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Original research
The outcome and related risk factors of unvaccinated patients with end-stage kidney disease during the Omicron pandemic: a multicentre retrospective study
  1. Quanchao Zhang1,
  2. Caibao Lu1,
  3. Shaofa Wu2,
  4. Jin He3,
  5. Han Wang3,
  6. Jie Li4,
  7. Zhifen Wu4,
  8. Bingshuang Ta5,
  9. Bingfeng Yang5,
  10. Shengli Liao6,
  11. Liao Wang6,
  12. Hongwei Chen1,
  13. Moqi Li1,
  14. Wenchang He1,
  15. Yiqin Wang1,
  16. Lili Jiang2,
  17. Jing-Hong Zhao1,
  18. Ling Nie1
  1. 1 Department of Nephrology, the Key Laboratory for the Prevention and Treatment of Chronic Kidney Disease of Chongqing, Chongqing Clinical Research Center of Kidney and Urology Diseases, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, China
  2. 2 Department of Nephrology, Youyang Hospital, A Branch of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  3. 3 Department of Endocrinology and Nephrology, Chonggang General Hospital, Chongqing, China
  4. 4 Urology and Kidney Disease Center, Yongchuan People's Hospital of Chongqing, Chongqing, China
  5. 5 Department of Nephrology and Endocrinology, Chong Qing Bishan District Hospital of Traditional Chinese Medicine, Chongqing, China
  6. 6 Hemodialysis Center, Nanchuan Hospital of Traditional Chinese Medicine, Chongqing, China
  1. Correspondence to Dr Ling Nie; ricknie{at}tmmu.edu.cn; Dr Jing-Hong Zhao; zhaojh{at}tmmu.edu.cn; Dr Lili Jiang; 315904749{at}qq.com

Abstract

Objectives The study aims to identify the outcome and the related factors of unvaccinated patients with end-stage kidney disease during the Omicron pandemic.

Design A multicentre retrospective study of patients with end-stage kidney disease undergone maintenance haemodialysis (HD) in China.

Setting 6 HD centres in China.

Participants A total of 654 HD patients who tested positive for SARS-CoV-2 were ultimately included in the study.

Outcome measures The primary outcomes of interest were adverse outcomes, including hospitalisation due to COVID-19 and all-cause mortality.

Results The average age of the patients was 57 years, with 33.6% of them being over 65 years. Among the patients, 57.5% were male. During the follow-up period, 158 patients (24.2%) experienced adverse outcomes, and 93 patients (14.2%) died. The majority of patients (88/158) developed adverse outcomes within 30 days, and most deaths (77/93) occurred within 1 month. An advanced multivariable Cox regression analysis identified that adverse outcomes were associated with various factors while all-cause mortality was related to advanced age, male gender, high levels of C reactive protein (CRP) and low levels of prealbumin. The Kaplan-Meier curves demonstrated significantly higher all-cause mortality rates in the older, male, high CRP and low prealbumin subgroups.

Conclusions Among unvaccinated HD patients with confirmed Omicron infections, various factors were found to be linked to adverse outcomes. Notably, age, sex, CRP and prealbumin had a substantial impact on the risk of all-cause mortality.

  • Dialysis
  • Mortality
  • Vaccination

Data availability statement

Data are available on reasonable request.

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STRENGTHS AND LIMITATIONS OF THIS STUDY

  • The study used a multicentre, large-scale data to include a sufficient number of unvaccinated patients with end-stage kidney disease with complete follow-up information that significantly enhances the robustness of the study.

  • The study used a comprehensive multivariable adjustment to reduce confounding influences affecting the association between not vaccinating against SARS-CoV-2 and patient prognosis.

  • The study could not include certain information due to data unavailability, including clinical classification, high-flow oxygen/ventilator application and intensive care unit (ICU) admission.

  • Despite our best efforts to adjust potential confounding variables, it is possible that some unmeasured confounding effects still influenced the outcomes owing to the retrospective nature of this study.

