Review of clinical characteristics and mortality outcomes in patients on maintenance hemodialysis during the Omicron surge: a single center experience

Review of clinical characteristics and mortality outcomes in patients on maintenance hemodialysis during the Omicron surge: a single center experience | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Review of clinical characteristics and mortality outcomes in patients on maintenance hemodialysis during the Omicron surge: a single center experience Yiyang Xue, Weiwei Feng, Ling Shi, Ning Cui, Wei Zhang, Junxiu Dong, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3837520/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: This hemodialysis center experienced the pandemic from December 2022 to January 2023. Therefore, we sought to describe the clinical characteristics and mortality outcomes in hemodialysis patients during this Omicron surge. Methods: According to whether they are infected, they are divided into two groups: SARS-CoV-2-positive and SARS-CoV-2-negative. The SARS-CoV-2-positive group was divided into a survival group and a non-survival group for comparison. ​ Results: 366 of 457 hemodialysis patients were infected with SARS-CoV-2. The most common symptoms observed were fever (43.2%) and cough (29.8%), Followed by diarrhea (1.4%). Hemodialysis patients with hypertension were more susceptible to SARS-CoV-2 infection. The lymphocyte count, serum creatinine, serum potassium, and serum phosphorus in the SARS-CoV-2-positive group were significantly lower than those in the SARS-CoV-2-negative group. The all-cause mortality rate for infection with SARS-CoV-2was 5.2%. Only 7 of 366 SARS-CoV-2-positive patients were admitted to the intensive care unit, but 6 of them died. Intensive care unit hospitalization rates were significantly higher in the non-survival group compared with the survival group. White blood cells count, neutrophil count, C-reactive protein, AST, and D-dimer in the non-survival group were higher than those in the survival group. The lymphocyte count, hemoglobin concentration, serum creatinine, serum albumin, serum phosphorus and parathyroid hormone in the non-survival group were lower than those in the survival group. Age>65 years, elevated C-reactive protein and AST are independent risk factors for death. Finally, no significant difference in vaccination status was found between the SARS-CoV-2-positive group and the negative group. Conclusions: Hemodialysis patients are at high risk for SARS-CoV-2 infection. Ensuring the adequacy of hemodialysis treatment and maintaining good physical condition of patients are the top priorities. SARS-CoV-2 Omicron hemodialysis clinical characteristics 1. Introduction At the end of 2019, a new coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged and quickly triggered an unusual viral pneumonia epidemic. Due to its high transmissibility, this novel coronavirus pneumonia, also known as coronavirus disease 2019 (COVID-19), has spread rapidly around the world [ 1 ]. This virus has mutated several times, among which the Omicron mutant strain will be the main circulating strain in China and even most parts of the world in 2022 [ 2 ]. According to a release from the Chinese Center for Disease Control and Prevention, from September 26, 2022 to January 23, 2023, China reported a total of 18,906 effective novel coronavirus genome sequences of local cases, all of which were Omicron mutant strains. From December 2022 to January 2023, the number of medical visits due to new coronavirus infection reached a peak in China, including outpatient medical treatment, general hospitalization and severe hospitalization [ 3 ]. Maintenance hemodialysis patients are a special category of patients during the novel coronavirus pandemic because they are at greater risk of exposure to infection than patients who are able to undergo home peritoneal dialysis. Although the pathogenicity of the Omicron variant is less than that of the previous strain, it is still accompanied by huge risks for patients receiving maintenance hemodialysis. The global prevalence of chronic kidney disease (CKD) is approximately 2%-10% and varies over time in the same region [ 4 – 6 ]. The overall morbidity and mortality rates of CKD patients with SARS-CoV-2 are higher than those of individuals without kidney disease, including patients receiving dialysis [ 7 – 10 ]. In the past three years, there has not been a large-scale epidemic in the area where our center is located, and it only withstood greater epidemic challenges during the current Omicron surge. In the past, most studies were conducted during the epidemic period of Alpha, Beta and others, but there is a lack of research on the clinical characteristics of maintenance hemodialysis patients in the Omicron environment. Therefore, we retrospectively analyzed all patients who were registered in our center and received long-term maintenance hemodialysis from December 15, 2022 to February 22, 2023, a total of 457 patients. Our paper presents the clinical profiles and outcomes of maintenance hemodialysis patients with confirmed and undiagnosed suspected SARS-CoV-2 infection in our center, as well as survival and non-survival cases among maintenance hemodialysis patients with confirmed SARS-CoV-2 infection. clinical characteristics and established different profiles and outcomes between the two groups of patients. 2. Patients and Methods 2.1. Study subjects This retrospective study was conducted at the Hemodialysis Center of Urology and Nephrology Hospital, Ningbo, Zhejiang Province. We retrospectively analyzed the clinical results of 457 patients who were registered and maintained hemodialysis in our center from December 15, 2022 to February 22, 2023, and divided them into SARS-CoV-2 positive and SARS-CoV-2 negative two groups. In addition, based on the confirmed SARS-CoV-2 positivity, the patients were divided into a survival group and a non-survival group for comparison. The diagnostic criteria for patients included in the study refer to the "Diagnosis and Treatment Plan for Novel Coronavirus Infection (Tenth Edition)" issued by the National Health Commission of China [ 11 ]. The diagnostic criteria for suspected cases combined epidemiological history and clinical symptoms, and blood index tests, antigen-antibody and chest CT examinations were performed, so asymptomatic cases were discovered. All patients are over 18 years old. Patients receiving temporary hemodialysis were excluded. Follow-up ends at the end of the study or when the patient dies. All patients were informed and agreed to participate in this study and signed an informed consent form. 2.2. Data collection Data were collected from the hospital HIS system of the Hemodialysis Center of Urology and Nephrology Hospital in Ningbo, Zhejiang Province. Data extracted from registered patient medical records included demographic and clinical information, including age, gender, and chronic comorbidities. Data related to SARS-CoV-2 include clinical symptoms (fever, cough, myalgia, fatigue, taste/smell disorder, etc.), laboratory indicators, chest CT, whether to receive intensive care, and length of hospitalization. Data related to maintenance hemodialysis include hemodialysis age, dry weight, duration of dialysis (months), and dialysis urea clearance index (KT/V). Vaccination status of all patients receiving maintenance hemodialysis, including primary immunization, booster and secondary booster immunization. 2.3. Statistical analysis Statistical description: Normally distributed measurement data are described by mean ± standard deviation, non-normally distributed measurement data are described by median (interquartile range), and count data are described by frequency (percentage). Statistical analysis: Normally distributed measurement data were subjected to t test, and non-normally distributed measurement data were subjected to rank sum test. Count data were analyzed using chi-square test and Fisher's exact probability method. Risk factor analysis used logistic regression analysis. P values < 0.05 were considered statistically significant. 3. Results 3.1. Epidemiological and clinical characteristics of all patients receiving maintenance hemodialysis During the study period, a total of 457 people met the inclusion criteria, with an average age of 59.82 ± 14.13 years (p > 0.05), 37.6% were female (172, p > 0.05), including 366 SARS-CoV-2 positive patients and 91 SARS-CoV-2 negative patients. Table 1 shows the comparison of epidemiological parameters, clinical symptoms, and hemodialysis-related data between SARS-CoV-2 positive and SARS-CoV-2 negative hemodialysis patients. The most common symptoms observed in hemodialysis patients after SARS-CoV-2 infection were fever (43.2%) and cough (29.8%), followed by diarrhea (1.4%). Other symptoms such as dyspnea, back pain, sore throat, headache, or taste/smell disorder are less common. However, the incidence of fatigue after infection with SARS-CoV-2 was reduced (0.5% vs 4.4%). Patients with hypertension and hemodialysis showed statistical differences between the SARS-CoV-2 positive group and the negative group (p < 0.001). All patients receiving maintenance hemodialysis showed no statistically significant differences in dialysis-related data (hemodialysis age, dry weight, duration of dialysis (months), KT/V). Finally, no statistically significant difference in mortality was observed between the two groups (5.2% vs 8.8%, p = 0.192). In addition, in terms of symptoms, fatigue showed completely opposite results to real-world observations (0.5% vs 4.4%, p < 0.016). In terms of mortality statistics, the all-cause mortality rate of 457 patients receiving maintenance hemodialysis was 5.9% (27/457), and the all-cause mortality rate of SARS-CoV-2-positive hemodialysis patients was 5.2% (19/366), while the all-cause mortality rate among SARS-CoV-2-negative hemodialysis patients was 8.8% (8/91). Through data analysis of all-cause mortality of the two groups of hemodialysis patients, no significant statistical difference was found (p = 0.192). Table 2 shows the comparison of laboratory indicators between SARS-CoV-2-positive and SARS-CoV-2-negative hemodialysis patients. In terms of blood cell count, no significant difference was observed between the two groups in terms of the total number of white blood cells. It was only observed that the lymphocyte count in the SARS-CoV-2 positive group was lower than that in the SARS-CoV-2 negative group (0.85 ± 0.43 vs 0.97 ± 0.47, p < 0.05). In the routine analysis of blood biochemistry, we found that the serum creatinine (Cr), serum potassium, serum phosphorus, and parathyroid hormone in the SARS-CoV-2 positive group were significantly lower than those in the SARS-CoV-2 negative group. Statistical significance (p < 0.05). During the follow-up period, we counted the vaccination status of all hemodialysis patients (Table 1 ). The vaccination rate for the first basic vaccination was the highest (61.1%), the booster vaccination rate dropped to 27.0%, and the second booster vaccination needle is only 11.9%. At the same time, no significant difference in vaccination status was found between the SARS-CoV-2 positive group and the negative group. 