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Kidney360
Kidney360
KIDNEY
Kidney360
Kidney360
2641-7650
American Society of Nephrology

39151048
K360-2023-000874
10.34067/KID.0000000000000490
00010
3
Clinical Research
Dialysis
Long-Term Morbidity and Mortality of Coronavirus Disease 2019 in Patients Receiving Maintenance Dialysis: A Multicenter Population-Based Cohort Study
https://orcid.org/0000-0002-7152-6195
Bota Sarah E. 1 2
McArthur Eric 1 2
Naylor Kyla L. 1 2 3
Blake Peter G. 2 4 5
https://orcid.org/0000-0001-8653-6778
Yau Kevin 6
https://orcid.org/0000-0001-9227-4292
Hladunewich Michelle A. 4 6 7
https://orcid.org/0000-0003-2438-8401
Levin Adeera 8 9
https://orcid.org/0000-0003-3334-0581
Oliver Matthew J. 7
1 ICES, Toronto, Ontario, Canada
2 Lawson Health Research Institute, London Health Sciences Centre, London, Ontario, Canada
3 Department of Epidemiology and Biostatistics, Western University, London, Ontario, Canada
4 Ontario Health, Toronto, Ontario, Canada
5 Division of Nephrology, London Health Sciences Centre, London, Ontario, Canada
6 Department of Medicine, University of Toronto, Toronto, Ontario, Canada
7 Division of Nephrology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
8 Division of Nephrology, University of British Columbia, Vancouver, British Columbia, Canada
9 BC Provincial Renal Agency, Vancouver, British Columbia, Canada
Correspondence: Dr. Matthew J. Oliver, email: Matthew.Oliver@sunnybrook.ca
8 2024
16 8 2024
5 8 11161125
6 12 2023
4 6 2024
Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Nephrology
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Visual Abstract

Key Points

The rates of long-term mortality, reinfection, cardiovascular outcomes, and hospitalization were high among coronavirus disease 2019 (COVID-19) survivors on maintenance dialysis.

Several risk factors, including intensive care unit admission related to COVID-19 and reinfection, were found to have a prolonged effect on survival.

This study shows that the burden of COVID-19 remains high after the period of acute infection in the population receiving maintenance dialysis.

Background

Many questions remain about the population receiving maintenance dialysis who survived coronavirus disease 2019 (COVID-19). Previous literature has focused on outcomes associated with the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it may underestimate the effect of disease. This study describes the long-term morbidity and mortality among patients receiving maintenance dialysis in Ontario, Canada, who survived SARS-CoV-2 infection and the risk factors associated with long-term mortality.

Methods

We conducted a population-based cohort study of patients receiving maintenance dialysis in Ontario, Canada, who tested positive for SARS-CoV-2 and survived 30 days between March 14, 2020, and December 1, 2021 (pre-Omicron), with follow-up until September 30, 2022. Our primary outcome was all-cause mortality while our secondary outcomes included reinfection, composite of cardiovascular (CV)–related death or hospitalization, all-cause hospitalization, and admission to long-term care or complex continuing care. We also examined risk factors associated with long-term mortality using multivariable Cox proportional hazards regression.

Results

We included 798 COVID-19 survivors receiving maintenance dialysis. After the first 30 days of infection, death occurred at a rate of 15.0 per 100 person-years (95% confidence interval [CI], 12.9 to 17.5) over a median follow-up of 1.4 years (interquartile range, 1.1–1.7) with a nadir of death at approximately 0.5 years. Reinfection, composite CV death or hospitalization, and all-cause hospitalization occurred at a rate (95% CI) of 15.9 (13.6 to 18.5), 17.4 (14.9 to 20.4), and 73.1 (66.6 to 80.2) per 100 person-years, respectively. In addition to traditional predictors of mortality, intensive care unit admission for COVID-19 had a prolonged effect on survival (adjusted hazard ratio, 2.6; 95% CI, 1.6 to 4.3). Reinfection with SARS-CoV-2 among 30-day survivors increased all-cause mortality (adjusted hazard ratio, 2.2; 95% CI, 1.4 to 3.3).

