key: cord-0772974-5v2rlpam authors: Miller, Jonathan; Wey, Andrew; Musgrove, Donald; Son Ahn, Yoon; Hart, Allyson; Kasiske, Bertram L.; Hirose, Ryutaro; Israni, Ajay K.; Snyder, Jon J. title: Mortality among solid organ waitlist candidates during COVID‐19 in the United States date: 2021-03-06 journal: Am J Transplant DOI: 10.1111/ajt.16550 sha: 0c39d740bb0be4164bd73d432571180f1a8f9ab0 doc_id: 772974 cord_uid: 5v2rlpam We examined the effects of COVID‐19 on solid organ waiting list mortality in the United States and compared effects across patient demographics (e.g., race, age, and sex) and donation service areas. Three separate piecewise exponential survival models estimated for each solid organ the overall, demographic‐specific, and donation service area‐specific differences in the hazard of waitlist mortality before and after the national emergency declaration on March 13, 2020. Kidney waiting list mortality was higher after than before the national emergency (adjusted hazard ratio [aHR], 1.37; 95% CI, 1.23–1.52). The hazard of waitlist mortality was not significantly different before and after COVID‐19 for liver (aHR, 0.94), pancreas (aHR, 1.01), lung (aHR, 1.00), and heart (aHR, 0.94). Kidney candidates had notable variability in differences across donation service areas (aHRs, New York City, 2.52; New Jersey, 1.84; and Michigan, 1.56). The only demographic group with increased waiting list mortality were Blacks versus Whites (aHR, 1.41; 95% CI, 1.07–1.86) for kidney candidates. The first 10 weeks after the declaration of a national emergency had a heterogeneous effect on waitlist mortality rate, varying by geography and ethnicity. This heterogeneity will complicate comparisons of transplant program performance during COVID‐19. This analysis used SRTR Standard Analysis File (SAF) candidate datasets from August 2020, which represent all patients in the United States who are, or have been, registered on the waiting list for a solid organ transplant since October 1, 1987 . The SRTR SAFs have been described in great detail previously. 6, 7 Because recording at least 95% of patient deaths on the waiting list can take 2 or more months due to a lag in reporting, candidates were included if they were prevalent on the organ transplant waiting list between March 13, 2019, and May 31, 2020. Therefore, this study presents early findings from the first 10 weeks after the declaration of the COVID-19 national emergency. Candidates with no reported listing date or age at listing or who were younger than 18 years at listing were excluded. Candidate follow-up was censored at transplant, recovery without a transplant, or transfer to another center. The analyses were performed separately for kidney, pancreas, liver, lung, and heart candidates. Waiting time and outcomes were included for patients regardless of whether they were listed as active or inactive. The primary outcome was waitlist mortality, specifically the causespecific hazard of waitlist mortality, which does not mathematically depend on the transplant rate. 8 Thus, any differences in the causespecific hazard of waitlist mortality before and after COVID-19 are not inherently attributable to lower transplant rates after COVID-19. The main predictor of interest was the COVID-19 pandemic, as defined by time before or after the declaration of a national emergency in the United States on March 13, 2020. These analyses track temporal trends in mortality before and after COVID-19, because individual-level incidence status and cause of death are not available in the SRTR SAF. Covariates modeled for all solid organ types were age in years, sex, ethnicity, race, urban or rural residence, miles between candidate and program, blood type, body mass index (BMI), primary diagnosis, insurance type, previous transplants, and waiting time. In addition, these covariates were modeled for these types of transplants: Candidate characteristics with time-varying values were updated at the beginning of each month before and after March 13, 2020. For example, the LAS constantly changes as patients become more or less sick. Thus, a patient's LAS value at the beginning of each month was the value used for analyses for that entire month. The last available value was used for follow-up after removal from the waiting list. Given the interest in the time-varying effect of COVID-19 on waitlist outcomes, piecewise exponential models (PEMs) were used to estimate the rate of waitlist mortality after the COVID-19 declaration on March 13, 2020, versus before. PEMs are proportional hazards models with a constant baseline hazard in a priori defined intervals. The models included two intervals for the baseline hazard: before and after COVID-19. The time scale for these models was calendar time. To ensure sufficient precision, each analysis required a minimum number of events after March 13, 2020, detailed below in each subsection. The overall effect of COVID-19 was the difference between the intervals before and after March 13, 2020. For this analysis, the models assumed each covariate had the same effect before and after COVID-19. These models were estimated only when the cohort had more than 10 deaths both before and after COVID-19. A post hoc sensitivity analysis additionally adjusted the models for patient inactive status as a time-varying covariate. To assess whether early trends in waitlist mortality rates attenuated in later months, a post hoc preliminary analysis using the December 2020 SAF modeled time trends in waitlist mortality hazard by month before and after COVID-19 using a PEM with a random effects for each month and adjusted for covariates. Generalized linear mixed models (GLMMs) estimated the DSA-level variability in waitlist mortality rates before and after COVID-19. Specifically, the model included two DSA-level random effects: one for before March 13, 2020, and one for after. The empirical Bayes estimates of the individual DSAs estimated difference of each DSA from the national average before and after COVID-19. Therefore, the kidney model included, for example, 58 DSA-specific pre-COVID effects and 58 DSA specific post-COVID effects. The GLMMs allowed a correlation between the random effects. The difference between the pre-and post-COVID effects identified the relative difference in waitlist mortality rates after, compared with before, COVID-19. The GLMMs included an offset equal to the linear predictors from the PEMs for the overall effect of COVID-19, which accounted for candidate risk