3.2. Comparison of clinical characteristics and laboratory indicators according to mortality among all SARS-CoV-2-positive hemodialysis patients Among the 366 SARS-CoV-2-positive patients, 19 died due to various causes including infection during hospitalization (5.2%), and the remaining 347 patients survived. Table 3 shows the comparison of demographic and laboratory data between the two groups. Age < 65 years showed significant differences between the survival group and the non-survival group (p < 0.001), and age was an independent risk factor for death (Table 5 ). Secondly, we also found that there was a statistical difference between the two groups in terms of age at starting dialysis (p < 0.001), that is, the older the age at starting dialysis, the higher the mortality rate. In the comparison of comorbidities, we found that the comorbidity rates of cardiovascular disease, hypertension, and heart failure in the non-survival group were significantly higher than those in the survival group. Only 7 of the 366 SARS-CoV-2-positive patients were admitted to the intensive care unit (ICU), accounting for 1.9%. Compared with the survival group, ICU rate was significantly higher in the non-survival group (0.3% vs 31.6%, p < 0.001). As shown in Table 4 , we also found that the total number of white blood cells, neutrophil count, C-reactive protein, AST, and D-dimer in the non-survival group were higher than those in the survival group. Among them, C-reactive protein and AST are independent risk factors for death in infected patients (Table 5 ). Not only that, we also found that the lymphocyte count, hemoglobin concentration, blood creatinine, serum albumin, blood phosphorus, and parathyroid hormone indicators in the non-survival group were lower than those in the survival group. Table 1 The baseline epidemiological and clinical characteristics of the patients. Variables Total n (%) SARS-CoV-2 (+) n (%) SARS-CoV-2 (-) n (%) p Fetures N = 457 n = 366 n = 91 Age (years) 59.82 ± 14.13 59.27 ± 14.35 62.02 ± 13.02 0.097 40 41(9.0%) 37(10.1%) 4(4.4%) 0.217 40–65 251(54.9%) 200(54.6%) 51(56.0%) ≥ 66 165(36.1%) 129(35.3%) 36(39.6%) Gender Male 285(62.4%) 230(62.8%) 55(60.4%) 0.672 Female 172(37.6%) 136(37.2%) 36(39.6%) Co-morbid disease Diabetes Mellitus 118(25.8%) 100(27.3%) 18(19.8%) 0.141 Coronary artery disease 12(2.6%) 10(2.7%) 2(2.2%) 0.775 Hypertension 447(97.8%) 364(99.5%) 83(91.2%) < 0.001 * Heart failure 227(49.7%) 180(49.2%) 47(51.6%) 0.673 Cancer 31(6.8%) 27(7.4%) 4(4.4%) 0.311 Chronic obstructive lung disease 4(1.1%) 4(1.1%) 0(0.0%) 0.996 Symptoms Fever 197(43.1%) 158(43.2%) 39(42.9%) 0.957 Cough 137(30.0%) 109(29.8%) 28(30.8%) 0.854 Dyspnea 3(0.7%) 2(0.5%) 1(1.1%) 0.487 Back pain 3(0.7%) 2(0.5%) 1(1.1%) 0.487 Diarrhea 5(1.3%) 5(1.4%) 0(0.0%) 1.000 Fatigue 6(1.3%) 2(0.5%) 4(4.4%) 0.016 * Sore throat 5(1.1%) 3(0.8%) 2(2.2%) 0.260 Headache 1(0.2%) 0(0.0%) 1(1.1%) 0.358 Taste/smell disorder 1(0.2%) 1(0.3%) 0(0.0%) 0.362 HD-related indicators Hemodialysis age 52.50(42.25, 64.25) 52.25(42.00, 64.50) 54.00(44.50, 62.00) 0.649 Dry weight 58.40(51.84, 66.45) 58.34(51.68, 66.53) 59.20(52.18, 76.70) 0.924 Duration of dialysis (months) 59.93(17.39,104.84) 58.98(17.29,101.03) 75.93(19.38,120.10) 0.245 KT/V 1.47 ± 0.51 1.48 ± 0.53 1.46 ± 0.42 0.776 Vaccination status Fundamental immunity Booster immunization Secondary booster immunization 118(61.1%) 52(27.0%) 23(11.9%) 102(62.6%) 42(25.8%) 19(11.6%) 16(53.4%) 10(33.3%) 4(13.3%) 0.621 Mortality 27(5.9%) 19(5.2%) 8(8.8%) 0.192 * Values that reach statistical significance. Table 2 Comparison of the laboratory findings of the patients. Variables Total n (%) SARS-CoV-2 (+) n (%) SARS-CoV-2 (-) n (%) P Fetures N = 457 n = 366 n = 91 Complete blood count White blood cells (10 9 /L) 5.88 ± 2.50 5.87 ± 2.53 5.89 ± 2.39 0.957 10 22(4.8%) 17(4.7%) 5(5.5%) Neutrophils (10 9 /L) 4.28 ± 2.26 4.31 ± 2.31 4.17 ± 2.04 0.579 Lymphocytes (10 9 /L) 0.87 ± 0.44 0.85 ± 0.43 0.97 ± 0.47 0.021 * Hemoglobin (g/L) 108.77 ± 16.58 108.07 ± 15.58 111.58 ± 19.98 0.120 <100 110(24.1%) 92(25.1%) 18(19.8%) 0.285 ≥ 100 347(75.9%) 274(74.9%) 73(80.2%) Platelets (10 9 /L) 176.35 ± 71.31 178.55 ± 73.91 167.48 ± 59.28 0.186 C-reactive protein (mg/L) 2.90(0.50,14.30) 3.10(0.70,14.70) 2.20(0.50,9.50) 0.075 Creatinine (mg/dl) 836(571,1099) 824(540,1086) 920(649,1123) 0.043 * Ferritin 200.00(100.85,376.40) 209.50(81.60,375.90) 199.25(103.40,377.10) 0.996 ALT (U/L) 11(8,17) 11(8,17) 11(7,16) 0.451 AST (U/L) 14.5(11.0,19.0) 14.0(11.0,19.0) 15.0(11.0,21.0) 0.320 Albumin (g/L) 35.95 ± 4.88 35.80 ± 4.90 36.55 ± 4.79 0.194 <35 167(36.5%) 141(38.5%) 26(28.6%) 0.078 ≥ 35 290(63.5%) 225(61.5%) 65(71.4%) Serum potassium (mmol/L) 4.54 ± 0.77 4.48 ± 0.74 4.80 ± 0.85 < 0.001 * Serum calcium (mmol/L) 2.18 ± 0.21 2.18 ± 0.21 2.17 ± 0.21 0.539 Blood phosphorus (mmol/L) 1.39 ± 0.50 1.34 ± 0.48 1.60 ± 0.55 < 0.001 * Parathyroid hormone (pg/ml) 303.00(177.93,464.33) 298.60(177.25,446.50) 352.20(180.50,581.40) 0.135 600 72(15.8%) 51(13.9%) 21(23.1%) D-dimer (mg/L) 331 (187,793) 328(185,7100) 360(209,1019) 0.509 <400 123(60.6%) 104(61.9%) 19(54.3%) 0.401 ≥ 400 80(39.4%) 64(38.1%) 16(45.7%) * Values that reach statistical significance. Table 3 Clinical characteristics of SARS-CoV-2 positive hemodialysis patients by mortality Variables Total n(%) Mortality p Survivors n(%) Nonsurvivors n(%) Fetures N = 366 n = 347 N = 19 Age(years) 59(49,70) 58(48,69) 75(67,81) < 0.001 * <65 230(62.8%) 226(65.1%) 4(21.1%) < 0.001 * ≥65 136(37.2%) 121(34.9%) 15(78.9%) Gender Male 230(62.8%) 219(63.1%) 11(57.9%) 0.647 Female 136(37.2%) 128(36.9%) 8(42.1%) Co-morbid disease Diabetes Mellitus 97(26.5%) 91(26.2%) 6(31.6%) 0.607 Coronary artery disease 7(1.9%) 3(0.9%) 4(21.1%) < 0.001 * Hypertension 348(95.1%) 336(96.8%) 12(63.2%) < 0.001 * Heart failure 175(47.8%) 160(46.1%) 15(78.9%) 0.005 * Cancer 26(7.1%) 25(7.2%) 1(5.3%) 1.000 Chronic lung disease 4(1.1%) 3(0.9%) 1(5.3%) 0.193 HD-related indicators Hemodialysis age 53.00(43.00, 65.00) 52.00(42.00, 64.00) 68.00(62.00, 78.00) < 0.001 * Dry weight 58.34(51.68, 66.53) 58.40(51.69, 66.88) 57.40(49.10, 62.80) 0.363 Duration of dialysis (months) 59.92(17.56, 102.53) 58.93(17.53, 102.50) 76.60(24.63, 118.60) 0.464 KT/V 1.47 ± 0.53 1.48 ± 0.53 1.37 ± 0.36 0.490 PCR Negative 100(28.6%) 100(30.2%) 0(0%) 0.005 * Positive 250(71.4%) 231(69.8%) 19(100%) Chest CT Normal 27(12.4%) 26(12.7%) 1(7.7%) 0.194 Mild 105(48.4%) 101(49.5%) 4(30.8%) Moderate 81(37.3%) 74(36.3%) 7(53.8%) Severe 4(1.8%) 3(1.5%) 1(7.7%) Intensive care follow-up No 359(98.1%) 346(99.7%) 13(68.4%) < 0.001 * Yes 7(1.9%) 1(0.3%) 6(31.6%) Lenght of stay in hospital 10.0(5.0, 17.0) 10.0(5.0, 17.0) 11.0(5.5, 23.0) 0.473 * Values that reach statistical significance. Table 4 Laboratory findings of SARS-CoV-2 positive hemodialysis patients by mortality Variables Total n(%) Mortality p Survivors n(%) Nonsurvivors n(%) Fetures N = 366 n = 347 n = 19 Complete blood count White blood cells (10 9 /L) 5.87 ± 2.53 5.80 ± 2.14 7.27 ± 6.30 0.013 * 10 17(4.7%) 15(4.3%) 2(10.5%) Neutrophils (10 9 /L) 4.31 ± 2.31 4.21 ± 1.91 6.16 ± 5.82 < 0.001 * Lymphocytes (10 9 /L) 0.85 ± 0.43 0.86 ± 0.42 0.53 ± 0.45 0.005 * Hemoglobin (g/L) 108.07 ± 15.58 108.57 ± 14.36 98.90 ± 29.31 0.008 * <100 92(25.1%) 82(23.6%) 10(52.6%) 0.010 * ≥ 100 274(74.9%) 265(76.4%) 9(47.4%) Platelets (10 9 /L) 178.55 ± 73.91 179.79 ± 72.24 155.95 ± 99.35 0.171 C-reactive protein (mg/L) 5.20(2.50, 20.90) 4.60(2.35, 17.00) 59.05(3.43, 97.20) 0.001 * Creatinine (mg/dl) 824.50(540.00,1091.25) 831.00(576.00,1092.00) 387.00(273.00,858.00) < 0.001 * Ferritin 200.00(105.98, 387.00) 200.00(104.40, 389.10) 214.70(106.50, 383.80) 0.860 ALT (U/L) 11.00(8.00, 17.00) 11.00(8.00,17.00) 11.00(5.00, 26.00) 0.880 AST (U/L) 14.00(11.00, 19.00) 14.00(11.00,18.00) 19.00(11.00, 29.00) 0.025 * Albumin (g/L) 35.85 ± 4.89 36.18 ± 4.64 29.86 ± 5.48 < 0.001 * <35 140(38.3%) 125(36%) 15(78.9%) < 0.001 * ≥ 35 226(61.7%) 222(64%) 4(21.1%) Serum potassium (mmol/L) 4.47 ± 0.74 4.49 ± 0.73 4.17 ± 0.75 0.081 Serum calcium (mmol/L) 2.18 ± 0.21 2.18 ± 0.20 2.24 ± 0.26 0.188 Blood phosphorus (mmol/L) 1.34 ± 0.48 1.36 ± 0.48 1.02 ± 0.38 0.002 * Parathyroid hormone (pg/ml) 299.40(177.00,446.80) 300.25(181.70,456.15) 219.40(97.50,359.20) 0.045 * 600 51(14.0%) 50(14.5%) 1(5.3%) D-dimer (mg/L) 324.00(184.00,718.00) 305.00(177.00,612.00) 1017.50(363.25,1093.50) 0.006 * <400 105(61.4%) 101(65.2%) 4(25%) 0.002 * ≥ 400 66(38.6%) 54(34.8%) 12(75%) * Values that reach statistical significance. Table 5 Logistic regression analysis of influencing factors of death Variables B SE Wald P OR OR(L) OR(U) Age 0.287 0.103 7.771 0.005 * 1.333 1.089 1.631 C-reactive protein 0.021 0.009 5.457 0.019 * 1.021 1.003 1.039 AST 0.043 0.018 5.791 0.016 * 1.043 1.008 1.080 * The multi-factor influencing factor analysis adopts logistic regression and includes all indicators with single factor P < 0.15. The analysis result P < 0.05 is an independent influencing factor, OR value 1 is a risk factor. 4. Discussion Experience since the COVID-19 pandemic has shown that patients receiving maintenance hemodialysis are at higher risk of severe SARS-CoV-2 infection and severe consequences compared with other groups, as this group must undergo treatment 2–3 times a week There are also disadvantages associated with traveling between the hospital and home, such as relatively older age, multiple comorbidities, and suppressed immune systems [ 12 ]. Although previous experience has told us that SARS-CoV-2 infection seriously threatens the health of hemodialysis patients [ 13 ], most of these studies were conducted in the early stages of the pandemic. However, in this central area, due to effective control policies, there has never been a large-scale outbreak or an epidemic affecting a large number of people. Only during the Omicron surge period from mid-December 2022 to February 2023 did more infection cases occur [ 14 ], and the relevant research information on Omicron mutant strains is limited. Therefore, we aimed to add some experience to this small information base by describing the susceptibility characteristics, clinical manifestations, and short-term outcomes of SARS-CoV-2 infection in hemodialysis patients during this period, and analyzing mortality and influencing factors. 4.1. Comorbidities and clinical symptoms Previous studies have shown that older patients with comorbidities are at higher risk of infection and fatal outcomes [ 15 , 16 ], and this situation is of greater concern in hemodialysis patients [ 17 , 18 ]. Studies have confirmed that patients with hypertension are at a higher risk of infection than other groups because these patients often have higher levels of angiotensin-converting enzyme 2 (ACE2), which facilitates infection with SARS-CoV-2 [ 19 ]. The results of our study strongly support this view. We found that hemodialysis patients with hypertension are more susceptible to SARS-CoV-2 virus infection (p < 0.001). Not only that, certain comorbid factors such as hypertension, cardiovascular disease, heart failure and mortality showed statistically significant differences. In our study, comorbidities such as chronic lung disease and diabetes, which have received much attention in the past, had no significant impact on susceptibility and mortality. Our study found that the most common symptoms observed after SARS-CoV-2 infection were fever (43.2%) and cough (29.8%), and these clinical characteristics are consistent with most studies [ 15 , 16 , 20 – 22 ]. Other symptoms, such as dyspnea, back pain, sore throat, headache or taste/smell disorder, occur in a much smaller proportion. Overall, our study found that the incidence of fever (43.2% vs 42.9%) and cough (29.8% vs 30.8%) in hemodialysis patients infected with SARS-CoV-2 was basically similar to that in uninfected people. Fatigue (0.5%) and diarrhea (1.4%) were rare manifestations in our study, however, studies have found that fatigue and gastrointestinal symptoms occur in high rates in hemodialysis patients after SARS-CoV-2 infection [ 23 ]. A study conducted by Wang et al. at Wuhan Zhongnan Hospital on 5 hemodialysis patients at the end of 2019 also reported that diarrhea (80%) was the most common manifestation [ 24 ]. Several cross-sectional studies have stated that the occurrence of fatigue in hemodialysis patients is related to sleep, living environment, and treatment conditions, and that elderly hemodialysis patients are prone to more severe fatigue [ 25 , 26 ]. Although the correlation with SARS-CoV-2 has not been demonstrated, we speculate that the symptoms may be atypical due to the complex and variable clinical manifestations of SARS-CoV-2 infection. Therefore, relying solely on symptoms to make a diagnosis is blind and should be taken seriously. 