Conclusions

The burden of COVID-19 persists beyond the period of acute infection in the population receiving maintenance dialysis in Ontario with high rates of death, reinfection, all-cause hospitalization, and CV disease among COVID-19 survivors.

cardiovascular events
chronic dialysis
COVID-19
hospitalization
mortality
COVID-19 Immunity Task Force2122-HQ-000071 Matthew J. OliverICESOntario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC) Not ApplicableOntario Health Data Platform (OHDP)Province of Ontario initiative to support Ontario’s ongoing response to COVID-19 and its related impacts Not ApplicableCOVID-19 Immunity Task Force2122-HQ-000071 ICESOntario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC) Ontario Health Data Platform (OHDP)Province of Ontario initiative to support Ontario’s ongoing response to COVID-19 and its related impacts OPEN-ACCESSTRUE
SDCT
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pmcIntroduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the coronavirus disease 2019 (COVID-19) pandemic, has had a significant effect on the population receiving maintenance dialysis.1,2 Unvaccinated patients receiving maintenance dialysis exhibited a high risk of severe SARS-CoV-2 infection in the first 18 months of the COVID-19 pandemic, which frequently resulted in hospitalization (63%–81%)3–6 and death (19%–30%) within 30 days of the acute infection.3–9 Factors such as impaired immune response10–14 and multimorbidity8,15–18 likely contribute to disease severity in this population. Before the COVID-19 pandemic, this population already exhibited a high rate of death (12.4 per 100 person-years in Ontario, Canada,19 and 17.3 per 100 person-years in the United States20) and a significant burden of disease.21

The majority of the COVID-19 research studies on the population receiving maintenance dialysis have examined the outcomes of the acute infection; however, less is known about the long-term effects of this disease or the characteristics of the individuals who survived. As we enter the fifth year of the COVID-19 pandemic, many patients on maintenance dialysis have been infected and many have survived. This study does not explore the continuation of COVID-19 symptoms (i.e., long coronavirus disease or post-coronavirus disease condition); rather, we are interested in other long-term sequelae that persist or appear after the acute infection. Individuals receiving maintenance dialysis may experience critical complications during their acute episode that leads to increased long-term morbidity or death. Furthermore, focusing on 30-day outcomes alone underestimates the effect of COVID-19 in this population. Two studies of 30-day COVID-19 survivors receiving hemodialysis found that those infected had an elevated hazard ratio (HR) of death compared with noninfected controls 1 year after infection.6,22 This finding has also been shown in the general population where the risk of excess death remained elevated between 91 and 180 days after infection.23

There is also a paucity of literature on other important outcomes. Recent evidence in the general post-acute COVID-19 population suggests that there may be an increased risk of cardiovascular (CV) events24; however, limited data are available for individuals receiving maintenance dialysis25 despite their established high risk of CV events in the absence of COVID-19.26 The rate of SARS-CoV-2 reinfection in the population receiving maintenance dialysis or the effect it has on the risk of death is also unknown.

Many questions persist about the population receiving maintenance dialysis who survived their initial SARS-CoV-2 infection, including whether, overall, these individuals exhibit better long-term outcomes after recovering from an infection because perhaps only the healthiest patients survive. Alternatively, these patients may experience long-term COVID-19–related health issues in the years after infection. In this study, we aimed to describe the morbidity and mortality of patients receiving maintenance dialysis who acquired SARS-CoV-2 infection in the pre-Omicron era and survived at least 30 days. We also explored the factors associated with long-term all-cause death in these COVID-19 survivors.

Methods

Study Design and Settings

We conducted a population-based cohort study of patients receiving maintenance dialysis in Ontario, Canada, with evidence of SARS-CoV-2 infection between March 14, 2020, and December 1, 2021 (pre-Omicron variant). These datasets were linked using unique encoded identifiers and analyzed at Institute for Clinical Evaluative Sciences (ICES). The use of the data in this project is authorized under Section 45 of Ontario's Personal Health Information Protection Act and does not require review by a Research Ethics Board. This study adheres to REporting of studies Conducted using Observational Routinely collected health Data guidelines (Supplemental Table 1).

Data Sources

We used several administrative databases collected as part of the universal health care system in the province. The Ontario Renal Reporting System captures patients receiving maintenance dialysis treatments while the Registered Persons Database contains information on demographics and vital status. The COVID-19 Integrated Testing Dataset contains all available PCR tests in the province and is derived from the Ontario Laboratories Information System, laboratories within the COVID-19 diagnostic network, and the Case and Contact Management System. We used the Canadian Institute of Health Information Discharge Abstract Database to capture hospitalization information and the Ontario Health Insurance Plan database for physician fee for services. The Continuing Care Reporting System was used to ascertain long-term care home and complex continuing care admissions. Supplemental Table 2 contains further information on the databases.

