To the Editor:
The end-stage kidney disease (ESKD) population receiving maintenance dialysis is highly vulnerable to the devastating consequences of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated coronavirus disease 2019 (COVID-19). Although uremia itself is associated with an immune-incompetent state, patients with ESKD are generally older and often have comorbid conditions that increase the risk for poor outcomes in COVID-19.1,2 To date, information on the clinical course of COVID-19 among the ESKD population is limited to single-center experiences and/or homogeneous populations.3, 4, 5, 6, 7, 8 We sought to characterize and determine hospitalizations and survival among a diverse ESKD dialysis population with COVID-19 from the United States.
We conducted a retrospective cohort study of patients with ESKD with COVID-19 within Kaiser Permanente Southern California (KPSC). KPSC is an integrated health system comprised of 14 medical centers, more than 200 clinics, and patients at more than 300 dialysis facilities throughout Southern California. The ESKD population is racially/ethnically diverse, reflective of the 4.7 million KPSC membership population.9 This study was approved by the KPSC Institutional Review Board and exempted from informed consent (IRB #12502). Among patients 18 years and older receiving maintenance hemodialysis or peritoneal dialysis as of March 1, 2020, COVID-19–infected patients with ESKD were identified based on a positive SARS-CoV-2 reverse transcriptase-polymerase chain reaction test result and/or clinical documentation of a positive test result between March 1, 2020, and June 30, 2020. The date of the positive test was considered the index date and all patients were followed up for a minimum of 30 days unless a death event occurred or until the end of the observation period (August 10, 2020). Information on demographics, medications, laboratory results, comorbid conditions, hospitalizations, and death within the observation period was extracted from the electronic health records.
Among 7,533 total patients with ESKD, 133 (16 peritoneal dialysis and 117 hemodialysis) patients had COVID-19 diagnosed in our observation period (Fig 1). Mean age was 66 years, with 38% women, 62% Hispanics, 16% Blacks, 11% Asians, and 9% Whites (Table 1). Overall, 76 (57%) patients required hospitalization, with a median hospitalization length of 10 days. There were 30 (23%) patient deaths, with a median survival of 16 days. Patients who died were older (68 vs 64 years) and had more comorbid conditions, including diabetes (93%), heart failure (33%), and ischemic heart disease (57%). Only 2 (7%) deceased patients were receiving an angiotensin-converting enzyme inhibitor compared with 25% among survivors. There appeared to be no differences in mortality by race/ethnicity and socioeconomic status. Inpatient laboratory studies revealed that deceased patients had higher peak lactate dehydrogenase levels compared with survivors.
Figure 1.
All patients within the Kaiser Permanente Southern California end-stage kidney disease population who had coronavirus disease 2019 (COVID-19) infection between March 1, 2020, and June 30, 2020. Abbreviation: SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
Table 1.