4.2. Laboratory indicators Our study also found that in infected patients, in addition to common lymphopenia, increases in leukocytes, neutrophils, CRP, AST and D-dimer were associated with severe disease and death outcomes (p < 0.05). This aspect is basically consistent with previous reports [ 27 – 29 ]. Lymphopenia is very common in patients with common infections or deaths, which may be related to direct viral infection that consumes immune cells or induces inflammatory cascades [ 30 – 33 ]. In patients who died, we observed significant increases in white blood cells, neutrophils, and CRP. Some researchers have speculated on this phenomenon and pointed out that since bacterial co-infection is more common in severe patients than ordinary patients, it is reasonable to suspect that bacterial co-infection will aggravate the condition and affect the laboratory indicators [ 21 ]. CRP is also an independent risk factor for disease progression and death [ 34 , 35 ]. This view was also proven in our study (Table 5 ). Compared with the non-survivors, hemoglobin concentration, albumin, blood phosphorus and parathyroid hormone remained at higher levels in the survivors (p < 0.05). Some studies have reported that the prevalence of hypophosphatemia is particularly significant among patients with end-stage renal disease infected with SARS-CoV-2 [ 36 ]. Some studies have shown that hypophosphatemia may be associated with increased mortality in critically ill patients [ 37 ]. The possible reasons for the imbalance of phosphate levels in hemodialysis patients are more complicated. Most of them are due to insufficient nutritional intake, especially in hospitalized patients. At the same time, patients with end-stage renal disease have impaired nutrient absorption due to primary diseases. Secondly, patients with SARS-CoV-2, especially those with respiratory distress, are often complicated by respiratory alkalosis, which further leads to a decrease in blood phosphate levels. In addition, vitamin D deficiency and obesity are also possible causes [ 38 ]. One study documented disorders in blood phosphorus, blood calcium, and parathyroid hormone in patients infected with SARS-CoV-2. The results indicate that the SARS-CoV-2 virus may disturb the balance, and SARS-CoV-2 has been confirmed to be a potential cause of hypoparathyroidism [ 39 ]. Serum potassium was only found to be statistically significant in the comparison between the SARS-CoV-2 positive group and the negative group in hemodialysis patients (Table 2 ). Although the indicators decreased in the positive group, they were still within the normal range. It is speculated that it may be related to the activation of renin-angiotensin-aldosterone (RAS) after infection with SARS-CoV-2 [ 40 ]. Studies have confirmed that infection with SARS-CoV-2 can induce a massive thrombotic state [ 41 – 43 ]. We have also observed this phenomenon, and clinicians at our dialysis center found that even when receiving anticoagulant doses (1000-3000IU) of low molecular weight heparin, some patients still found that intravenous pot dialyzer tubing developed during dialysis. There was coagulation in the patient, and our doctors intervened promptly to avoid a more dangerous event. A single-center retrospective study reported that despite the use of more anticoagulants, hemodialysis patients infected with SARS-CoV-2 are still at high risk of dialysis circuit coagulation [ 44 ]. Although our study results showed no significant difference in D-dimer changes between uninfected and infected hemodialysis patients, we then found that D-dimer increased in the comparison between the non-survivors and the survivors. There is significant statistical significance (p = 0.006). A recently published report reached a similar conclusion, showing the non-survivors had higher D-dimer levels compared with those who survived [ 45 ]. We also observed an increase in AST in the non-survivors (p < 0.05). Combined with the above changes in D-dimer, we suspect that SARS-CoV-2 is very likely to damage the myocardium and blood vessels. We found that in the comparison of infected and uninfected hemodialysis patients, there was basically no difference in liver function and albumin indicators. This may be in the early stages. Once the disease worsens or even leads to death, there is a significant difference between the increase in AST and the decrease in albumin. Among them, elevated AST is an independent risk factor for death (Table 5 ). 4.3. Discussion on the impact of hemodialysis adequacy, nutritional status and age factors on clinical outcomes Notably, our study also found that higher serum creatinine was associated with better survival outcome. Although for patients who receive maintenance hemodialysis for a long time, serum creatinine is often affected by the time and frequency of hemodialysis, but it can still be used to evaluate the patient's nutritional status [ 46 ]. We have reason to speculate that higher serum creatinine reflects, to a certain extent, patients' greater muscle mass, greater exercise capacity, and better nutritional conditions. Patients registered in our center and receiving long-term maintenance hemodialysis performed well in various indicators reflecting the body, such as KT/V, hemoglobin concentration, albumin, blood calcium, and blood phosphorus, all maintained at high levels (Table 3 ). To some extent, this reflects the nutritional status of the patient and the adequacy of hemodialysis. It is statistically significant that the hemoglobin, albumin, and blood phosphorus of deceased patients were significantly lower than those of surviving patients (p < 0.01). Studies have shown that hemoglobin concentration, serum albumin, and serum phosphorus are negatively correlated with mortality [ 37 , 47 , 48 ]. Finally, we boldly speculate that hemodialysis patients with better basic physical conditions will show stronger tolerance and better clinical outcomes during the surge of Omicron. In the early stages of the SARS-CoV-2 epidemic in the past, many research centers had already considered age ≥ 65 years as one of the adverse prognostic factors [ 21 , 49 ]. Even now when the Omicron strain is the main circulating strain, our study concluded that age is still an independent risk factor for death (Table 5 ). Age ≥ 65 years was associated with higher mortality (p < 0.001). Among dialysis-related indicators, although no difference between the two groups was observed in the comparison of duration of disorder, hemodialysis age was significantly different between survivors and non-survivors (p < 0.001), which showed that it was related to the age factor. Consistent results. Therefore, we concluded that older age (≥ 65 years or hemodialysis age) is associated with higher mortality. 4.4. Vaccines and mortality Up to now, data on immune cell responses following vaccination in patients on maintenance hemodialysis are limited. Most studies indicate that the vaccine response rate in the dialysis population is lower than expected and that the relative risk is higher in the dialysis population compared with the general population [ 50 – 54 ]. In our study, we asked 413 registered dialysis patients about their vaccination status. The results show that the majority (61.1%) received one dose, 27% received two doses, and only 11.9% received three doses (Table 1 ). And no significant difference was observed in the comparison between infected and uninfected patients (p = 0.621). We analyze that the reasons may be as follows: the vaccines administered to hemodialysis patients in our center are mainly divided into the first dose of adenovirus vector vaccine, the second dose of inactivated vaccine, and the third dose of recombinant protein vaccine. These types of vaccines have certain Due to the lag, we speculate that the mutation process of the virus may be much faster than the development and update of vaccines. Therefore, during the Omicron surge period, the protective effect of these vaccines developed against previous strains will be lower than expected; secondly, due to various factors such as hemodialysis patients being generally advanced in age, suffering from a variety of chronic diseases, limited health awareness, fear of side effects, and distrust of new things, hemodialysis patients are not very receptive to vaccines [ 55 ]. Although the response titer of vaccination in hemodialysis patients is low, it is undeniable that vaccination is still a powerful measure to prevent SARS-CoV-2 infection and serious consequences [ 56 , 57 ]. According to the Chinese Center for Disease Control and Prevention, the overall mortality rate of SARS-CoV-2 is 2.3% [ 58 ]. It should be pointed out that the mortality rate of SARS-CoV-2 infection in patients receiving maintenance hemodialysis varies greatly in different periods or regions. During the study follow-up period in our center, 27 hemodialysis patients died, of which 8 patients died from non- SARS-CoV-2 infection causes. Our study ultimately reported an all-cause mortality rate of 5.2% (19/366) in patients with confirmed SARS-CoV-2 infection and a mortality rate of 2.7% (10/366) due to SARS-CoV-2 infection alone. Although the ICU admission rate among hemodialysis patients diagnosed with SARS-CoV-2 infection was 1.9%, the mortality rate was as high as 85.7% (6/7). During the diagnosis and treatment process in the dialysis center, it is recognized that not all patients diagnosed with infection need to be hospitalized. Elderly patients, patients with pulmonary or cardiovascular diseases, and patients with previous frailty can be arranged for hospitalization. In most cases, patients hospitalized in general wards Only nasal cannula or mask oxygen is required, and very few patients need to be admitted to the ICU and intubated [ 59 ]. During this period, not only our medical center, but most qualified medical centers are doing their best to open their wards to meet the demand for treatment. Thank you again for the efforts of all medical colleagues! 5. Conclusions In summary, patients receiving maintenance hemodialysis are at high risk for infection with the novel coronavirus. Our research points out that the mortality rate of hemodialysis patients infected with SARS-CoV-2 is higher than that of the general population. Our research report emphasizes that not only age is an independent risk factor for death, but also ensuring the adequacy of hemodialysis treatment and maintaining patients' good physical condition are top priorities. It is crucial to ensure regular dialysis treatment for hemodialysis patients, even during the SARS-CoV-2 outbreak. It is unwise to stop dialysis because of fear of infection, which may cause more complications and lead to dangerous outcomes. Through this retrospective study, this article puts forward the above points for communication in anticipation of the need to re-evaluate public health and social measures to deal with any more transmissible SARS-CoV-2 variants in the future. Declarations E thics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki, and approved by the ethics committee. Informed consent was obtained from all subjects involved in the study. Consent for publication: Not applicable. Data Availability Statement: To protect patient privacy, the data in this article have not been made public. But are available from the corresponding author on reasonable request. Conflicts of Interest: The authors declare no conflict of interest. Funding: This research was funded by 2021 Ningbo Medical Science and Technology Plan Project, grant number 2021Y52 and The APC was funded by the project. Authors` contributions: Formal analysis, Y.X.; Writing—original draft, Y.X. and J.W.; Writing—review & editing, Y.X., W.F., L.S., N.C., W.Z., J.D., C.L. and J.H. All authors have read and agreed to the published version of the manuscript. Acknowledgments: We are indebted to the many physicians and nurses who take care of these patients and are facing the COVID-19 pandemic in our country. References Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3837520","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268246652,"identity":"8ddb41f4-d484-4442-994e-878083d8a41b","order_by":0,"name":"Yiyang