Population Receiving Maintenance Dialysis

Maintenance dialysis was defined as evidence of dialysis treatments for at least 30 days and included both prevalent and incident patients. Patients entered the cohort if they had evidence of a positive PCR SARS-CoV-2 test, and they survived 30 days from the date of their positive PCR test. The positive PCR SARS-CoV-2 test date plus 30 days was the cohort entry date (i.e., index date). We excluded patients with a missing or invalid ICES key number, age, or sex; those who died before the index date; non-Ontario residents (data cleaning); those younger than 18 years (to remove the pediatric population); or evidence of kidney function recovery, transfer, kidney transplant, withdrawal from dialysis, or loss to follow-up in the Ontario Renal Reporting System before their index date. COVID-19–related hospitalization occurring anytime between their positive SARS-CoV-2 PCR test and 30 days thereafter (including the index date) was an important baseline predictor identified a priori. We captured patients who were discharged before their index date and those who remained hospitalized beyond 30 days.

Outcomes

Our primary outcome was all-cause mortality. Our secondary outcomes included reinfection, a composite of CV-related death27 or hospital admission for a major CV event (i.e., ischemic stroke, myocardial infarction, or congestive heart failure), all-cause hospitalization, and admission to a long-term care (i.e., nursing home that provides 24-hour care) or complex continuing care (i.e., nonacute facility-based program that provides medically complex and specialized chronic care services) facility. Individuals who were not discharged from hospital at the start of follow-up were excluded from the hospitalization and composite CV outcome analyses. Similarly, those who were found to be residents of long-term care or receiving complex continuing care at baseline were removed from the analysis of those outcomes. We followed patients from their index date to a maximum follow-up date of September 30, 2022 (Omicron variant in circulation during the follow-up period). All relevant variables and their codes are available in Supplemental Table 2.

Statistical Analyses

We reported categorical variables as frequencies and percentages and continuous variables as medians and interquartile percentiles (25th, 75th). For all outcomes, we reported the frequency, percentage, total person-years of follow-up, median follow-up, and event rate per 100 person-years (95% confidence interval [CI]). We stratified baseline characteristics and outcomes by baseline COVID-19–related hospitalization (defined as a hospitalization between their PCR test date and 30 days [index date]). Differences across these strata were estimated using standardized mean differences where we considered a difference ≥0.10 as significant.28 Missing data were minimal, but where present, single imputation was used.

We estimated the factors that are associated with long-term death using adjusted Cox proportional hazards models. Covariates were selected using the literature and clinical knowledge, and we included age, sex, income quintile, Charlson Comorbidity Index, dialysis modality (in-center hemodialysis versus home modalities), dialysis vintage, previous hospitalizations, previous emergency department visits, vaccination status, hospitalization with COVID-19 (no intensive care unit [ICU] admission), and ICU admission with COVID-19 in the models. The proportionality assumption was tested using the Kolmogorov-type supremum test; when nonproportionality was present, we stratified the covariate by time. We also fit a second Cox model where we included the covariates of interest plus a time-varying covariate for reinfection during follow-up. A long-term death risk factor analysis was also done in a subgroup of those who survived 90 days from their PCR-positive test date to understand the effect of the acute infection period on long-term mortality. All analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC). Two-sided P values < 0.05 were considered statistically significant.

Results

Baseline Characteristics

We found 1099 (of 17,664) patients receiving maintenance dialysis with a positive PCR test who survived 30 days. One hundred and fifty-two (15%) patients died within 30 days of their positive test date and were excluded from this study. After all the data cleaning and exclusions were applied, 798 patients remained in our cohort (Supplemental Figure 1).

The median age was 65 years, and most were male (58%) (Table 1). Eighty percent of the cohort were receiving in-center hemodialysis at baseline, and the median dialysis vintage was 3 (1, 5) years. The majority of the cohort were infected when the wild-type (50.4%) and Alpha (41.6%) viruses were the dominant strains (January 17, 2021, to June 12, 2021) (Supplemental Figure 2) and when vaccination rates were low (70.8% were not vaccinated at the time of their infection).