Introduction

SARS-CoV-2 was initially reported at the end of 2019, giving rise to a worldwide pandemic that has become a significant public health challenge.1 As of 10 January 2023, the WHO has documented over 660 million confirmed cases of COVID-19, which have culminated in more than 6.6 million fatalities linked to COVID-19.2 In China, the government adhered to a nationwide dynamic COVID Zero strategy to minimise morbidity and mortality from COVID-19. This approach successfully kept the infection rate at extremely low levels for over 2.5 years.3 However, on 7 December 2022, the strategy was relaxed and the epidemic quickly spread throughout the country. During this time, the Omicron variant had emerged as the dominant strain during the global pandemic, and a phenomenon mirrored in China.

SARS-CoV-2 gains entry into host cells by binding to ACE2 receptors. While ACE2 is predominantly found in the respiratory system, it has also been found in the gastrointestinal tract, heart, kidneys and brain.4–7 Therefore, SARS-CoV-2 affects not only the lungs but also other organs, potentially leading to multiorgan failure and increased mortality.8 9 Furthermore, elderly individuals and those with pre-existing comorbidities experience worsened complications associated with COVID-19.10 In the case of dialysis patients, who often suffer from multiple comorbidities and are of advanced age, their vulnerability to infection is heightened, resulting in higher hospitalisation rates and increased morbidity and mortality due to weakened immunity caused by chronic kidney disease (CKD).11 12

In the present global COVID-19 pandemic, the most cost-effective strategy for reducing the global burden of the disease lies in the widespread implementation of safe and effective vaccines.13 It is undeniable that vaccination plays a crucial role in mitigating breakthrough infections of SARS-CoV-2 and reducing the occurrence of adverse outcomes among dialysis patients. However, certain patients continue to exhibit hesitancy towards receiving the vaccine due to various reasons. In this context, it is imperative to explore methods of minimising the occurrence of adverse outcomes. Subsequently, the objective of this study is to identify factors linked to adverse outcomes in unvaccinated dialysis patients infected with the Omicron variant, with the aim of offering assistance for clinical treatment.

Materials and methods

Study subjects

The study retrospectively evaluated a cohort of haemodialysis (HD) patients from six HD centre in China. The patient underwent follow-ups between 7 December 2022 (the initiation of the dynamic COVID Zero strategy) and 28 February 2023. The inclusion criterion was as follows: patients received maintenance HD treatment for at least 3 months; age above 18 and confirmed SARS-CoV-2 infection for the first time. The exclusion criteria were as follows: age below 18 years old; without SARS-CoV-2 infection or have been infected before the start of the study; vaccinated for SARS-CoV-2 prior to the present investigation and lack of clinical information data or clear medical history. The flow chart of inclusion and exclusion is shown in figure 1.

Figure 1

The flow chart of inclusion and exclusion of participants. HD, haemodialysis.

Patient and public involvement

Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Clinical and laboratory information

The following data were collected: age, sex, body mass index, dialysis vintage, vascular access, dialysis frequency, combination with peritoneal dialysis or not and CKD aetiology. Comorbidities such as diabetes, cardiocerebrovascular disease (myocardial infarction, cerebral infarction, cerebral haemorrhage, coronary heart disease, chronic heart failure and peripheral vascular diseases), chronic obstructive pulmonary disease and tumour were also recorded. Haemoglobin, serum albumin, serum calcium, serum phosphorus, serum intact parathyroid hormone, Kt/Vurea, serum albumin, alanine transaminase, aspartate transaminase (AST), prealbumin and ferritin were obtained from the most recent routine laboratory tests prior to the acquisition of COVID-19. Drugs use surveys containing ACE inhibitors/angiotensin-receptor blockers, immunosuppressant and antiviral drugs. Only antiviral drugs, here referred to paxlovid and azvudine, are used for the treatment of COVID-19 while other drugs are from baseline. Drugs use was obtained through medical records.