Characteristics of the KPSC COVID-19 ESKD Population and by Hospitalization and Survival Outcomes
| All ESKD Patients With COVID-19 |
Severity |
Mortality |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| No Hospitalization After COVID-19 |
Hospitalized After COVID-19 |
Alive |
Died During Follow-up After COVID-19 |
P |
||||||
| N = 133 | N | N = 57 (42.9%) | N | N = 76 (57.1%) | N | N = 103 (77.4%) | N | N = 30 (22.6%) | ||
| Age, y | 66.0 [52.0-74.0] | 63 [50.0-74.0] | 66.0 [54.0-75.0] | 64.0 [50.0-74.0] | 68.0 [61.0-80.0] | 0.02 | ||||
| Female sex | 51 (38.3%) | 24 (42.1%) | 27 (35.5%) | 41 (39.8%) | 10 (33.3%) | 0.52 | ||||
| Race | 0.34 | |||||||||
| White/Caucasian | 12 (9%) | 5 (8.8%) | 7 (9.2%) | 8 (7.8%) | 4 (13.3%) | |||||
| Black | 21 (15.8%) | 8 (14%) | 13 (17.1%) | 17 (16.5%) | 4 (13.3%) | |||||
| Hispanic | 83 (62.4%) | 38 (66.7%) | 45 (59.2%) | 66 (64.1%) | 17 (56.7%) | |||||
| Asian Pacific Islander | 14 (10.5%) | 6 (10.5%) | 8 (10.5%) | 11 (10.7%) | 3 (10%) | |||||
| Other | 3 (2.3%) | 0 (0%) | 3 (3.9%) | 1 (1%) | 2 (6.7%) | |||||
| Household income, $ | 56,100 [44,018-67,024] | 56,407 [43,809-66,264] | 55,793 [44,701-67,217] | 55,782 [43,442-70,416] | 57,179 [45,236-63,942] | 0.87 | ||||
| Weight, lbs | 180.1 [152.5-214.5] | 173.6 [141.2-200.4] | 182.9 [158.8-219.8] | 174.2 [152.1-212.5] | 185.5 [158.5-219.1] | 0.49 | ||||
| Body mass index, kg/m2 | 28.4 [25.0-32.6] | 27.9 [23.8-32.4] | 29.0 [25.2-33.0] | 28.3 [24.8-32.6] | 29.1 [25.1-33.4] | 0.68 | ||||
| Baseline BP, mm Hg | ||||||||||
| Systolic BP | 135.0 [118.0-156.0] | 138.0 [121.0-157.0] | 133.0 [111.0-155.0] | 132.0 [114.0-154.0] | 143.0 [118.0-158.0] | 0.21 | ||||
| Diastolic BP | 67.0 [59.0-78.0] | 67.0 [60.0-78.0] | 65.5 [59.0-77.0] | 66.0 [59.0-77.0] | 68.0 [60.0-80.0] | 0.55 | ||||
| Primary cause of ESKD | 0.40 | |||||||||
| Diabetes | 93 (69.9%) | 37 (64.9%) | 56 (73.7%) | 68 (66%) | 25 (83.3%) | |||||
| Hypertension | 19 (14.3%) | 11 (19.3%) | 8 (10.5%) | 17 (16.5%) | 2 (6.7%) | |||||
| Glomerulonephritis | 10 (7.5%) | 5 (8.8%) | 5 (6.6%) | 9 (8.7%) | 1 (3.3%) | |||||
| Polycystic kidney disease | 2 (1.5%) | 1 (1.8%) | 1 (1.3%) | 2 (1.9%) | 0 (0%) | |||||
| Other | 9 (6.8%) | 3 (5.3%) | 6 (7.9%) | 7 (6.8%) | 2 (6.7%) | |||||
| History of transplant | 0.18 | |||||||||
| Kidney | 4 (3%) | 2 (3.5%) | 2 (2.6%) | 3 (2.9%) | 1 (3.3%) | |||||
| Other organs | 1 (0.8%) | 0 (0%) | 1 (1.3%) | 0 (0%) | 1 (3.3%) | |||||
| Modality | 0.36 | |||||||||
| Peritoneal dialysis | 16 (12.0%) | 5 (8.8%) | 11 (14.5%) | 14 (13.6%) | 2 (6.7%) | |||||