Table 1 Characteristics of severe acute respiratory syndrome coronavirus 2–positive patients receiving maintenance dialysis, overall and stratified by hospitalization within 30 days of their acute infection

Characteristic	SARS-CoV-2 Infection
n=798	Hospitalization with SARS-CoV-2
n=316	No Hospitalization with SARS-CoV-2
n=482	Standardized Difference	
Age at index	65 (55–74)	67 (56–76)	63 (54–73)		
Female	335 (42.0)	133 (42.1)	202 (41.9)	0.00	
Income quintilea					
 Quintile 1	312 (39.1)	123 (38.9)	189 (39.2)	0.01	
 Quintile 2	184 (23.1)	68 (21.5)	116 (24.1)	0.06	
 Quintile 3	156 (23.1)	55 (17.4)	101 (21.0)	0.09	
 Quintile 4	86 (10.8)	42 (13.3)	44 (9.1)	0.13	
 Quintile 5	60 (7.5)	28 (8.9)	32 (6.6)	0.09	
Rural residence	30 (3.8)	10 (3.2)	20 (4.1)	0.05	
Dialysis vintage	3 (1–5)	3 (2–6)	3 (1–5)		
Dialysis type					
 In-center hemodialysis	640 (80.2)	253 (80.1)	387 (80.3)	0.01	
 Home modalityb	158 (19.8)	63 (19.9)	95 (19.7)	0.01	
Prior kidney transplant	23 (2.9)	11 (3.5)	12 (2.5)	0.06	
Vaccination status (doses)c					
 0	565 (70.8)	231 (73.1)	334 (69.3)	0.08	
 1	99 (12.4)	43 (13.6)	56 (11.6)	0.06	
 2	134 (16.8)	42 (13.3)	92 (19.1)	0.16d	
Dominant variant of concerne					
 Wild-type	402 (50.4)	155 (49.1)	247 (51.2)	0.04	
 Alpha	332 (41.6)	128 (40.5)	204 (42.3)	0.04	
 Delta	64 (8.0)	33 (10.4)	31 (6.4)	0.14d	
Hospitalized between PCR-positive test and index date	316 (39.6)	316 (100)	—	—	
ICU admission between PCR-positive test and index date	60 (7.5)	60 (19.0)	—	—	
Hospitalized on index date	100 (12.5)	100 (31.6)	—	—	
Comorbid conditions					
 Diabetes	576 (72.2)	246 (77.8)	330 (68.5)	0.21d	
 Hypertension	750 (94.0)	300 (94.9)	450 (93.4)	0.06	
 Myocardial infarction	55 (6.9)	28 (8.9)	27 (5.6)	0.13d	
 Congestive heart failure	388 (48.6)	177 (56.0)	211 (43.8)	0.25d	
 Charlson Comorbidity Index	4 (2–5)	4 (2–5)	4 (2–5)		
Emergency department visits	1 (0–3)	2 (1–3.5)	1 (0,3)		
Hospitalizations	1 (0–2)	1 (0–2)	1 (0–2)		
Long-term care resident	82 (10.3)	24 (7.4)	58 (12.0)	0.15d	
Complex continuing care admission	21 (2.6)	11 (3.5)	10 (2.1)	0.08	
Medication prescriptions					
 Ontario drug benefit eligiblef	706 (88.5)	291 (92.1)	415 (86.1)	0.19d	
 Immunosuppressants	90 (12.7)	42 (14.4)	48 (11.6)	0.08	
Categorical variables are represented as frequencies and percentages, and continuous variables as medians and interquartile percentiles (25th and 75th). ICU, intensive care unit; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

a Less than six individuals had missing data. Their values were imputed as category 1.

b Home modalities include home hemodialysis and peritoneal dialysis.

c The study accrual window is March 14, 2020, to December 1, 2021. Severe acute respiratory syndrome coronavirus 2 vaccinations became available in Ontario, Canada, in December 2020. The low vaccination events are a consequence of the time period of interest; that is, many of the individuals captured in this study were infected before receiving their first two doses of vaccine. Less than six individuals had evidence of three doses. Their values were imputed as two in accordance with ICES privacy policies.

d A standardized mean difference of ≥0.10 was considered statistically significant.

e Individuals in the cohort were assigned a variant of concern on the basis of the date of their PCR-positive test and the dominant variant circulating in Ontario in that time period. Dominant variant time frames were determined using Public Health Ontario surveillance reports. The time periods were as follows: (1) Earlier variant/non-variant of concern: before January 17, 2021; Alpha: January 17, 2021 to June 12, 2021; and Delta: June 13, 2021 to December 1, 2021.29,30

f Individuals qualify for the Ontario Drug Benefit (ODB) program when they turn 65 years, or they belong to certain subgroups such as residents of long-term care. This concept captures the individuals in our cohort who are ODB eligible.