Xue","email":"","orcid":"","institution":"Health Science Center, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Yiyang","middleName":"","lastName":"Xue","suffix":""},{"id":268246653,"identity":"38fd5b36-55db-46cf-886d-3d393cfe4a2f","order_by":1,"name":"Weiwei Feng","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Feng","suffix":""},{"id":268246654,"identity":"25cd4072-d6cc-4010-887e-aa3b97b0cefb","order_by":2,"name":"Ling Shi","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Shi","suffix":""},{"id":268246655,"identity":"8b3d4a5f-7b34-4e26-b83a-9ee2aeabf6fb","order_by":3,"name":"Ning Cui","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Cui","suffix":""},{"id":268246656,"identity":"9a195dcd-7118-4851-a58d-118089a47852","order_by":4,"name":"Wei Zhang","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""},{"id":268246657,"identity":"952e2ab7-ad49-4501-b0cd-ceec57d243ab","order_by":5,"name":"Junxiu Dong","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Junxiu","middleName":"","lastName":"Dong","suffix":""},{"id":268246658,"identity":"5e4a2549-d2ed-4b15-acd1-279a456e1ce0","order_by":6,"name":"Chunying Li","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunying","middleName":"","lastName":"Li","suffix":""},{"id":268246659,"identity":"c5f117d5-a995-4e7c-959c-06eeb0639899","order_by":7,"name":"Jinjin Hu","email":"","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jinjin","middleName":"","lastName":"Hu","suffix":""},{"id":268246660,"identity":"75a6c859-371f-4749-81a4-fe5128113624","order_by":8,"name":"Junjun Wei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYFACxgYDBgYJO35m5gMHPlQQr8UiWbK9LfHgjDPEW1XBuKHnjPFh3hYi1Bocb24o5t0hwWwgkfPhAG8Dgzy/2AECWs4cbDDmPSPBZy6Ru+GA5A4Gw5mzE/BrMbuRCNTSJsFsOQOoxfAMQ4LBbUJa7j8Ea2HccCPnwYHENmK03GCEajlzhuHAQWK02J9JbDCc2yYBCmSDgw1nJAj7RbL9+DODt211oKh8/PlPhY08vzQBLUDAZoDEkSCoHASYHxClbBSMglEwCkYuAAAMzEn9AuTeOwAAAABJRU5ErkJggg==","orcid":"","institution":"Blood Purification Center, Ningbo Urol \u0026 Nephrol Hospital","correspondingAuthor":true,"prefix":"","firstName":"Junjun","middleName":"","lastName":"Wei","suffix":""}],"badges":[],"createdAt":"2024-01-05 14:45:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3837520/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3837520/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50048472,"identity":"8c82d261-922e-416f-8fae-7cc1cbad3387","added_by":"auto","created_at":"2024-01-23 16:20:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":566738,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3837520/v1/877249be-51c2-4751-9fb4-da3645ab23d8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Review of clinical characteristics and mortality outcomes in patients on maintenance hemodialysis during the Omicron surge: a single center experience","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAt the end of 2019, a new coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged and quickly triggered an unusual viral pneumonia epidemic. Due to its high transmissibility, this novel coronavirus pneumonia, also known as coronavirus disease 2019 (COVID-19), has spread rapidly around the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This virus has mutated several times, among which the Omicron mutant strain will be the main circulating strain in China and even most parts of the world in 2022 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to a release from the Chinese Center for Disease Control and Prevention, from September 26, 2022 to January 23, 2023, China reported a total of 18,906 effective novel coronavirus genome sequences of local cases, all of which were Omicron mutant strains. From December 2022 to January 2023, the number of medical visits due to new coronavirus infection reached a peak in China, including outpatient medical treatment, general hospitalization and severe hospitalization [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMaintenance hemodialysis patients are a special category of patients during the novel coronavirus pandemic because they are at greater risk of exposure to infection than patients who are able to undergo home peritoneal dialysis. Although the pathogenicity of the Omicron variant is less than that of the previous strain, it is still accompanied by huge risks for patients receiving maintenance hemodialysis. The global prevalence of chronic kidney disease (CKD) is approximately 2%-10% and varies over time in the same region [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The overall morbidity and mortality rates of CKD patients with SARS-CoV-2 are higher than those of individuals without kidney disease, including patients receiving dialysis [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the past three years, there has not been a large-scale epidemic in the area where our center is located, and it only withstood greater epidemic challenges during the current Omicron surge. In the past, most studies were conducted during the epidemic period of Alpha, Beta and others, but there is a lack of research on the clinical characteristics of maintenance hemodialysis patients in the Omicron environment. Therefore, we retrospectively analyzed all patients who were registered in our center and received long-term maintenance hemodialysis from December 15, 2022 to February 22, 2023, a total of 457 patients. Our paper presents the clinical profiles and outcomes of maintenance hemodialysis patients with confirmed and undiagnosed suspected SARS-CoV-2 infection in our center, as well as survival and non-survival cases among maintenance hemodialysis patients with confirmed SARS-CoV-2 infection. clinical characteristics and established different profiles and outcomes between the two groups of patients.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study subjects\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis retrospective study was conducted at the Hemodialysis Center of Urology and Nephrology Hospital, Ningbo, Zhejiang Province. We retrospectively analyzed the clinical results of 457 patients who were registered and maintained hemodialysis in our center from December 15, 2022 to February 22, 2023, and divided them into SARS-CoV-2 positive and SARS-CoV-2 negative two groups. In addition, based on the confirmed SARS-CoV-2 positivity, the patients were divided into a survival group and a non-survival group for comparison. The diagnostic criteria for patients included in the study refer to the \"Diagnosis and Treatment Plan for Novel Coronavirus Infection (Tenth Edition)\" issued by the National Health Commission of China [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The diagnostic criteria for suspected cases combined epidemiological history and clinical symptoms, and blood index tests, antigen-antibody and chest CT examinations were performed, so asymptomatic cases were discovered. All patients are over 18 years old. Patients receiving temporary hemodialysis were excluded. Follow-up ends at the end of the study or when the patient dies. All patients were informed and agreed to participate in this study and signed an informed consent form.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data collection\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eData were collected from the hospital HIS system of the Hemodialysis Center of Urology and Nephrology Hospital in Ningbo, Zhejiang Province. Data extracted from registered patient medical records included demographic and clinical information, including age, gender, and chronic comorbidities. Data related to SARS-CoV-2 include clinical symptoms (fever, cough, myalgia, fatigue, taste/smell disorder, etc.), laboratory indicators, chest CT, whether to receive intensive care, and length of hospitalization. Data related to maintenance hemodialysis include hemodialysis age, dry weight, duration of dialysis (months), and dialysis urea clearance index (KT/V). Vaccination status of all patients receiving maintenance hemodialysis, including primary immunization, booster and secondary booster immunization.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStatistical description: Normally distributed measurement data are described by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, non-normally distributed measurement data are described by median (interquartile range), and count data are described by frequency (percentage). Statistical analysis: Normally distributed measurement data were subjected to t test, and non-normally distributed measurement data were subjected to rank sum test. Count data were analyzed using chi-square test and Fisher's exact probability method. Risk factor analysis used logistic regression analysis. P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Epidemiological and clinical characteristics of all patients receiving maintenance hemodialysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDuring the study period, a total of 457 people met the inclusion criteria, with an average age of 59.82\u0026thinsp;\u0026plusmn;\u0026thinsp;14.13 years (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), 37.6% were female (172, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), including 366 SARS-CoV-2 positive patients and 91 SARS-CoV-2 negative patients.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the comparison of epidemiological parameters, clinical symptoms, and hemodialysis-related data between SARS-CoV-2 positive and SARS-CoV-2 negative hemodialysis patients. The most common symptoms observed in hemodialysis patients after SARS-CoV-2 infection were fever (43.2%) and cough (29.8%), followed by diarrhea (1.4%). Other symptoms such as dyspnea, back pain, sore throat, headache, or taste/smell disorder are less common. However, the incidence of fatigue after infection with SARS-CoV-2 was reduced (0.5% vs 4.4%). Patients with hypertension and hemodialysis showed statistical differences between the SARS-CoV-2 positive group and the negative group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). All patients receiving maintenance hemodialysis showed no statistically significant differences in dialysis-related data (hemodialysis age, dry weight, duration of dialysis (months), KT/V). Finally, no statistically significant difference in mortality was observed between the two groups (5.2% vs 8.8%, p\u0026thinsp;=\u0026thinsp;0.192). In addition, in terms of symptoms, fatigue showed completely opposite results to real-world observations (0.5% vs 4.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.016).\u003c/p\u003e \u003cp\u003eIn terms of mortality statistics, the all-cause mortality rate of 457 patients receiving maintenance hemodialysis was 5.9% (27/457), and the all-cause mortality rate of SARS-CoV-2-positive hemodialysis patients was 5.2% (19/366), while the all-cause mortality rate among SARS-CoV-2-negative hemodialysis patients was 8.8% (8/91). Through data analysis of all-cause mortality of the two groups of hemodialysis patients, no significant statistical difference was found (p\u0026thinsp;=\u0026thinsp;0.192).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the comparison of laboratory indicators between SARS-CoV-2-positive and SARS-CoV-2-negative hemodialysis patients. In terms of blood cell count, no significant difference was observed between the two groups in terms of the total number of white blood cells. It was only observed that the lymphocyte count in the SARS-CoV-2 positive group was lower than that in the SARS-CoV-2 negative group (0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43 vs 0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the routine analysis of blood biochemistry, we found that the serum creatinine (Cr), serum potassium, serum phosphorus, and parathyroid hormone in the SARS-CoV-2 positive group were significantly lower than those in the SARS-CoV-2 negative group. Statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eDuring the follow-up period, we counted the vaccination status of all hemodialysis patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The vaccination rate for the first basic vaccination was the highest (61.1%), the booster vaccination rate dropped to 27.0%, and the second booster vaccination needle is only 11.9%. At the same time, no significant difference in vaccination status was found between the SARS-CoV-2 positive group and the negative group.