| Hemodialysis | 117 (88.0%) | 52 (91.2%) | 65 (85.5%) | 89 (86.4%) | 28 (93.3%) | |||||
| ESKD duration, y | 3.5 [1.9-5.8] | 3.0 [1.4-6.1] | 4.0 [2.2-5.7] | 3.1 [1.5-5.7] | 4.6 [3.1-6.4] | 0.05 | ||||
| Comorbid conditions | ||||||||||
| Congestive heart failure | 34 (25.6%) | 14 (24.6%) | 20 (26.3%) | 24 (23.3%) | 10 (33.3%) | 0.27 | ||||
| Ischemic heart disease/coronary artery disease | 54 (40.6%) | 19 (33.3%) | 35 (46.1%) | 37 (35.9%) | 17 (56.7%) | 0.04 | ||||
| Hypertension | 129 (97%) | 55 (96.5%) | 74 (97.4%) | 99 (96.1%) | 30 (100%) | 0.27 | ||||
| Diabetes mellitus | 103 (77.4%) | 38 (66.7%) | 65 (85.5%) | 75 (72.8%) | 28 (93.3%) | 0.02 | ||||
| Peripheral vascular disease | 8 (6%) | 1 (1.8%) | 7 (9.2%) | 4 (3.9%) | 4 (13.3%) | 0.06 | ||||
| Cerebrovascular disease | 8 (6%) | 2 (3.5%) | 6 (7.9%) | 5 (4.9%) | 3 (10%) | 0.30 | ||||
| Liver disease | 22 (16.5%) | 13 (22.8%) | 9 (11.8%) | 17 (16.5%) | 5 (16.7%) | 0.90 | ||||
| Chronic obstructive pulmonary disease | 13 (9.8%) | 6 (10.5%) | 7 (9.2%) | 11 (10.7%) | 2 (6.7%) | 0.51 | ||||
| Asthma | 17 (12.8%) | 8 (14.0%) | 9 (11.8%) | 13 (12.6%) | 4 (13.3%) | 0.92 | ||||
| Obesity | 51 (38.3%) | 20 (35.1%) | 31 (40.8%) | 38 (36.9%) | 13 (43.3%) | 0.52 | ||||
| Smoking | 0.77 | |||||||||
| Never | 83 (62.4%) | 33 (57.9%) | 50 (65.8%) | 62 (60.2%) | 21 (70%) | |||||
| Current | 1 (0.8%) | 0 (0%) | 1 (1.3%) | 1 (1.0%) | 0 (0%) | |||||
| Former | 44 (33.1%) | 22 (38.6%) | 22 (28.9%) | 36 (35%) | 8 (26.7%) | |||||
| Elixhauser comorbidity score | 0.39 | |||||||||
| 1-3 | 9 (6.8%) | 2 (3.5%) | 7 (9.2%) | 8 (7.8%) | 1 (3.3%) | |||||
| ≥4 | 124 (93.2%) | 55 (96.5%) | 69 (90.8%) | 95 (92.2%) | 29 (96.7%) | |||||
| Drugs taken within 1 y before admissions | ||||||||||
| Antiplatelets/nonsteroidal inflammatory agents | 17 (12.8%) | 6 (10.5%) | 11 (14.5%) | 14 (13.6%) | 3 (10%) | 0.60 | ||||
| Antiarrhythmic | 3 (2.3%) | 2 (3.5%) | 1 (1.3%) | 2 (1.9%) | 1 (3.3%) | 0.65 | ||||
| Calcium channel blockers | 68 (51.1%) | 29 (50.9%) | 39 (51.3%) | 56 (54.4%) | 12 (40%) | 0.17 | ||||
| Lipid-lowering agents | 91 (68.4%) | 36 (63.2%) | 55 (72.4%) | 69 (67%) | 22 (73.3%) | 0.51 | ||||
| β-Blockers | 84 (63.2%) | 35 (61.4%) | 49 (64.5%) | 62 (60.2%) | 22 (73.3%) | 0.19 | ||||
| Angiotensin-converting enzyme inhibitors | 28 (21.1%) | 15 (26.3%) | 13 (17.1%) | 26 (25.2%) | 2 (6.7%) | 0.03 | ||||
| Angiotensin receptor blockers | 34 (25.6%) | 15 (26.3%) | 19 (25.0%) | 26 (25.2%) | 8 (26.7%) | 0.88 | ||||