Baseline hospitalization related to the acute infection was high (39.6%) in the 30-day survivors, and 7.5% of those hospitalized were admitted to the ICU. An eighth (12.5%) of the cohort were still hospitalized 30 days after their positive test date. The subgroup of patients hospitalized for their acute SARS-CoV-2 infection were older (67 years) compared with those who were not hospitalized (63 years) (Table 1). We also found that patients who were hospitalized were on dialysis longer (4 versus 3 years) and had a higher proportion of comorbidities compared with those who were not hospitalized at baseline.

All-Cause Mortality

After surviving at least 30 days from the acute SARS-CoV-2 infection, 167 (20.9%) patients on maintenance dialysis died in follow-up with an event rate of 15.0 per 100 person-years (95% CI, 12.9 to 17.5) (Table 2). The median length of follow-up was 1.4 (interquartile range, 1.1–1.7) years. Mortality within 90 days of their index date was 4.3% with a rate of 17.9 per 100 person-years (95% CI, 12.8 to 25.1). For the entire cohort, the probability of survival declined steadily over time, as shown in the Kaplan–Meier curve (Figure 1), with a survival probability of 72.0% at 2 years. The 1-year survival probability from this curve was 87.0% (95% CI, 84.4 to 89.2). The hazard function in Figure 2 shows a bathtub-shaped curve where the nadir of death is approximately 0.5 years, after which there is a monotonic increase until the end of the study. Compared with those who were not hospitalized for their acute infection, long-term mortality was much higher among patients who were hospitalized (26.6% versus 17.2%), with a rate of 20.3 (95% CI, 16.4 to 25.2) versus 11.9 (95% CI, 9.6 to 14.7) per 100 person-years (Table 3). The hazard function curves in Figure 3 show slightly higher rate of death among those who were hospitalized for their acute infection compared with patients who were not.

Table 2 Primary and secondary outcomes of patients on maintenance dialysis who survived their acute severe acute respiratory syndrome coronavirus 2 infection (30 days after PCR-positive test date)

Outcome	N	%	Total Person-Years of Follow-Up	Event Rate per 100 Person-Years (95% CI)	Median (IQR) Follow-Up Years	
Death	167	20.9	1113	15.0 (12.9 to 17.5)	1.4 (1.1–1.7)	
SARS-CoV-2 reinfection	161	20.2	1013	15.9 (13.6 to 18.5)	1.4 (0.9–1.7)	
CV-related death or hospital admission for a major CV eventa,b	157	22.5	900	17.4 (14.9 to 20.4)	1.4 (0.9–1.7)	
All-cause hospitalizationa	448	64.2	613	73.1 (66.6 to 80.2)	0.9 (0.3–1.4)	
Long-term care placementa	29	4.1	972	3.0 (2.1 to 4.3)	1.4 (1.1–1.7)	
Complex continuing care placementa	41	5.3	1054	3.9 (2.9 to 5.3)	1.4 (1.0–1.7)	
CI, confidence interval; CV, cardiovascular; IQR, interquartile range; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

a Those with evidence of an admission to hospital, long-term care, or complex continuing care on the index date were removed from each respective analysis. The denominator is n=698 for hospitalization/composite cardiovascular outcomes, n=716 for LTC, and n=777 for CCC.

b Major cardiovascular events included myocardial infarction, congestive heart failure, or ischemic stroke.

Figure 1 Kaplan–Meier curve of the probability of survival among patients receiving maintenance dialysis who survived their acute SARS-CoV-2 infection (30 days after PCR-positive test). SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Figure 2 Hazard function and 95% CI of long-term mortality among patients receiving maintenance dialysis who survived their acute SARS-CoV-2 infection (30 days after PCR-positive test). CI, confidence interval.

Table 3 Primary and secondary outcomes of patients on maintenance dialysis who survived their acute severe acute respiratory syndrome coronavirus 2 infection (30 days after PCR-positive test date) stratified by baseline hospitalization