Exposure and outcome

The primary exposure was confirmed SARS-CoV-2 infection through PCR or antigen testing, and all patients included in the study were experiencing their first infection. Unvaccinated patient was considered a person who did not receive any SARS-CoV-2 vaccines before and during the follow-up period. The data on vaccination were sourced from National Medical Security System database. The primary outcomes of interest were adverse outcomes, which included hospitalisation due to COVID-19 and all-cause mortality. A COVID-19-associated hospitalisation was defined as any person who tested positive for SARS-CoV-2 was admitted to hospital, regardless of the reason for hospitalisation. All-cause mortality was defined as any death occurring within 30 days after SARS-CoV-2 infection.

Statistical analysis

Continuous variables are represented as the average±SD or the median and IQR depending on the normal distribution results using the Kolmogorov-Smirnov test, whereas categorical variables are described as percentages (%). The t-test was applied for normally distributed data, and the Mann-Whitney U test was applied for non-normally distributed data. The χ2 test was applied for categorical variable data. HRs were estimated using Cox regression analyses for the relationships between all covariates (including demographic, clinical and laboratory information) and adverse outcomes. Receiver operating characteristic curves (ROCs) were used to evaluate the predictive abilities of multivariable models for adverse outcomes. The Kaplan-Meier curve is used to display the occurrence of adverse outcomes in the whole population and in special subgroups. All statistical analyses were performed with SPSS Statistics V.23 (IBM). A p<0.05 was considered significant. To avoid excluding possible significant factors, we have elevated the testing level of multivariable analysis to 0.1.

Results

During the period from December 2022 to February 2023, we included a total of 654 unvaccinated HD patients with confirmed SARS-CoV-2 infection from 6 HD centres in the study. The median age of the participants was 57, and 57.5% of the participants were male. The majority (87.8%) of participants underwent thrice-weekly dialysis sessions, and 96.8% had an autologous arteriovenous fistula or arteriovenous graft for permanent vascular access. When considering the aetiology of CKD, glomerulonephritis was present in 245 patients (37.5%), diabetic nephropathy in 118 patients (18%), hypertensive nephropathy in 59 patients (9%) while 72 patients (11%) had other or unknown causes.

Throughout the follow-up period, 158 (24.2%) patients suffered adverse outcome while 93 (14.2%) patients died. Predominantly (88/158) of patients experienced adverse outcomes within 30 days. All deaths occurred within 3 months, most (77/93) of them died within 1 month (figure 2). Compared with people with adverse outcomes, these individuals were older, had fewer dialysis frequencies and more patients had diabetes, cardiocerebrovascular diseases as well as higher levels of AST and C reactive protein (CRP). Additionally, the levels of haemoglobin and prealbumin were lower in these individuals. Lastly, these individuals had a higher usage of inhalation drugs, immunosuppressant drugs and antiviral drugs against SARS-CoV-2. Table 1 provides a summary of the patients’ characteristics and laboratory data.

Figure 2

Occurrence of adverse outcomes (A) and all-cause mortality (B) showed by K-M curves. K-M, Kaplan-Meier.

Table 1

The general clinical characteristics of the included participants

We initially performed a univariable Cox regression analysis to analyse potential risk factors linked to adverse outcomes. The results demonstrated a positive association (p<0.05) between adverse outcomes and variables such as haemoglobin, serum albumin, AST, CRP and prealbumin. Regarding categorical variables, age ≥65, dialysis frequency, diabetes, tumour and use of antiviral drugs were found to be positively linked to adverse outcomes. Subsequently, we performed a multivariable analysis and incorporated additional potential risk variables (with a p<0.1). The Cox regression analyses revealed that age ≥65, usage of dialysis catheter and antiviral drugs, diabetes, higher AST, CRP and lower prealbumin were independently associated with higher rates of adverse outcomes. These results are presented in table 2.

Table 2

Univariate and mutilvariable analysis of the associations between variables and adverse outcomes using Cox regression analyses

Employing the same methodology, we investigated risk factors associated with all-cause mortality. In both the univariable and multivariable Cox analysis, the only significant factors associated with all-cause mortality were age ≥65 (HR 9.9 (95% CI 3.6 to 27.2), p<0.001), male gender (HR 3.7 (95% CI 1.3 to 10.6), p=0.014), CRP (HR 1.5 (95% CI 1.2 to 1.9), p<0.001) and prealbumin (HR 0.6 (95% CI 0.4 to 0.84), p=0.005) (table 3).