| Diuretics | 3 (2.3%) | 2 (3.5%) | 1 (1.3%) | 3 (2.9%) | 0 (0%) | 0.34 | ||||
| Insulin | 45 (33.8%) | 14 (24.6%) | 31 (40.8%) | 32 (31.1%) | 13 (43.3%) | 0.21 | ||||
| Oral hypoglycemics | 21 (15.8%) | 8 (14%) | 13 (17.1%) | 15 (14.6%) | 6 (20%) | 0.47 | ||||
| Laboratory values | ||||||||||
| Hemoglobin, g/dL | 10.8 [9.7-11.7] | 57 | 10.5 [9.4-11.6] | 76 | 11.1 [9.9-11.7] | 103 | 10.8 [9.6-11.8] | 30 | 10.7 [9.8-11.4] | 0.18 |
| Albumin, g/dL | 3.3 [2.8-3.7] | 57 | 3.2 [2.6-3.7] | 74 | 3.3 [2.9-3.7] | 101 | 3.2 [2.8-3.7] | 30 | 3.3 [2.9-3.7] | 0.72 |
| Hemoglobin A1c, % | 6.0 [5.3-7.2] | 54 | 6.0 [5.2-7.0] | 76 | 6.1 [5.3-7.3] | 100 | 5.9 [5.3-7.1] | 30 | 6.5 [5.3-7.3] | 0.48 |
| Total cholesterol, mg/dL | 131.5 [102.5-155.5] | 57 | 131.0 [106.0-161.0] | 75 | 132.0 [100.0-154.0] | 102 | 139.0 [107.0-161.0] | 30 | 117.5 [90.0-146.0] | 0.01 |
| High-density lipoprotein cholesterol, mg/dL | 38.5 [31.0-47.0] | 57 | 39.0 [33.0-47.0] | 75 | 38.0 [30.0-46.0] | 102 | 39.5 [32.0-47.0] | 30 | 34.5 [30.0-44.0] | 0.09 |
| Low-density lipoprotein cholesterol, mg/dL | 61.5 [44.5-87.0] | 57 | 61.0 [46.0-85.0] | 75 | 62.0 [44.0-88.0] | 102 | 62.0 [46.0-91.0] | 30 | 56.5 [40.0-79.0] | 0.09 |
| Inpatient laboratory valuesa | ||||||||||
| Triglycerides, mg/dL | 266.0 [189.0-363.0] | 25 | 266.0 [189.0-363.0] | 16 | 257.0 [182.0-360.5] | 9 | 316.0 [189.0-390.0] | 0.90 | ||
| D-Dimer, mcg/mL | 2.4 [1.8-4.4] | 43 | 2.4 [1.8-4.4] | 28 | 2.3 [1.8-4.2] | 15 | 2.5 [2.0-4.4] | 0.70 | ||
| Fibrinogen, mg/dL | 649.0 [501.0-762.0] | 23 | 649.0 [501.0-762.0] | 14 | 638.5 [546.0-768.0] | 9 | 653.0 [486.0-689.0] | 0.61 | ||
| C-Reactive protein, mg/L | 180.0 [99.4-315.8] | 53 | 180.0 [99.4-315.8] | 37 | 186.1 [98.7-285.4] | 16 | 177.9 [116.5-319.2] | 0.55 | ||
| Lactate dehydrogenase, U/L | 363.0 [243.5-481.0] | 52 | 363.0 [243.5-481.0] | 38 | 304.5 [241.0-473.0] | 14 | 426.5 [353.0-523.0] | 0.04 | ||
| Creatine kinase, U/L | 177.0 [85.0-304.0] | 33 | 177.0 [85.0-304.0] | 23 | 142.0 [80.0-304.0] | 10 | 243.0 [107.0-340.0] | 0.24 | ||
| Lymphocyte count, 103 × cells/mL | 1.3 [0.6-1.7] | 58 | 1.3 [0.6-1.7] | 39 | 1.3 [0.7-1.7] | 19 | 1.3 [0.4-1.7] | 0.41 | ||
Note: Values expressed as median [interquartile range] or number (percent).
Abbreviations: BP, blood pressure; COVID-19, coronavirus disease 2019; ESKD, end-stage kidney disease; KPSC, Kaiser Permanente Southern California.
The highest levels during the hospitalization were used to capture patients who may have met criteria for cytokine storm syndrome.