Outcome	Acute SARS-CoV-2 Hospitalization	No Acute SARS-CoV-2 Hospitalization	
Total Person-Years of Follow-Up	Event Rate per 100 Person-Years (95% CI)	Total Person-Years of Follow-Up	Event Rate per 100 Person-Years (95% CI)	
Death	413.4	20.3 (16.4 to 25.2)	699.5	11.9 (9.6 to 14.7)	
SARS-CoV-2 reinfection	374.7	18.7 (14.8 to 23.6)	638.2	14.3 (11.6 to 17.5)	
CV-related death or hospital admission for a major CV eventa,b	256.0	19.9 (15.1 to 26.2)	644.1	16.5 (13.6 to 19.9)	
All-cause hospitalizationa	152.2	102.5 (87.6 to 119.9)	469.5	63.4 (56.5 to 71.1)	
Long-term care placement	367.2	4.9 (3.1 to 7.8)	604.5	1.8 (1.0 to 3.3)	
Complex continuing care placement	384.9	6.0 (4.0 to 9.0)	669.1	2.7 (1.7 to 4.3)	
CI, confidence interval; CV, cardiovascular; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

a Acute severe acute respiratory syndrome coronavirus 2 hospitalization was defined as evidence of a hospitalization within 30 days of their PCR-positive test date.

b Major cardiovascular events included myocardial infarction, congestive heart failure, or ischemic stroke.

Figure 3 Hazard function and 95% CI of long-term mortality among patients receiving maintenance dialysis who survived their acute SARS-CoV-2 infection (30 days after PCR-positive test) stratified by acute COVID-19 hospitalization. COVID-19, coronavirus disease 2019.

Risk Factors of Long-Term Mortality

In the risk factor analysis, we found that age (per 10-year increase), male sex (versus female), Charlson Comorbidity Index (per 1-unit increase), dialysis vintage (per 1-year increase), COVID-19–related hospitalization, and COVID-19–related ICU admission were all significantly associated with long-term death in the population receiving maintenance dialysis (Figure 4). The strongest associations were observed in individuals who were admitted to the ICU for their acute infection with a 150% increased rate of death (adjusted HR of 2.5 [95% CI, 1.5 to 4.0]). The Charlson Comorbidity Index and previous hospitalization count had evidence of nonproportionality and were stratified by time. When we accounted for reinfection in the model, we found that all the risk factors from the previous model remained statistically significant, and there was a 120% increased rate of long-term death for those who were reinfected (adjusted HR, 2.2; 95% CI, 1.4 to 3.3).

Figure 4 Risk factors of long-term death among patients receiving maintenance dialysis who survived their acute SARS-CoV-2 infection (30 days after PCR-positive test). ED, emergency department; HR, hazard ratio; ICHD, in-centre hemodialysis ICU, intensive care unit.

In a subgroup analysis of those who survived 90 days after their PCR-positive test, the risk factors of long-term death were age (per 10-year increase), Charlson Comorbidity Index, previous hospitalizations, and COVID-19–related ICU admission (Figure 5). When we included reinfection in the subgroup risk factor model, age (per 10-year increase) (adjusted HR, 1.5; 95% CI, 1.3 to 1.7), COVID-19–related ICU admission (adjusted HR, 2.3; 95% CI, 1.3 to 4.0), and reinfection (adjusted HR, 2.2; 95% CI, 1.5 to 3.4) remained statistically significant.

Figure 5 Subgroup analysis of the risk factors of long-term death among patients receiving maintenance dialysis who survived their acute SARS-CoV-2 infection 90 days after PCR-positive test.

CV Outcomes, Reinfection, All-Cause Hospitalization, Long-Term Care, and Complex Continuing Care

Twenty-three percent of the cohort who were discharged at index experienced either a CV-related death or hospitalization for a major CV event during follow-up at a rate of 17.4 per 100 person-years (95% CI, 14.9 to 20.4). SARS-CoV-2 reinfection during follow-up occurred in 20.7% of the cohort at a rate of 15.9 per 100 person-years (95% CI, 13.6 to 18.5). Among those who were discharged from hospital at index, a new all-cause hospitalization event during follow-up was high (64.2%) and occurred at a rate of 73.1 per 100 person-years (95% CI, 66.6 to 80.2) (Table 2). New long-term care and complex continuing care placements occurred in 4.1% (3.0 per 100 person-years, 95% CI, 2.1 to 4.3) and 5.3% (3.9 per 100 person-years, 95% CI, 2.9 to 5.3) of the patients, respectively.

When we stratified the secondary outcomes by baseline COVID-19–related hospitalization, we found that the rates of the composite CV, reinfection, all-cause hospitalization, and long-term and complex continuing care outcomes were higher among those who were hospitalized compared with those who were not hospitalized (Table 3).

Discussion

In this study of patients receiving maintenance dialysis who survived at least 30 days after their acute SARS-CoV-2 infection, we found that one-fifth died within the follow-up period. A number of preexisting and acute infection factors were associated with a significant risk of long-term death, particularly COVID-19–related ICU admission and reinfection. As new phases of the pandemic continue to emerge, it is important to monitor health outcomes31 in high-risk populations to inform the pandemic response for decision makers and health care providers.