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Comparison of clinical characteristics and laboratory indicators according to mortality among all SARS-CoV-2-positive hemodialysis patients\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAmong the 366 SARS-CoV-2-positive patients, 19 died due to various causes including infection during hospitalization (5.2%), and the remaining 347 patients survived.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the comparison of demographic and laboratory data between the two groups. Age\u0026thinsp;\u0026lt;\u0026thinsp;65 years showed significant differences between the survival group and the non-survival group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and age was an independent risk factor for death (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Secondly, we also found that there was a statistical difference between the two groups in terms of age at starting dialysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), that is, the older the age at starting dialysis, the higher the mortality rate. In the comparison of comorbidities, we found that the comorbidity rates of cardiovascular disease, hypertension, and heart failure in the non-survival group were significantly higher than those in the survival group. Only 7 of the 366 SARS-CoV-2-positive patients were admitted to the intensive care unit (ICU), accounting for 1.9%. Compared with the survival group, ICU rate was significantly higher in the non-survival group (0.3% vs 31.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, we also found that the total number of white blood cells, neutrophil count, C-reactive protein, AST, and D-dimer in the non-survival group were higher than those in the survival group. Among them, C-reactive protein and AST are independent risk factors for death in infected patients (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Not only that, we also found that the lymphocyte count, hemoglobin concentration, blood creatinine, serum albumin, blood phosphorus, and parathyroid hormone indicators in the non-survival group were lower than those in the survival group.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe baseline epidemiological and clinical characteristics of the patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSARS-CoV-2 (+)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSARS-CoV-2 (-)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.82\u0026thinsp;\u0026plusmn;\u0026thinsp;14.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.27\u0026thinsp;\u0026plusmn;\u0026thinsp;14.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.02\u0026thinsp;\u0026plusmn;\u0026thinsp;13.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41(9.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e251(54.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200(54.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(56.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165(36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129(35.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(39.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e285(62.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230(62.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55(60.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e172(37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136(37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(39.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCo-morbid disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118(25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100(27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary artery disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e447(97.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e364(99.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83(91.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227(49.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180(49.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47(51.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic obstructive lung disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197(43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158(43.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137(30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109(29.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBack pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiarrhea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSore throat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaste/smell disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eHD-related indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemodialysis age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.50(42.25, 64.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.25(42.00, 64.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.00(44.50, 62.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.40(51.84, 66.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.34(51.68, 66.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.20(52.18, 76.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of dialysis (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.93(17.39,104.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.98(17.29,101.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.93(19.38,120.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT/V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccination status\u003c/p\u003e \u003cp\u003eFundamental immunity\u003c/p\u003e \u003cp\u003eBooster immunization\u003c/p\u003e \u003cp\u003eSecondary booster immunization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118(61.1%)\u003c/p\u003e \u003cp\u003e52(27.0%)\u003c/p\u003e \u003cp\u003e23(11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102(62.6%)\u003c/p\u003e \u003cp\u003e42(25.8%)\u003c/p\u003e \u003cp\u003e19(11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(53.4%)\u003c/p\u003e \u003cp\u003e10(33.3%)\u003c/p\u003e \u003cp\u003e4(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* Values that reach statistical significance.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the laboratory findings of the patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSARS-CoV-2 (+)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSARS-CoV-2 (-)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eComplete blood count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cells (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75(16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(13.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e360(78.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286(78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74(81.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.28\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108.77\u0026thinsp;\u0026plusmn;\u0026thinsp;16.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108.07\u0026thinsp;\u0026plusmn;\u0026thinsp;15.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111.58\u0026thinsp;\u0026plusmn;\u0026thinsp;19.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110(24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(25.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e347(75.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e274(74.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73(80.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelets (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176.35\u0026thinsp;\u0026plusmn;\u0026thinsp;71.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178.55\u0026thinsp;\u0026plusmn;\u0026thinsp;73.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.48\u0026thinsp;\u0026plusmn;\u0026thinsp;59.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.90(0.50,14.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.10(0.70,14.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.20(0.50,9.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e836(571,1099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e824(540,1086)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e920(649,1123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200.00(100.85,376.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e209.50(81.60,375.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199.25(103.40,377.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(8,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(8,17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(7,16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.5(11.0,19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0(11.0,19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.0(11.0,21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.55\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167(36.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141(38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290(63.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225(61.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65(71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum potassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum calcium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood phosphorus (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParathyroid hormone (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e303.00(177.93,464.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298.60(177.25,446.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e352.20(180.50,581.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93(20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72(19.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.048\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e150\u0026ndash;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e292(63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243(66.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49(53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72(15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51(13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e331 (187,793)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328(185,7100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e360(209,1019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123(60.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104(61.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80(39.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64(38.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* Values that reach statistical significance.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of SARS-CoV-2 positive hemodialysis patients by mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNonsurvivors\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(49,70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58(48,69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75(67,81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230(62.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226(65.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136(37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121(34.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(78.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230(62.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219(63.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(57.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136(37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128(36.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(42.