Table 3

Univariate and mutilvariable analysis of the associations between variables and all-cause death using Cox regression analyses

Moreover, we conducted an evaluation to assess the predictive capability of CRP and prealbumin for all-cause mortality employing ROC curves. Both ROC curves demonstrated strong predictive performance for all-cause mortality, with the area under the curves (AUC) of 0.80 (95% CI 0.72 to 0.88) and 0.80 (95% CI 0.71 to 0.88) for CRP and prealbumin, respectively. The identified cut-off values for CRP and prealbumin were 14.6 mg/L and 292.2 g/L, respectively (online supplemental figure 1). Furthermore, CRP and prealbumin were transformed into categorical variables based on these cut-off values, splitting the whole population into higher and lower groups. Using Kaplan-Meier curves, we compared all-cause mortality among the various categories defined by these four independent influencing factors. The results indicated a significant increase in all-cause mortality within the elderly, male, higher CRP or lower prealbumin groups (online supplemental figure 2).

Supplemental material

Discussion

The results of this study’s findings show that among unvaccinated HD patients with confirmed SARS-CoV-2 Omicron infections, various factors were linked to adverse outcomes while only age, sex, CRP and prealbumin significantly influenced the risk of all-cause mortality. To the best of our knowledge, prior studies have not reported the risk factors that affect the adverse outcomes of unvaccinated HD patients with Omicron infections.

In this study, we found an adverse outcome incidence rate of 24.2% and a mortality rate of 14.2%. Additionally, it was found that more than half of adverse outcomes occurred within 30 days while 70% (65/93) of deaths occurred within 20 days (figure 2). Our findings differ somewhat from previous data obtained from dialysis patients in China. A recent study reported an adverse outcome rate of 27.4% and a mortality rate of 5.7% among 106 dialysis patients infected with Omicron in China.14 The discrepancy between our study and this research lies in the absence of vaccination in our population, a much larger sample size and a relatively younger patient population. According to our hypothesis, younger populations may experience a lower incidence of adverse events while the absence of vaccination may contribute to an increased risk of all-cause mortality. Another study conducted in China on the outcome of a dialysis population reported a mortality rate of approximately 11%, but this study’s population consisted solely of hospitalised dialysis patients.14

Advanced age, malegender, elevated levels of CRPand reduced levels of prealbumin significantly increased the risk of all-cause mortality, which were consistent with previous studies on COVID-19 outcomes. Advanced age has been consistently identified as a significant risk factor for severe illness and mortality in COVID-19 patients, which probably results from a decrease in immune function due to ageing and a rise in comorbidities.15 Male gender has also been associated with a higher risk of severe outcomes, possibly due to hormonal and immunological differences between sexes.16 Elevated CRP, an inflammation indicator, aligns with a dysregulated immune response, subsequently leading to a poor prognosis in COVID-19 patients.7 17 18 Similarly, low prealbumin levels, which indicate malnutrition and poor overall health status, have been previously associated with adverse outcomes in various diseases.17Recognising these risk factors in the context of HD patients with SARS-CoV-2 infection delivers significant insights for risk stratification and possible interventions in this susceptible population. These findings emphasise the importance of targeted monitoring and management strategies in this high-risk population.

In this study, all infections recorded during the study period were caused by the Omicron variant, and all of these infections were first-time occurrences of SARS-CoV-2. Referring to the Chinese Center for Disease Control and Prevention analysed a total of 24 789 valid COVID-19 genome sequences nationwide between 1 December 2022 and 30 March 2023.19 The report identified all sequences as the Omicron variant, observing 62 distinct evolutionary branches. The dominant epidemic strains were identified as BA.5.248 (49.1%), BF.7.14 (27.3%) and DY.1 (9.0%). Numerous research substantiates that the Omicron variant strain exhibits significantly reduced pathogenicity compared with previous strains.20–22 Consistently, the mortality rate among unvaccinated individuals in our study was significantly lower than previously reported.23–27