The literature on the long-term mortality of COVID-19 survivors receiving maintenance dialysis is limited and mostly captures patients receiving hemodialysis in the early pandemic period. Our study, which captures all dialysis modalities up to September 2022, found that 21% of the patients died by the end of follow-up at a rate of 15.0 per 100 person-years. The prepandemic rate of death has been estimated to be 12.4 per 100 person-years in Ontario.19 In a study following patients receiving in-center hemodialysis who survived>30 days post-acute infection, 34% died by the end of follow-up (<1.5 years) compared with 20% of those who had not been infected (P value < 0.001; HR, 1.8; 95% CI, 1.3 to 2.5).6 In another study, 25% of survivors receiving hemodialysis died >30 days after infection, and the authors found the 12-month all-cause mortality to be significantly higher in the SARS-CoV-2–positive group compared with patients without infection (HR, 3.0; 95% CI, 1.6 to 5.5).22 Both studies captured infections in the pre-Omicron period. Evidence to date suggests that the frequency of long-term death after an acute SARS-CoV-2 infection is high and is greater than those without an infection. This has also been shown in the general US Veterans population where long-term death was found to be higher in COVID-19 survivors compared with uninfected controls up to 2 years (8.7% versus 4.1%).23

A number of studies have looked at the risk factors of death during an acute SARS-CoV-2 infection8,32–34; however, few have looked at the post-acute risk factors associated with death.35,36 In these few studies, risk factors of long-term death were found to be age, dialysis vintage, laboratory measurements (such as albumin, hemoglobin), comorbidities, and poor nutrition. Similarly, age, sex, comorbidity, and dialysis vintage were found to be significantly associated with long-term death in our study; however, COVID-19–related ICU admission and reinfection were the most pronounced. Although most of these factors are not modifiable, they can be used to risk stratify patients and guide monitoring strategies. Continuation of vaccination programming is fundamental to controlling outbreaks and reduce severity.

In our study, one fifth of the cohort had evidence of the composite CV outcome in follow-up, with a rate of 17.4 per 100 person-years. In the MyTEMP pragmatic cluster-randomized trial, CV death or CV hospitalization occurred at a rate of 11.2 per 100 person-years among patients receiving standard in-center hemodialysis care (control).37 An increased risk was also found in two large observational studies of COVID-19 30-day general population survivors with significantly increased risks of incident CV disorders, dysrhythmia, heart disease, other cardiac disorders, and thrombotic disorders, when compared with controls.24,38 In a subgroup analysis, these risks persisted despite CKD status.24 COVID-10 survivors receiving maintenance dialysis should be monitored for CV disease as part of their post-COVID-19 care strategy.

It is important to continue testing high-risk populations for COVID-19 infection; at least, one fifth of patients receiving maintenance dialysis had reinfection in less than 2 years. Reinfection was found to be associated with a two times higher hazard of death, which may be, in part, due to sequelae or inadequate immune response after the initial infection. Early evidence on lasting immune response in patients receiving hemodialysis with a preexisting SARS-CoV-2 infection is promising.39,40 However, there is only anecdotal evidence on the basis of case reports on reinfection outcomes in the population receiving dialysis at this time.41,42 In the general population, reinfection has been found to be associated with additional risks of death and hospitalization.43,44 Our findings suggest that reinfection may be an influential risk factor of death in the population receiving maintenance dialysis. More knowledge is needed to quantify rates of reinfection and understand the risks for those receiving maintenance dialysis. Until more is known, prevention of initial and subsequent SARS-CoV-2 infection, continued adherence to vaccination schedules, and testing are essential for this population.