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbid disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97(26.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91(26.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary artery disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e348(95.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e336(96.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175(47.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160(46.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(78.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26(7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic lung disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHD-related indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemodialysis age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.00(43.00, 65.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.00(42.00, 64.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.00(62.00, 78.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.34(51.68, 66.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.40(51.69, 66.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.40(49.10, 62.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of dialysis (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.92(17.56, 102.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.93(17.53, 102.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.60(24.63, 118.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT/V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100(30.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250(71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e231(69.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest CT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(48.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101(49.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(30.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81(37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74(36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(53.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntensive care follow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e359(98.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346(99.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(31.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLenght of stay in hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.0(5.0, 17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.0(5.0, 17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.0(5.5, 23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* Values that reach statistical significance.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLaboratory findings of SARS-CoV-2 positive hemodialysis patients by mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNonsurvivors\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete blood count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cells (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.80\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.27\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58(16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e286(78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e274(79.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(63.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(10.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.16\u0026thinsp;\u0026plusmn;\u0026thinsp;5.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108.07\u0026thinsp;\u0026plusmn;\u0026thinsp;15.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108.57\u0026thinsp;\u0026plusmn;\u0026thinsp;14.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.90\u0026thinsp;\u0026plusmn;\u0026thinsp;29.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92(25.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82(23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(52.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e274(74.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e265(76.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(47.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelets (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178.55\u0026thinsp;\u0026plusmn;\u0026thinsp;73.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179.79\u0026thinsp;\u0026plusmn;\u0026thinsp;72.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e155.95\u0026thinsp;\u0026plusmn;\u0026thinsp;99.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.20(2.50, 20.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.60(2.35, 17.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.05(3.43, 97.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e824.50(540.00,1091.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e831.00(576.00,1092.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e387.00(273.00,858.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200.00(105.98, 387.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200.00(104.40, 389.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214.70(106.50, 383.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.00(8.00, 17.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.00(8.00,17.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.00(5.00, 26.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.00(11.00, 19.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.00(11.00,18.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.00(11.00, 29.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.85\u0026thinsp;\u0026plusmn;\u0026thinsp;4.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.18\u0026thinsp;\u0026plusmn;\u0026thinsp;4.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.86\u0026thinsp;\u0026plusmn;\u0026thinsp;5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140(38.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125(36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(78.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226(61.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222(64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(21.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum potassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum calcium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood phosphorus (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParathyroid hormone (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299.40(177.00,446.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300.25(181.70,456.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219.40(97.50,359.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71(19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63(18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(42.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e150\u0026ndash;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e241(66.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e231(67.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(52.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51(14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50(14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(5.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e324.00(184.00,718.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e305.00(177.00,612.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1017.50(363.25,1093.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(61.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101(65.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66(38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(75%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* Values that reach statistical significance.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of influencing factors of death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR(L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR(U)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.631\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* The multi-factor influencing factor analysis adopts logistic regression and includes all indicators with single factor P\u0026thinsp;\u0026lt;\u0026thinsp;0.15. The analysis result P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is an independent influencing factor, OR value\u0026thinsp;\u0026lt;\u0026thinsp;1 is a protective factor, and OR\u0026thinsp;\u0026gt;\u0026thinsp;1 is a risk factor.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eExperience since the COVID-19 pandemic has shown that patients receiving maintenance hemodialysis are at higher risk of severe SARS-CoV-2 infection and severe consequences compared with other groups, as this group must undergo treatment 2\u0026ndash;3 times a week There are also disadvantages associated with traveling between the hospital and home, such as relatively older age, multiple comorbidities, and suppressed immune systems [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although previous experience has told us that SARS-CoV-2 infection seriously threatens the health of hemodialysis patients [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], most of these studies were conducted in the early stages of the pandemic. However, in this central area, due to effective control policies, there has never been a large-scale outbreak or an epidemic affecting a large number of people. Only during the Omicron surge period from mid-December 2022 to February 2023 did more infection cases occur [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and the relevant research information on Omicron mutant strains is limited. Therefore, we aimed to add some experience to this small information base by describing the susceptibility characteristics, clinical manifestations, and short-term outcomes of SARS-CoV-2 infection in hemodialysis patients during this period, and analyzing mortality and influencing factors.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Comorbidities and clinical symptoms\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePrevious studies have shown that older patients with comorbidities are at higher risk of infection and fatal outcomes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and this situation is of greater concern in hemodialysis patients [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Studies have confirmed that patients with hypertension are at a higher risk of infection than other groups because these patients often have higher levels of angiotensin-converting enzyme 2 (ACE2), which facilitates infection with SARS-CoV-2 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The results of our study strongly support this view. We found that hemodialysis patients with hypertension are more susceptible to SARS-CoV-2 virus infection (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Not only that, certain comorbid factors such as hypertension, cardiovascular disease, heart failure and mortality showed statistically significant differences. In our study, comorbidities such as chronic lung disease and diabetes, which have received much attention in the past, had no significant impact on susceptibility and mortality.