The most cost-effective solution to reduce the global burden of COVID-19 is the implementation of safe and effective vaccines. China has adopted the same strategy, starting nationwide vaccination in April 2021. Up until December 2021, 2.5 billion vaccinations have been completed nationwide. The most cost-effective approach to mitigate the global impact of COVID-19 is by deploying safe and effective vaccines. China has embraced a similar approach and initiated nationwide vaccination efforts in April 2021. By December 2021, a total of 2.5 billion vaccinations had been administered across the country.28 However, there remains a degree of hesitancy among selected groups regarding receiving the SARS-CoV-2 vaccines. This hesitancy could be ascribed to multiple factors. First, following the onset of the COVID-19 epidemic, diverse forms of vaccines were promptly developed, manufactured and used, surpassing the speed of previous vaccine development.29 This has led to concerns regarding the safety and efficacy of the vaccine. Second, the potential side effects associated with vaccination are particularly concerning for patients with pre-existing comorbidities and advanced age, including those undergoing dialysis, inducing them afraid of getting vaccinated. In addition, China’s unique national conditions have played a role in the current situation. The robust protection offered by the COVID Zero strategy has seemingly diminished the populace’s motivation to get vaccinated. As a consequence, a majority of dialysis patients have chosen not to get vaccinated, leaving notably susceptible to the Omicron infection.

However, dialysis patients should be vaccinated as much as possible because the protective effect of vaccines on dialysis patients has been confirmed by multiple studies,23–27 30 including our previous single-centre study.31 In that study, we found that vaccination can indeed reduce the risk of death, but it cannot reduce hospitalisation rates. In the present multicentre study, among the 201 vaccinated individuals not included in the study, 27 (13.4%) were hospitalised during follow-up, and 9 (4.5%) died. The hospitalisation rates were similar, but the mortality rate was significantly lower than that of the unvaccinated population. This is another important proof of the protective effect of vaccines in the dialysis population.

Supplemental material

Data availability statement

Data are available on reasonable request.

Ethics statements

Patient consent for publication

Acknowledgments

We thank all the nursing staff who helped with the recording of this data. Mengxia Wu, Hong Ding, Jingxin Tan, Ying Shen, Ying Yin, Hui Yan, Ying Chen, Xiaoxue Wang, Mei Huang, Weiyu Zeng, Zhen Xing, Lin Gong, Min Tan, Yan He, Linshu Li, Xiaoyuan Li, Jing Zhang, Daxiang Hu, Wenting Ye, Ning Wang, Fang Zou, Fang Fang, Lingli Ding, Chunjing Xiang, Jinyu Yang, Fenglin Li, Xiaoyu Ding, Siyu Tan, Yuan Mi, Yuting Zhang, Yang Liu, Quan Yan, Ling Yang, Jieru Yang, Xiangli Zeng, Wei Guo, Ran Wang, Yu Zou, Lu Yu, Can Huang, Hao Zhong, Ying Liu, Zhou Xiong, Wei Wang, Huiling Ma, Ping Wang, Linqi Wang, Maolin Gan, Gongming Wang, Yanli Wen, Jialin Pang, Shanqing Ma, Chaojun Chen, Qian Zou, Xiaoxia Guo, Li Gong, Shuqiong Xiang, Chuan Bo, Jiumao Feng, Linling Guo, Shujun Jiang, Hongmei Jiao, Zeqin Ding.

References

Footnotes

  • QZ, CL and SW contributed equally.

  • Contributors Conceptualisation: QZ, CL, LJ, JH and LN; Formal analysis, QZ and CL; Data curation, QZ, CL, SW, JH, HW, JL, ZW, BT, BY, SL, LW, HC, ML, WH and YW; Writing-original draft preparation: QZ, CL and SW; Writing-review and editing, LJ, J-HZ and LN; Visualisation: QZ; Funding acquisition: QZ; Guarantor: NL.

  • Funding This work was supported by grants from the National Natural Science Foundation of China (NO. 82101967).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.