Our study is the first to report on reinfection events and expands the follow-up window to capture longer-term outcomes in the entire population receiving maintenance dialysis in a single Canadian province. Furthermore, our linked databases are a comprehensive source of information following patients across the continuum of care. However, we recognize that our study has a number of limitations. First, we do not have a variant of concern data for every positive PCR test done in the province. Instead, we used a surrogate for the variant on the basis of the PCR test date and the dominant variant circulating in Ontario at that time. Furthermore, all initial infections in this study are pre-Omicron, and our results may not be generalizable to the post-Omicron period. The study accrual period occurred before the widespread availability of vaccines, so many individuals included in this study had little or no preexisting immunity at the time of infection. Therefore, the HRs associated with vaccination status should be interpreted with caution. There were a number of policy and practice patterns that changed throughout the pandemic period that had an effect on data availability. For example, in December 2021, access to PCR testing in Ontario changed such that free tests were restricted to certain high-risk groups, which did not specifically include patients receiving maintenance dialysis. This change, along with the rise in rapid antigen testing for at-home use, limited our ability to capture reinfection in the follow-up period, particularly among those receiving home dialysis modalities. Patients receiving in-center hemodialysis retained access to hospital PCR testing services throughout the follow-up period. Therefore, the rates of reinfection in our study are likely underestimated. In addition, these policy and practice patterns might have affected access to care. An argument could be made that a 30-day survival window may not be sufficient to capture recovery of the acute infection for the sickest patients. Extension of this survival window to 90 days may be more appropriate. In this descriptive study, we did not capture a comparison group of patients receiving maintenance dialysis who did not have a positive PCR test, but we were able to make a comparison with the established rates of all-cause and CV mortalities in our population receiving maintenance dialysis.

In this study describing the long-term morbidity and mortality of COVID-19 in patients receiving maintenance dialysis, we found that the rates of death, reinfection, all-cause hospitalization, and CV outcomes were high, and there were a number of factors associated with the risk of long-term mortality. This study adds to the evidence on the long-term effect of COVID-19 in the population receiving maintenance dialysis, which demonstrates that the burden remains high beyond acute infection. Additional research is needed to better understand the long-term effects of COVID-19–related morbidity and mortality in the population receiving maintenance dialysis.

Supplementary Material

Acknowledgments

This study was completed at the ICES Western site. Parts of this material are based on data and information compiled and provided by Ontario Health, MOH, and the Canadian Institute for Health Information. This document used data adapted from the Statistics Canada Postal CodeOM Conversion File, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from ©Canada Post Corporation and Statistics Canada We thank IQVIA Solutions Canada Inc. for using their Drug Information File. The analyses, conclusions, opinions, and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. This study was supported by the Ontario Health Data Platform (OHDP), a Province of Ontario initiative to support Ontario's ongoing response to COVID-19 and its related impacts. The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by the OHDP, its partners, or the Province of Ontario is intended or should be inferred. We thank Nadiyah Rehman for her assistance on this manuscript.

Disclosures

Disclosure forms, as provided by each author, are available with the online version of the article at http://links.lww.com/KN9/A548.

Funding

M.J. Oliver: COVID-19 Immunity Task Force (2122-HQ-000071). This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). This study also received funding from the COVID-19 Immunity Task Force (CITF).

Author Contributions

Conceptualization: Sarah E. Bota, Eric McArthur, Kyla L. Naylor, Matthew J. Oliver.

Data curation: Sarah E. Bota, Eric McArthur, Kyla L. Naylor, Matthew J. Oliver.

Formal analysis: Eric McArthur.

Funding acquisition: Matthew J. Oliver.

Investigation: Peter G. Blake, Sarah E. Bota, Eric McArthur, Kyla L. Naylor, Matthew J. Oliver.

Methodology: Sarah E. Bota, Eric McArthur, Kyla L. Naylor, Matthew J. Oliver.

Project administration: Sarah E. Bota, Kyla L. Naylor.

Visualization: Eric McArthur.

Writing – original draft: Sarah E. Bota.

Writing – review & editing: Peter G. Blake, Sarah E. Bota, Michelle A. Hladunewich, Adeera Levin, Eric McArthur, Kyla L. Naylor, Matthew J. Oliver, Kevin Yau.

Data Sharing Statement

Data cannot be shared. The dataset from this study is held securely in coded form at ICES. While legal data sharing agreements between ICES and data providers (e.g., health care organizations and government) prohibit ICES from making the dataset publicly available, access may be granted to those who meet prespecified criteria for confidential access, available at www.ices.on.ca/DAS (email: das@ices.on.ca). The full dataset creation plan and underlying analytic code are available from the author upon request, understanding that the computer programs may rely upon coding templates or macros that are unique to ICES and are therefore either inaccessible or may require modification.

Supplemental Material

This article contains the following supplemental material online at http://links.lww.com/KN9/A547.

Supplemental Table 1. Checklist of recommendations for reporting of observational studies using the Reporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement.

Supplemental Table 2. Study concept definitions.

Supplemental Figure 1. Cohort flow diagram.

Supplemental Figure 2. Frequency of SARS-CoV-2 infections among patients receiving maintenance dialysis during the study accrual window.
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