\u003c/p\u003e \u003cp\u003eOur study found that the most common symptoms observed after SARS-CoV-2 infection were fever (43.2%) and cough (29.8%), and these clinical characteristics are consistent with most studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Other symptoms, such as dyspnea, back pain, sore throat, headache or taste/smell disorder, occur in a much smaller proportion. Overall, our study found that the incidence of fever (43.2% vs 42.9%) and cough (29.8% vs 30.8%) in hemodialysis patients infected with SARS-CoV-2 was basically similar to that in uninfected people. Fatigue (0.5%) and diarrhea (1.4%) were rare manifestations in our study, however, studies have found that fatigue and gastrointestinal symptoms occur in high rates in hemodialysis patients after SARS-CoV-2 infection [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A study conducted by Wang et al. at Wuhan Zhongnan Hospital on 5 hemodialysis patients at the end of 2019 also reported that diarrhea (80%) was the most common manifestation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Several cross-sectional studies have stated that the occurrence of fatigue in hemodialysis patients is related to sleep, living environment, and treatment conditions, and that elderly hemodialysis patients are prone to more severe fatigue [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although the correlation with SARS-CoV-2 has not been demonstrated, we speculate that the symptoms may be atypical due to the complex and variable clinical manifestations of SARS-CoV-2 infection. Therefore, relying solely on symptoms to make a diagnosis is blind and should be taken seriously.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Laboratory indicators\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur study also found that in infected patients, in addition to common lymphopenia, increases in leukocytes, neutrophils, CRP, AST and D-dimer were associated with severe disease and death outcomes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This aspect is basically consistent with previous reports [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Lymphopenia is very common in patients with common infections or deaths, which may be related to direct viral infection that consumes immune cells or induces inflammatory cascades [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In patients who died, we observed significant increases in white blood cells, neutrophils, and CRP. Some researchers have speculated on this phenomenon and pointed out that since bacterial co-infection is more common in severe patients than ordinary patients, it is reasonable to suspect that bacterial co-infection will aggravate the condition and affect the laboratory indicators [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. CRP is also an independent risk factor for disease progression and death [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This view was also proven in our study (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Compared with the non-survivors, hemoglobin concentration, albumin, blood phosphorus and parathyroid hormone remained at higher levels in the survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Some studies have reported that the prevalence of hypophosphatemia is particularly significant among patients with end-stage renal disease infected with SARS-CoV-2 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Some studies have shown that hypophosphatemia may be associated with increased mortality in critically ill patients [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The possible reasons for the imbalance of phosphate levels in hemodialysis patients are more complicated. Most of them are due to insufficient nutritional intake, especially in hospitalized patients. At the same time, patients with end-stage renal disease have impaired nutrient absorption due to primary diseases. Secondly, patients with SARS-CoV-2, especially those with respiratory distress, are often complicated by respiratory alkalosis, which further leads to a decrease in blood phosphate levels. In addition, vitamin D deficiency and obesity are also possible causes [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. One study documented disorders in blood phosphorus, blood calcium, and parathyroid hormone in patients infected with SARS-CoV-2. The results indicate that the SARS-CoV-2 virus may disturb the balance, and SARS-CoV-2 has been confirmed to be a potential cause of hypoparathyroidism [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Serum potassium was only found to be statistically significant in the comparison between the SARS-CoV-2 positive group and the negative group in hemodialysis patients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although the indicators decreased in the positive group, they were still within the normal range. It is speculated that it may be related to the activation of renin-angiotensin-aldosterone (RAS) after infection with SARS-CoV-2 [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies have confirmed that infection with SARS-CoV-2 can induce a massive thrombotic state [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. We have also observed this phenomenon, and clinicians at our dialysis center found that even when receiving anticoagulant doses (1000-3000IU) of low molecular weight heparin, some patients still found that intravenous pot dialyzer tubing developed during dialysis. There was coagulation in the patient, and our doctors intervened promptly to avoid a more dangerous event. A single-center retrospective study reported that despite the use of more anticoagulants, hemodialysis patients infected with SARS-CoV-2 are still at high risk of dialysis circuit coagulation [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Although our study results showed no significant difference in D-dimer changes between uninfected and infected hemodialysis patients, we then found that D-dimer increased in the comparison between the non-survivors and the survivors. There is significant statistical significance (p\u0026thinsp;=\u0026thinsp;0.006). A recently published report reached a similar conclusion, showing the non-survivors had higher D-dimer levels compared with those who survived [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. We also observed an increase in AST in the non-survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Combined with the above changes in D-dimer, we suspect that SARS-CoV-2 is very likely to damage the myocardium and blood vessels. We found that in the comparison of infected and uninfected hemodialysis patients, there was basically no difference in liver function and albumin indicators. This may be in the early stages. Once the disease worsens or even leads to death, there is a significant difference between the increase in AST and the decrease in albumin. Among them, elevated AST is an independent risk factor for death (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Discussion on the impact of hemodialysis adequacy, nutritional status and age factors on clinical outcomes\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eNotably, our study also found that higher serum creatinine was associated with better survival outcome. Although for patients who receive maintenance hemodialysis for a long time, serum creatinine is often affected by the time and frequency of hemodialysis, but it can still be used to evaluate the patient's nutritional status [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. We have reason to speculate that higher serum creatinine reflects, to a certain extent, patients' greater muscle mass, greater exercise capacity, and better nutritional conditions. Patients registered in our center and receiving long-term maintenance hemodialysis performed well in various indicators reflecting the body, such as KT/V, hemoglobin concentration, albumin, blood calcium, and blood phosphorus, all maintained at high levels (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). To some extent, this reflects the nutritional status of the patient and the adequacy of hemodialysis. It is statistically significant that the hemoglobin, albumin, and blood phosphorus of deceased patients were significantly lower than those of surviving patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Studies have shown that hemoglobin concentration, serum albumin, and serum phosphorus are negatively correlated with mortality [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Finally, we boldly speculate that hemodialysis patients with better basic physical conditions will show stronger tolerance and better clinical outcomes during the surge of Omicron.\u003c/p\u003e \u003cp\u003eIn the early stages of the SARS-CoV-2 epidemic in the past, many research centers had already considered age\u0026thinsp;\u0026ge;\u0026thinsp;65 years as one of the adverse prognostic factors [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Even now when the Omicron strain is the main circulating strain, our study concluded that age is still an independent risk factor for death (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Age\u0026thinsp;\u0026ge;\u0026thinsp;65 years was associated with higher mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among dialysis-related indicators, although no difference between the two groups was observed in the comparison of duration of disorder, hemodialysis age was significantly different between survivors and non-survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which showed that it was related to the age factor. Consistent results. Therefore, we concluded that older age (\u0026ge;\u0026thinsp;65 years or hemodialysis age) is associated with higher mortality.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Vaccines and mortality\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eUp to now, data on immune cell responses following vaccination in patients on maintenance hemodialysis are limited. Most studies indicate that the vaccine response rate in the dialysis population is lower than expected and that the relative risk is higher in the dialysis population compared with the general population [\u003cspan additionalcitationids=\"CR51 CR52 CR53\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. In our study, we asked 413 registered dialysis patients about their vaccination status. The results show that the majority (61.1%) received one dose, 27% received two doses, and only 11.9% received three doses (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). And no significant difference was observed in the comparison between infected and uninfected patients (p\u0026thinsp;=\u0026thinsp;0.621). We analyze that the reasons may be as follows: the vaccines administered to hemodialysis patients in our center are mainly divided into the first dose of adenovirus vector vaccine, the second dose of inactivated vaccine, and the third dose of recombinant protein vaccine. These types of vaccines have certain Due to the lag, we speculate that the mutation process of the virus may be much faster than the development and update of vaccines. Therefore, during the Omicron surge period, the protective effect of these vaccines developed against previous strains will be lower than expected; secondly, due to various factors such as hemodialysis patients being generally advanced in age, suffering from a variety of chronic diseases, limited health awareness, fear of side effects, and distrust of new things, hemodialysis patients are not very receptive to vaccines [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Although the response titer of vaccination in hemodialysis patients is low, it is undeniable that vaccination is still a powerful measure to prevent SARS-CoV-2 infection and serious consequences [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to the Chinese Center for Disease Control and Prevention, the overall mortality rate of SARS-CoV-2 is 2.3% [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. It should be pointed out that the mortality rate of SARS-CoV-2 infection in patients receiving maintenance hemodialysis varies greatly in different periods or regions. During the study follow-up period in our center, 27 hemodialysis patients died, of which 8 patients died from non- SARS-CoV-2 infection causes. Our study ultimately reported an all-cause mortality rate of 5.2% (19/366) in patients with confirmed SARS-CoV-2 infection and a mortality rate of 2.7% (10/366) due to SARS-CoV-2 infection alone. Although the ICU admission rate among hemodialysis patients diagnosed with SARS-CoV-2 infection was 1.9%, the mortality rate was as high as 85.7% (6/7). During the diagnosis and treatment process in the dialysis center, it is recognized that not all patients diagnosed with infection need to be hospitalized. Elderly patients, patients with pulmonary or cardiovascular diseases, and patients with previous frailty can be arranged for hospitalization. In most cases, patients hospitalized in general wards Only nasal cannula or mask oxygen is required, and very few patients need to be admitted to the ICU and intubated [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. During this period, not only our medical center, but most qualified medical centers are doing their best to open their wards to meet the demand for treatment. Thank you again for the efforts of all medical colleagues!