause mortality among dialysis patients. These mortality rates are similar to mortality estimates for COVID-19 in the general population. Accordingly, such surveillance efforts may be particularly valuable to institute measures similar to those implemented in the COVID-19 pandemic.[11] Sharing of such data will need a national plan and should cross boundaries of data ownership for societal good. Extending this further, longitudinal data for individual patients using the algorithms of artificial intelligence may even provide diagnostic information for patients and serve as an early sign of infection or a cardiovascular event.

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