We describe the clinical course of all 133 patients with ESKD with COVID-19 diagnosed within a large integrated health system. Most (57%) required hospitalization. The 23% mortality in our ESKD cohort is significantly greater than the 1.3% within KPSC, 1.8% in California, and the 3% to 4% mortality reported from the Centers for Disease Control and Prevention and the World Health Organization for people with COVID-19 diagnosed. The dialysis population is more likely to be identified with COVID-19 given the frequency of screening and care they receive at health facilities because they have a low threshold for screening and testing. Tests were routinely performed based on clinical presentation (fever and symptoms) or history of exposure. Beginning early March 2020, individual dialysis units throughout California instituted strict policies and procedures to screen for SARS CoV-2 infection to protect patients and personnel throughout these dialysis centers.
Among our COVID-19–infected ESKD population, there appeared to be a greater proportion of Hispanics (62% vs 38%) and lesser proportion of Blacks (16% vs 23%) and non-Hispanic Whites (9% vs 28%) compared with the overall KPSC ESKD population.9 The 12% of peritoneal dialysis patients with COVID-19 was lower than the 20% of the prevalent home dialysis/peritoneal dialysis population at KPSC. We observed no apparent differences in survival based on race/ethnicity or socioeconomic status. Patients who died were older and had more comorbid conditions; specifically, heart failure, ischemic heart disease, and diabetes. Our findings are comparable to a French National ESKD cohort with an overall 21% mortality.3 Previous observations among hospitalized patients with ESKD with COVID-19 have observed mortality rates ≥30% reported in relatively homogeneous populations.4,5
Strengths of our study include our observation period of 30 or more days to fully capture the clinical course of patients with ESKD. Information was drawn from a single integrated system that tracks this population using a comprehensive internal registry and thus was able to reliably capture all hospitalizations and deaths. Limitations include the fact that we cannot fully determine that deaths were due to COVID-19 or whether patients opted for palliative care/hospice. The reported death rate, although high, is an aggregate over a 3-month period. It does not reflect changing rates of mortality, which may occur with the evolving care of COVID-19, including more aggressive oxygenation support, screening and monitoring for cytokine storm syndrome, and earlier use of steroids, immunosuppression, prophylactic anticoagulation, and expanded remdesivir use to include patients with ESKD.
Although the overall COVID-19 rates were low among the ESKD population, we observed high mortality among patients with ESKD with COVID-19. Although cardiovascular disease and diabetes were higher among deceased patients, there were no differences in race/ethnicity and socioeconomic status compared with survivors.
Article Information
Authors’ Full Names and Academic Degrees
John J. Sim, MD, Cheng-Wei Huang, MD, David C. Selevan, PMP, Joanie Chung, MS, Mark P. Rutkowski, MD, and Hui Zhou, PhD.
Authors’ Contributions
Research area and study design: JJS, C-WH; data acquisition: DCS, JC, MPR, HZ, JJS; analysis or interpretation of data: JJS, HZ, C-WH, MPR; study supervision: JJS; statistical analysis: HZ; administrative, technical, or material support: MPR. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability of the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.
Support
This study was funded by Kaiser Permanente Southern California Regional Research. This study was also supported by the Kaiser Permanente Southern California Clinician Investigator Award (Dr Sim). KPSC Regional Research, which funded the study, had no role in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.
Financial Disclosure
The authors declare that they have no relevant financial interests.
Acknowledgements
The authors thank Ron Nadjafi, MD, MS, for generosity sharing his work on the KPSC COVID-19 population; Nitin Dhamija, MD, CPPS, and Harjeet Kaur for tremendous work creating the KPSC COVID-19 dashboard for provider use; and Noel Pascual, Paul Saario, and Tuan Le, MD, for assistance and support through the KPSC Renal Business Group.
Peer Review
Received September 24, 2020. Evaluated by 1 external peer reviewer, with direct editorial input from the Statistical Editor and the Editor-in-Chief. Accepted in revised form November 13, 2020.
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