\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn summary, patients receiving maintenance hemodialysis are at high risk for infection with the novel coronavirus. Our research points out that the mortality rate of hemodialysis patients infected with SARS-CoV-2 is higher than that of the general population. Our research report emphasizes that not only age is an independent risk factor for death, but also ensuring the adequacy of hemodialysis treatment and maintaining patients' good physical condition are top priorities. It is crucial to ensure regular dialysis treatment for hemodialysis patients, even during the SARS-CoV-2 outbreak. It is unwise to stop dialysis because of fear of infection, which may cause more complications and lead to dangerous outcomes. Through this retrospective study, this article puts forward the above points for communication in anticipation of the need to re-evaluate public health and social measures to deal with any more transmissible SARS-CoV-2 variants in the future.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003cstrong\u003ethics\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eapproval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by the ethics committee. Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e To protect patient privacy, the data in this article have not been made public.\u0026nbsp;But are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by 2021 Ningbo Medical Science and Technology Plan Project, grant number 2021Y52 and The APC was funded by the project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors` contributions:\u003c/strong\u003e Formal analysis, Y.X.; Writing\u0026mdash;original draft, Y.X. and J.W.; Writing\u0026mdash;review \u0026amp; editing, Y.X., W.F., L.S., N.C., W.Z., J.D., C.L. and J.H.\u0026nbsp;All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We are indebted to the many physicians and nurses who take care of these patients and are facing the COVID-19 pandemic in our country.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWu JT, Leung K, Leung GM. 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Hypophosphatemia in Coronavirus Disease 2019 (COVID-19), Complications, and Considerations: A Systematic Review. \u003cem\u003eBioMed research international\u003c/em\u003e 2022, 2022:1468786.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Xiao C, Chen L, Zhang X, Kou Q. Impact of hypophosphatemia on outcome of patients in intensive care unit: a retrospective cohort study. BMC Anesthesiol. 2019;19(1):86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMercola J, Grant WB, Wagner CL. Evidence Regarding Vitamin D and Risk of COVID-19 and Its Severity. Nutrients 2020, 12(11).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonnet JB, Berchoux E, Sultan A. Decompensated primary hypoparathyroidism in a patient with COVID-19. Ann Endocrinol. 2021;82(2):123\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMabillard H, Sayer JA. Electrolyte Disturbances in SARS-CoV-2 Infection. F1000Research. 2020;9:587.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoyd S, Sheng Loh K, Lynch J, Alrashed D, Muzzammil S, Marsh H, Masoud M, Bin Ihsan S, Martin-Loeches I. The Incidence of Venous Thromboembolism in Critically Ill Patients with SARS-CoV-2 Infection Compared with Critically Ill Influenza and Community-Acquired Pneumonia Patients: A Retrospective Chart Review. Med Sci (Basel Switzerland) 2022, 10(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Xiao M, Zhang S, Xia P, Cao W, Jiang W, Chen H, Ding X, Zhao H, Zhang H, et al. Coagulopathy and Antiphospholipid Antibodies in Patients with Covid-19. N Engl J Med. 2020;382(17):e38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParks AL, Auerbach AD, Schnipper JL, Bertram A, Jeon SY, Boyle B, Fang MC, Gadrey SM, Siddiqui ZK, Brotman DJ. Venous thromboembolism (VTE) prevention and diagnosis in COVID-19: Practice patterns and outcomes at 33 hospitals. PLoS ONE. 2022;17(5):e0266944.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhoo BZE, Lim RS, See YP, Yeo SC. Dialysis circuit clotting in critically ill patients with COVID-19 infection. BMC Nephrol. 2021;22(1):141.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb haemostasis: JTH. 2020;18(4):844\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalther CP, Carter CW, Low CL, Williams P, Rifkin DE, Steiner RW, Ix JH. Interdialytic creatinine change versus predialysis creatinine as indicators of nutritional status in maintenance hemodialysis. Nephrol Dial Transplant. 2012;27(2):771\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong H, Wei C, Hu H, Wan Q. Association of the serum albumin level with prognosis in chronic kidney disease patients. Int Urol Nephrol. 2022;54(9):2421\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan W, Han Y, Hu H, He Y. Association between hemoglobin and chronic kidney disease progression: a secondary analysis of a prospective cohort study in Japanese patients. BMC Nephrol. 2022;23(1):295.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Li W, Shi X, Chen Z, Jiang B, Liu J, Wang D, Liu C, Meng Y, Cui L, et al. Early antiviral treatment contributes to alleviate the severity and improve the prognosis of patients with novel coronavirus disease (COVID-19). J Intern Med. 2020;288(1):128\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCantarelli C, Angeletti A, Perin L, Russo LS, Sabiu G, Podest\u0026agrave; MA, Cravedi P. Immune responses to SARS-CoV-2 in dialysis and kidney transplantation. 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Kidney Int. 2021;100(4):928\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStumpf J, Siepmann T, Lindner T, Karger C, Schw\u0026ouml;bel J, Anders L, Faulhaber-Walter R, Schewe J, Martin H, Schirutschke H, et al. Humoral and cellular immunity to SARS-CoV-2 vaccination in renal transplant versus dialysis patients: A prospective, multicenter observational study using mRNA-1273 or BNT162b2 mRNA vaccine. Lancet Reg health Europe. 2021;9:100178.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarakizlis H, Nahrgang C, Strecker K, Chen J, Aly M, Slanina H, Sch\u0026uuml;ttler CG, Esso I, Wolter M, Todorova D, et al. Immunogenicity and reactogenicity of homologous mRNA-based and vector-based SARS-CoV-2 vaccine regimens in patients receiving maintenance dialysis. Clin Immunol (Orlando Fla). 2022;236:108961.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiao J, Cheung JK, Wu P, Ni MY, Cowling BJ, Liao Q. Temporal changes in factors associated with COVID-19 vaccine hesitancy and uptake among adults in Hong Kong: Serial cross-sectional surveys. Lancet Reg health Western Pac. 2022;23:100441.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu CM, Weiner DE, Manley HJ, Aweh GN, Ladik V, Frament J, Miskulin D, Argyropoulos C, Abreo K, Chin A, et al. Seroresponse to SARS-CoV-2 Vaccines among Maintenance Dialysis Patients over 6 Months. Clin J Am Soc Nephrology: CJASN. 2022;17(3):403\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliver MJ, Thomas D, Balamchi S, Ip J, Naylor K, Dixon SN, McArthur E, Kwong J, Perl J, Atiquzzaman M, et al. Vaccine Effectiveness Against SARS-CoV-2 Infection and Severe Outcomes in the Maintenance Dialysis Population in Ontario, Canada. J Am Soc Nephrol. 2022;33(4):839\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlfano G, Morisi N, Frisina M, Ferrari A, Fontana F, Tonelli R, Franceschini E, Meschiari M, Donati G, Guaraldi G. Awaiting a cure for COVID-19: therapeutic approach in patients with different severity levels of COVID-19. Le Infezioni in Medicina. 2022;30(1):11\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, Omicron, hemodialysis, clinical characteristics","lastPublishedDoi":"10.21203/rs.3.rs-3837520/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3837520/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThis hemodialysis center experienced the pandemic from December 2022 to January 2023. Therefore, we sought to describe the clinical characteristics and mortality outcomes in hemodialysis patients during this Omicron surge.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e According to whether they are infected, they are divided into two groups: SARS-CoV-2-positive and SARS-CoV-2-negative. The SARS-CoV-2-positive group was divided into a survival group and a non-survival group for comparison.\u003c/p\u003e\n\u003cp\u003e​\u003cstrong\u003eResults:\u003c/strong\u003e 366 of 457 hemodialysis patients were infected with SARS-CoV-2. The most common symptoms observed were fever (43.2%) and cough (29.8%), Followed by diarrhea (1.4%). Hemodialysis patients with hypertension were more susceptible to SARS-CoV-2 infection. The lymphocyte count, serum creatinine, serum potassium, and serum phosphorus in the SARS-CoV-2-positive group were significantly lower than those in the SARS-CoV-2-negative group. The all-cause mortality rate for infection with SARS-CoV-2was 5.2%. Only 7 of 366 SARS-CoV-2-positive patients were admitted to the intensive care unit, but 6 of them died. Intensive care unit hospitalization rates were significantly higher in the non-survival group compared with the survival group. White blood cells count, neutrophil count, C-reactive protein, AST, and D-dimer in the non-survival group were higher than those in the survival group. The lymphocyte count, hemoglobin concentration, serum creatinine, serum albumin, serum phosphorus and parathyroid hormone in the non-survival group were lower than those in the survival group. Age\u0026gt;65 years, elevated C-reactive protein and AST are independent risk factors for death. Finally, no significant difference in vaccination status was found between the SARS-CoV-2-positive group and the negative group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eHemodialysis patients are at high risk for SARS-CoV-2 infection. Ensuring the adequacy of hemodialysis treatment and maintaining good physical condition of patients are the top priorities.\u003c/p\u003e","manuscriptTitle":"Review of clinical characteristics and mortality outcomes in patients on maintenance hemodialysis during the Omicron surge: a single center experience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-23 16:12:28","doi":"10.21203/rs.3.rs-3837520/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-07T15:03:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-25T14:50:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-02T18:53:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e012e934-7873-46fb-ae49-3d430b93ea84","date":"2024-02-02T17:55:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b3d03c84-dec3-4442-af1f-a87380a07425","date":"2024-02-01T21:49:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-30T17:35:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-30T17:32:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-20T14:59:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-20T14:56:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-01-05T14:40:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8576a7b8-3ece-4c5a-80c2-d45ee35d4304","owner":[],"postedDate":"January 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-05-29T09:06:35+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-23 16:12:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3837520","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3837520","identity":"rs-3837520","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}