factors. These models were estimated only when the number of deaths in the post-COVID-19 period was more than twice the number of DSAs. Separate models estimated the subgroup-specific effects of COVID-19. Specifically, the model included an interaction between each candidate risk factor and the overall effect of COVID-19, allowing the effect of COVID-19 to differ across, for example, candidate age groups. Models were only estimated for each of the covariates listed above when deaths in the post-COVID-19 period were at least 10 plus 2 times the number of variables in the model. CI, 0.57-1.54) candidates were similar before and after COVID-19 ( Figure 1 ). Additionally adjusting for time-varying candidate inactive status did not meaningfully change the hazard ratios (Supplemental File 1). SAF showed that the hazard ratios for waitlist mortality among kidney candidates declined from the peak immediately following COVID-19 but remained high. The hazard ratios for other organs did not notably vary from month to month and did not increase after COVID-19 ( Figure 2 ). The hazard of waitlist mortality among kidney candidates in the New York City DSA was 2.52 times higher after the COVID-19 national emergency declaration than before, even after accounting for the higher hazard of waitlist mortality in the United States ( Figure 3) . Similarly, waitlist mortality was higher among kidney candidates after than before COVID-19 in New Jersey (aHR, 1.84) and Michigan (aHR, 1.56). Differences across DSAs in waitlist mortality for liver transplant candidates were notably smaller. The largest difference after, compared with before, COVID-19 occurred in DSAs serving primarily Milwaukee, Wisconsin (aHR, 1.11) and Hartford, Connecticut (aHR, 1.10). Models for lung, heart, and pancreas candidates were not estimated due to an insufficient number of deaths after March 13, 2020 (Supplemental File 2). Only kidney and liver transplants had a sufficient number of deaths on the waiting list after COVID-19 to estimate differences in waitlist mortality across candidate subgroups. African American kidney waitlist candidates were the only subgroup with early signs of higher waitlist mortality rates after than before COVID-19 (aHR, 1.41; 95% CI, 1.07-1.86, compared with White candidates, Table 1 ). Liver candidates had dramatically higher waitlist mortality rates at higher MELD scores prior to COVID; this trend remained but was notably attenuated after the emergence of COVID-19 (Table 1) . However, the confidence intervals for many subgroups, especially among liver transplant candidates, were notably wide, indicating relatively imprecise estimates. Waitlist mortality rates were notably higher at the outset of the COVID-19 national emergency among kidney waitlist candidates but not other solid organ transplant candidates. The differences in kidney waitlist mortality rates varied geographically, with dramatically higher rates in the New York City DSA. The relative waitlist mortality rate for African Americans compared with White kidney candidates was higher after COVID-19 than before. The differences in waitlist mortality rates across categories of MELD attenuated in the months after the pandemic began, though the COVID-19 pandemic coincided with the beginning of the liver acuity circle allocation policy-an alternate possible explanation for changed in waitlist mortality rates at higher MELD scores. Waitlist mortality rates have historically been lower for kidney candidates than for candidates for other solid organs. 9 However, the largest number of candidates are listed for kidney transplant, and kidney candidates have the longest waiting times. 9 Thus, a higher hazard of waitlist mortality among kidney candidates can represent a substantial number of additional deaths, especially if the higher waitlist mortality is sustained over a long period. Among the many possible causes of the increased mortality rates among kidney waitlist candidates, a few warrant additional discussion. One hypothesis is that the mortality rate increased due to delayed transplants. We estimated the differences in the cause-specific hazard of waitlist mortality before and after COVID-19. The causespecific hazard does not mathematically or inherently depend on changes in the transplant rate, although residual confounding could still cause a relationship between waitlist mortality and transplant rates. A second hypothesis is that the mortality rate increased due to deaths from COVID-19 directly or as the result of delayed medical care due to fear of infection. A limitation of the SRTR database showed peaks in April and July-consistent with the peaks in waitlist mortality found in this study, and giving support to the hypothesis of direct increases in mortality due to COVID-19. 10 In the USRDS analysis, in-home peritoneal dialysis was protective against COVID-19 as compared to in-center hemodialysis. The USRDS also found that non-COVID hospitalizations were decreased compared to the same months in 2017-2019, giving support to the hypothesis of increases in mortality due to delayed medical care. 10 Additionally, evidence of to the date at which geographic variability is reduced. The trend of higher waitlist mortality among African American kidney candidates after than before COVID-19 should be monitored. Americans and Whites. 11 Ongoing monitoring will be important in identifying widening health disparities in specific parts of the The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation. Trends in US heart transplant waitlist activity and volume during the coronavirus disease 2019 (COVID-19) pandemic SARS-CoV-2 infection and early mortality of wait-listed and solid organ transplant recipients in England: a national cohort study The many estimates of the COVID-19 case fatality rate Real estimates of mortality following COVID-19 infection Estimating case fatality rates of COVID-19 Scientific registry of transplant recipients: collecting, analyzing, and reporting data on transplantation in the United States Big data in organ transplantation: Registries and administrative claims Program-specific transplant rate ratios: association with allocation priority at listing and posttransplant outcomes USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Disease COVID-19 and African Americans Mortality among solid organ waitlist candidates during COVID-19 in the United States The data that support the findings of this study are available from the corresponding author upon reasonable request.